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| The Butterfly Dream |
"Man models himself after Earth. Earth models itself after Heaven. Heaven models itself after Tao. And Tao models itself after Nature." - Lao Tzu (Wing-Tsit Chan trans.)John Maynard Smith and Eörs Szathmáry in "The Major Transitions in Evolution" wrote that the inculcation of proper behavior is often achieved by ritual and myth. So that "throughout their lives, in speech, story, and song, all people sing the same tune" (Plato, Laws). To see an example of this, John Miller in his book, "A Crude Look at the Whole" writes that on the island of Bali, the need for coordinated cropping by farmers opened up "a niche for an elaborate religious institution with various shrines and temples tied to the irrigation systems." Joseph Henrich also described how religious rituals leveraged the reputations of prestigious individuals and created community bonds through synchronous movement, music, and dancing. This effectively standardized beliefs and increased cultural transmission across generations.
“Thus have I made as it were a small globe of the intellectual world, as truly and faithfully as I could discover.” - Francis Bacon (1605)
"You can't do much carpentry with your bare hands and you can't do much thinking with your bare brain." - Bo Dahlbom (unpublished, cited in Dennett, 2000)
"... one of the main functions of an analogy or model is to suggest extensions of the theory by considering extensions of the analogy, since more is known about the analogy than is known about the subject matter of the theory itself ... A collection of observable concepts in a purely formal hypothesis suggesting no analogy with anything would consequently not suggest either any directions for its own development.” - Mary Hesse (1952)
"Systems modelers say that we change paradigms by building a model of the system, which takes us outside the system and forces us to see it whole. I say that because my own paradigms have been changed that way." - Donella Meadows (Leverage Points)
Goal oriented processes, whether biological or social, are always made in reference to some kind of model, simulation, or semiotic scaffold, which corresponds with greater or lesser degree of accuracy to the world we inhabit. As Judea Pearl wrote in The Book of Why, "To speak of causality, and to interpret data, we must have a mental model of the world... Anytime you see a paper or a study that analyzes the data in a model-free way, you can be certain that the output of the study will merely summarize, and perhaps transform, but not interpret the data." According to Charlie Stross, “Consciousness seems to be a mechanism for recursively modeling internal states within a body.” Animals, such as humans, use their senses, their nervous system, to construct a model that allows them to optimize their living conditions. Philosophy is, in one sense, an attempt to “model the model”, and technology is providing us with a more direct route to do this via better sense data. These models are what we use to navigate and explore possibilities and understand our relationships. The so-called ‘simulacrum account of explanation’ suggests that we explain a phenomenon by constructing a model that fits the phenomenon. On this account, the model itself is the explanation we seek. It uncovers causal relations that hold between certain facts or processes. We spend a great deal of time building, testing, interpreting, comparing and revising these valuable tools. Think of models as gedanken experiments, parallel thought universes we can explore. They project complex objects onto a low-dimensional scale that allows us to extrapolate or interpolate within them. At some point extrapolations based on limited information will break down and result in paradoxes or conflicts. When this happens it becomes necessary to expose and then examine unconscious assumptions. Models are only models, not the thing in itself, so we can’t expect them to be truly right. But what’s amazing is how well they sometimes work.
From a semiotic perspective, we might say that models are an icon/index/symbol compound. The simplest models are primarily "rhematic iconic sinsigns", that is they are representations that stand for something else because they closely resemble its qualities. These simple models are among the least abstract of all signs. But metaphors, analogies, and models that have many interacting parts can become very complex, as in the case of mathematical models. Peirce held that mathematics is done by diagrammatic thinking, through the observation of, and experimentation on, diagrams. (Recently Arran Gare pointed out that Robert Rosen came to a compatible conclusion.) It is interesting to reflect how modeling, simulation, and mathematics have this close relationship and origin within foundational semiotic processes. Significant parts of scientific investigation are carried out on models rather than on reality itself because by studying a model we can discover features of, and ascertain facts about, the system the model stands for; in brief, models allow for surrogative reasoning. Once the model is built we have to use and manipulate it in order to elicit its secrets. Such dynamic models, which involve time, are simulations. From an anthropological viewpoint, simulations are often used to imitate 'real' events, people and things, ranging from rituals and objects representing supernatural entities and forces, to calendars, schedules, essay outlines, and computer simulations; they help us to ‘extend ourselves’, as it were. Humans, and indeed many animals as well, have used models and simulations (cosmologies, for example) for thousands of years to help us survive, understand the world, and order society. They are ubiquitous throughout history. Herbert Stachowiak postulated that “all cognition is cognition in models and by models”. Indeed, one's conscience or "inner voice" is itself a model that seeks to bring our actions in congruence with our thoughts. Paul Cobley, in Cultural Implications of Biosemiotics, wrote "Humans’ modeling explains the foundations of culture... ethics is a natural phenomenon arising out of human modeling." So it should come as no surprise that we need to engage with these cognitive tools all the more now. Historically, the level of engagement needed to sustain lasting change has only been achieved at the cultural level.
Let's explore the nexus between cultural anthropology (an enormously rich area) and modeling and simulation (also extensive). Gregory Bateson, Jesper Hoffmeyer, Jakob von Uexküll (umwelt), Robert Trivers, Terrence Deacon, and Joseph Henrich are just a few of the names who either have or are continuing to publish in this area. Doubtless many others are as well. But among these, who is applying this knowledge to contemporary problems in social and environmental health? To begin, let's consider how rituals, ceremonies, traditions, etc. within cultures function to provide an orienting cosmology which structures the physical and social lives of large numbers of people and influences the way we see things, our personalities, and our day-to-day activities in largely unconscious ways. So much so that when we sever ties to established traditional models and simulations, which can be a good thing to do insofar as they may be harmful, we also disrupt the beneficial regulation and cooperative capabilities that they have enabled.
Disruption comes with a cost, but it also offers an opportunity. New models and simulations can be created through an open process of discovery and a willingness to incorporate new knowledge and insights, as they arise. Since our point of view of things will always be rooted in a cultural model and worldview, we cannot float listless at sea for long. But disruption is coming hard and fast today. Social media, especially when manipulated against our will, has contributed to creating the conditions that have eroded confidence in any single model of reality, thereby handicapping our ability to address common problems and cooperate effectively. But in addition to harming us, these new tools, that are now a part of our cognitive assemblage, can also be used to improve models and simulations, as many researchers have shown (notably Alex Pentland in the "Red Balloon Challenge" contest, or the "Peacemaker" game for understanding complex conflicts).
Among these improved simulations are climate models that can accurately track numerous variables and generate startling predictions. Simply read one recent summary of this progress: “In the late 1970's, supercomputers performed about 16 billion computations a second. In contrast, the world's soon-to-be fastest computer coming online at the Oak Ridge National Laboratory in 2021 will perform 1.5 quintillion computations per second. Not only will computers of the future be capable of processing information on everything from the upper atmosphere to ocean currents and all the details in between — such as sea spray, dust, ice sheets and biogeochemical cycles — but they will be able to do so while capturing the ways humans influence the climate and how climate change influences humans.” Zeke Hausfather, lead author of a study published Wednesday by UC Berkeley, MIT, and NASA, found that the majority of climate simulation models have accurately predicted global heating for the past 50 years. He said “It is impossible to know exactly what human emissions will be in the future. Physics we can understand, it is a deterministic system; [but] future emissions [also] depend on human systems, which are not necessarily deterministic.” This is important; we can model and simulate deterministic physical systems, such as the solar system, but the future depends upon how we interact with those systems, and that can always change.
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| The Map is not the Territory. Harry Beck's map. |
The choices we make are determined by the mental models we hold in our heads for how things work. Instead of good or bad people, we have good or bad models for life and society which are shared through cultural transmission. The better these models are, the healthier our interactions with each other and the environment tend to be. Everyone gets a model handed to them at birth, and as they grow they decide in what ways to shape and change it, adding some things and modifying others. If a person starts off life with a very poor model, even though they may be a "good" person they may still make some bad choices with harsh consequences due to their faulty model. If they begin with a very good model, even if they are a "bad" person they may still make some good choices simply on the strengths of the mental model they inherited from others. Life is this process of continually refining our shared models and mental simulations of the world, upon which so much depends. Even our identities, our notions of who we are as individuals and hence our conceptions of well being, self worth, and how we relate to others, are formed based upon these models and simulations.
Maps and models
Schafer and Schiller write: “The brain builds, stores and uses mental maps. These models of the world enable us to navigate our surroundings, despite complex, changing environments—affording the flexibility to use shortcuts or detours as needed. Model building or mapmaking extends to more than physical space. Mental maps may exist at the core of many of our most “human” capacities, including memory, imagination, inferences, abstract reasoning and even the dynamics of social interactions, recording how close or distant one individual is to another and where that individual resides in a group’s social hierarchy. Biological relatedness, common group goals, the remembered history of favors and slights—all determine social proximity or distance. Relationships can be conceived of as coordinates in social space that are defined by the dimensions of hierarchy and affiliation. That the same mapping system may underlie navigation through space and time, reasoning, memory and imagination, and even social dynamics suggests that our ability to construct models of the world might be what makes us such adaptive learners. Fresh concepts can be related to older ideas. And a new acquaintance can reshape our social space. Models let us simulate possibilities and make predictions, all within the safety of our own heads, enabling us to navigate life itself.”
Models of Health
Too often people cause harm to each other and the planet we all have to share. A lot of the reason for that is people tend to get stuck in a way of doing things that might not work like it used to, if it ever worked well to begin with. We need to stop, and ask ourselves if it's time to change our habits, patterns, and models before they cause any more harm. An analogy would be a person who has a prediabetic condition. They have a mental model that tells them sugar tastes good. This model worked very well a long time ago when sugar was very hard to get. But today that's no longer the case. The store sells all the sugary drinks and ice cream we like to eat, and at affordable prices, so we can go there, buy it, and consume it daily. But now we know it's causing harm. Maybe our BMI has increased, and our metabolic functions are no longer normal. The doctor says we are on track for diabetes without a change of habits. Now we are faced with a choice. We can retain our mental model as is, and continue with our habits. A simulation based upon this model yields a predictable result when extended into the future. Or we can modify our models, avoid buying and consuming all that sugar, and forestall or even reverse our path to diabetes. We can go even further than that. If enough people realize the harm refined sugar is causing society in poor health and medical costs, we can make better regulations that reduce added sugar in foods, and make healthy alternatives more accessible and more affordable, and so on. Together we can update the models that society uses. This addresses the "evil" that has slowly crept into modern society due to placing the profit (generated from selling unhealthy products) over the well being of people. By promoting an improved model and simulation for how we want to live and conduct our lives, we can advance the public good, and make people's lives, including our own, better.
There are now very good scientific models incorporating knowledge of the myriad drivers of depression. Millions of people fight depression every year. With better tools for understanding how it works, we can prevent the loss of thousands to its tragic effects. We also have models for the stress response in humans, which is facilitated by the adrenal glands and controlled by a few cortical areas. This brain-adrenal connectome has implications for controlling cardiac funtion. Researchers have found that a chronic high level of daily stress releases cortisol into the bloodstream, a stress hormone that is particularly damaging to our delicate coronary artery cells.
According to the "medical model", medical treatment, wherever possible, should be directed at the underlying pathology. The biopsychosocial model later expanded this with a description of the complex interaction of biological factors (genetic, biochemical, etc.), psychological factors (mood, personality, behavior, etc.) and social factors (cultural, familial, socioeconomic, etc.), allowing for a broader intersection within the Nature versus Nurture debate. For any given pathology, which of these factors should be addressed? For example, a person may have a genetic predisposition for depression, but he or she must have social factors such as extreme stress at work and family life and psychological factors such as a perfectionistic tendencies which all trigger this genetic code for depression. Similarly in discussing climate change, we tend to focus on one or two contributing factors, such as the material conditions, while ignoring or minimizing the contribution of cultural, psychological, and philosophical factors. It’s time to reconsider our climate recovery model.
Models of pandemics
Dennis Carroll spent years studying infectious diseases. He formed a USAID program called PREDICT, where he guided research into viruses hiding and waiting to emerge. As he describes it, "PREDICT was a beautiful project. It was scientifically well executed. It was forward-leaning. But its scale was small. It discovered slightly more than 2,000 viruses. If you’re going to have a public health impact, finding 2,000 viruses out of a pool of 600,000, over 10 years, isn’t going to transform your ability to minimize public health risk. And PREDICT didn’t really navigate the second step in a critical equation—turning science into policy. We didn’t design it for that purpose. Also, even an annual budget of $20 million is not sufficient. You’d need about $100 million a year to carry out the kind of global program that would give us evidence to transform how we think about viral risk and how we should prepare for it. That’s what my new Global Virome Project aims to do. ...I’m an internationalist. Figure out how to care for our people. Pay attention to communities around the world that need assistance. We’re all part of the same ecosystem. This is a global issue. We either prepare for it and respond to it in the context of a global lens, or we don’t. If our preparations and responses are country-centric, we’re in for some serious trouble." (You can see Carroll in the Netflix documentary series "Pandemic".) Current models and simulations of the spread of SARS-CoV-2 predict several possible outcomes.
Epidemiological models and political games
An article in The Atlantic today reports "Epidemiologists routinely turn to models to predict the progression of an infectious disease. But sometimes people get mad when those models aren’t crystal balls. Why aren't they snapshots of the future? They describe a range of possibilities that are highly sensitive to our actions. So when an epidemiological model is believed and acted on, it can look like it was false. The range of predictions all depend on how people react. That such a variety of potential outcomes can come from a single epidemiological model may seem extreme and even counterintuitive. But that’s an intrinsic part of how they operate, because epidemics are especially sensitive to initial inputs and timing, and because epidemics grow exponentially. So if epidemiological models don’t give us certainty—and asking them to do so would be a big mistake—what good are they? Epidemiology gives us something more important: agency to identify and calibrate our actions with the goal of shaping our future. We can do this by pruning catastrophic branches of a tree of possibilities that lies before us. Models provide a way to see our potential futures ahead of time, and how that interacts with the choices we make today. Sometimes it looks like we overreacted. A near miss can make a model look false. But that’s not always what happened. It just means we won. And that’s why we model.
Rogers and Molteni describe how federal agencies like the Centers for Disease Control and Prevention and the National Institutes of Health have modeling teams, as do many universities. Since the 2009 outbreak of H1N1 influenza, researchers worldwide have increasingly relied on models and simulations informed by what little data they can find, and some reasoned inferences. But the ongoing catastrophe of testing for the virus means that no researcher in the United States has an overall number of infections that would be a reasonable starting point for untangling how rapidly the disease spreads. As with simulations of Earth’s changing climate or what happens when a nuclear bomb detonates in a city, the goal is to make an informed prediction—within a range of uncertainty—about the future. In the case of Covid-19, responding to those models may yet be the difference between global death tolls in the thousands or the millions. While our current models are imperfect, they’re better than flying blind—if you use them right. That's the key. Unfortunately, just as happens with models of climate change, the presentation of a range of possible futures in epidemiological models provides a lever for political opposition.
"After Governor Andrew Cuomo based a request for tens of thousands of ventilators on model projections, the president told television personality Sean Hannity, “I don't believe you need 40,000 or 30,000 ventilators.” He based that opinion, he said, on “a feeling.” Lisa Brandenburg, president of the University of Washington Medicine Hospitals and Clinics, would take the models over a feeling any day. Even before Covid-19, scientists had trouble getting policymakers to pay attention to their warnings. Now they can’t get enough data to make those warnings specific, and politicians are working to undermine what little the scientists are sure of. What was already a tragedy has evolved into a disaster, reaching toward catastrophe. And all of it was predictable."
Challenge prevailing beliefs
The Monthly Review writes: “Other than describing the wild food market in the typical orientalism, little effort has been expended on the most obvious of questions. How did the exotic food sector arrive at a standing where it could sell its wares alongside more traditional livestock in the largest market in Wuhan? ...Models such as the Imperial study explicitly limit the scope of analysis to narrowly tailored questions framed within the dominant social order. By design, they fail to capture the broader market forces driving outbreaks and the political decisions underlying interventions.” This is why we must interrogate our models. For if we do not, history will surely repeat itself.
From the Guardian: “Most leaders lack the discipline to do routine risk-based horizon scanning, and fewer still develop the requisite contingency plans. Even rarer is the leader who has the foresight to correctly identify the top threat far enough in advance to develop and implement those plans. ...But the Trump administration’s unprecedented indifference, even willful neglect, forced a catastrophic strategic surprise on to the American people. The White House detachment and nonchalance during the early stages of the coronavirus outbreak will be among the most costly decisions of any modern presidency. These officials were presented with a clear progression of warnings and crucial decision points far enough in advance that the country could have been far better prepared. But the way that they squandered the gifts of foresight and time should never be forgotten, nor should the reason they were squandered: Trump was initially wrong, so his inner circle promoted that wrongness rhetorically and with inadequate policies for far too long, and even today. Americans will now pay the price for decades.”
Models respond to salient features
As Aaron Bernstein pointed out, "if we want a robust response to a pandemic, we have to have the systems in place to do that". And as Jamie Margolin points out, the pandemic is proof that we can mobilize. We can quickly switch from a BAU model to a model which understands humanity is facing a common threat that doesn’t respect national boundaries, a model that values preparedness and a rapid response. This is the kind of model we need. The question Margolin asks is: Why didn’t we get it earlier? That likely depends on what we, individually and as a society, consider to be the salient features of our environment. Perhaps human evolution didn't adequately prepare us to respond to threats like climate disruption. There were few opportunities to understand the dynamics of climate change, properly appreciate the danger it represents, or practice a coordinated and effective response. Now compare this to our ability to recognize the signs of disease, which seems to trigger an immediate and automatic fear response. Transposing the response we have to a pandemic and applying it to climate disruption rests entirely on the strength of the analogy we can make between the two. If we leverage a sort of “pandemic model" of climate disruption, perhaps we can tap into this intuitive existential dread, and by adapting a “pandemic response template” for developing the social institutions and systems we need to tackle climate change, maybe we can improve our effectiveness in addressing these environmental problems. After all, evolution constantly appropriates body parts evolved for one purpose and adapts them for another (gills become mouths, legs become wings, etc.), so modifying social models by way of analogy seems entirely natural (pandemic response becomes climate response). It certainly helps that we now have the proof that rapid global behavioral change is possible.
Substance abuse, health care: facts and models
If we want to achieve meaningful goals, we need good models, and if we want good models, we need reliable facts. Einstein showed that no sequence of events can be metaphysically privileged – can be considered more real – than any other. But we have even more immediate concerns to address than investigating the limitations of metaphysics. At the 2020 Health Summit in Anchorage this week Alfgeir Kristjansson's presentation referenced the “social determinants” of health (SDOH), which do not receive enough attention, and Anthony Iton's excellent presentation. Preventing a problem always makes more sense than treating it later. Here are two examples. Cardiovascular disease is the leading cause of death in America, but many people with a low ejection fraction (EF) can improve it through exercise and other lifestyle changes. It is thought that the survival of preindustrial humans depended on moderate-intensity, endurance-like activity (e.g. hunting, gathering, and then farming). Research published in a 2019 paper titled "Selection of endurance capabilities and the trade-off between pressure and volume in the evolution of the human heart" provides evidence that the human heart in fact did evolve for this purpose (see also the "endurance running hypothesis"). Lifelong low blood pressure appears to be partly sustained by regular moderate-intensity endurance physical activity, whose decline in postindustrial societies likely contributes to the modern epidemic of heart disease. Kristjansson's presentation, however, addressed the Icelandic model for reducing substance use among teens. They focused on prevention rather than treatment, and abuse rates plummeted dramatically. "If the Icelandic model was adopted in other countries, it would benefit the general psychological and physical well-being of millions of kids, not to mention the coffers of healthcare agencies and broader society." Understanding the facts related to the SDOH, and using the appropriate models once these are uncovered, remains a significant challenge in much of the world today.
More Applications:
In a recent interview, Naomi Klein pointed out that although there had been widespread dissatisfaction within society, popular movements like Arab Spring and Occupy did not generate the kind of social changes their members aspired to because there wasn't "a clear demand of what the alternative to this failed model is". She went on to say "I think that in the intervening years so many people who are part of those movements have taken the responsibility of coming up with an alternative vision on an alternative plan really seriously. So now when we have one of those tipping moments I don't think we are going to make the same mistake of opening up a vacuum that somebody else can exploit". If social change is to be real and lasting, we cannot avoid engaging with these models. Revolutionaries of all kinds throughout history have advocated the adoption of alternative models, and their success is generally improved when such models are carefully thought out. Revolution without an alternative model, however, tends to simply perpetuate the conditions that generated discontent to begin with.
Greta Thunberg sees the world through a different model than most of us do. Combine that with a supportive family and community, access to rich educational resources, the use of effective messaging and media attention, and a public audience ready and eager to hear her and her message, she quickly catapulted into the international spotlight. What scares the powerful most of all is her tenacious and uncompromising vision of a different way of living, which is justifiably critical of the contemporary model: “I couldn’t understand how that could exist, that existential threat, and yet we didn’t prioritize it,” she says. “I was maybe in a bit of denial, like, ‘That can’t be happening, because if that were happening, then the politicians would be taking care of it.’” Thunberg’s Asperger’s diagnosis helped explain why she had such a powerful reaction to learning about the climate crisis. Because she doesn’t process information in the same way neurotypical people do, she could not compartmentalize the fact that her planet was in peril. ...Some of her opponents have attacked her personally. So many people have made death threats against her family that she is now often protected by police when she travels. But for the most part, she sees the global backlash as evidence that the climate strikers have hit a nerve. “I think that it’s a good sign actually,” she says. “Because that shows we are actually making a difference and they see us as a threat.” One model is being succeeded by another.
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| Computational science |
Education can often serve to amplify our predispositions, at least when we reason like lawyers and less like scientists. In regard to climate change, it's been shown that the more education that Democrats and Republicans have, the more their beliefs tend to diverge. This appears to ignore exactly what that "more education" consisted of. For example, was it a degree in business, politics, engineering, ecology, physics, etc.? And what was the actual percentage of individuals who are on either side of the divergence? In the case of climate scientists, they diverge with over 99% supportive of the consensus and less than one percent disagreeing. That suggests to me we can conclude education has a net positive effect on our ability to think through questions effectively and arrive at factual conclusions. However it is when facts conflict with the models of reality that we tend to hold without reflective consideration that we are more likely to reject or distort information. We want new knowledge to conform to our preferred worldview, but effective thinking involves critically testing these models. If they are not subject to possible revision, we cannot think rationally.
As Howard Gabennesch pointed out, since our knowledge on any subject is fallible, incomplete, and subject to change, when we use our models and simulations, we do so with the understanding that these are provisional (this is the key to skeptical, critical thinking skills). Keeping this in mind, recently Vincent Liegey said “It is interesting to analyze how GDP became a religion: A central tool used by politicians, states, economists and by a lot of journalists – like a totem. Like something that should measure what is a successful or unsuccessful society or life.” We have seen how the religious promotion of GDP and market fundamentalist polices above issues of environmental and social justice have exacerbated climate change. This model is simply no longer tenable as it exists today without risking significant future harm. So have we forgotten that economic models are provisional? Even religions can, and often do, change when it’s time for a better model.
Today the calls for system change are everywhere; people feel fearful, insecure, and anxious. In a recent interview, Jason Moore said we need to ask questions that connect oppression, sustainability, and the political economy of capitalism. Models of "environmental holism" and "social holism" have always excluded a lot. But now we're at a moment when we can begin to put these together within a larger, expanded framework. (From this perspective that he notes the phrase “anthropogenic climate change” is really just blaming the victims of exploitation, violence, and poverty. More accurately, we are experiencing a “capitalogenic climate crisis”.) Systems theory views the world as a complex system of interconnected parts. One can make simplified representations (models) of the system in order to conceptualize it and to predict or influence its future behavior. Systems modeling is used both in engineering and in social sciences to define the structure and behavior of systems. In "Wall Street Is a Way of Organizing Nature: An Interview with Jason Moore", Moore describes the growth and influence of capital accumulation:
Capitalism is the gravitational field within which the “big picture” historical movements of the past five centuries have unfolded, and at its vortex is the commodity. Capital accumulation survives by turning the rest of the world into a commodity, a vast storehouse of interchangeable parts. In doing so, it undermines the very webs of life that sustain its project. The accumulation of capital doesn’t explain everything, but it’s hard to say much about the history of the past five centuries without understanding the contradictions of accumulation. Civilizations long before capitalism expanded across space, and drew in vital resources necessary for war, commerce, and culture. Resource frontiers are an enduring feature of human civilization. For all their variation, there was a common dynamic. Populations grew within established zones of settlement leading to various overflows of people into new frontiers. Commerce then followed these settlement frontiers. With the rise of capitalism after 1450, however, we see something radically different. We see a shift from resource frontiers to commodity frontiers. Instead of commerce following people as had been the case in premodern civilizations, people now followed the commodity. Financialization, shifts in family structure, the emergence of new racial orders, colonialism and imperialism, industrialization, social revolutions and workers’ movements – these are all world-ecological processes and projects, all with powerful visions for re-ordering human- and extra-human natures. Wall Street is a way of organizing nature, differently but no less directly than a farm, a managed forest, a factory, a market, a financial center, or an empire. Capitalism, in other words, does not have an ecological regime; it is an ecological regime.
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| Address root causes or symptoms? |
At the end of the day, reality has to be the ultimate test, not “fairy tales of eternal economic growth”, as Greta Thunberg put it. Any model that places the economy at the top of the food chain, where the sole purpose of the environment is as an input to production, and it is assumed that growth will translate to benefits for all, is incapable of responding to environmental crises. And so such a model must be restructured or replaced. This is why Stiglitz is suggesting a rather modest adjustment to capitalism: change our primary measurement tool. Will that alone be sufficient to place the economy in its proper role, dependent upon society and the natural world (instead of the other way around)? Of course not. But this is an important first step. As Foucault once wrote “In political thought and analysis, we still have not cut off the head of the king.” In economic thought and analysis, GDP is still the king. We have not done our job yet.
In 1972 the first edition of "The Limits to Growth" analyzed the environmental sustainability problem using a system dynamics model. The widely influential book predicted that the limits to growth on this planet will be reached some time in the 21st century, largely due to the effects of systemic resistance to change. Sources of social resistance included pursuing narrow national, corporate, or individual self-interests (reflected in values, habits, and mental models). This resistance further decouples the human system from the greater system it lives within: the environment. If we use structural modeling to discover systemic root causes for both the change resistance and proper coupling subproblems, then higher leverage points for resolving them can be found. Solutions then push on these leverage points in the system. Engaging with these cognitive tools at the level of cultural models can uncover the root of the paradigm of unlimited economic growth and exploitation, allowing us to transition from an "expand, conquer, consume" mentality to a sort of "contract, cooperate, cultivate" story of living in harmony with the Earth, as promoted by ecological civilization. There are many other alternative models (such as the slow movement and degrowth). How do alternative models function? What can we learn?
When employers seek to consistently exclude any consideration of basic human needs, what kind of model and simulation are they running within corporate HR? How can they change? (Perhaps they can begin by reading Michael Ende's book Momo.) The bottom line is that their models are far too narrow. It may appear that they are improving their competitiveness within a cutthroat business marketplace, but the corrosive effects these practices have on the larger society suggest they are also taking us down a dark path. We can't ignore this. Gabriel Winant's article describes how many employers now “demand a workforce that can think, talk, feel, and pick stuff up like humans—but with as few needs outside of work as robots. They insist their workers amputate the messy human bits of themselves — family, hunger, thirst, emotions, the need to make rent, sickness, fatigue, boredom, depression, traffic...”
Some models are better than others
In "The Secret of Our Success", Joseph Henrich wrote "once humans became good cultural learners, they needed to locate and learn from the best models". In this context, he is referring to the skilled members of one's social group. (Who are your role models?) In "Solving for Pattern", Wendell Berry quoted Sir Albert Howard when he said that a good farm is an analogue of the forest which “manures itself.” A good farm is modeled on nature, as is the development of an ecological civilization. Nature is perennially viewed to be the best model we have. Slavoj Zizek, in the article Defenders of the Faith, wrote "More than a century ago, in "The Brothers Karamazov" and other works, Dostoyevsky warned against the dangers of godless moral nihilism, arguing in essence that if God doesn't exist, then everything is permitted... This argument couldn't have been more wrong: the lesson of today's terrorism is that if God exists, then everything, including blowing up thousands of innocent bystanders, is permitted — at least to those who claim to act directly on behalf of God, since, clearly, a direct link to God justifies the violation of any merely human constraints and considerations." (To balance that out, it’s important to point out that “engaged spirituality” has been a positive influence when we consider Ruskin, Tolstoy, Gandhi, MLK, and Thich Nhat Hanh.) In 2013 David Simon gave a presentation at the "Festival for Dangerous Ideas." We can end war if we wanted, all we have to do is end the monetization of our legislative branch (what others call a "dollarocracy" - one dollar one vote) so we get real effective democratic representation in government instead of (what David Simon calls) our currently inert government.
Chris Fisher wrote, “As archaeologists, we are trained to be time travelers: imagining the world as it existed in the past, seeing the world as it is today, and modeling change into the future. We are the ideal scientists to build an Earth Archive as a legacy for future generations. Those future generations will have different technologies and tools at their disposal, and will want to ask different questions. No one knows exactly how they will use this data, but it will surely be useful.” If we ask which models and simulations are meaningful to ourselves alone, but go no further, the real value and potential is lost. The question is, which of all these models and simulations are most meaningful to others? Which of these are meaningful within our larger associations? Where do they coincide and where do they diverge? Only by carefully studying and learning these things, only by seeing through the eyes of another, by viewing the world as those who have cared for us and whom we care for in return, will we discover what is truly meaningful. So here's a second experiment in trying to promote greater interaction and engagement with "modeling and simulation" tools (in addition to the DIY carbon tax described above): identify the models we use, what they consist of, where these coincide with and diverge from each other, and how they influence our relationships.
This takes us back through cultural anthropology and the significance of "mindreading" in the evolution of our species. "According to the 'Deep Social Mind' theory, humans have become cognitively adapted to reflexivity and intersubjectivity: as a species, we are well-adapted to read the minds of trusted others while at the same time assisting those others in reading our own minds. I read your mind as you are reading mine. Therefore, between us, we can gain an awareness of our own minds as if from the outside: my mental states as these are reflected in yours and yours as they are reflected in mine. In that sense, if this argument is accepted, our minds mutually interpenetrate. 'Mind' in the human sense is not locked inside this or that skull but instead is relational, stretching between us." But why this "enactive" process of co-production? Some have speculated a deceptive, indeed "Machiavellian" purpose behind this evolved capacity to read minds, which would improve our ability to manipulate others. But the cooperative benefits are equally apparent. The implications for interpenetrating models and shared simulations are profoundly important, and should be made more explicit for applications of cultural anthropology to contemporary global issues.
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| A worldview |
Robert Rosen argued that mathematics should be understood as a way of modeling, and modeling is really only a special instance of analogical thinking, ubiquitous in everyday life. Modeling, Rosen argued, "is the art of bringing entailment structures into congruence". He continued, "It is an art, just as surely as poetry, music, and painting are. Indeed, the essence of art is that, at root, it rests on the unentailed, on the intuitive leap". (Rosen 1991, p.152) Rosen highlighted the central place models have in all living systems, including societies where models are central to defining themselves and their place in the world. Once this is understood and it is appreciated that with life, including all human organizations, modeling is ubiquitous, Rosen's work on modeling should be seen as relevant to societies and the functioning of democracies. What is required is an interrogation of the models that societies have of themselves and their relationship to their ambience or environments.In The Diversity of Life (1992), Edward O. Wilson wrote, "The best of science doesn’t consist of mathematical models and experiments, as textbooks make it seem. Those come later. It springs fresh from a more primitive mode of thought, wherein the hunter’s mind weaves ideas from old facts and fresh metaphors and the scrambled crazy images of things recently seen. To move forward is to concoct new patterns of thought, which in turn dictate the design of the models and experiments.” And Philip Henshaw, in Life’s Hidden Resources for Learning (2008), describes how, instead of taking our abstract models as reality or discarding them, we should be using these to reveal life. As he put it, after you adopt your model, keep both your model and observations going side by side. Then it becomes a sensitive detector of differences and can highlight the life around you. This continues the creative thought processes that occur when we first ‘make sense’ of things. (Interestingly, Henshaw is highly critical of the idea that the engine of evolution is the struggle for survival. He argues that organisms for the most part are "engaged in resourceful exploration, using what they find while avoiding conflict".) It is because our models so deeply influence society that understanding their origins and limitations is all the more important.
It is not only the sciences that are dominated by assumptions deriving from Newtonian scientific models, these assumptions dominate economics, as a consequence of which societies have acted on and continue to act on fundamentally defective models of themselves. It is through reformulating their models that societies form and transform themselves, and Judith Rosen in her preface to "Anticipatory Systems" pointed out that this is now essential if we are to work out how to choose "the most optimal pathways towards a healthy and sustainable future".
Expectation, Anticipation, Prediction
In “Expecting the Earth: Life, Culture, Biosemiotics”, Wendy Wheeler wrote: “The biosphere, as well as the semiosphere, is built upon expectations. One important meaning of legs (i.e. their function) is 'for walking'. The child in the womb has never walked, yet biological life incorporates into its processes legs and the expectation of precisely such a relation with the Earth yet to come... Expectations are an important part of what it means to be alive. No life walks or crawls or swims around expecting nothing. We all expect the Earth to be there when we put a foot out to walk or a fin to swim. We all expect the air to be there to breathe each day... In what more detailed sense might it be right to say that we, and all living organisms, are 'expecting the Earth'? What sort of expectations might this involve?"
Postscripts:
Treat the disease while you manage the symptoms
Our models of the world are inducing so much anxiety that we are increasingly turning to the support of organizational aids to manage our lives and coordinate with others. Why? Examples given in this article include tracking New Year’s resolutions, classes, jobs, assignments, deadlines, chores, self-care, fitness goals, and family events. None of these are by any means “new”, perhaps the only thing that may be new is the perfusion (or illusion) of choices that are now available. It is good to be organized, but we need to treat the disease and not just manage the symptoms. Emma Lee said “Planning has changed my life for the better. I write a lot more, I think more clearly, I’m more emotionally stable. It’s made a huge impact on everything.” Gretchen Klobucar said “People come to [planning] for a variety of reasons. In most cases, they’re seeking to manage a role or expectation they’re anxious about. They want to be able to plan so they can live the life they envision.”
Models of proper mental hygiene
Jim Kwik highlighted how the form of the media we consume influences our mental states: “When you wake up you’re in this theta alpha state and you’re highly suggestible. Every like, comment, share, you get this dopamine fix and it’s literally rewiring your brain. What you’re smart device is doing especially if that’s the first thing you grab when you wake up and you’re in this alpha theta state, is rewiring your brain to be distracted.” As Srinivas Rao explains: "You can either start you day with junk food for the brain (the internet, distracting apps, etc) or you can start the day with healthy food for the brain (reading, meditation, journaling, exercising, etc). Don't create a self imposed handicap. A few simple recommendations: Don’t use your devices in the morning, set aside 20 minutes to meditate, and focus an hour a day on uninterrupted creation time." Interestingly, many productive people follow similar advice. Karl Friston, for example, "does not own a mobile phone, and though he's very active on email within certain hours of the day, he limits other forms of electronic access, and generally does not utter a word before noon. He protects his time by “sticking rigidly to a diary, and making sure that there's somebody else in charge of the diary who knows the formula and can regiment it.” Regimented routine is his way of creating a cocoon around himself despite all these demands on his time—a Markov blanket, he calls it—in which to minimize the free energy of distractions, complexity, and avoidable uncertainty. Our growing impatience and distractibility are failed adaptations to the growing uncertainty of a world filled with more information than we can metabolize."
Mind over Matter
What is the effect of our mind on our bodies? The mind has a propensity to make predictions, and then ensure those predictions come to pass. “This [idea of expectation-based bodily response] is an evolved mechanism that allows us to capitalize on untapped resources at critical points in our existence,” Christopher Beedie says. The chemistry of expectation and belief is also the world of placebo, which is the effect of one’s beliefs on their body. These effects are chemical, employing things like dopamine, endogenous opioids, serotonin, and other chemicals your brain keeps on hand in case it needs to adjust what’s happening in the body. In his book, Suggestible You, Erik Vance talked to scientists around the world who investigate placebos, internal pharmacies, hypnosis, and the power of belief on the body and mind. One of his favorite quotes came from Alia Crum, a psychologist at Stanford. “I don’t think the power of mind is limitless,” she said. “But I do think we don’t yet know where those limits are.”
Reactance and Comparative modeling
DJ Khaled, the one-man internet meme, is known for warning his tens of millions of social media followers about a group of villains he calls “they.” “They don’t want you motivated. They don’t want you inspired,” he blares on camera. “They don’t want you to win,” he warns. But who are they? Like so many things, reactance is a double edged sword. We definitely must react, so long as we know who the real enemies are. Eliciting reactance has been used successfully in public health efforts, so I wonder: How can reactance be used effectively in climate change and other environmental efforts, which lie at the root of all public health? To me "they" are the models premised on myopic greed and ignorance. They lie in wait, ready to insinuate themselves into our lives and communities when we let down our vigilance. And they become more clear when we engage in comparative scenarios modeling. I can briefly sketch the sort of behavior model we would like and compare it to the problematic model that we find ourselves within, bringing the contrast between the two into stark relief. This illuminates who "they" are and allows us to confront them. Comparative modeling can also help identify models with less temporal discounting and those that promote greater shared experiences of social value.
Mental models and mindfulness
In their paper Mindfulness: A Proposed Operational Definition the authors write: "Much of cognition occurs in the service of goals, comparing what is with what is desired, and much of our thoughts and behaviors function in the service of reducing any discrepancies. When there is a discrepancy, negative affect occurs (e.g., fear, frustration) setting in motion cognitive and behavioral sequences in an attempt to move the current state of affairs closer to one’s goals, desires, and preferences. If the discrepancy is reduced, then the mind can exit this mode and a feeling of well-being will follow until another discrepancy is detected, again setting this sequence in motion. When goals cannot be met, and especially if the goal is afforded high value, then the mind will continue to dwell on the discrepancy and search for potential strategies for avoiding anticipated future negative events. This can lead to the maintenance or heightening of anxiety and escalate a spiraling cycle of dysphoric affect that can eventually lead to a major depressive episode. Rumination will continue until the person either satisfies or gives up the goal. Thus, disengaging from one’s goals [by establishing a reflective self awareness] should facilitate a release from ruminative thinking and thereby reduce vulnerability to certain forms of psychopathology." As Thomas Metzinger said, we should not be forced to consciously identify with thwarted or frustrated preferences via models from which we cannot effectively distance ourselves (and interrogate if need be, whether these models are personal or suprapersonal).
This is where comparative modeling, which Robert Rosen discussed at length (he called it the "modeling relation"), can address these forms of psychopathology. Rosen argued that modeling "is the art of bringing entailment structures into congruence", which is to say that it is all about reducing discrepancy. When we compare "what is with what is desired", we are comparing two different systems, reality and our desired model of reality. What the paper's authors suggest is that since the discrepancies we observe by means of this comparison can lead to anxiety, rumination, and depression, the mindfulness approach of recognizing and accepting these mental events as comparative modeling processes can be therapeutic. In order to reduce the anxiety I expose myself to, I need a position from which to manage the discrepancy between "what is" and "what is desired". The process for exploring counterfactual scenarios, and possibly later adopting them, begins by comparing at least two different models: a control model consistent with current patterns (what is), and one or more introduced new models congruent with a goal (what is desired). I can then ask myself the question: "What if, instead of the status quo model, I followed one of these new models? What would I do differently? How would things change?" This self reflective thought exercise of mindfulness sheds light on the implicit models we use that influence our choices, behaviors, and mental health every day, allowing us to work with them in a healthier way.
In "Life Itself" Rosen wrote "Category Theory comprises in fact the general theory of formal modeling, the comparison of different modes of inferential or entailment structures. Moreover, it is a stratified or hierarchical structure, without limit. The lowest level, which is familiarly understood by Category Theory is, as I have said, a comparison of different kinds of entailment in different formalisms. The next level is, roughly, the comparison of comparisons. The next level is the comparison of these, and so on." (54) In Anticipatory Systems (2nd Ed.) he wrote "The study of models is the study of man. The preservation of models is the preservation of self. A change in models is a change of identity. The identification of one's self with one's models explains, perhaps, why human beings are so often willing to die; i.e. to suffer biological extinction, rather than change their models, and why suicide is so often, and so paradoxically, an ultimate act of self-preservation." (370)
Monkey mind makes mental models
"Monkey mind" is an archetype, a term for the restless, capricious, fanciful, inconstant, confused, indecisive, and uncontrollable characteristics of much of our mental life and inner narrative thought. Our minds tend toward distraction and negligence, anxiety and forgetfulness, leaping from one thought to the next, in short, our minds are often disordered and irrational. And yet despite this, somehow they manage to make sense of things. They produce and interpret coherent narratives. Monkey minds develop, deploy, modify, and use complex models that allow us to anticipate and respond to what is anticipated. Robert Rosen once wrote that modeling is an art, whose essence is the "intuitive leap". If that is true, and complex models rely on the intuitive leap, perhaps we should not grow so impatient and chastise our monkey minds when, from time to time, they seem entirely intractable. For this apparent flaw may also be the source of their greatest strength. Few creatures are more capable of taking great leaps than monkey. Incidentally, Rosen's statement has support from Whitehead, who wrote "Philosophy is the search for premises. It is not deduction. Such deductions as occur are for the purpose of testing the starting-points by the evidence of the conclusions." And from E. O. Wilson, who wrote that the design of models "springs fresh from a more primitive mode of thought, wherein the hunter’s mind weaves ideas from old facts and fresh metaphors and the scrambled crazy images of things recently seen."
Models explaining causality and models describing behavior
Spyridon Koutroufinis: “One way to consider the essential difference between theoretical and systems biology is to make a clear discrimination between two kinds of models. First, there are models for explaining how the behavior of a system is generated. Those models are developed for explaining the internal causality of a system. Newton’s model of the solar system, for example, qualifies as a model that aims at explaining the causal relations between celestial bodies. Second, there are models that aim at describing the known behavior of a system, so that predictions of new behaviors emerging under new conditions can be made. The ancient astronomy that was based on the mathematics of epicycles provided a model describing the behavior of the solar system without explaining the underlying causality (gravitational attraction). Systems biology may content itself with making models that predict the behavior of biological systems in a way that supports the development of new biomedical applications. In contrast, the role of theoretical biology should be to suggest models that explain the causality of organisms.”
Model-Dependent Realism
Stephen Hawking and Leonard Mlodinow in "The Grand Design" (page 172) wrote, "Our brains interpret the input from our sensory organs by making a model of the outside world. We form mental concepts of our home, trees, other people, the electricity that flows from wall sockets, atoms, molecules, and other universes. ...The brain is so good at model building that if people are fitted with glasses that turn the images in their eyes upside down, their brains, after a time, change the model so that they again see the world the right way up…” Paul Austin Murphy commented, “Yes, reality-as-it-is-in-itself clearly exists. But that doesn’t mean that we can access (or describe) it as it is in itself. After all, contingent brains (with their contingent “pictures”) and persons are doing the assessing and describing. And precisely because of that, a perfect model or theory will always be out of the question." As Hawking writes, “these mental concepts are the only reality we can know. There is no model-independent test of reality.”
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| Based on Rosen's fig. in Anticipatory Systems |
Howard Pattee wrote, “All models are incomplete in the sense that all possible observables cannot be consistently incorporated into a single model. Therefore, we believe in the necessity of multiple alternative models to understand complex systems.” How do these models work? “We encode natural systems into formal models such that the inferences or theorems we can elicit within these formal models become predictions about the natural systems” which can then be verified by further observation. See also these excellent slides by Judith Rosen.
Biosemiotics and Modeling
Arran Gare presented a paper at the annual Biosemiotics Gathering in Moscow this year titled Biosemiosis and Causation: Defending Biosemiotics Through Rosen’s Theoretical Biology. When I realized that few people have taken modeling more seriously than Rosen, who looked deeply into how models allow us to anticipate the future, I decided to read that paper again. Throughout Gare advances his main thesis, which is that Rosen’s work concurs with Peirce’s philosophy and biosemiotics in a number of ways. These two paragraphs really stood out:
It is important to emphasise that Rosen, like Schelling, was totally rejecting Cartesian dualism, so that organism’s ‘ambience’ as he characterized its immediate environment, was not seen as totally separate from it, but as a differentiation within a broader process by which the organism separates itself and maintains this separation within this process, in so doing, dividing the subjective from the objective. To do this, the organism has to maintain a model of itself, again with this model being part of this process while being partially autonomous and having this autonomy maintained. The model as the condition for the organism to differentiate itself from the ambient environment, anticipating developments in this environment and in itself and responding to what has been anticipated, can be conceived as a complex sign facilitating the production of more specific signs involved in a process of distinguishing significant aspects within the organism and within its ambient environment, anticipating and then responding to what is anticipated by constraining activity in the present. Doing so organisms produce chemicals, and beyond this can grow, move, and in some cases, think and engage in critical dialogue. This ‘activity’ involves creating, maintaining, modifying and then reproducing structures which make such semiotic ‘activity’ possible. This ‘activity’ in turn creates, maintains, modifies and reproduces these structures, including codes, cognitive structures and models. What is responded to and to some extent causes the response can be characterized as the ‘Dynamical Object’, following Peirce, but following Schelling, would be better characterized as the ‘dynamical process’, a ‘community of causation’ that includes the differentiation by the organism from its environment and also what is differentiated in this environment.
Human semiosis includes everyday practical activities including transformations of the physical world, the production of goods, speech acts, the production and interpretation of narratives, and the development, deployment and utilization of more abstract models, including mathematical and other scientific models, openning up new levels of freedom. ‘Subjects’ and worlds of Immediate Objects co-emerge with the capacity of organisms for greater anticipation involving more complex models, more complexly differentiated worlds, and greater capacity to respond to what is anticipated, and also a greater capacity to modify their models and their worlds. The development of human culture characterised by ‘with’ worlds (Mitwelten) or life-worlds (Lebenswelten) involving the dialectics of labour, recognition and representation, again being components of each other without being reducible to each other, magnify the possibilities for freedom and creative semiosis. These in turn make possible reflexivity, generating ‘self’ worlds (Eigenwelten) in which people come to understand themselves as individuals living out stories and taking responsibility for themselves and their communities.What models are we transmitting to future generations?
All our vain ambitions to colonize new worlds (which sounds disturbingly all too familiar) will be for naught so long as we ignore the harm we cause to the one we have. Earth’s past, the world we knew, is surely gone. And even the likes of today, as troubled as they are, will not be seen again for a very long time. At this point, all we can do is try to minimize the harm. Reversing it is far more difficult. Perhaps the best thing we can do is pass on the best models we have to help guide future generations in meeting the challenges they will face. They will hopefully take and improve upon these as they are able. Gare put this another way when he wrote "the model of the original organism is bequeathed to its progeny functioning as a sign of the progeny’s environment, and the developing progeny is an interpretant". When I look back at ages gone by, to the thought leaders who came before us, regardless of what other titles and positions they held, I see people who deeply considered the models contemporary to their time and place. People who questioned received wisdom and advanced radical notions, promulgated new ideas, and formulated new models, putting these into practice as best they could. Succeeding generations look back upon them, sometimes with admiration and sometimes more critically.
New models are always a threat to established dogma and ideology. So while Thomas à Kempis didn’t rock the boat when he wrote “The Imitation of Christ”, which was essentially a distillation of the Christian model for life, Baltasar Gracián encountered more resistance with his critical scholarship (he is best known for “Practical Wisdom for Perilous Times”). These authors lived hundreds of years ago. Far more recently, in 1954, Scott Nearing co-authored with his wife, Helen, “Living the Good Life: How to Live Simply and Sanely in a Troubled World”, in which he advocated a modern-day "homesteading” model that has continued to resonate with people today. Today I’m reading “Japanese Philosophy: A Sourcebook”. Within the space of 1340 dense pages it records the evolution of cultural models in Japan. Near the beginning, on page 51, the story of Kūkai is recounted. He “was struck by the alternative model of knowing implied in the esoteric text” of the Mahāvairocana sutra and later went on to found the Japanese Shingon school of esoteric Buddhism. This cemented his reputation and made him arguably the most famous Buddhist figure in Japan... So I ask again: What models are we transmitting to future generations to help guide them in meeting the challenges they will face?
The Nordic Model
In his Op-ed in the New York Times today, Capitalism and ‘Culturecide’, Ai Weiwei writes that "Extraction of profit from slave labor is not new; the main difference today is that the extraction is happening in distant countries." Do the protests in Hong Kong signal a global weakening of democratic values? He suggests they do. Are the concentration camps in Xinjiang supported by global corporations who benefit from the arrangement? He points out that yes, they do. What does this say about our model of civilization? Not so long ago, during the 2016 presidential election, the "Nordic model" of government was frequently brought up. And with Bernie Sanders in the race the for American presidency once again four years later, it may receive the same attention. At that time an article by Ann Jones described it thus: "the Nordic model is a smart and simple system that starts with a deep commitment to equality and democracy. That’s two concepts combined in a single goal because, as far as they’re concerned, you can’t have one without the other." Ai Weiwei's article proves once again that this is more true than any of us likely appreciate. Will we sacrifice our commitment to equality and democratic values in exchange for the illusions of market fundamentalism? I don't think we can afford to. The strengths and weaknesses of our political and economic models will determine whether our values are retained or discarded. Ignoring that relationship comes at too high a cost.
Rom Coles on political philosophy
Having read, just last July, some of Arran Gare’s work (another fine Australian!), I’m reading this article through an interpretive lens consisting, among other things, of various ideas about the function of social models and the 'Deep Social Mind' theory, according to which humans have become cognitively adapted to reflexivity and intersubjectivity. So approaching it from that angle, I think this article does a great job of highlighting the importance of not just understanding how we relate to our models (ecological, political, or otherwise), but also the importance of learning about how other people relate to their models, and crucially putting these two together, discovering how we should relate to each other in light of both their and our models, understanding where these coincide with and diverge from each other. Coles‘ use of the smart grid analogy to illuminate certain aspects of political action that have either been neglected or underused was an inspired choice. And I think it is effective. This might be just the sort of forum conducive to the process of model interrogation Gare and Rosen consider essential for a functioning democracy. Coles writes:
The inferno of the living continues to burn with a fury across the East Coast of Australia, home for tens of thousands of years to Aboriginal peoples. We offer our respect to Elders, past, present and future, who have cultivated countless modes of understanding and living responsively. One of the most vital practices in relational organising is listening carefully to each other share experiences about the challenges created by the dominant political economic order. In this process, we begin not only to understand others. We gain a sense of how others feel the world. What specific issues are making people’s everyday lives unliveable now? (Like buildings that bake people in heat waves, fires that threaten communities, poorer neighbourhoods consistently located in flood zones, myriad aspects of food insecurity, and so on.) ...Instead of being guided so thoroughly by the image of a bullhorn, we might also imagine our actions together as collectively manifesting large, powerful ears, as well. The substantial power of many movements has come in large part from listening attentively to others, as well as from loud dramatic expression. Imagine if, in addition to shouting slogans and “speaking truth to power,” activists sought to create potent performances that engage bystanders, not as a passive audience, but as fellow citizen-participants to be invited, welcomed and curiously engaged in intense — but open-ended and dialogical — dramas around, for example, climate emergency:
* How is it affecting our lives, the places we love, the futures of our children?
* How is this making people feel?
* How might we stop the madness and create a better world together?
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| Model of depression |
If I ever thought changing my models would be easy or result in immediate observable changes, I was wrong. Why doesn't it? Why is change hard? One reason is because the environment remains the same. New habits need a supportive environment to take root and grow in. Changes in our models require that we make corresponding structural changes in our habits and environments. There is no magic. The same goes for political and economic systems. Recently Warren Buffett said that companies cannot be moral arbiters. Government must create the rules. Business is not about ethics, but about profit. Buffett would have invested in coal if it was profitable. This is, of course, in direct contradiction with most of what corporate America claims. Predictably, their public relations campaign wants to make you think they are a force for good. Plenty of people have been conned into believing that 'free markets' can solve every kind of problem, when in fact they cause many of our biggest issues when not kept in check. There is no magic.
This is related, though somewhat tangentially, to what Jesper Hoffmeyer describes in "The Semiotics of Nature" as "models of embodiment – i.e., models where the bodily anchoring of cognitive or biological functionality are seen as essential to that functionality". As Søren Brier says, we must recognize that the "social and psychological system of emotions, willpower and meaning are just as real as the mechanical system... it is no longer viable to model nature as purely mechanical or mind as only computational". A focus on embodiment, and the connections between emotion and matter, is fertile ground in contemporary scholarship.
In a speech he gave in 1994, Charlie Munger (Warren Buffett’s investment partner) summed up his approach to practical wisdom through understanding mental models by saying: “Well, the first rule is that you can’t really know anything if you just remember isolated facts and try and bang ’em back. If the facts don’t hang together on a latticework of theory, you don’t have them in a usable form. You’ve got to have models in your head. And you’ve got to array your experience both vicarious and direct on this latticework of models. You may have noticed students who just try to remember and pound back what is remembered. Well, they fail in school and in life. You’ve got to hang experience on a latticework of models in your head.”
Circular economies presuppose circular models
Jevon's paradox occurs when greater efficiency allows consumption to occur proportional to rising demand. One would think demand would eventually taper and flatten out (however that is highly dependent upon other factors). The problem is consumption and demand, not efficiency per se. Consumption can partially be addressed through material substitutions (for example, dietary choices). And demand can be addressed through natural demographic transitions and better models that couple the human system with the greater system it lives within: the environment. We need more interconnected models for all aspects of society (economic, resource use, education, etc.). So while efficiency and resource substitutions can prolong economic growth and reduce its environmental impacts, what we would benefit from most is better modeling, which illuminates how limits are an inherent part of any particular system. All systems have limits, they just draw them differently. And of course, our current human-planet system is breaking down due to exceeding the limits we blithely ignore, even at the highest levels of governance. The challenge is to design a closed-loop system that will allow a high quality life for all members of our ecosphere without exceeding system limits. Any system model that is unable to close the information loop on reality has absolutely no hope of closing the physical loop on energy and materials.
As Michael Braungart and William McDonough wrote on the subject of industrial ecology: “Human beings don’t have a pollution problem; they have a design problem. If humans were to devise products, tools, furniture, homes, factories, and cities more intelligently from the start, they wouldn’t even need to think in terms of waste, or contamination, or scarcity. Good design would allow for abundance, endless reuse, and pleasure.” That's the techno-utopian idea in a nutshell, focused on closing the physical loop. But again, implicit to that perspective is the requirement to close the information loop on reality. The "design problem" Braungart and McDonough described is really a "modeling problem" for closing the information loop: How do you model the human and ecological subsystems such that they provide quality within system constraints? First things first, check to ensure your information feedback loop is closed, both Robert Rosen and Hugh Dubberly have emphasized this precondition.
Intentional communities and virtual communities
Ecovillages, like Dancing Rabbit, or "transition towns" are intentional communities formed with the purpose of living in greater harmony with the environment. They seek to couple the human system with the greater system it lives within. The basic model of an intentional community has been around for centuries, however promoting local and global sustainability as their primary focus is a more recent development. According to the theory, you can more quickly and easily develop sustainable modes of living if you eliminate the sources of systemic resistance to environmental action by living in a cooperative arrangement with like-minded people. I like this idea very much; it is a good model and has worked for many people. But it hasn't caught on quickly enough and I think it is important to ask why. I also think that we need to identify possible alternatives that might help speed progress to the same goals. What I'd like to propose is a "virtual transition town" model (I can't be the first to have proposed this). We could create a virtual community center that combines the enormous resources of many distributed homes. Think of it as a virtual intentional community or ecovillage. This kind of networking has already been successfully tried in a few well-defined situations, and a few businesses have grown by leveraging peer-to-peer networks in similar ways. The early growth of e-commerce saw Ebay, then Craigslist, and now Facebook marketplace. What you can't get from them you can order from Amazon with free shipping. But none of these business models incorporate environmental responsibility, the core value of ecovillages, into their models.
What we need is a local, distributed, and publicly owned "Amazon fulfillment center", a virtual warehouse with an online searchable database. With this we can pool local talent and resources for community use. Although different, this is the same basic model that used bookstores, tool libraries, "free stores", and second hand economies of reuse are built upon. This is what advocates of a "circular economy", industrial ecology, and economic degrowth have been promoting. Maybe this would look something like Craigslist, but with democratically agreed upon measures of sustainability built into a voluntary system to promote greater community health. For many reasons, joining or forming an intentional community may not be an option for many people, but maybe we can create an equivalent model that can help bring the ecovillage dream to them, without sacrificing the local networks they have already developed. If it is to work, just like an ecovillage itself, it has to be a group effort.
Models for energy, housing, and community spaces
Fossil fuels are woven into the fabric of modern life, into almost everything we touch. They seem normal. But cracks are appearing. They are spreading, and a world based on another model is showing through. Last month Mark Z. Jacobson, Mark A. Delucchi and the team in Stanford released another study showing the electrical generation mix for 139 countries worldwide using wind, water, and solar. They write: “Air heating and cooling will be performed with ground-, air-, or water-source electric heat pumps. Hot water will be generated with heat pumps, in some cases with an electric resistance element for low temperatures, and with solar hot water heaters. Cook stoves will be electric induction. Clothes dryers will all be electric. […] Electric arc furnaces, induction furnaces, dielectric heaters, and resistance heaters will provide high temperatures for industrial processes.” So that's the energy mix we are headed toward in a fossil fuel free, net zero emissions (or even carbon negative) world. Housing can improve as well, and there are some promising models and examples for this that deserve greater attention. We know, for example, that poorly designed cities have mental health consequences for their residents. So why not design for greater interaction, as is being done in Barcelona? The benefits are not just theoretical. New Hampshire has a net zero multi-family building. Whittier, that quirky Alaskan village, houses the majority of its residents under a single roof. And though in their case it was more the result of historical accident and necessity, that sort of model can attract people in other contexts, as with the Independence Library and Apartments by John Ronan Architects in Chicago, or the Unisphere in Maryland. The "la ville du quart d’heure" model has gained significant attention. If you can walk or bike to work in 15 minutes—and can make it to a grocery store, a park, cafés, your kids’ school, or anywhere else you might want to go on a typical day in the same amount of time—you’re living in what’s called a “15-minute neighborhood.” A more recent article by Michael Eliason describes additional trends in sustainable communities including the "productive city": production can include urban agriculture, energy production, food production/processes, recycling centers, etc. It's a return to the way cities developed centuries ago, but with significantly less pollution and safety hazards.
Detailed Digital Doubles, Counterfactual Duplicates
Models form an additional layer over the existing semiotic web. They are counterfactual abstractions. When rendered in computer code, Pedro Domingos called these “digital doubles”. Domingos said “We're going to have to decide what kind of society of models we want to have, what's allowed, and what's not. How do we make sure that everyone benefits? How do we smooth the transition? There is a lot to figure out. If we do, there's a bright future where our lives will be happier and more productive. If we don't, it'll be a huge missed opportunity. It's in our hands." Our models reflect both the good and less desirable aspects of our human nature, providing us the ability to reinforce those behaviors that promote our common good, and exert greater restraint over those that detract from it. Alexander Krylatov, a mathematics professor, echoes this perspective when applied to a particular example of our engineered environment: “Traffic demands and available infrastructure can only be balanced with digital modeling that creates an entire “twin” of existing roadways. The software will be an extremely useful thought tool in the hands of transport engineers.” If traffic models are complex, then ecosystem models are an order of magnitude still more complex, not that this consideration would stop ecologists like H.T. Odum from trying to capture their dynamics in full detail. By comparison, a simple aquarium is a (mostly faithful) microcosm of some of these same processes. Exploring these models, whether simple or complex, can provide both practical and aesthetic rewards.
Mirrorworld
In his article "Welcome to Mirrorworld" Kevin Kelly speculated about the potential benefits of building a "mirror world", the most detailed digital model of the world ever created. This could unlock the power of counterfactual thinking and active inference. It might even overcome the limitations of temporal discounting, which has prevented us from acting in our own best interest in many areas of life. Kelly writes, "Time is a dimension in the mirrorworld that can be adjusted. Unlike the real world, but very much like the world of software apps, you will be able to scroll back. With a swipe of your hand, you will be able to go back in time, at any location, and see what came before. You will be able to lay a reconstructed 19th-century view right over the present reality. To visit an earlier time at a location, you simply revert to a previous version kept in the log. The entire mirrorworld will be like a Word or Photoshop file that you can keep “undoing.” Or you’ll scroll in the other direction: forward. Artists might create future versions of a place, in place. The verisimilitude of such crafty world-building will be revolutionary. These scroll-forward scenarios will have the heft of reality because they will be derived from a full-scale present world. In this way, the mirrorworld may be best referred to as a 4D world."
The Power and Influence of Models
There is, on the one hand, the intersection between anthropology and cultural models. And on the other hand the intersection between politics and environmental simulations. Can we join both hands, so they work together? It seems clear that, regardless of what else happens, cultural models have always been with us and always will be, as a basic precondition for life. As to whether we expand these through the adoption and use of “cognitive prostheses”, that seems a likely scenario, as life tends to seek out new symbiotic relationships and synergies whenever possible. (Peter Corning and Eörs Szathmáry have made this much clear.) Today there is a dramatic expansion and proliferation of new models and simulations, and these are are highly experimental and exist mostly on the fringes of society. They are regarded, justifiably, with suspicion. But we live with one foot in the future, even as we keep one firmly rooted in the traditions of the past; with one hand grasping at the root and the other reaching for the branch tips. And this is necessarily so. As Robert Rosen put the matter, any changes we make today are due to the predictions we have for the future, and we make those predictions based on our models. We have a collective responsibility to do our best to anticipate and prepare for the future that we and our communities will have to face.
Many Americans today have a poor understanding of the dynamics of power and how it is exerted through institutions, systems, and models. And this intersects with artificial intelligence, because it will be by virtue of better modeling and simulation that AI will be able to multiply the capabilities of both existing and new power structures. There may be no single subject that is more consequential, nor that more people on the political Right (at least those easily manipulated through ideological propaganda) seem incapable of understanding. Problematically, the political Left’s tendency to ignore or even resist opportunities for incremental progress in favor of the “big win” is also a strategic failure and suggests that many of them do not have a sufficiently clear understanding of modeling processes either. When Elie Wiesel said, “always take sides”, he recognized one of the central features of a good model: our choices and actions have consequences. If we ignore this, then we renounce our collective responsibility to shape the course of the future. Allen Tien recently noted that “Our world is complex; how different things are related is hard to understand. Our leaders don't fully use good models for what to invest time and money into. While symptoms are addressed, root causes tend to be ignored.”
Synergistic Semiotics
Robert Rosen and Peter Corning, thought leaders who have both advanced new and challenging heterodox scientific ideas compatible with the extended evolutionary synthesis, have each compared society to a superorganism. Corning, who has made frequent use of the superorganism analogy, titled his forthcoming book "Superorganism: A New Social Contract for Our Endangered Species". Rosen has also described society as an integrated, socially organized species. He wrote "many tantalizing parallels exist between the processes characteristic of biological organisms and those manifested by social structures or societies. Probably their most direct expression is found in the old concept of society as a super-organism... What would it mean if common modes of organization could be demonstrated between social and biological structures?" (Anticipatory Systems, 4) Interestingly, these two authors meet in the scholarship of Arran Gare, who has published articles by Peter Corning in his online journal "Cosmos and History" and recently wrote a paper on Rosen and biosemiotics titled "Biosemiosis and Causation: Defending Biosemiotics Through Rosen’s Theoretical Biology; or, Integrating Biosemiotics and Anticipatory Systems Theory. At this time I would like to propose another integration, that of Jesper Hoffmeyer's biosemiotics with Peter Corning's synergism hypothesis, to produce what I'd term "synergistic semiotics", a subject I think could be broadly characterized as homologous to the "modeling relation" described by Robert Rosen. After all, one might say that a model is a complex, synergistic relationship among signs. Taken together, biosemiotics, synergistic selection, and relational biology appear to form a substantial theoretical foundation for work bridging the physical and social sciences, making these fields directly relevant to the complex problems we face today.
Human ancestry
If a person alive in 1,000 BC has any descendants alive today, they have all of us — even people from different continents and isolated populations. Another way of putting this: Anyone who was alive 2,000-3,000 years ago is either the ancestor of everyone who’s now alive, or no one at all. How do we know this? This was the surprising conclusion of a study published in 2004, "Modeling the recent common ancestry of all living humans", in which models of human genetics incorporating population substructure and historical dynamics (such as the tendency of individuals to choose mates from the same social group and the relative isolation of geographically separated groups) indicated that the most recent common ancestor (MRCA) of all present-day humans lived just a few thousand years ago. So what does this mean? It means that we really are one big family swimming in the same big gene pool, and that our apparent differences are better accounted for by cultural and environmental factors.
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| The Markov Blankets of life |
When my wife got tendonitis in her shoulder she was curious about the effects of diet on inflammation and recovery, so she watched The Game Changers about plant based diets. The film interviews the most macho men in contemporary culture (UFC fighters, weightlifters, football players), at the very pinnacle of physical strength and performance, who attribute their abilities in sport and endurance to a vegetarian diet. Would you believe that this is more convincing to the average person than if a scientist or doctor had told them the same thing? It is. And the reason is simple: these people have immense social prestige; they are public idols. Combined with a bit of personal motivation from say, a physical injury, these role models are able to convince almost anyone in a single day, my wife included, what you or I likely couldn't in decades.
The power of prestige and role modeling can't be underestimated. A person's willingness to adopt a perspective or opinion, on any given subject, is often more influenced by whether their role models expressed or shared it (or one similar to it). This is no more apparent than in the spread of dogma and ideology, whether cultural or religious, political or economic. To understand any movement, you can't do much better than to find out who the leaders and role models within it are, and why they are those particular individuals. Consider for example the conservative political movement in America within the Republican party since the time of Ronald Reagan. By claiming the moral high ground and appealing to self interest, the architects of this political strategy projected an image attractive to a certain segment of America. Who would represent their values, understand their needs, and defend their interests? They knew that if you can convince a person of this, you can control them, and they will follow you almost anywhere you lead. Although he used the term "elites" instead of "role models", this phenomenon was perceptively described by David Roberts when he wrote:
Conservative elites have made climate denialism part of conservative identity. If an individual conservative questions climate denialism, he or she risks being attacked, shamed, or shunned by trusted peers and authorities. Real, tangible social damage could be done. Conservatives will accept the scientific facts of climate change when conservative elites signal that that’s what conservatives do — when they demonstrate trust in the institutions of climate science. How can conservative elites be persuaded to think and communicate differently about climate change?
In a recent interview Yuval Levin said:
"We have to be able to say that people with power have certain
obligations. All of us have some roles to play within some institutions,
even if that's our family or community or workplace, let alone national
institutions and politics and the economy. We each have to say, given
my role here, what's my responsibility? We can't stand and say: "Well,
what do you expect?" One of the effects that Trumpism has had on our
politics is a lowering of expectations, that makes it very hard for us
to come back from the kinds of problems we've encountered in our
politics. We expect a lot better than this. People in power owe us more
than this. As a as a parent, as a neighbor, as a member of the PTA, as a
member of Congress, as a CEO, we must all ask: "What should I do in
this situation?" Not just what do I want, not just what would look good,
but given my role here, what should I do? It is a question you ask when
you take the institutions that you're part of seriously." Similarly, A.T. Ariyaratne said, "To be awakened is to realize that one has a role in the harmonious development of all and to strive to fulfill that role." He started the Sarvodaya Shramadana Movement, whose name means "welfare for all through our shared labor".
Archetypes, mental models in our imagination, tend to be one dimensional, simplified characters that can be used (and misused) in advertising and propaganda to promote a desired image. The line between archetype and caricature can be indistinct. They make great theatrical characters in movies, like Hanzo in "Kubo and the Two Strings" or Bak Mei and Hattori Hanzo in "Kill Bill". When Quentin Tarantino made that movie, he drew upon some of the most masculine archetypes available to him in cinematic traditions both East and West, which in turn drew upon earlier records like the Hagakure (compiled 1709-1716), which was viewed as the definitive guide of the samurai, an archetype inseparable from Japanese culture. Which archetypal models are informing our contemporary culture?
Fast and slow thinking and the pursuit of long-term goals
David Roberts describes how Daniel Kahneman's book "Thinking, Fast and Slow" challenges “homo economicus,” the conventional economic view of human beings as rational interest maximizers. At its heart is a distinction between System 1 (S1) thinking and System 2 (S2) thinking. It is only through S2, through perspective-taking and regulating our short-term impulses, that we get work done, develop long-term skills, or stay physically healthy. But using S2 to successfully regulate S1 isn’t easy. Most of the time, for most people, S2 serves S1, not the other way around. (As philosopher David Hume put it, “reason is a slave to the passions.”) Very rarely do people question the assumptions and biases they have inherited.
Our ability to self-regulate and restrain our S1 thinking, our group-level gut instincts, is more or less what has enabled complex global civilization. How can S2 thinking be built into society in an enduring way? Some claim that there are no S2 models, only competing factions, their truth or ours. As a result, trust in S2 models, and social trust generally, is at a historic low. What becomes of a nation that loses its capacity for S2 self-regulation, when its constituent groups are no longer able to abide by a shared set of rules, pursue a shared set of long-term goals, or even accept a shared set of facts? What becomes of a society in which social media lacks any serious, thoughtful filtering? Stopping the spread of hate and misinformation requires moderation. It requires S2 models. Just as an individual can only pursue long-term goals by using S2 thinking to shape, direct, and correct the flaws of S1 thinking, so too a pluralist democracy can only prosper in the long-term by designing some kind of S2 model infrastructure — institutions, laws, rules, procedures, and norms — to prevent its various internal factions and identities from falling into zero-sum struggle. A country without functioning S2 models ceases to be a nation. It becomes an erratic collection of factions locked in zero-sum struggle, reacting to situations as they arise, unable to look ahead or effectively plan — unable, for instance, to implement a coherent multi-decade policy program to both prepare for and prevent the worst of climate change.
Political power and voter manipulation
Guy Debord, who wrote "The Society of the Spectacle", and Jean Baudrillard, who wrote "Simulacra and Simulation" both attempted to uncover how deceptive many social processes really are, and how willingly and unquestioningly we often accept them at face value. After all, we are encultured from youth to do so. But things are often not as they seem, and this is just as true concerning political processes. In a 2009 interview Howard Zinn said "You know, traditional history creates passivity because it gives you the people at the top and it makes you think that all you have to do is go to the polls every four years and elect somebody who’s going to do the trick for you. And no. We want people to understand that that’s not going to happen. People have to do it themselves." Creating passivity, creating what David Simon called an "inert government", reinforcing the illusions of accountability, moral leadership, or change, and all the while gerrymandering voting districts, disenfranchising voters, reinforcing inequality through the electoral college, and in general manipulating elections by virtually any other means. No wonder Zinn concluded "We’ve never had our injustices rectified from the top, from the president or Congress, or the Supreme Court." Change doesn't come from elections that replace one figurehead with another, while ignoring the greater system beneath, whose entire purpose is to maintain business as usual. By all means, we must vote in the next presidential election, but we should entertain no illusions that this will create substantial change. The potency of democracy has been removed as far as possible from the process. Our civic responsibility requires more from us than a symbolic act every four years.
Fear, control, cults, and the apocalypse
On Sunday I read an article on life and ethics in which Thomas Metzinger pointed out that "We will do almost anything to prolong our own existence. It’s a biological imperative." He called this the "existence bias". We constantly check our environment to see if the evidence for our continued existence is good. If the evidence isn't good, then we set about to change our conditions. This creates a tension between our perception of reality and our perception of ourselves. Which one should change? It is both a source of fear and the desire for control. Here is where religious beliefs take root. Religions serve many purposes within a culture, among them providing reassurance to the faithful that their existence and preferences will continue, even in the face of an uncertain future. In short, religions speak directly to our "existence bias". But when religious fear and control becomes pathological, to the extent of causing significant immediate harm, it is called a cult. The lines between religions and cults, as between most things, are not always clear. In a longer interview Metzinger speculates on the role of fear in the growth of nationalism in contemporary politics: "Many people have the feeling this is just too much, it's too much information, the change is too fast for me. I want something simple and traditional, and that is "my tribe, my nation, my territory" and that is now happening at many places at the same time. It is very, very dangerous." Elsewhere, we can see fear of "the event" (environmental collapse, social unrest, nuclear explosion, unstoppable virus, in short "the apocalypse") causing both rich and poor to assess their chances of survival and prepare for the worst. Simply by living, we are all aware of the tension between reality and our continued survival. Managing this tension so that it does not become pathological or self-fulfilling, like an autoimmune disease, is an ongoing challenge.
Japanese models for gun ownership and law enforcement
Japan has one of the lowest rates of gun crime in the world (and a great lost-and-found model). In 2014 there were just six gun deaths, compared to 33,599 in the US. Japan was the first nation to impose gun laws, laying down the precedent that guns really don't play a part in civilian society. Consequently the Japanese do not view gun ownership as a civil liberty. They reject the idea of firearms as something you use to defend your property against others. Japanese police officers rarely use guns and put much greater emphasis on martial arts - all are expected to become a black belt in judo. "The response to violence is never violence, it's always to de-escalate it." says Iain Overton, executive director of Action on Armed Violence. Contrast this with the American model, which he says has been "to militarise the police... but if you have too many police pulling out guns at the first instance of crime, you lead to a miniature arms race between police and criminals". Gun crime has sharply declined in Japan over the last 15 years, and the laws have been a problem for Japanese gangsters. Those who continue to carry firearms have had to find ingenious ways of smuggling them into the country. Retired police officer Tahei Ogawa said "we have discovered cases where they have actually hidden a gun inside a frozen tuna".
Models of abuse
Sexually predatory behavior is a pervasive problem across many societies. And in those societies where countervailing constraints are lacking within the culture, or where these behaviors are ignored or considered legally permissible, the problem has reached epidemic proportions. It's now common knowledge that rates of sexual assault and domestic violence against women in Alaska are several times the national average. As a result women are forced to assume that nearly every man is a potential threat to their safety. While no one wants to regard all members of a single category in this way, in point of fact generalizations of this kind make sense when the threat of harm is significant. Such heuristics have adaptive value (though it can be difficult to know which stereotypes are useful in this way, and then of those in which contexts). We tell hikers to assume every bear is potentially a threat. We tell children to assume every adult who is a stranger, and whom we have no prior experience with, is potentially dangerous. These are all situations in which a power imbalance exists, along with a potential motive to take advantage of that imbalance. Any time those two conditions occur together the probability that abuse will occur increases, absent mitigating conditions, and it is good advice to exercise an appropriate amount of caution. By employing such a model we can better predict and prevent abuse before it occurs. This also highlights the importance of identifying protective factors. Lastly, having a model for abuse can free us from over reliance upon gender stereotypes, which can be easily misapplied with harmful consequences to everyone.
It is the responsibility of all of us to protect the vulnerable from those who would take advantage of them, and we must do a much better job. I think one of the reasons we continue to struggle to address this is that we have not confronted the most common models of violence and abuse, which tend to follow the same scripts again and again. Perhaps no one understands this better than Laura Zúñiga Cáceres, daughter of indigenous environmental activist Berta Cáceres, who was shot dead inside her home in La Esperanza, Honduras. In an interview Friday, Laura said "Just like the land and our territory is violated and destroyed, so are our bodies. And that is something that is a constant in countries like Honduras. We know that we are at risk. We know that they kill us, that they rape us, that they attack our families... When these threats and murders happen, it is also the destruction of present and future life. I think it also changes the direction of how we are imagining our future, because we have to face and resist a very, very aggressive model destroying us."
In every domain of social life, and even within communities and organizations we consider to be paragons of virtue, the model at the heart of exploitation operates with impunity whenever the conditions are right. Members of religious or otherwise ideological communities are no exception, and it would be foolish to expect they are. In fact, due to the power imbalance that exists in a religious hierarchy, the conditions are nearly perfect for the model of abuse. Just five days ago, Pema Chodron, a name that should be familiar to Buddhists in the West, resigned her position after a series of events surrounding the rape of another woman by the son of her religious figurehead. The situation has been reported in complex detail by Matthew Remski, which does not entirely excuse Pema from her involvement in it. Faced with the choice of supporting the victim of an abusive social model, or rationalizing the situation and remaining within her religious organization, she initially chose the latter. Only recently did it become too much for her to accept.
When confronting any problem, the first step is often to simply recognize what it is and what we need to do to fix it. Without understanding the psychological defense mechanisms that sustain and perpetuate problematic models, we may continue to "wave a feather" over them without ever making meaningful changes to the underlying systems of patriarchy, racism, and class privilege that sustain them. The Me Too movement did a lot to destigmatize the conversation around sexual abuse, improve the social understanding of this epidemic, and work to address it. When we can see a general model of abuse that exists at all levels of society, and operates in areas of life that are both personal and public, we can better anticipate and prevent the conditions that favor it. We are then better able to identify and take down models of abusive, systemic violence and oppression, and confront the rationalizations constructed to excuse them. One such attempt to deflect responsibility is "women can and have been predators as well". We should not minimize that, nor ignore how complicated the picture can become when we also consider rape of men by men, or women by women, or by either men or women of children, or by women of men. These can all be instances where our stereotypes and models might fail to give us an accurate representation of the situation; we do need to be careful and improve our models. Nonetheless, the statistics for rates of violence have consistently shown that the perpetrators are overwhelmingly men. Why is this? According to the very simple model outlined above, the proximal cause is a power imbalance combined with a motive and an opportunity, but the distal causes are far more complicated and controversial. To discover them we must ask questions of the form: Why would one person impose their will on another against either their expressed desire, or their best interests? Are men fundamentally unable to understand the concept of consent or provide a safe and caring environment for others? No, and so behaviors in violation of such social norms are inexcusable on those grounds. Within our culture today, men are not doing enough to uphold these values and maintain greater responsibility for both their words and actions.
The fabric of society and global health, as Laura Cáceres in her interview and Paul Hawken in "Drawdown" have both pointed out, as have many others, depends on women. Because of their crucial role, sexual violence against women inevitably affects all of us in one form or another. While the phrase "protect the vulnerable" can mean many things to many different people, differences in apparent physical strength are only one very narrow type of vulnerability. Much more insidious are forms of abuse that derive from cultural institutions, differences in legal or economic conditions, and psychological and emotional manipulation. The principle role of government is to provide protection, in the recognition that humans by their very nature are vulnerable. Oppressive governments discriminate preferentially between who will receive assistance and protection and who will be denied and exploited. My sex/race/class has provided me protections that others have not enjoyed. These protections, and others besides, need to be extended to everyone.
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| Models evolve (Hugh Dubberly), see this model. |
At some point during child raising, most parents begin to think more seriously about what options their children will have after high school. Maybe that will be college, vocational training, inheriting the family business, or some other combination. When I graduated from high school, college tuition was more affordable. But finding direction in a sea of career possibilities was challenging, though not entirely bad as I was able to explore a wide range of options. Looking back now would I have done it differently? How will our children navigate through their choices, while avoiding the shoals of crippling debt? I think this might be a modeling and simulation problem. We need to address financial resources, individual skill and aptitude, employment opportunities, but also mental health and well-being. Young adults not only seek a job that will allow them to live, but will also provide a level of satisfaction and sense of purpose. Does a model exist that might enable them to discover the answers to these questions and suggest a range of attractive options to choose from? In a more general way, commenting on the role of models in education, Harry Fletcher-Wood recently wrote:
Mental models help students comprehend and retain new information. They provide a structure against which to test/through which to view this information. Mental models also allow students to apply their knowledge to answer questions accurately and solve problems creatively. For example, a mental model of poetic forms allows students to recognise that a poem is a sonnet, or to write a sonnet themselves. A mental model of the Seventeenth Century makes sense of Charles I’s actions by placing them in a political and religious context. A mental model of atomic structures explains the characteristics of helium and how it can be used. Mental models allow students to put their knowledge to work. ...We recognise students effective use of mental models, but how we can help students’ develop them is less obvious. We need to teach the utility, use, and creation of knowledge organisation, but it’s hard enough ensuring students recall the basics: this may be why teachers and textbooks “pay much more attention to the content of conveyed knowledge than to its organization.” If we are to develop students’ mental models, we need to know what a useful mental model looks like: to identify the structures and connections which help students make sense of and organise their learning.Our education system evolved to suit factory work as the spread of industrialization created a need for compliant, literate workers. As Joel Mokyr explains: "Workers had to be taught to follow orders, to respect the space and property rights of others, be punctual, docile, and sober." Many aspects of this model no longer make sense today. In what ways can we improve our model of the education system? Mike Colagrossi notes how Finland reformed their educational system to focus on individualization over standardization, cooperation over competition, and to provide a learning environment that promotes biopsychosocial health. With less stress and regimentation, more caring, and without having to worry about grades and busy-work students are able to better focus on learning and growing as a human being.
Colagrossi writes "Children are stuck in the K-12 circuit jumping from teacher to teacher. Each grade a preparation for the next, all ending in the grand culmination of college, which then prepares you for the next grand thing on the conveyor belt. Many students don't need to go to college or flounder about trying to find purpose and incur massive debt. Finland solves this dilemma by offering options that are equally advantageous for the student continuing their education. There is less focus on the dichotomy of college-educated versus trade-school or working class. Both can be equally professional and fulfilling for a career." The contemporary educational model in America has imposed this artificial dichotomy upon our career options, however the most rewarding work reflects an inter-disciplinary approach combining aspects of both academic and trade work, as each informs and enriches the other. Finland has also mandated that "phenomenon-based learning", a process where new information is applied to the phenomenon or problem, be provided alongside traditional subject-based instruction. Has Finland found the path toward reintegrating them together?
Models of kinship and family structure
David Brooks wrote “Ever since I started working on this article, a chart has been haunting me. It plots the percentage of people living alone in a country against that nation’s GDP. There’s a strong correlation. That chart suggests two things, especially in the American context. First, the market wants us to live alone or with just a few people. That way we are mobile, unattached, and uncommitted, able to devote an enormous number of hours to our jobs. Second, when people who are raised in developed countries get money, they buy privacy. But a lingering sadness lurks, an awareness that life is emotionally vacant when family and close friends aren’t physically present, when neighbors aren’t geographically or metaphorically close enough for you to lean on them, or for them to lean on you. Today’s crisis of connection flows from the impoverishment of family life.”
“We’re likely living through the most rapid change in family structure in human history. The causes are economic, cultural, and institutional all at once. People who grow up in a nuclear family tend to have a more individualistic mind-set than people who grow up in a multigenerational extended clan. People with an individualistic mind-set tend to be less willing to sacrifice self for the sake of the family, and the result is more family disruption. Many people growing up in this era have no secure base from which to launch themselves and no well-defined pathway to adulthood. For those who have the human capital to explore, fall down, and have their fall cushioned, that means great freedom and opportunity—and for those who lack those resources, it tends to mean great confusion, drift, and pain. Starting around 2012, the share of children living with married parents began to inch up. And college students have more contact with their parents than they did a generation ago. We tend to deride this as helicopter parenting or a failure to launch, and it has its excesses. But the educational process is longer and more expensive these days, so it makes sense that young adults rely on their parents for longer than they used to.”
There was a time when it was common for each family to pass on to their children a family trade, fields, flocks, or hunting grounds. This was an intergenerational model, a legacy, an inheritance, a promise that they would never be in want, or fear for lack of shelter, food, and other basic needs. Youth could depend upon the accumulated knowledge, traditions, and wisdom that spanned many lives and passed from hand to hand as each new generation rose to replace the last. A path was clearly laid out, and they could follow it, or leave it as they chose. Families provide some of the best role models for how to live, so children don't have to begin from scratch and reinvent the wheel all over again. Of course there are no guarantees in life, and even our best plans to provide for the needs of future generations may come to nothing, but what can we strive for, as a society, or as families to provide our children with? The market economy of today has slowly eroded the fabric of extended families, and at the same time social supports are under attack. What are we doing? The Iroquois Constitution said "Look and listen for the welfare of the whole people and have always in view not only the past and present but also the coming generations, even those whose faces are yet beneath the surface of the ground - the unborn of the future Nation." They need our help, now more than ever.
Labor workforce modeling
It is difficult to capture the relationships between and among specific jobs and goals, and how and in what way they relate to one another. But that's where the value of a model lies, in providing a systems level understanding and the many benefits that brings with it. Hai Zhuge described the importance of modeling workforce relationships: "Technology alone cannot transform a city without the participation and cooperation of its citizens. Geographically dispersed users will be able to cooperatively accomplish tasks and solve problems by using the network to actively promote the flow of material, energy, techniques, information, knowledge, and services". The benefits of a better model include the ability to identify: problem areas, goals and the tasks relevant to addressing them, unmet needs and possible organizational improvements, spot inefficiencies, anticipate disruptions before they occur, facilitate adaptive changes, and offer a descriptive analysis of existing conditions.
Workforce modeling attempts to match the need for workers at a particular point in time (demand) with the availability and preferences of the workers (supply), shedding more light on the structure and processes of human labor. Given this, one might expect that there should be an app, or maybe even an employment website, capable of aggregating the data from all the other employment websites (like FlexJobs, Upwork, Fiverr, Craigslist Jobs, etc.). This would help job hunters access the most complete and accurate model of the global labor market and be asset for any employment matching service. Ideally, such a model would also be able to display the relationships between jobs and social problems/community goals, advertising position availability and growth according to model predictions. For example, it could help address complex problems and projects with a clear goal like the Green New Deal. But there may be other benefits as well. Rutger Bregman pointed out that countries with a shorter work week have a smaller ecological footprint, and could potentially cut greenhouse gas emissions in half. By spotting inefficiencies, perhaps a better labor model could help bring about the revolution needed to realize the 15 hour work week Keynes once predicted in his famous essay “Economic Possibilities for Our Grandchildren".
The "deficit model" and the "conflict model"
Consider the science of science communication. The theory many scientists seem to swear by is technically known as the "deficit model", which states that when people’s opinions differ from scientific consensus it is because they lack scientific knowledge. However studies have shown that increasing science literacy alone won’t change minds. The obstacles faced by science communicators are not epistemological but cultural, and the skills required are not those of a university lecturer but a rhetorician. Scientists need to learn how to communicate science strategically. The 19th century witnessed the inception of the "conflict model" of science and religion. This was the view that history can be understood in terms of a ‘conflict between two epochs in the evolution of human thought – the theological and the scientific’. However this is a mistaken view of the past, and leads to a flawed vision of the future.
Narrative models and quasi-religious storytelling
Modern narratives tend to focus on the idea that people on opposite sides of conflicts have different moral qualities, and fight over their values. And once that idea entered our storytelling, the peculiar moral physics of good guys versus bad guys has been remarkably consistent. This narrative approach promotes social stability and is useful for getting people to sign up for armies and fight in wars with other nations. When we read, watch, and tell stories of good guys warring against bad guys, we are essentially persuading ourselves that our opponents would not be fighting us, indeed they would not be on the other team at all, if they had any loyalty or valued human life. But our stories have not always been this simple, and one wonders the influence this modern trend has on polarization and the stories we tell ourselves about ourselves and our place in the world.
Model disruption
The Estonian palaeontologist Ivar Puura introduced the word semiotsiid (semiocide) to signify “a situation where someone´s malevolence or negligence brings along destruction of signs and stories, which are meaningful to someone else, whose identity is thus violated”. If the Anthropocene is the Age of Man, then it is also the era of an emerging global semiocide. In this tragic development, when models persist that no longer reflect the rapid scale of change, they turn around and actually become dangerously misleading and maladaptive because they are no longer reliable predictors of the future. Ed Yong has documented this loss in the case of both bighorn sheep and great apes. Plants have models they use to predict the future too. “For a tree that lives, say, 250 years, 13,000 years represents only 52 generations. In an evolutionary sense, the trees don’t yet realize that the megafauna are gone.” Without the megafauna, seed dispersal became far less efficient. Recently, the addition of nonnative horses, cows, and other proxy herbivores helped return these plants to their earlier range of distribution. We can see this in terms of models (semiotic webs). The plants have a model in which megafauna eat their fruit and disperse their seeds. After the megafauna were removed that model was no longer accurate. But the later addition of horses and cows filled that role once again, and the model functioned as originally intended, more or less. The critical aspect, as far as the trees are concerned, isn’t the megafauna species per se, so much as the ecological processes that the model assumes will be carried out.
Model corruption
Senator Richard Burr, chairman of the Intelligence Committee, dumped up to $1.6 million of stock after reassuring Americans that we were prepared to deal with the coronavirus. A week later the stock market began a sharp decline. We knew we were not ready. We knew America was not prepared, but we did not know that Burr's lies (backing up a narrative that it is a "hoax" and a "cold") were a calculated attempt to safeguard his personal wealth. He had inside knowledge, he knew earlier than anyone that this was going to be very bad, he placed his own interests over those of the American public whom he solemnly swore to preserve and protect. And with his privileged position, he had access to intelligence and a better model than most. He could predict unfolding future events before most others. But instead of sharing that model, he corrupted it. He duplicitously handed out a false model that served no one's interests but his own. That lie bought just enough time for him, and perhaps his friends (senators Loeffler and Inhofe, and others), to get into their lifeboats and escape the ship before it sank. Given the narrative promoted by the president at the time, one wonders if Trump was a part of this as well.
And now the president is calling it a "Chinese virus", a scapegoat with just enough plausible deniability that it's a simple geographic description with no racist overtones. If there's any lesson to be learned here, it is that these lies and mischaracterizations are not innocent. They are a Trojan horse, a parasitic model. A parasite is a free rider, it doesn't work but takes a share of the profit anyway. The only work it does is deception, misdirection, and it ingratiates itself to the host. Richard Burr is a parasite, he placed is wealth before the welfare of the nation. What are we to make of this latest scapegoat, when Trump calls the virus Chinese? He's not merely describing its place of origin, as he would have us innocently believe. He's turning us against ourselves so his parasitism can be conducted more easily. It's his way of distracting people from the more serious issues (short sighted policies, lack of preparation, coddling the rich, etc.). Naomi Klein clearly identifies the effects. During a disorienting event like the pandemic, radical free market policies are pushed through along with government bailouts for financial markets, industries driving climate change, and private health insurance companies. None of this has to be inevitable though.
Model disintegration
Malena Marvin wrote: "Like all humans before us, we live in tumultuous and chaotic times. We evolved by being able to share stories that explained the world around us and knitted small communities together for survival through shared worldview. This served as a compass in confusing times. Now that we have so many options to choose from, we have to be careful about which stories and communities we choose to live with. We have to make conscious choices as we try to figure out who to trust, which voices to listen to, and how to build community. We need to use discernment." If we stand by as community values disintegrate, turn inward in fear as we fail to discern in whom we can trust, and allow distortion and conspiracy to flourish because we are afraid of what we do not understand, then what is the value of our stories, our worldview, and our inner compass? These are the models we live by. Their entire purpose is to prevent distortion and conspiracy. If they fail to do that, then we need to ask ourselves some tough questions.
Panpsychism and models of consciousness
In his article, George Musser writes: "Traditional philosophical panpsychism comes in multiple varieties, but all have one intuition in common: that subjective experience can’t be reduced to mechanistic physics. Proponents make three main arguments. The first is that there doesn’t seem to be any principled way to draw the line between conscious and non-conscious. Second, panpsychism would solve the hard problem of consciousness and matter by proposing that everything is conscious to some degree, and has phenomenal as well as material qualities. Third, several of today’s leading theories of consciousness imply panpsychism. One line of thinking, based on the free-energy principle put forward by neuroscientist Karl Friston, observes that any self-sustaining structure has to maintain its boundary against external insults, which requires an internal model of the world. That is a core feature of mind."
Philosophical perspectives: Anekantavada and bounded rationality
Fung Yu-lan wrote “Philosophy gives no information about matters of fact, and so cannot solve any problem in a concrete and physical way... What it can do, however, is to give man a point of view... From the “practical” point of view, philosophy is useless, yet it can give us a point of view which is very useful. To use an expression of the Chuang-tzu, this is the “usefulness of the useless.” (A Short History of Chinese Philosophy, Chapter 10, The Third Phase of Taoism: Chuang Tzu, p115) Yu-lan Fung described philosophy as “thinking about thinking.” It can provide us with new models for viewing the world, but we need more than one. In the classic tale about a group of blind men who touch an elephant to learn what it is like, each one touches a different part, such as the side or the tusk. They then compare notes on what they felt, and learn they are in complete disagreement. The blind man who feels a leg says the elephant is like a tree; the one who feels the tail says the elephant is like a rope; the one who feels the trunk says the elephant is like a snake; the one who feels the ear says the elephant is like a fan; the one who feels the belly says the elephant is like a wall; and the one who feels the tusk says the elephant is like a spear. Each blind man has interesting and useful things to say, but what seems an absolute truth is relative due to where each blind man stands. The story is used to indicate that reality may be modeled differently depending upon one's perspective.
Philosophical and Spiritual models
Stoicism comports well with the slow movement. In the current age of acceleration, when electronic media affords instant transmission of information the pace of life has become frenetic. Can we pump the brakes and consider what a slower pace means when it comes to accessing the latest news? Or not jump on the latest health bandwagon and consider, perhaps, what slower exercise is? Maybe working slower is more rewarding? Or entertainment that needn't be as fast? Related to Stoicism is Taoism. As a way of life, it denotes simplicity, spontaneity, tranquility, weakness, and non-action (wúwéi). Learning how not to force a thing is among those skills that we must all learn as we grow up. Laozi wrote “Tao is empty like a bowl. It may be used but its capacity is never exhausted. It is bottomless, perhaps the ancestor of all things. Deep and still, it appears to exist forever. Close the mouth. Shut the doors. Blunt the sharpness. Untie the tangles. Soften the light. Become one with the dusty world. This is called the profound identification.” There are similarities with Buddhism as well, in particular the four Brahmaviharas of benevolence, compassion, empathic joy, and equanimity. The bodhisattva model for cultivating bodhicitta promotes these moral and spiritual qualities. Perhaps they are worth greater consideration. As Seneca wrote “Life is long if you know how to use it”. He warned against “laborious dedication to useless tasks” and Zhuangzi, similarly warned "Your life has a limit but knowledge has none. If you use what is limited to pursue what has no limit, you will be in danger". Later, Marcus Aurelius wrote “All things are interwoven with one another; a sacred bond unites them; there is scarcely one thing that is isolated from another. Everything is coordinated, everything works together in giving form to one universe. The world-order is a unity made up of multiplicity.” This model of reality has been expressed by many people in many times and places. For example, the Sanskrit phrase "Tat Tvam Asi" or "Thou art that" (Chandogya Upanishad, 900 to 600 BCE) illustrates the need for relating one thing to another. Such traditions share a common perspective and can inform the development of a healthier model for society.
If models shape what we see and let ourselves notice, if they tell us what is important, what counts, and what to look for, then an understanding of the models that we have of ourselves and our relationships is critically important. When Ram Dass recently died, people repeated his well known saying “Be here now”. It’s generally good advice, but in the context of modeling and simulation processes that direct and filter cognition and attention, does that mean we should adopt a “mindfulness approach” whereby we separate our experience of the present from the models we use to interpret it? Probably. But if we are interested in the applications of this for a socially "engaged spirituality", how do we use this meta awareness of models, whether they are idiosyncratic or conventional, to promote greater well-being? That’s a hard question, but one that Klaus Niemeyer, in his paper A Contribution to Model Theory, is clearly trying to figure it out. He believes addressing future problems will require improving our collective decision making processes, and clearly helping others improve their models would advance that goal.
A basis for trust, collaboration, and action
Hugh Dubberly: “Models are closely tied to stories. We explain models by telling stories, and when we tell stories, listeners form models - mental pictures of the actors, how they are related, and how they behave. Models provide a basis for shared understanding, agreement, and group action. They also build trust and enable collaboration. Agreement begins with individual understanding - forming our own models. Through conversation, we begin to understand each other’s models - to form models of the other’s models. We compare our model with the other’s model. Are our models congruent? Do we agree? And then, do we agree that we agree? If so, we have reached “an agreement over and understanding.” We have a basis for trust, collaboration, and action. Models also shape what we see - what we let ourselves notice. Our models tell us what is important, what counts, what to look for. Peter Senge wrote, “Models [are] so powerful in affecting what we do... because they affect what we see. Two people with different mental models can observe the same event and describe it differently, because they’ve looked at different details.” In a similar way, models already shared within an organization may limit its ability to see new evidence, understand changing situations, or act in its own interest. Old models often resist new ones and inhibit learning. That’s why organizations need to expose the fundamental models that guide them and periodically challenge those models. Creating or revising a model is meta-activity, taking us outside the primary activity in which we were engaged. It requires attention, energy, and time.”
There exists a "political paradox": How do we collectively bring ourselves to face the reality of social and environmental problems while avoiding a backlash? To resolve this we require a few things at minimum: the ability to engage in goal oriented behavior, the ability to decide between two or more choices (using some standard of comparison), and the ability to understand that our choices are a reflection of our models. Most people can do the first two, but how many realize the third? Why are we motivated to interpret in ways that make us comfortable in our own skin and society? Why do we hold on to our own models so tightly and resist even the possibility of entertaining alternative models (and the choices they might imply)? Possibly fear, insecurity, perceived threats to conceptions of self identity, etc. The notion of "bounded rationality" takes into account that in decision making, the rationality of individuals is limited by the information they have, their cognitive abilities, and the amount of time available. The same considerations apply to all life, and so organisms simply "try something", and hope they can change later if a problem arises.
But how do we decide which are a better fit? And in the final analysis, who is to say that an optimal solution exists? According to Peirce all claims about reality are radically subject to error, and Herbert Simon defined two cognitive styles: maximizers who try to make an optimal decision, and satisficers who simply try to find a solution that is "good enough". He pointed out that human beings lack the resources to maximize. If we look at the attributes of life (effort, function, and fittedness) there is among these no requirement for inerrancy or certainty. Evolutionary solutions do not need to be perfect, or even that good. They just need to be "good enough" (a point made by Daniel Milo in his book of the same name). Maybe Voltaire right to quote the Italian proverb: "perfect is the enemy of good". Models need to be adequate, not optimal. How do we choose adequate shared models of reality absent the ability to eliminate error? Peter Corning wrote, "the next major transition in evolution must sustain and enhance our interdependent collective survival enterprise.” Interrogating our models according to the basic constraints for survival would seem to be a "good enough" place to start.
If we can encourage people to “take a step back” and understand that our choices are a consequence of our various interpretive schema, or models, we can create space for the possibility of understanding how different models would lead to different choices. Many differences of opinion are often "matters of interpretation" resolved through interrogating our models, and discovering their imperfections. To take an example, let's assume a person examines the "computational model" of life and discovers that it does not explain numerous essential characteristics shared by living organisms. Hence computationalism, as a model, is imperfect. If that person manages to convince another person (who had formerly believed it was an accurate model) that computationalism is flawed, then the other would see that their interpretation of a talking robot being analagous to a talking human was, in fact, equally flawed as well, and their former difference of opinion would be, in some meaningful sense, that much closer to being resolved. They would then be moving in the direction toward an agreement that talking robots are not analagous to talking humans. Steven Pinker wrote: "Though people in all cultures can react sympathetically to kin, friends, and babies, they tend to hold back when it comes to larger circles of neighbours, strangers, foreigners, and other sentient beings. In his book The Expanding Circle, the philosopher Peter Singer has argued that over the course of history, people have enlarged the range of beings whose interests they value as they value their own. An interesting question is what inflated the empathy circle; a good candidate is the expansion of literacy." Why literacy? It allows for greater perspective-taking, for the ability to entertain alternative models of the world, and different interpretive approaches. In a democracy we need to be able to share our models of reality with each other.
Embodied prediction, empathy, and altruism
“It is important,” writes a team of leading neuroscientists, “to emphasize the stark differences between brains and computers... Software and hardware, which can be easily separated in a computer, are completely interwoven in brains – a neuron’s biophysical makeup is intrinsically linked to the computations it carries out.” Jeremy Lent points out that our human experience is fundamentally embodied and cannot be separated from our physical existence in the way software can be separated from hardware. If your right temporoparietal junction (rTPJ) is bigger, people are more likely to behave altruistically. If the neurons within it are better-connected (and well-linked to other parts of the brain), people show less bias towards their own in-groups. If the area is stimulated by electric currents, people become better at taking someone else’s perspective. And if the region is disrupted, it changes our ability to reason about morality. But “Even in my own small lab, people disagree about the function of the rTPJ,” says Liane Young. If self-control is just "empathy with your future self", then the rTPJ plays an important role in how we respond to our own predictions about the future.
And yet humans are far from alone in experiencing empathy or making future plans, which casts some doubt on the role of the rTPJ for these cognitive functions. For example Frans de Waal has observed chimpanzees soothe distressed neighbors and bonobos share their food. This bottom-up explanation of morality has a lot of support. Another example is provided by Kristin Andrews and Susana Monsó, who describe how "rats don’t live merely in the present but are capable of reliving memories of past experiences and mentally planning ahead a navigation route they will later follow. They reciprocally trade different kinds of goods with each other – and understand not only when they owe a favour to another rat, but also that the favour can be paid back in a different currency. When they make a wrong choice, they display something that appears very close to regret. Despite having brains that are much simpler than humans’, there are some tasks in which they’ll likely outperform you. ...The most unexpected discovery, however, was that rats are capable of empathy." If rats can feel empathy and make future plans, then even we with our embodied minds should do the same.
To protect, we must predict
In his book "Making up the Mind", Chris Frith wrote, "In my brain, perception depends upon prior belief. It is not a linear process. For my brain, perception is a loop. When we perceive something, we actually start on the inside: a prior belief, which is a model of the world in which there are objects in certain positions in space. Using this model, my brain can predict what signals my eyes and ears should be receiving. These predictions are compared with the actual signals and, of course, there will be errors. My brain welcomes these errors. These errors teach my brain to perceive. The existence of the errors tells my brain that its model of the world is not good enough. The nature of the errors tells the brain how to make a better model of the world.
My brain discovers what is out there in the world by constructing models of that world. These models are not arbitrary. They are adjusted to give the best possible predictions of my sensations as I act upon the world. All that matters is that the model works. Does it enable us to make the appropriate actions and survive for another day? As long as our predictions are correct, the pattern remains stable. A failure of prediction shakes up the pattern so that a new one can emerge to replace the old one. In this way we can adapt our behavior to an ever-changing world. There are many reasons why prediction is a good thing. If we know what is going to happen, then we can relax. We don’t have to keep making new plans about what to do. We need to change our plans only when something unexpected happens. Also if we know what is going to happen, then we feel that we are in control."
Recently Hannah Pickard recommended focusing on the importance of protection when trying to communicate the need for addressing environmental disruption. This is good advice. Protection is all about avoiding harm. It's the reason people fear the threat of pandemics, the reason why fear is a motivating emotion, and why care for the vulnerable and defenseless is culturally valued. We protect ourselves and those we love. But our ability to protect depends entirely upon our ability to predict. If we cannot correctly predict which things may later threaten us or cause us future suffering, then we cannot protect at all. Prediction is hard. We must not only accurately determine what threatens us, but also correctly predict the means by which the threat can be averted. For example, if I identify the outbreak of a novel viral disease as a possible threat, but I believe I can prevent it through racially motivated violence as opposed to focusing on better identification and treatment of disease, then my failure to understand how disease is spread will mean I have failed to protect myself and my loved ones. Instead I have only caused greater harm. Let's encourage the natural desire people have to protect. We must only ensure their predictions follow from accurate models, and avoid the failures of poorer models. Whether intentional or accidental, a failure to predict comes at a high cost.
Procrastination, perceptual control theory, and predictive processing
Why do today what you can put off until tomorrow? As David Asch recently observed, hard work pays off in the future, but laziness pays off right now. Even physics seems to obey the principle of least action. As Elbert Hubbard wrote, "The path of least resistance is what makes rivers run crooked." Rivers are beautiful things, so taking the path of least resistance isn't necessarily bad in and of itself, it is simply efficient. But Thoreau drew a different moral lesson: "The path of least resistance leads to crooked rivers and crooked men.” H. G. Wells was still more blunt: "The path of least resistance is the path of the loser." And so, we must be wise enough to know the difference between what is efficient, and what is simply avoidant. The subject of avoidance, or procrastination, is fascinating to consider on the level of society, and it has been personally interesting to me for many years, ever since as a youth I was told to "stop procrastinating." About eleven years ago I read an article by Timothy Pychyl about self-regulation failure, in which he referred to George Miller's "test-operate-test-exit" model for self-regulating systems. Pychyl used a simple example, "The thermostat executes the key test and exit roles, based on a chosen standard (or target) that we set." But a more descriptive account is William Powers' perceptual control theory, according to which living organisms act to keep perceptual variables in pre-specified states, protected from disturbances caused by variations in environmental circumstances. The variable that is controlled is not the output of the system (a person's actions), but rather its input (their perceptions). Today perceptual control theory is not well known, but it's advocates are persuasive. In a recent article, Timothy Carey describes this "framework for a genuine biopsychosocial model of health and wellbeing":
"It is self-evident that control is important in psychopathology. Psychological distress is experienced when people feel unable to control their thoughts, actions, emotions, or some other aspect of their day to day living. Control has also been recognized as fundamental to health generally. Marmot (2006) describes control as an organizing principle in the social determinants of health. He uses control as a framework to explain inequalities in health within and between countries. He suggests that “control over life circumstances reduces chronic stress and has favorable biological effects.” Crucial to the notion of control is the ability of people to lead lives they have reason to value. “What is important is not so much what you have but what you can do with what you have.”People who experience distress as a result of uncertainty, surprise, or anxiety will often display behaviors that impact daily functioning such as delaying action to complete tasks, and so reconceptualizing procrastination in these cases as the result of control systems functioning "too well" may be a promising way of looking at it. Josh Kaufman wrote that procrastination is "essentially a big bundle of control systems in conflict. If part of you wants to get things done and part of you feels tired or overwhelmed and wants to rest, you’ll experience a feeling of inner conflict, and you’ll neither really work or really rest until it’s resolved." He provides an example. "Think of a heater and and air conditioner that are both measuring the temperature of the same room. The heater wants the temperature above 71F, and the air conditioner wants it below 69F - mutually incompatible goals. As a result of the conflict, both systems will try to have things their way, a lot of energy will be expended, and neither system will ever succeed in bringing the system under control." What is the best way to resolve this problem? The conflict exists in how the models that determine the control set-points were created and utilized, and so gaining a better understanding of these is needed to resolve the conflict. PCT is in turn related to Karl Friston's free energy principle, and that has connections to: the good regulator theorem, self-assembly, pattern formation, autopoiesis, practopoiesis, and themes considered in cybernetics, synergetics, and embodied cognition. It is also related to the maximum entropy principle and the principle of least action. The control system paradigm, partially a reaction to behavioralism, has also been applied to social anthropology by Ted Cloak and sociology by Kent McClelland.
Knowing that control is important, however, is not enough. It is crucial to understand how control works. Since the 1950s and 1960s, a science of control has been developing based on the idea of a hierarchy of closed, causal, negative feedback loops and using the methodology of the physical sciences in terms of building functional models that simulate the phenomenon under investigation to rigorously test basic principles and mechanisms. The theory underpinning this approach is Perceptual Control Theory (PCT, Powers, 2005). Many elements of PCT are not new. Negative feedback, for example, is well recognized as an important neural mechanism. PCT, however, clarifies and explicates how elements such as negative feedback function in an integrated unit. PCT provides an elegant and sophisticated framework that could unite disparate programs of research and help make sense of apparently anomalous findings. Some of the learnings from PCT will be surprising. For example, rather than explaining severe psychological distress as a brain disorder or dysfunction, PCT suggests that distress of this kind arises when well-functioning, high-gain control systems become conflicted. From this perspective, it could be argued that the control systems are functioning too well, rather than not well enough."
Advocates of the PCT paradigm, upon encountering Karl Friston's work on predictive coding, active inference, and free energy immediately recognize the numerous similarities between these two approaches. (Interestingly, while Powers designed medical research devices, Karl Friston wrote neuroimaging software.) These exist primarily at the level of generalizations, as they are both trying get at the same "what". (In "Surfing Uncertainty", Andy Clark references Powers on p190.) The important differences exist at the level of formulation, the specifics of "how". As Eli Sennesh puts it, "The first thing is that we have to situate Friston’s work in its appropriate context of Marr’s Three Levels of cognitive analysis: computational (what’s the target?), algorithmic (how do we want to hit it?), and implementational (how do we make neural hardware do it?). Friston’s work largely takes place at the algorithmic and implementational levels. He’s answering How questions, and then claiming that they answer the What questions. This is rather like formulating Hamiltonian Mechanics and saying, “I’m solved physics by pointing out that you can write any physical system in terms of differential equations for its conserved quantities.” Well, now you have to actually write out a real physical system in those terms, don’t you? What you’ve invented is a rigorous language for talking about the things you aim to explain." This is where Friston introduced variational Bayesian methods (variational free energy) to describe how systems try to minimize the difference between their model of the world and their associated perception. According to Michael Edward Johnson, "Karl Friston’s Free Energy Principle (FEP) argues that any self-organizing system which effectively resists disorder must (as its core organizing principle) minimize its free energy, that free energy is equivalent to surprise (in a Bayesian sense), and that this surprise-minimization drives basically all human behavior. This minimization of surprise revolves around Bayesian-type reasoning: the brain is always getting bottom-up sense data flowing in, more than it can handle. So it relies on top-down predictive models that attempt to sort through all this data so we can focus on the surprising stuff, the stuff that can’t be effortlessly predicted. The core of the FEP is the details of how this ‘handshake’ between bottom-up and top-down happens, and what can influence it."
The Free energy context
In her article "The mind-expanding ideas of Andy Clark", Larissa MacFarquhar describes how an influential view of life developed: "Christoph Mathys mentioned to Karl Friston the similarity between his free-energy principle and Freud’s model, and said that they had a common ancestor in the Prussian physicist Hermann von Helmholtz. Freud’s version of free energy (he used the same term) was similar to his notion of excitation: an uncomfortably stimulating psychic energy, which the nervous system sought to discharge. “Accumulation of excitement,” he wrote in “The Interpretation of Dreams,” “is perceived as pain and... the diminution of the excitement is perceived as pleasure.” The urge to discharge the free energy was what drove a person to act—to move around, to seek sex, to work. Friston’s version of free energy—prediction error—could sound at first as if it were all about cognition, just as Freud’s version could sound at first as if it were all about sex, but at root they were both about survival. Minimizing prediction error, in other words, was much bigger than it sounded. When the brain strove to minimize prediction error, it was not just trying to reduce its uncertainty about what was going on in the world; it was struggling to resolve the contradictions between fantasy and reality—ideally by making reality more like fantasy. The brain had to do two things in order to survive: it had to impel its body to get what it needed, and it had to form an understanding of the world that was realistic enough to guide it in doing so. Free energy was the force that drove both.
To Jakob Hohwy this emphasizes how very difficult it is for the brain to understand things outside itself. “A lot of us feel that we are not very much in tune with the world. The world hits us and we don’t know what to do with the sensory input we get. We are constantly second-guessing ourselves, withdrawing, and trying to figure out what is happening. Something that is very familiar to a lot of people, certainly myself, is social anxiety. We are trying to infer hidden causes—other people’s thoughts—from their behavior, but they are hidden inside other people’s skulls, so the inference is very hard. A lot of us are constantly wondering, Did I offend that person? Do they like me? What are they thinking? Did I understand their intentions?” Hohwy noticed how often things went wrong. “I think a lot about mental illness,” he says. “We forget what a high percent of us have some mental illness or other, and they’re all characterized by the internal model losing its robustness. One percent of us have schizophrenia, ten percent depression, and then there is autism. The server crashes more often than we think.”
Eli Sennesh elaborates on the importance of feeling "in tune with the world". He writes: "The core of “emotion” is really this thing we call core affect, and it’s actually the core job of the brain, any biological brain, at all. This is: regulate the states of the internal organs (particularly the sympathetic and parasympathetic nervous systems) to keep the viscera functioning well and the organism “doing its job” (survival and reproduction). What exactly does “its job” comprise? Well, that’s where we actually get programmed-in, innate “priors” that express goals. Evolution endows organisms with some nice idea of what internal organ states are good, in terms of valence (goodness/badness) and arousal (preparedness for action or inaction, potentially: emphasis on the sympathetic or parasympathetic nervous system’s regulatory functions). You can think of arousal and sympathetic/parasympathetic as composing a spectrum between the counterposed poles of “fight or flight” and “rest, digest, reproduce”. Spending time in an arousal state affects your internal physiology, so it then affects valence.
"The brain is thus a specialized organ with a specific job: to proactively, predictively regulate those internal states (allostasis), because reactively regulating them (homeostasis) doesn’t work as well. [See Peter Sterling's article.] Note that the brain now has its own metabolic demands and arousal/relaxation spectrum, giving rise to bounded rationality in the brain’s Bayesian modeling and feelings like boredom or mental tiredness. The brain’s regulation of the internal organs proceeds via closed-loop predictive control, which can be made really accurate and computationally efficient. We observe anatomically that the interoceptive (internal perception) and visceromotor networks in the brain are at the “core”, seemingly at the “highest level” of the predictive model, and basically control almost everything else in the name of keeping your physiology in the states prescribed as positive by evolution as useful proxies for survival and reproduction.
"Get this wrong, however, and the brain-body system can wind up in an accidental positive feedback that moves it over to a new equilibrium of consistently negative valence with either consistent high arousal (anxiety) or consistent low arousal (depression). Depression and anxiety thus result from the brain continually getting the impression that the body is in shitty, low-energy, low-activity states, and then sending internal motor commands designed to correct the problem, which actually, due to brain miscalibration, make it worse. You sleep too much, you eat too much or too little, you don’t go outside, you misattribute negative valence to your friends when it’s actually your job, etc. Things like a healthy diet, exercise, and sunlight can try to bring the body closer to genuinely optimal physiological states."
The allostasis model
In "Principles of allostasis: optimal design, predictive regulation, pathophysiology and rational therapeutics" Peter Sterling convincingly describes the importance of allostasis for adaptive fitness: "The goal of regulation is not constancy, but rather, fitness under natural selection. Allostasis considers an unusual parameter value, not as a failure to defend a set-point, but rather as a response to some prediction. For example, body fat is not regulated to a set-point, but varies according to some prediction – in this case, future hunger. Consequently, the allostasis model would redirect therapy, away from manipulating low-level mechanisms, toward improving higher levels in order to restore predictive fluctuation – which under this model is the hallmark of health. (This hints that the biggest improvements in health might be achieved by enhancing public life.) "Clamping" renders a variable insensitive to predicted need, which opposes the whole point of physiological regulation. The goal is not constancy, but coordinated variation to optimize performance at the least cost. In short, natural selection ensures prediction down to the limit set by physical laws."
Environmental disruption and the language of prediction
Prediction. McKibben is in the job of predicting the future. The problem isn't that we can't predict the consequences of our actions with a high degree of accuracy. We can. The problem is there are several things preventing an appropriate response from occurring. McKibben described the surface level systemic greed, exploitation, and abuse of power. Supporting this at a slightly lower level is disinformation and psychological manipulation (the thesis of Naomi Oreskes' Merchants of Doubt). We are very familiar with both of those. Below them there is a third level that subsumes them both. The very process of predicting the future and taking appropriate action is susceptible to various pathologies, preventing a healthy response to existential threats. In fact, many problems in society (market fundamentalism, violence, etc) are symptomatic of these deeper unexamined psychopathologies. This is a social and individual mental health crisis that explains anxiety, depression, suicide (and even autism and schizophrenia). The impact of social cognitive health on environmental health cannot be understated. Our ability to collectively model, predict, and take appropriate action is of central importance to addressing disinformation and resisting exploitation, and so at the very least, we need to be aware of these connections. They are often hidden to us, but they can illuminate some of the more promising avenues for intervention. This is why I'm reading Andy Clark's book "Surfing Uncertainty". As we live through accelerating periods of political upheaval, environmental disruption, and novel disease outbreaks, it is all the more critical to be in tune with the world, and use the conceptual language that describes how to do that.
According to the Free Energy Principle, in general people naturally tend to focus on what is surprising to them. We focus on the things that don't fit into our models, the differences. We don't focus nearly as much on the things that aren't so surprising, that fit nicely into our models and expectations, or in other words, the similarities we share with each other. This natural human tendency is reflected in our conversations and gets amplified by the limited forms of expression enabled by social media. These attenuated and context deprived channels of communication can then easily serve as a wedge that further divides society into two or more polarized camps. Note how paradoxical this has all become - the very way we model, predict, and take appropriate action has now turned around against us to frustrate many of those very processes.
As Rebecca Onie describes, "We are torn apart by immigration, education, guns and health care... But what if underneath all the noise, we're not divided? What if the things that we don't ask about are the things that we most agree upon? It turns out that when we ask the right questions, the answers are startling, because we agree, not on health care, but on something more important: we agree on health. Why? We agree on health because it is common sense." She suggests "changing the questions we ask and quieting the noise to hear each other's answers" and see "the radical possibility... that we agree". What does this tell us? It suggests to me that there is a profound connection between (1) the way our minds key into certain features of the world, (2) on the basis of which we make behavioral choices, and (3) the broad consequences these choices have for our health. As Rebecca Onie demonstrates, we can do so much more when we are aware of these connections. Our models of the world share more in common than we would readily admit. If we begin our conversations from this place of shared understanding, we can work together much more effectively in pursuit of our common goals.
When one political faction seeks short term gains by cutting regulatory oversight, weakening the social safety net, and eroding government institutions, there will be harmful consequences for people and the survival of the republic. If they were widely exposed for these actions, they would lose support, so naturally they can only conduct their actions in secrecy or, if later exposed, through misdirection by blaming a scapegoat (a minority faction, foreign group, social institution, or more fundamentally, the very nature of government itself) while claiming personal victimization and unquestionable moral integrity. All this doesn't actually solve anything, but that's not the point anyway. It allows the corrupt faction to retain power while redirecting the growing public dissatisfaction to the scapegoats and absolving themselves of culpability. None of this would succeed if it wasn't for the fact that it is easier to highlight the differences among social groups rather than celebrate the similarities we share. If we are 98% similar and 2% different, that is all the justification many people need to weaken or eliminate public services. So the survival of these social institutions, and the republic itself, relies upon which features of the world we believe are most salient and how they shape our cultural, political, and economic models. For a republic in the grip of nationalist ideologues, it isn't so much that the electorate supporting them is immune to reality, so much as the electorate's view of reality has been distorted. (And this distortion is sustained and reinforced by the stressful conditions that result from the deprivation of basic needs.) They have been encultured to pay inordinate attention to the surprising elements, the differences, the sources of fear, and generally dismiss the far greater elements which are commonly shared by all.
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| Rosen (top) and Friston (bottom) |
Karl Friston pointed out that humans act "to avoid possible surprises in the future (such as being cold, hungry or dead)". When we consider environmental issues such as climate change, these should concern us deeply, because extreme weather, crop failures, and mass death for both humans and other species are exactly the sort of future events we can expect from our inability to sufficiently address this existential threat. But let's begin with the basic theory. For Friston, to be alive is to act in ways that reduce the gulf between your expectations and your sensory inputs. The connection between the mental world of meaning, interpretation and prediction and the physical world of signs is also highlighted in biosemiotics, and so researchers who have published on biosemiotics, like Mel Andrews, have found Friston's ideas insightful as well. The philosopher Arran Gare, who noted the application of Rosen's modeling relation to biosemiotics, apparently hasn't remarked upon Friston, though I would be interested in hearing his thoughts on that. You can see how similar this all sounds to Robert Rosen's modeling relation described in his book Anticipatory Systems. Friston's work has been called "predictive coding" or predictive processing, a theory of brain function in which the brain is constantly generating and updating a mental model of the environment. This model is used to generate predictions of sensory input that are compared to actual sensory input, and any resulting prediction errors are then used to update and revise the mental model. Friston explains this in more detail:
To predict one’s own states you must have an internal model of how such sensations are generated. The brain is a self-evidencing organ of inference. What distinguishes conscious and non-conscious creatures is the way they make inferences about action and time. This rests upon the reciprocal relationship between the [formal] system and the world [the natural system]. The world acts on the system to provide the sensory impressions that form the basis of inference. Meanwhile, the system acts upon the world to change the flow of sensations to fit with the model of the world it has discerned. A creature cannot infer the consequences of its actions unless it possesses a model of its future. It needs to know what to expect if it does this as opposed to that. For example, I need to know (or subconsciously model) how my sensations will change if I look to the left, to the right or, indeed, close my eyes. But the sensory evidence for the consequences of an action is not available until it is executed, thanks to the relentless forward movement of time.As Daniel Dennett noted in "Darwin’s Dangerous Idea", "Getting it right, not making mistakes, has been of paramount importance to every living thing on this planet for more than three billion years, and so these organisms have evolved thousands of different ways of finding out about the world they live in, discriminating friends from foes, meals from mates, and ignoring the rest for the most part." All adaptive systems must gather information about the external world, infer models of events and causes in the outside world based on this information, and take action based on these models, updating them as novel experiences offer new precedents. This process, as Dennett noted, began billions of years ago when life was first being formed, and has been rediscovered by cultural evolution. The ability to use our brains to construct models is what allows us to explain the world around us. We even make models of our brains, that is, we model the model making process itself, and this is where Robert Rosen's axioms for anticipatory systems provide the philosophical foundation for current approaches by Karl Friston and others. Consistent with much that has been written regarding the extended evolutionary synthesis, Friston proposes we can “endow existential dynamics with a purpose and teleology... attractors are the product of processes engaging in inference to summon themselves into being. In other words, attractors are the foundation of what it means to be alive. Complex systems validate the principle that underpins their own existence. Attractors push systems to fall into predictable states and thereby reinforce the model that the system has generated of its world. ...the mind comes into being when the process of self-evidencing this model has a temporal thickness or counterfactual depth, which grounds the inferences it can make about the consequences of future actions.” Friston explains further: “The time horizon or depth of these models may be very short or very long. Usually, the deeper the model, the greater the number of policies that can be entertained — and the greater the counterfactual breadth or richness. Put another way, counterfactual breadth scores the latitude an agent has to select among viable policies that she expects to resolve uncertainty (i.e., reduce the expected surprise of being hungry or ignored).”
As a result of the arrow of time, systems that can grasp the impact of their future actions must necessarily have a temporal thickness. They must have internal models of themselves and the world that allow them to make predictions about things that have not and might not actually happen. Such models can be thicker and thinner, deeper or shallower, depending on how far forward they predict, as well as how far back they postdict, that is, whether they can capture how things might have ended up if they had acted differently. Systems with deeper temporal structures will be better at inferring the counterfactual consequences of their actions. The neuroscientist Anil Seth calls this counterfactual depth. So if a system has a thick temporal model, what actions will it infer or select? The answer is simple: it will minimise the expected surprise following an action. How do systems minimise expected surprises, in practice? First, they act in order to reduce uncertainties, that is, to avoid possible surprises in the future (such as being cold, hungry or dead). We might call this kind of system an agent or a self: something that engages in proactive, purposeful inference about its own future, based on a thick model of time.
Jesse Bettinger and Timothy Eastman in "Foundations of anticipatory logic in biology and physics" suggest that the purpose of our models of self and environment is for regulatory oversight, monitoring of conditions, and threat assessment. Organisms work toward fulfilling their existential needs before these become a crisis, but their models are only as good as the information they are based upon, and vulnerable to "quick" and "radical" changes (Rosen, 1980); “as a result, they are often incapable of dealing with or surviving change that is unprecedented. But, as long as environmental changes are slow enough and congruent with what the model entails, the system is robust and remains stable”. Today we know we are heading toward a future of radical, quick environmental changes, the effects of which could be devastating. The process philosopher Alfred North Whitehead believed that causal connection takes place, not in virtue of the cause, but of the effect, in other words that causality pulls us ever toward the future. As John Deely wrote "the future beckons the present", or as Rosen said, models pull "the future into the present". As the present begins to merge with the future, we see all the more clearly the possible effects of the actions we take today. Friston wrote "beliefs about outcomes in the distal future influence beliefs about states in the proximal future and present. That these beliefs then drive policy selection suggests that, under the generalised free energy formulation, (beliefs about) the future can indeed cause the past."
An indeterministic model of time
"Intuitionist math also offers a novel interpretation of our conscious experience of time. In this framework, the continuum is sticky, impossible to cut in two. Nicolas Gisin associates this stickiness with our sense that the present is “thick” — a substantive moment rather than a zero-width point that cleanly cleaves past from future. In standard physics, based on standard math, time is a continuous parameter that can take any value on the number line. “However,” Gisin said, “if the continuum is represented by intuitionistic mathematics [where the law of excluded middle, a vaunted principle since the time of Aristotle, doesn’t hold] then time can’t be cut in two sharply.” It’s thick, he said, “in the same sense as honey is thick.” The lack of the law of excluded middle is akin to indeterministic propositions about the future. And an indeterministic future lends further credence to the importance of counterfactual thinking. Paraphrasing Judea Pearl in "The Seven Tools of Causal Inference": "The understanding of cause-effect connections is a hallmark of human cognition that allows us to choreograph a parsimonious and modular representation of our environment, interrogate that representation, distort it by acts of imagination and finally answer “What if?” questions. Examples are interventional questions: “What if I make it happen?” and retrospective or explanatory questions: “What if I had acted differently?” or “What if my flight had not been late?”
Markov blankets and the modeling relation
Rosen said “Life is the manifestation of a certain kind of (relational) model. A particular material system is living if it realizes this model.” In "Life Itself" he wrote: "Category Theory comprises in fact the general theory of formal modeling, the comparison of different modes of inferential or entailment structures. Moreover, it is a stratified or hierarchical structure, without limit. The lowest level, which is familiarly understood by Category Theory is, as I have said, a comparison of different kinds of entailment in different formalisms. The next level is, roughly, the comparison of comparisons. The next level is the comparison of these, and so on." Rosen’s focus on entailment was (and is) shared by Judea Pearl, who in 1988 coined the term “Markov blanket”. Now compare what Rosen wrote with "Life as we know it" (2013) by Karl Friston: "The Markov blanket of an animal encloses the Markov blankets of its organs, which enclose Markov blankets of cells, which enclose Markov blankets of nuclei and so on... there are probably an uncountable number of Markov blankets in the universe. ...Life comprises Markov blankets of Markov blankets — all the way down to cellular organelles and molecules like DNA, and all the way up to organisms and their environments, both ecological and social. The organizational boundaries of living systems are open and flexible in the precise sense that such boundaries need not be co-extensive with an organism's bodily boundaries." Friston's illustration of Markov blankets, reminiscent of the “action-perception cycle” and which have appeared in subsequent papers of his as well, could be derived from Rosen's illustration of the modeling relation, and in both cases these involve a sort of circular causality. (Life both predicts external causes of sensory states and causes the external causes of sensory states through action.) For ease of comparison, both authors describe the process of active inference (Friston) or inferential entailment (Rosen) and have conveniently placed the natural system or environment on the left hand side.
Autopoiesis/autogenesis in Deacon and Friston
Francis Varela described ‘the intriguing paradox’ of an autonomous identity: How can a living system both distinguish itself from its environment and, at the same time, maintain its energetic coupling to its environment to remain alive? The answer, as explored in a paper coauthored by Friston, lies in the conditional independencies induced by the presence of a Markov blanket, which separates internal states and external states while creating a coupling between organism and environment via sensory and active states. "The cell is an intuitive example of a living system with a Markov blanket. Without possessing a Markov blanket a cell would no longer be, as there would be no way by which to distinguish it from everything else. This is to say that, if the Markov blanket of a cell deteriorates, there will be no evidence for its existence, and it will cease to exist. The biological world is a world populated by Markov blankets... The very existence of living systems can therefore be construed as a process of boundary conservation, where the boundary of a system is its Markov blanket."
Terrence Deacon explored this question as well and proposed a model of "simple autogenesis", defined as self-reconstitution with respect to potential destruction, and claimed this is an interpretant production process that distinguishes self from non-self. He asked, "How can a molecular structure become a representation of the essential functional constraints of the system that can be referenced in the process of repairing or reproducing its essential system integrity and synergistic unity?" His solution was that processes of reciprocal catalysis (autocatalysis), the same as those involved in creating viral capsules, lipid membranes, and microtubules, produce the very constraints required for their perpetuation, and are all examples of a general "autogen model". To what extent is it possible to describe each of these examples (capsules, membranes, and microtubules) as Markov blankets? And would a minimal system defined by a Markov blanket be another way to describe an autogen? In statistics and machine learning, the Markov blanket for a system forms an interface between it and the external environment. The consilience between the approaches used by Deacon and Friston may not end here however, as interpretant generation and self-assembly may bear significant similarities to the concept of "self-evidencing", as the term is used by Friston, or "self-actualising" as used by Maslow (though the connection with psychology is more speculative). One could even say that, combining multi-scale and self evidencing perspectives, the self actualizing person maximizes evidence for the larger community, culture, and higher scale categories (such as the larger biotic community).
To Karl Friston, evolutionary theory is basically a process of inference and natural selection is really model selection. What sorts of models are fit for an eco-niche? In "Free Energy and the Brain" he describes how biological systems encode a model of their environment implicit in their phenotype, and this model allows them to make predictions and act to avoid phase-transitions that would irreversibly alter their structure, possibly resulting in death. These models also encourage selective sampling of the environment to either reinforce or correct the model. This improves model predictions and minimises free-energy across a lifetime. By identifying the model entailed by an organism’s structure, we can predict how it will change. Looking at this process as it plays out over evolutionary timescales, depending upon the heritability of key model components, we can see how models themselves are selected for as a population explores its "model space". Simply put, species with a low free-energy will be selected over species with a higher free-energy, and species which fail to minimise free-energy will ultimately experience extinction.
In "The Markov blankets of life" the authors provide a simple metaphor for life: "Any organism that must adapt to the changing dynamics of its environment must be able to infer the sensorimotor consequences of its own actions. It cannot do so without possessing a generative model of its future states dependent on how it acts. This is what adaptive active inference is: the capacity to infer the results of future actions given a history of previous engagement with the world, harnessed in the prior probabilities reflected in the generative model. Intuitively, to remain alive an organism must avoid crossing terminal species-specific phase boundaries. An example of a phase boundary that makes this clear is the bank of a river. On one side of this boundary, an organism will retain its structural integrity. On the other side, it will not (unless it is amphibious). Being near a riverbank thus presents such an organism with at least two probabilistic outcomes relative to how it might act. It can move in such a way that it falls over the side of the riverbank. Or it can move to remain at some distance to the riverbank. This means that an organism must have prior probabilistic beliefs about (the consequences of) its behaviour, which, in turn, implies that it must be able to sample across different probabilistic outcomes of its own actions.
"What might happen were it to jump into a fast flowing river? Note that such a creature cannot access sensory observations of such outcomes, until it undertakes one action, at the expense of others. This means that systems able to make such future-oriented inferences must possess a generative model with temporal or counterfactual depth. A system with a temporally deep generative model will be a system capable of acting (i.e. inferring) ahead of actuality. The deeper the temporal structure of a living system's generative model, the better it will be at sampling across the probabilistic outcomes of its own actions — and the better it will be at entertaining a repertoire of possible actions. In the absence of any prior beliefs about what it would be like to be in the water, the river holds an epistemic affordance (i.e. novelty), in the sense that entering the water resolves uncertainty about ‘what would happen if I did that’. If the unfortunate creature subsequently drowned, priors would emerge (with a bit of natural selection) in her conspecifics that water is not a natural habitat. A few generations down the line, the creature, when confronted with a riverbank, will maintain a safe distance in virtue of avoiding expected surprise, i.e. fulfilling the prior belief that ‘creatures like me are not found in water.’ Hence, if a creature cannot swim it becomes imperative to keep away from the banks of the river. This, in turn, implies that its imperative for action selection must be guided by priors stating that whichever action is selected it must be one that minimizes expected surprise. Survival is therefore premised on having a generative model with a particular temporal thickness."
The Free-energy principle, active inference, and self-evidencing
Connor Wood writes: "If the brain has the prior belief that “an organism like me occupies a temperature range of 97-99 degrees Fahrenheit,” but then discovers that in fact its body temperature is 96 degrees, it won’t just shrug and conscientiously revise its model. If it did, you would die of hypothermia, and then the brain’s single most important model – the model that predicts that the brain exists and inhabits a living body – would be falsified. So instead, the brain tells the body to go inside from the cold, sit near the heater, and drink a hot cup of cocoa. Pretty soon, your body temperature has recovered, and the Bayesian prior predicting that the body will occupy a temperature range between 98 and 99 degrees is once more nicely corroborated by the data. In all cases, the goal is to get the internal models to match external reality, or to minimize the gap between model predictions and data.
"Now, active inference is the key to maintaining low-entropy conditions all the way up and down the Great Chain of Being (or Markov Blankets, as it were). When a bacterium perceives that its glucose levels are low, it does not correct its “model” to encompass low-glucose states as being compatible with its own existence. Instead, it whips its little flagellum around, or whatever, and goes out and devours something. Every living system needs to update models to better fit reality and update reality to better fit the models. We don’t think strictly in order to aquire true beliefs and become more knowledgeable, but in order to survive and adapt in a difficult world. The purpose of cognition, biologically speaking, is the maximization of model evidence for the existence of the cognizing entity.
"A number of free-energy theorists think that the entire biological world is Markov blankets all the way up and down, from the tiniest cells to the biggest human societies. This means that, just as the brain tries to maximize evidence for its own existence (and thus avoiding states of hypothermia, glucose shortage, oxygen deprivation, and so forth), a nation-state (for example) is also trying to maximize evidence for its own existence. It induces people to act in ways that alter the world so as to corroborate the prior hypothesis that it exists. This is why symbols are so important for countries, religions, and marriages. “Believe that the United States exists, and act in ways that cause this belief to meet with good model evidence.”
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| Julie Pitt |
Is “fake it till you make it” good advice? Why do we believe a fantasy? What is needed to maintain the illusions we hold most dear? These are questions about models that we want to be true, but we don’t know if they can or will be. These models, whether they are about a life of sobriety, a successful career, or a happy marriage, require that we put in the work to produce the evidence needed to support them, the evidence that will make them true for us. That’s called “model evidence”. As Karl Friston wrote, “This implies that a sufficient explanation for valuable behavior is the accumulation of evidence for internal models of our world". Elsewhere he and coauthors write: "Modern economic models of choice, dating to the 1950s, suggest that the aim of human decision-making is to maximize ‘utility’, a quantity tied to notions of pleasure and reward. More recently a different line of reasoning has stressed the notion of homeostasis (or allostasis), recognizing that agents maintain their states within certain bounds to persist in the face of a changing world. From an information-theoretic perspective this implies that agents have to optimize a model of their environment and, given that model, minimize surprise about the states they find themselves in. This is equivalent to maximizing the evidence for their model of the world (because, negative surprise is Bayesian model evidence). Based on this view, belief, as opposed to reward, based formulations of choice behavior are attracting interest. For a purely passive agent, surprise can be minimized through learning and inference (changing an internal model to make better predictions). However, embodied agents are capable of acting on the world, enabling them to minimize surprise through (epistemic or pragmatic) actions and select the outcomes they expect (i.e., are the least surprising). This notion is at the heart of active inference, which provides an increasingly influential account of action and choice behavior."
"We provide evidence for a belief-based (active inference) formulation of choice, based on surprise minimization, as opposed to a classical economic treatment of decision-making as maximizing value or utility. ...This may provide important insights into how agents ‘make sense out of the world’ and how certain aberrancies in these processes may induce psychopathological behavior." If environmental destruction is psychopathological behavior on a civilizational scale, then perhaps a belief-based formulation of choice can also provide insight into this as well. As the authors say in a related paper, the tendency for "visiting new and informative states to maximize model evidence (i.e., improve our model of the world) may lay the foundation for future developments [in economic decision-making tasks]." Also note in Friston's paper "What is value: accumulated reward or evidence?" where he writes: "active inference replaces policies in normative models with prior beliefs about the (future) states agents should occupy." This suggests that the best way to gain support for a particular normative model and associated policies is to address whether and how it provides evidence for prior beliefs, and if not, whether those priors can be reassessed in light of their inability to provide such evidence. When we "treat control problems as inference problems" and formulate them in terms of prior beliefs, which in turn "depend upon the parameters of the generative model (transition probabilities among hidden states)", we can shift our perspective from utility to belief, from control to inference, and from uncertainty to model evidence. Each shift offers promising new possibilities for engaging with formerly intractable problems.
To persist in the face of a changing world we must be able to maintain ourselves within certain bounds. To do this we construct a model of a world in which we are able to persist, and then we seek to maximize the evidence for it. We can now define valuable behavior to be the search for, and accumulation of, such model evidence (self evidence). In contrast, psychopathological behavior is either the construction of an inaccurate model of the world, or a model in which, for whatever reason, we are unable to accumulate evidence that we are able to persist. ...The first order of business is to design an adequate model. The next step is to use the model to act in the world in such a way as to anticipate and select the outcomes that maximize the evidence for this model. For example, the most salient feature for a single-celled organism, like a paramecium, is the presence of food (glucose). But for us, in addition to what is required for the basic life functions of growth and reproduction, our model evidence may include any of a variety of activities and qualitative perceptions, ethical norms, and aesthetic values, such as beauty, purity, trustworthiness, and how these are measured and evaluated. In short, the task of selecting the right model evidence among the salient features of the environment is as much a form of art as it is a science.
Anil Seth: “This is why understanding the constructive, creative mechanisms of perception has an unexpected social relevance. Perhaps once we can better appreciate the diversity of experienced realities scattered among the billions of perceiving brains on this planet, we will find new platforms on which to build a shared understanding and a better future—whether between sides in a civil war, followers of different political parties, or two people sharing a house and faced with washing the dishes.”
Models creating models, or transposing internal and external
One of the most beautiful things I heard Friston say concerns embodied cognition: "You can't just look at the brain again as some glorified stimulus-response link, some bank of filters that's presencing information. You really have to think about the action-perception cycle, the circular causality induced by the notion that the environment is acting upon you and you are acting upon the environment. It's a dance, a dialogue. If it's the case that the key thing is in the exchange between you, with your internal states, and the environment, with the external states, across the thing that separates us from our environment (the internal and the external states across this boundary that has sensations going in this direction and actions going in that direction), that structure mathematically can be completely transposed and nothing changes. Which means that your action upon the world becomes the world's way of perceiving you. And the world acts upon you, through your perception of the world. There's a beautiful symmetry there. Buddhism talks to this circular causality, of being causally embedded in a world through the embodiment of our brain." Elsewhere he said "The environment is trying to learn about you as much as you are trying to learn about the environment." The world acts on the system to provide the sensory impressions that form the basis of inference. Meanwhile, the system acts upon the world to change the flow of sensations to fit with the model of the world it has discerned. A simple example of these embodied processes was later given in "The Markov blankets of life", a paper he coauthored. "It is possible to consider the physiological make-up of a fish, as a model of the fluid dynamics and other elements that constitute its aquatic environment — its internal dynamics depends on the dynamics of the eco-niche in which it lives. It is in this embodied sense that an organism is a model of the world it lives in. And by virtue of being a model, it is able to encode or represent that world (within a mental model)."
Life depends on healthy processes of active inference and model building
The brain is continuously engaged in an act of interpretation Karl Friston calls “active inference”, which is the process of building models of our environment that we update with evidence we collect, all in the service of making the world a more learnable, predictable place. “It means that you can choose which data you sample in order to make inferences about the causes of those data. In the past these choices would have been specified by cultural evolution, by the physical limits of travel, and the number of people that we can physically converse with,” says Friston. “But now those constraints are gone. Technology has extended the capacity for active inference to overcome uncertainty. We have to relearn how to attend, what to attend to, and what to ignore. If we don't assign the right confidence to different sources of information that we've engineered for ourselves with technology,” he says, “then we could end up making false inferences very much along the same lines as people with schizophrenia might make false inferences about the causes of certain things they're witnessing.” (Plato began his allegory of the cave by talking about how we make false inferences as well.) As a corollary of active inference, Friston has proposed what he calls the “free energy principle”. This describes how systems seeking to make the world a more predictable place will consequently try to minimize the difference between their model of the world and their sensory perception of it by either correcting their model or actively changing the world. “You could look at this as a physics of sentient systems,” he says. “Cells, organs, brains, people, societies, eco-niches, banks - anything that self-assembles and maintains its structural and functional integrity is subject to this principle. Institutions, even cultures could at some level be accounted for by the underlying mechanics.” This simple idea has very far ranging consequences for the way we work and organize ourselves socially.
Thomas Metzinger, ethics, and the role of suprapersonal models
Karl Friston makes reference to the work of Thomas Metzinger, and his book “Being No One” (which in turn referenced Philip Johnson-Laird and his book “Mental Models”). Metzinger identifies an insight into how models work: “you cannot recognize your self-model as a model, it is transparent: you look right through it. You don’t see it. But you see with it. In other words, as you read these lines you constantly confuse yourself with the content of the self-model currently activated by your brain.” In his TED talk Metzinger continued: "You live through that transparent window. But you don't see the window itself. You can never experience consciousness as such. We don't see the window but only the bird flying by. This gives us the experience of being directly in contact with the world. Conscious experience is an integrated model of reality. We can be unaware of the medium through which information reaches us that means we have the feeling of being directly in touch. Philosophers call this the phenomenology of direct realism and it creates the experience that something exists and that it is real." Metzinger pointed out that the observation that consciousness is like a window was earlier articulated by G. E. Moore in a 1903 article he wrote. Walter Benesch frequently made a related point about the subject and object dichotomy: we can be aware of the contents of subjective thought, but not turn subjectivity itself into an object.
In his book, Metzinger also speculates on the role of models in ethics: “The classical notion of “virtue” can be interestingly reinterpreted, namely, in terms of increasing the internal and social consistency of the self-model, for example, in terms of functionally integrating cognitive insight, emotional self-modeling, and actual behavioral profile. Traditional notions like “intellectual integrity” and “moral integrity” now suddenly possess new and obvious interpretations, namely, in terms of a person having a highly consistent self-model. Ethical behavior may simply be the most direct way of maximizing the internal coherence of the self-model. It could therefore be directly related to the concept of mental health.” And in a recent interview identified the role of suprapersonal models in society: “Human societies are very special. For instance, you are a moral subject, and I'm a moral subject, but together we create a new subject, a suprapersonal self model. Parliament would be an example of a self model of society where the different parts are coherently represented.” These suprapersonal models open up questions about self-construal, and are exactly those which concern me most when considering our ability as a society to anticipate disruptions before they occur and facilitate adaptive changes.
A good regulator is proactive, not just reactive
In Conant and Ashby’s oft-cited 1970 paper, “Every good regulator of a system must be a model of that system”, they use the example of a cow, which is homeostatic for blood temperature. In its brain is an error-control center that, if the blood temperature falls, increases the generation of heat in the muscles and liver. But because the blood temperature must fall first, error-control regulation is an inferior method of regulation. Thankfully for the cow, this reflex acts only as a reserve. Ordinarily the nervous system senses at the skin that the cause of a potential fall has occurred, perhaps from a sudden gust of ice cold air for example, then predicts a need to regulate preemptively before the error even happens, raising the blood temperature without any preliminary fall. Evolution equipped organisms with progressively more effective types of regulation such as this, able to use information from the environment about causes as the source of regulatory actions.
This example is used by Conant and Ashby to support their conclusion that the living brain, so far as it is to be successful and efficient as a regulator for survival, must proceed, in learning, by the formation of a model (or models) of its environment so that it can anticipate change before it occurs. They write “the best regulator of a system is one which is a model of that system as seen through a mapping... For centuries, the study of the brain has been guided by the idea that as the brain is the organ of thinking, whatever it does is right. But this was the view held two centuries ago about the human heart; today we know what the heart, as a pump, ought to do and so we can measure its efficiency. The developing knowledge of regulation, information processing, and control is building similar criteria for the brain. Now that we know that any regulator must model what it regulates, we can proceed to measure how efficiently the brain carries out this process. There can no longer be any question about whether the brain models its environment: it must.” And so we may fairly assume society at all levels from local to global must model its environment and it's impacts thereupon, so that it may anticipate future change and take proactive measures to ensure survival.
Rewards and costs
Andy Clark: "Behaviors are brought about by the interaction of our beliefs with the environment. Reward and pleasure are consequences of some of those interactions, but they are not the cause of those interactions. Instead, complex expectations drive behavior, causing us to probe and sample the world in ways that may often deliver reward or pleasure. In this way, reward is a perceptual (hedonic) consequence of behavior, not a cause." (Surfing Uncertainty, 129) This implies that if we want to motivate people, the best way to do that is to appeal to their beliefs and models, and not rely on the fear of pain or enticement of pleasure overmuch. This also sheds light on “bad habits”, why people will sometimes consistently engage in activities that are harmful or have costly consequences, even when they know that negative outcomes are probable. In these cases, it appears they are simply unable to alter their internal models, which override their knowledge of the likely rewards and costs. This may explain why destructive systems and behaviors are so difficult to change - they are surprisingly resistant to modification through incentives. We have to address the dysfunctional models that lie at their root.
The Dialectics of Free Energy Minimization
Boonstra and Slagter write: "From a Hegelian perspective, the tension between whether an organism is a secluded entity separated from its surroundings, or whether it is a dynamical system characterized by perpetual openness and mutual exchange, is sustained over the course of its life. Not only does the organism’s secluded existence depend on a perpetual relation with its surroundings, but the condition for there to be such a relation is the existence of a secluded entity. This contradiction—tension internalized—is at the center of Friston’s anticipatory organism and grounds the perpetual process of free energy minimization. ...The challenge is to show how the unsolvable minimization problem of Friston’s framework actualizes the tension between seclusion and openness.
"The brain is a self-organizing system that undergoes change as a way to resist change. This is where Hegel’s 19th century philosophy and Friston’s free energy minimization converge. ...By taking the preconditions of the organism as a starting point, “the FEP (free energy principle) provides a normative, teleological essence to the synthesis of biology and information” (Allen and Friston, 2018). In other words, the organism’s internal purposiveness (“teleological essence”) follows from the necessary condition that has to be met for there to be an organism. Both in the case of Friston and Hegel, such a necessary precondition is the existence of a boundary between the organism and its surroundings: “the events that ‘take place within the spatial boundary of a living organism’ [Schrödinger] may arise from the very existence of a boundary or blanket, which itself is inevitable in a physically lawful world” (Friston, 2013). In Hegel’s words: “Nature’s formations are determinate [bestimmt], bounded [beschränkt], and as such enter into existence” (Hegel, 1830). In other words, natural objects are to be bounded if they are to exist.
"The living organism (subject) feels contradiction, and its activity is directed towards overcoming this contradiction by getting rid of (negating) the feeling of need: the process begins with “the feeling of lack [Mangel], and the urge [Trieb] to get rid of it [ihn aufzuheben]” (Hegel, 1830). But because the organism’s contradiction is constitutive for its existence, there is no definite escape from it as long as the organism is alive: “[t]his contradiction, that they are and are not, […], manifests itself as a perpetual process” (Hegel, 1830). Therein resides the paradoxical status of living beings: the organism harbors at once the maintenance of its own identity, as well as the negation of this identity. An unresolvable state of tension arises concurrently with the imposition of a boundary; with the precondition for the organism’s existence. For the organism, there is no way to establish the accuracy of its anticipations. All the organism can do is minimize the discrepancy between its anticipations and its elicited sensory states, by either changing its anticipatory model, or its sensory states through action."
Ecological-Enactive Free-Energy Principle
Congruence between our econiche and our system of anticipations (our so-called generative models) is at the heart of the free-energy principle. Here Bruineberg and Rietveld propose the "ecological-enactive free-energy principle" (E-FEP), which extends this core synchronization and resonance by making a dual appeal. First, our system of anticipations needs to be congruent with the structure of our environment. By being better attuned we are able to anticipate the relevant affordances it enables. Second, we must minimize the discrepancy between our anticipations and the feedback we are getting. By being situationally responsive to the relevant affordances our interaction with the environment improves and we can thrive in the characteristic states that make up the human ecological niche: playfulness, seeking novelty, and acquiring new skills in new practices.
Karl Friston wrote: “An agent does not have a model of its world—it is a model. In other words, the form, structure, and states of our embodied brains do not contain a model of the sensorium—they are that model” (Friston, 2013). We do not have a model of the world—we are a model of that world we seek to bring forth. The synchrony between ourselves and the world is crucial because a flourishing future requires that we are able to both (1) anticipate and (2) work to bring about the conditions that are compatible with our future existence and ways of flourishing. The problem is that, although we know a lot about the things we need to do, we are still out of tune with the environment and out of step with each other. This has led to environmental and social disharmony, making our work at times seem nearly impossible. We need to ask not only what must be done, but we must also select, nurture, and develop those models that are most capable of guiding the future course of our work despite the constant threat of disruption.
Moving this from theory to application, many of the adaptive strategies we use often begin very well - they are highly responsive to context when first conceived and implemented - but over time the models they are based upon “lose their grip” and become less relevant. This makes them less effective over time and causes them to tend to fall apart. Ensuring our models retain situational awareness and responsiveness while retaining their distinct features and purpose is important. We are constantly trying to minimize the discrepancy between what we anticipate (through the use of our models) and what we actually perceive (through the use of our senses). This is done by continually updating our models and changing the world through action. This agrees with the Transition Towns community movement, for example, which begins with a goal and a model embodied by the movement itself. This model moves in the direction of the particular future that it anticipates by means of adaptive tactics and shifting strategies that are situationally responsive to the relevant affordances. Bruineberg and Rietveld describe this in their paper: “The key question is… how the agent acts on the world so as to make the environment conform to what it anticipates. If the agent anticipates a flourishing state, the system of anticipations will steer its interactions with the environment toward flourishing. Our E-FEP approach has generalized synchronization and resonance at its core and attempts to explain how, as a result of free-energy minimization, neurodynamics becomes attuned to anticipate relevant affordances that make the whole system tend toward grip on its ecological niche.”
Applied to the Transition Towns community movement, once that model anticipates a flourishing future state, it steers its interactions with the environment toward this future by means of becoming attuned to the relevant affordances that exist within its eco-niche. This is generalizable to any movement. But clearly, not all movements realize their goals. According to this theory, a common reason for failure is no longer being in tune with the relevant affordances. When we fail to update our models, we lose our “grip”, and can no longer make reasonable predictions nor identify and take appropriately informed actions. If Transition Towns, or any movement, is going to avoid that sort of fate, they may want to take heed of the E-FEP model. It is all about how successful individuals, species, communities, and movements lay a path toward long term survival. As the authors note, "Given that we live in a highly dynamic world, being metastably poised to switch to multiple new relevant action-readiness patterns is itself an adaptive trait, and necessary for an agent to tend toward grip on its interactions with the environment." The world has become a much more dynamic place over the last few centuries, and our models are straining (failing) to keep up with the pace of change. We are losing (have lost) our grip. Without a proper account of "anticipation and selective consolidation" of the sort described here, it may be more difficult to improve our grip and switch to multiple new relevant action-readiness patterns.
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| value is model evidence of our world |
My friend remarked today (4/22/20): "After 50 years, shouldn't we be asking, how did we get so close to the brink?" There are many ways to answer that question, and most of them are about what “theory of change” we use. Here's one that I was just thinking about... The classical economic treatment of decision-making as maximizing value or utility doesn't always work. What people really try to maximize, at a more fundamental level, is simply their model evidence. So if we want to shift the economy in some predetermined direction, then in addition to the usual attempts to maximize economic value by making it easy and affordable, we should also see how this shift would impact model evidence for all stakeholders. To do so requires making our models and the prior beliefs within them more explicit. If you doubt the effectiveness of this approach, consider that the fashion industry and the experience economy, to name a few, operate almost exclusively in this way. (The advertising industry does as well, though far more deceptively.) This can shed light upon irrational economic decisions. Given a choice between two options where one has greater utility than the other, the option with less utility may nonetheless be selected if it provides greater model evidence by comparison. And model evidence does not only influence choice, it also influences the models themselves via feedback and mutual interaction. Along with numerous other market failures and barriers, the influence of model evidence understood in this context should not be underestimated. It might explain why any theory of economic/ political/ social change that is overly reliant upon a single form of intervention, whether Pigouvian tax or otherwise, has met with limited success so far.
There are significant differences between micro and macro economics, in terms of the particular motivations, constraints, and relative influence, but there are similarities as well. Any given individual or institution will operate in a fairly regular and predictable way. If they didn't, they couldn't persist at all and would soon dissolve. What allows them to persist is their ability to model their interactions within the world so that they can adapt and respond to changes in a way that preserves their identity. Both people and institutions must know how to meet certain needs, else die or be dissolved though lack of maintenance. All models begin with this basic utility. Model evidence is, in one sense, self reassurance in all it's forms. Reassurance that our beliefs are true, that indeed we are successful, that we will be able to meet our needs in the future. That, in effect, our models and thus ourselves are useful representations of a world that is dynamic and complicated. So you can see why individuals would want this, at at some level, so do institutions. We want to believe our models have utility.
From what I've read, the "ESG investing" model looks like a logical application of this theory of change. It replaces less responsible investment model evidence (profit only) with more responsible model evidence (principles of sustainabilty). That can certainly help to realign markets. In so many words, unregulated markets seek the wrong model evidence (increasing inequality) determined by an inaccurate model (infinite growth). But the ESG investing model is only the beginning. In every case, we should be able to identify how psychopathological economic behavior is a direct consequence of aberrant models and model evidence. To "cure the disease" and realign markets, we must use accurate models and correct model evidence; all else is treating the symptoms and offering temporary relief (which can buy much needed time). Conceptually, this is a relatively simple problem. But in practice, it may be a lot of work to determine exactly how our models have gone wrong, whether and how they can be fixed, and how this affects "model evidencing" processes. There is a research community engaged in this work today, but the applications for contemporary social problems have barely begun. We will have to identify those models that are most congruent with human needs and ecological limits. As with ESG Investing, most people already understand that we need better models to drive policy. However we still need to bring more attention to modeling processes, and not just the models themselves. For this reason, a comprehensive project that focuses on the intersection between modeling processes and contemporary issues should be a priority.
We use model evidence to evaluate everything, including ourselves, our institutions, and our policies. When the evidence of our senses is surprising, in other words that things have not gone as we predicted and everything is falling apart (as with current planetary boundaries), we have two main jobs: diagnosis and treatment - highlight the aberrant modeling processes that brought us to this fateful condition, then correct them to restore balance to the system. Anyone would be skeptical about whether treatment is really needed if they do not understand the nature of their pathology, so we do need to accurately highlight the pathology. A diagnosis could begin using something like an informal health questionnaire:
- Are you able to make future plans? [Do you have internal models?]
- Are things going according to plan? [Are those models accurate?]
- Are you optimistic about your future? [What does your model evidence tell you?]
- What do you think you would need to feel better about it? [What model evidence are you looking for today?]
- What sort of future do you want? [What model evidence is ultimately needed?]
- How do your plans lead to this future? [Is there congruence between models and model evidence?]
- How did you come up with these plans? [Is there congruence between the world and your model?]
The point of the questionnaire is to validate our individual needs, while at the same time interrogating methods. If economic/ political/ social/ problems can be ultimately traced to mental health and medical problems, and those can be shown to derive from model selection, the inferences they lead to, and the evidence we seek for confirmation, then some variation on these questions could shed light on those models and modeling processes, and if/whether they are functional. If they are dysfunctional, then we can point out that lack of congruence and suggest healthier alternatives using a comparative approach.
Karl Friston asked "What is value - accumulated reward or [model] evidence?" And the answer is model evidence, not reward. Speaking for myself, I never cared too much about whether I am rewarded or not, but rather whether my beliefs are evidenced or not. So why do we respond to people with facts when for the most part they only care about beliefs? We should be trying to understand why people believe what they do, and how they try to find support for these beliefs. Without that no progress is possible. All of us like to think that our evidence will lead to reward, though many times we do not know for sure. But if evidence does not lead to reward, then disaster is not far off. This is why an apostate is shunned - they are a constant and uncomfortable reminder that the model evidence of the faithful may not in fact lead to the reward they seek. All my life I've been surrounded by people telling me that reward is important, and while that is true, reward means nothing to me at all if I cannot connect it to evidence. That is why people would rather believe a lie that they can understand, than a fact that makes no sense to them. And that is why we all need good model evidence. That said, the goal of the nervous system isn't acurate representation, but useful behavior. This may be another reason why merely telling somone that their representational model is wrong won't convince them that their behavior isn't useful. Instead we must show that their are internal conflicts within whatever models that they use, and (especially) between those models and the model evidence they seek.
If you've ever tried to convince someone of anything, you might've heard the response, in so many words, "Oh yeah, but what's in it for me?" Fair question. To answer it we need to know what motivates people. And at bottom, what motivates us is any evidence that reduces our uncertainty. And specifically, uncertainty about the beliefs we hold that are relevant to the future. Money, for instance, can be very compelling evidence. If I have a higher salary or larger bank account, then that is evidence for my belief that I should be able to afford basic needs like health care, housing, food, recreation, etc. That money helps to reduce the economic uncertainty I feel. This shows that we value money because it serves as evidence for prior beliefs that exist within our mental models. Which means we have several points of intervention for motivating people. We can offer money (tokens for needs), we can offer more direct evidence for beliefs (actual provision of needs), or we can change mental models (what are our needs?). You can see where various policy approaches fit on different levels here. It can be very difficult to motivate anyone if they already have what they believe is sufficient evidence for their beliefs. In other words, preliminary to this discussion, it is necessary to first establish that the future is indeed less certain than we suppose (given the projections for global heating and associated costs). Only once that has been established does any proposal for addressing this uncertainty begin to make sense. And even then, any policy proposals, in order to motivate action, must be sufficiently compelling when compared against a background of many other policies to address other sources of uncertainty, such that the proposal would still be allocated some measure of our time and energy (in exchange for tokens, evidence of uncertainty reduction, etc.)
Wang Yangming, active inference, and self-evidencing
In "The Instructions for Practical Living" (Ch'uan-hsi lu) Wang Yangming (1472 - 1529) wrote, "There have never been people who know but do not act. Those who are supposed to know but do not act simply do not yet know. But people today distinguish between knowledge and action and pursue them separately, believing that one must know before he can act. They will discuss and learn the business of knowledge first, they say, and wait till they truly know before they put their knowledge into practice. Consequently, to the last day of life, they will never act and also will never know. This doctrine of knowledge first and action later is not a minor disease and it did not come about only yesterday. My present advocacy of the unity of knowledge and action is precisely the medicine for that disease. The doctrine is not my baseless imagination, for it is the original substance of knowledge and action that they are one. Now that we know this basic purpose, it will do no harm to talk about them separately, for they are only one. If the basic purpose is not understood, however, even if we say they are one, what is the use? It is just idle talk. Knowledge is the beginning of action and action is the completion of knowledge. Learning to be a sage involves only one effort. Knowledge and action should not be separated." These lines came to mind when I read “action and perception are facets of the same underlying imperative” in the paper "A Duet for One" by Friston and Firth. A later paper states "loops of action and perception are called active inference. Put simply, this suggests that action and perception operate synergistically to maintain homeostasis and optimise the organism's generative model. In other words, every organism seeks to maximise sensory evidence for its own existence; it is essentially ‘self-evidencing’. [This] alludes to Maslow's ‘hierarchy of needs’ – it suggests that the meaning of life is to self-actualise.” I am beginning to see why Wang Yangming was held in such high esteem by my philosophy professor.
The Butterfly Dream
"Once upon a time, I, Zhuangzi, dreamt I was a butterfly, fluttering hither and thither, to all intents and purposes a butterfly. I was conscious only of following my fancies as a butterfly, and was unconscious of my individuality as a man. Suddenly, I awaked, and there I lay, myself again. Now I do not know whether I was then a man dreaming I was a butterfly, or whether I am now a butterfly dreaming I am a man. ...Fools think that they are awake now, and believe they know it distinctly. How stupid! Both Confucius and you were dreaming. When I say you were dreaming, I am also dreaming. This way of talking may be perfectly strange. If after ten thousand ages, we could once meet a great sage who knows how to explain it, it would be as if we meet him in a very short time."
That story, now over two thousand years old, is a complete rejection of the distinction between subject and object, between the dreamer and the dream, the modeler and the model, what is real and what is an illusion. Recently it was given a modern interpretation from Nick Bostrom and Elon Musk, who believe we may be living in a simulation as opposed to "base reality". But the point was never whether we are butterflies or humans, or living in reality or a simulation. The point is that we cannot reasonably make any distinction between the two because it would involve an infinite regression of relationships. (Are we butterflies dreaming that we are humans dreaming that we are butterflies? Or are we humans dreaming that we are butterflies dreaming that we are humans dreaming that we are butterflies? Ad infinitum.) The general form this takes is asking whether we are just simulations simulating simulations, role models role modeling role models, signs signifying signs, dreams dreaming dreams. If I say "no", then I am Zhuangzi's fool....Putting a slightly different spin on this perennially favorite metaphor, recently Winona LaDuke compared social and environmental activism to the dramatic physiological transformation that occurs in metamorphosis. This process is orchestrated by imaginal cells, which are special stem cells that contain all the information about the new model of life under development. As LaDuke put it, we are the imaginal cells of society.
Big History approach to models
Yuval Noah Harari's book “Sapiens” proposed that “three important revolutions shaped the course of history. The Cognitive Revolution kick-started history about 70,000 years ago, the Agricultural Revolution sped it up about 12,000 years ago, and the Scientific Revolution, which got under way only 500 years ago, may well end history and start something completely different.” This is "big history", the time frame of aeons to the time frame of punditry — of now, and soon. Harari built a big model about an extremely big process. Unlike conventional history which typically begins with the introduction of farming and civilization, or with the beginning of written records, "big history" tries to grasp history as a whole, looking for common themes across multiple time scales. Has anyone written a book that takes a "big history" approach to modeling and simulation? In "The Secret of Our Success", Joseph Henrich wrote that culture arises from genetically evolved psychological adaptations for locating and learning from the best models. And Jeremy Lent's book "The Patterning Instinct" explores how the instinctual human ability to detect patterns allowed us "to make meaning of all the different events we experience and construct models for how to live our lives". He outlined the path of history according to the "core pattern of meaning" used by the people who lived at that time. Lent asks "Might a greater understanding of our cognitive patterns help us to construct a more integrated worldview that could put humanity on a sustainable path?" That's a great question. Our ability to perceive regularities in the world around us lead to the construction of models based upon that information, and those models have allowed us to anticipate the future and dramatically change the world around us. This is indeed big history, and the last word on that topic hasn't been written yet. Will you write the next chapter?
[Currently this article could probably use more structure. Throughout, I’ve tried to consistently promote greater realization of the influence of models on our thinking, their roots in philosophy, biology, and culture, and their numerous applications in health care, economic, infrastructure, education, labor, and many other sectors. While I clearly favor some more than others, I’m not advocating for any single model in particular, as these are extremely context dependent and always changing. What follows is a rough outline of the above contents.]
Resources:
Clark, Andy. Surfing Uncertainty. 2015
Seth, Anil. Being You: The Inside Story of Your Inner Universe. 2021
Seth, Anil. The Real Problem. 2016
Beni, Majid Davoody. Structuring the Self. 2019
Hohwy, Jakob. The Predictive Mind. 2014
Frith, Chris. Making up the Mind: How the Brain Creates Our Mental World. 2007
Bruineberg, Jelle. What’s Inside Your Head Once You’ve Figured Out What Your Head’s Inside Of. 2019
Additonal resources:
The Dialectics of Free Energy Minimization
Where There is Life There is Mind: In Support of a Strong Life-Mind Continuity Thesis
Radical Disruptions of Self-Consciousness
Self-supervision, normativity and the free energy principle
Where There is Life There is Mind: In Support of a Strong Life-Mind Continuity Thesis
A Multi-scale View of the Emergent Complexity of Life: A Free-Energy Proposal
Extended active inference: Constructing predictive cognition beyond skulls
Minimizing prediction errors in predictive processing: from inconsistency to non-representationalism
The Nature Of Reality & The Reality Of Nature (with Prof. Anil Seth)
On Markov blankets and hierarchical self-organisation
Thomas Bayes and the crisis in science
A Theory of Reality as More Than the Sum of Its Parts
Being Realist about Bayes, and the Predictive Processing Theory of Mind
Knowledge is crude
Structuring the Self
The Predictive Processing Paradigm Has Roots in Kant
The interoceptive turn
A more human approach to artificial intelligence
Active inference: building a new bridge between control theory and embodied cognitive science
A tale of two densities: active inference is enactive inference
Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems
How to Argue With Kindness and Care: 4 Rules from Philosopher Daniel Dennett
How to Knit Your Own Markov Blanket
Organism, Machine, Process. Towards a Process Ontology for Organismic Dynamics
Troubles with Bayesianism: An introduction to the psychological immune system
Computational enactivism under the free energy principle
Contents:
Introduction
Culture, Religion, Anthropology, and Semiotics
Climate Science and modeling
Maps and models
Models of Health
Models of pandemics
Epidemiological models and political games
Challenge prevailing beliefs
Models respond to salient features
Substance abuse
Social and environmental movements
Economy, capitalism, and GDP
The Limits to Growth
Problematic models
'Deep Social Mind' theory
Treat the disease while you manage the symptoms
Models of proper mental hygiene
Mind over Matter
Reactance and Comparative modeling
Mental models and mindfulness
Monkey mind makes mental models
Models explaining causality and models describing behavior
Model-Dependent Realism
Laws, Constraints, and the Modeling Relation
Robert Rosen, Biosemiotics, and Modeling
Model transmission to future generations
The Nordic Model
New Bottles For New Wine
Circular economies presuppose circular models
Intentional communities and virtual communities
Models for energy, housing, and community spaces
Detailed Digital Doubles, Counterfactual Duplicates
Mirrorworld
The Power and Influence of Models in society
Human ancestry models
The power of role models to shape culture
Fast and slow thinking and the pursuit of long-term goals
Political power and voter manipulation
Fear, control, cults, and the apocalypse
Japanese models for weapons and law enforcement
Models of abuse
Education
Models of kinship and family structure
Labor workforce modeling
The "deficit model" and the "conflict model"
Narrative models and quasi-religious storytelling
Model disruption
Model corruption
Model disintegration
Philosophical perspectives: Anekantavada and bounded rationality
Philosophical and Spiritual models
A basis for trust, collaboration, and action
Embodied prediction, empathy, and altruism
To protect, we must predict
Procrastination, perceptual control theory, and predictive processing
The free energy context
The allostasis model
Environmental disruption and the language of prediction
Karl Friston, existential threats, and predictive coding
An indeterministic model of time
Markov blankets and the modeling relation
Autopoiesis/autogenesis in Deacon and Friston
Will Earth cross a terminal phase boundary?
The Free-energy principle, active inference, and self-evidencing
From utility to belief, from control to inference, from minimizing surprise to maximizing evidence
Models creating models, or transposing internal and external
Life depends on healthy processes of active inference and model building
Thomas Metzinger, ethics, and the role of suprapersonal models
A good regulator is proactive, not just reactive
Rewards and costs
The Dialectics of Free Energy Minimization
Ecological-Enactive Free-Energy Principle
Earth Day reflections on theories of change
Wang Yangming, active inference, and self-evidencing
The Butterfly Dream
Big History approach to models
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