The Attention Economy

"Go to the ant, thou sluggard; consider her ways, and be wise." - Proverbs 6:6
"Blessed are the meek: for they shall inherit the earth." - Matthew 5:5

It's late September, and for some reason articles about termites are popping up in my newsfeed. Three days ago, in "What termites can teach us" Amia Srinivasan explored the concept of the "extended organism" and what Radhika Nagpal calls "extended stigmergy." Just two days ago, in "A giant crawling brain: the jaw-dropping world of termites" (an extract from "Underbug: An Obsessive Tale of Termites and Technology") Lisa Margonelli writes "one scientific metaphor for the inscrutable termite is a neuron in a giant crawling brain." [3] Okay, so termites are interesting, but if you want to see what eusocial insects are really capable of, consider ants, specifically the Argentine ant, Linepithema humile, whose name literally means “humble” or “weak.” About this species a paper was written titled "The global expansion of a single ant supercolony."

Feng Gao at the 2014 Umbrella Movement

It's the ability to indirectly coordinate large groups of individuals, via the mechanism of stigmergy, that makes these insects so successful. They benefit from the synergistic effects of working together. The central insight of stigmergy is that global coordination can be achieved by individual agents interacting locally. Two fundamental principles govern this: 
1. No matter how large the environment grows, because agents interact only locally, their limited processing capabilities are not overwhelmed. (This is useful, since today no single person understands every aspect of society which affects them.) [4]
2. Through the dynamics of self-organization, local interactions can yield a coherent system-level outcome that provides the required control. (This is useful, since we have a need to coordinate goals with people we will never speak to.) [1,7]

Originally, the concept of stigmergy was used to build up a coherent explanation of the so-called "coordination paradox" between the individual and the societal level. The explanation to the coordination paradox provided by stigmergy is that individuals interact indirectly: each affects the behavior of others by indirect communication. [2] Andy Clark and David Chalmers' paper "The Extended Mind" explores a related concept to stigmergy and other forms of indirect communication/coordination, they write: "Does the extended mind imply an extended self? It seems so. ...This view will have significant consequences. It may be, for example, that in some cases interfering with someone's environment will have the same moral significance as interfering with their person. In any case, once the hegemony of skin and skull is usurped, we may be able to see ourselves more truly as creatures of the world." [5]

If this is as far as we go, then we understand the basic idea of stigmergy and may even suspect that it could be capable of greater utility. Radhika Nagpal, in her TED talk, said "We can actually take these rules that we've learned from nature and combine them and create entirely new collective behaviors of our very own." [6] Leave it to Daniel Estrada and Jonathan Lawhead to give what I consider to be one of the best descriptions of how stigmergy can be leveraged in human society. In doing so, they bring in several additional ideas. The first of these is the concept of "natural human computing," (aka human-based computation). [18] This is analogous to stigmergy. Just as we can think of ants or termites as neurons within a brain, individual human behavior patterns, via their interaction, can be thought of as cooperating to compute the solution to a problem. The second of these ideas is that of the "attention economy." The short explanation is that an attention economy treats our attention as a finite resource constantly produced by conscious attenders. Today we live in a money-based economy, so the movement toward an attention-based economy would parallel the movement from the “object dimension” to the “subject dimension" of philosophical space. [8] Per Estrada, "what makes this flow of attention different from every financial economy we are familiar with: you can't store attention. You can't stockpile attention or reserve a bank of attention units. There is no debt in an attention economy and there can be no surplus of attention. There is just the total amount of attention being produced, and the many ways we allocate that attention among all the things we spend our time doing.” [9]

Now we are ready for Estrada and Lawhead's paper "Gaming the Attention Economy," which establishes two very important ideas: (1) how to leverage the normal behavior of individuals to solve complex problems, and (2) how to uncover the real value of things that our current economic system fails to recognize. By utilizing the new tools enabled by augmented reality and digital communities for exchanging goods and services (like Craigslist), we can efficiently address energy, environment, and resource related problems. To me, the potential for addressing climate change holds significant promise. [15, 17] Today we have just glimpses of how utilizing the computational dynamics of natural human activity, acting upon high quality information about local patterns of attention, use, and interaction, can solve the economic optimization problem (and even non-economic social problems). In fact, as Daniel Estrada and Jonathan Lawhead write, that’s a reason why it may eventually replace our current money-based system.

According to Estrada, “Attention models are fundamentally a measure of consensus and therefore may function as the legitimate grounds for a self-organized system of governance, while at the same time working as a model for collectively planning the production, distribution, consumption, and recycling of our natural resources. In this sense, an Attention Economy is a complete system for social organization, and therefore may function in the ideal case without significant contributions from either money or centralized political institutions. ...The attention economy unifies what have traditionally been considered the “separate magisteria” of human social organization: the domains of economics, of governance, and of culture, each of which are traditionally assumed to operate by their own internal dynamics. In fact, these domains are deeply interconnected, and an attention economy will allow us to visualize these relations directly. ...As we collectively confront problems that require social, coordinated action, human societies will increasingly appeal to attention-based models rather than other kinds of models for solving coordination problems.” [9] "[These] provide the essential feedback loops for allowing human communities to self-organize at a global scale," [10] end various forms of exploitative hierarchical systems, and restore the traditional reverse dominance hierarchy to humankind.

Paraphrasing Estrada, we have a lot of work to do: the social networking tools for generating spontaneous direct actions and broad democratic consensus are important. They must operate openly, transparently, and independent of any centralized state or corporate control. [13, 14] State and corporate interests often diverge from the collective interests of the people, so instead of state power generating conformity to social norms, self-organizing social networks will need to ensure that control stays on the side of the people, and include a method for social credit monitoring to manage the distribution of labor and resources such that they are effectively abundant and accessible to all participants in a fair and democratic way. [11, 12, 16] We have some good models for how to do this, but we are a long way from realizing their potential. 

Tags: attention economy, human-based computation, social computing, superorganism, (extended) stigmergy, extended mind, distributed cognition, agent-environment feedback loop, crowdsourcing, augmented reality, gamification (in government), game theory, social credit system (China), Aadhaar (India), persuasive technology, coordination paradox, multi-agent systems, interpersonal utility comparison problem, distributed autonomous organization (DAO), personal autonomous organization (PAO), social physics, sousveillance (reciprocal accountability), algorithmic social contract, Scalable Cooperation Group, 共識主動性社會 (stigmergy society)

Footnotes:
[1] A Survey of Environments and Mechanisms for Human-Human Stigmergy, 2006
[2] Cognitive Stigmergy: A Framework Based on Agents and Artifacts, 2006
[3] Heylighten, Accelerating socio-technological evolution, 2007: "Quantitative stigmergy is nearly identical to the process of reinforcement learning that differentially strengthens connections between neurons in the brain. Qualitative stigmergy is the true motor of innovation."
[4] Heylighen, Stigmergy as a Universal Coordination Mechanism: components, varieties and applications, 2016: "Compared to traditional methods of organization, stigmergy makes absolutely minimal demands on the agents... by coordinating initially independent actions into a harmonious whole."
[5] The Extended Mind
[6] What intelligent machines can learn from a school of fish
[7] Heather Marsh, A societal singularity: We have reached a "societal singularity" characterized as a state where "no one can understand every aspect of society which affects them" yet we have a need to "coordinate goals with people we will never speak to."
[8] Walter Benesch, “An Introduction to Comparative Philosophy.”
[9] The Attention Economy 
[10] The Attention Economy Primer
[11] Sesame Credit will (eventually) make fully automated luxury queer space anarcho-communism possible
[12] David Brin: "The combined weight of all the new surveillance technologies heading our way is a recipe for disaster, beyond Orwell’s wildest nightmares. The only way we can stop them from becoming instruments of repression is by giving everyone access to these tools so that the powerful will be stymied and held accountable, and ordinary citizens will be empowered. By answering surveillance with sousveillance. By demanding that Aadhaar report to the people more effectively than to the mighty."
[13] Alex Pentland, Reinventing Society in the Wake of Big Data: “The most efficient and robust architectures tend to be ones that have no central points. It means that there's no single place for a dictator to grab control."
[14] LeRon Shults, Artificial Intelligence Shows Why Atheism Is Unpopular: “It’s going to be done. So not doing it is not the answer.” Instead, he believes the answer is to do the work with transparency and simultaneously speak out about the ethical danger inherent in it.
[15] Inducing Peer Pressure to Promote Cooperation, 2013
[16] Morality in the Machines, "Jonathan Zittrain’s ambition for the AI initiative is immense: to democratize social media’s secret algorithms, artificial intelligence and similar technologies."
[17] Gamification and Climate Change Activism - Beneficial or Detrimental?
[18] Human computation is an approach to solving complex problems that leverages the personal informatics of normal individual behaviors to increase the effect of coordinated action. It does this by using the tools of social computation (social networks, marketplaces, fine-grained details, augmented reality, etc.) to make information about normal human behaviors available to their users. This increased information availability creates robust progress feedback loops that allow humans to select individual behaviors or characteristics for either reinforcement, interruption, alteration, (etc.)
[0] Peter Corning and Eörs Szathmáry, "Synergistic Selection": A Darwinian frame for the evolution of complexity, 2015: "...new forms of information have played a key role in the emergence of complexity at every level, from DNA coding sequences in the genome to pheromone “signals” in social insects, the evolution of language in humankind, and (now) the binary/digital code of the internet age."

Additional Sources:
Big Idea: Attention Economy
Daniel Estrada on Bruce Sterling’s “The Caryatids” As a Model for the Attention Economy
Vivek Singh, Ankur Mani, and Alex (Sandy) Pentland, Social Persuasion in Online and Physical Networks
Daniel Estrada, Rethinking Machines: Artificial Intelligence beyond the Philosophy of Mind (The central issue in human computation concerns the integration of human brains into a general computing architecture that allows for efficient and useful results when applied to challenging computational tasks. How do we attract and sustain the attention of multiple agents, and under what conditions do they perform well?)
Social Norms: Social Identity, (how social identities and relationships motivate choices and actions)
Daniel Estrada's Polytopolis: A distributed framework for organizing communities and values (inspired by the psychology of social identity and collective behavior).
Patchwork theory
Heather Marsh, Inteligencia Colectiva para la Democracia (video presentation)
Heather Marsh, The evolution of democracy (transcript of above presentation)
Stigmergic epistemology, stigmergic cognition, 2007
A Brief History of Stigmergy
Stigmergic Collaboration: A Theoretical Framework for Mass Collaboration, 2007
Kosorukoff, A., Goldberg D. E. “Evolutionary computation as a form of social organization”
Introduction to Human Computation
Jane McGonigal “Reality Is Broken: Why Games Make Us Better and How They Can Change the World”
Climate Change? There’s a Game For That
Gamification for health and wellbeing: A systematic review of the literature (persuasive technology, serious games, and personal informatics; game design elements can be mapped to established behavior change techniques; like personal informatics, gamification tracks of individual behaviors, displayed to the user, enrolled in some form of goal-setting and progress feedback)
Gamification: An Introduction to Its Potential (human based computation game) Game mechanics and dynamics tap into fundamental human needs and desires, such as the desire for reward, status, achievement, self-expression, self-efficacy, competition, and altruism, among others. Intrinsically rewarding activities can be enhanced with gamified elements (and access to greater information and new forms of social interaction), potentially accelerating real-world change on an individual, social, and global scale.
Hive-mind solves tasks using Google Glass ant game
New game creates a hive mind out of Google Glass users

Gedanken Experiment

Democritus (430-380 BC) said "I would rather discover one causal relation than be King of Persia." Was he just being an eccentric philosopher, devoted to knowledge for its own sake? Or did he realize that an understanding of causal relations has myriad possible applications, and such a discovery could make him even more powerful than the most powerful person on Earth at the time? ...I think it was a little of both.

David Hume (1711-1776) distinguished between analytic claims (the product of thoughts) and empirical claims (matters of fact), classifying causal claims as empirical rather than analytic. He identified the source of all empirical claims with human experience, namely, sensory input.

Albert Einstein (1879-1955) said "Development of Western science is based on two great achievements: The invention of the formal logical system (in Euclidean geometry) by the Greek philosophers, and the discovery of the possibility to find out causal relationships by systemic experiment (during the Renaissance)."

Judea Pearl (1936- ) said "I am convinced that the entire story of causality unfolds from just three basic principles: (1) causation encodes behavior under interventions, (2) interventions are surgeries on mechanisms, and (3) mechanisms are stable functional relationships." In assessing our current position in relation to Einstein's quote, Pearl states that while the observational component of science has benefited from the power of formal methods, the design of new experiments is still managed by the unaided human intellect. But, when experimental science enjoys the benefit of formal mathematics along with its observational component, another scientific revolution will occur that will be equal in impact to the one that took place during the Renaissance. And AI will be the major player in this revolution.

When considering counterfactuals and digital models (essentially two sides of the same coin), the greatest agency to effect change (according to one's goals and abilities) will lay with whomever has a better understanding of mechanisms, causal relationships, and possible interventions. This is the takeaway message from Judea Pearl, and ties in considerably with Pedro Domingos and David Brin as well.

What I really believe, and what I am confident Democritus did as well, is that aside from the erudite novelty and numerous applications of a causal understanding, the greatest benefit of all is that it can bring the beauty and wonder of the world around us into clearer focus. And that is likely what motivated him most of all.

Source: Reasoning with Cause and Effect, by Judea Pearl

The Social Landscape

“The mind may be compared to a pan of water. If you place the pan on a level and do not jar it, then the heavy sediment will settle to the bottom and the clear water will collect on top, so that you can see your beard and eyebrows in it and examine the lines of your face.“ - Xunxi

In Freud's letter to Einstein in 1932, he said that human instincts are of two kinds: those that conserve and unify, and those that destroy and kill. The well known Love and Hate, attraction and repulsion. But he was quick to add that they are not good and evil, as "each is as indispensable as its opposite, and all the phenomena of life derive from their activity, whether they work in concert or in opposition." He went on: "If the propensity for war be due to the destructive instinct, we have always its counter-agent... All that produces ties of sentiment between man and man must serve us as war’s antidote... All that brings out the significant resemblances between men calls into play this feeling of community, identification, whereon is founded, in large measure, the whole edifice of human society." 

I'm reflecting on these polar tendencies in the context of computational social science, the result of the work of people like Alan Turing, Judea Pearl, Alex Pentland, Molly Crocket, and Radhika Nagpal (to name but a few). Pentland, for example, focused on social networks in his paper on promoting cooperation. One might say that these researchers are trying to map out the "social landscape" (to contrast with Harris' book The Moral Landscape). In our society today, despite the current social media services available, there are many people with few meaningful connections to others, people who replace social ties with unhealthy addictions, and those who find the thrill of tearing down more appealing than the work of building up. 

In a society with many broken parts, we need to chart a clearer course toward healthy relationships. Freud made contributions in this direction (arguably some better than others). And researchers like Elinor Ostrom demonstrated that it takes a LOT of documentation from history and ethnography, not just formal models. Now, combining detailed data with new analytic tools has created the potential today to extend that effort still further. For example, Iyad Rahwan described an algorithmic social contract. 

In "Rise of the Machines: A Cybernetic History" author Thomas Rid devotes a chapter to one of the interesting and less well known results of the social upheaval that occurred in the '60s and '70s. The psychedelic counterculture incorporated cybernetic ideas, which profoundly affected people like Kevin Kelly and Stewart Brand (of the Whole Earth Catalog) and influenced many who later became Silicon Valley innovators. Is there any similarity between John Lennon's idealistic lyrics in "Imagine" and a hypothetical algorithm for world peace, or as Freud said in his letter, "a formula for an indirect method of eliminating war?" They all draw their influences from the same cultural trends.

Cultural Genesis and Evolution

Melvin Kranzberg's first law of technology states: "Technology is neither good nor bad; nor is it neutral." I propose a parallel law: "Culture is neither good nor bad; nor is it neutral." There isn't perfect symmetry here though, since culture includes all of technology but technology doesn't include all of culture. The relationship between the two is very strong nonetheless, and will only increase. Technology has a growing influence on society, some aspects of which are obvious, others are nearly imperceptible, but all contribute to shaping our choices and actions. This much is generally well recognized. The implication is that if you control these influences, you can steer the future course of events in the direction of your choosing. This fact isn't as well appreciated, but the potential for direct and often invisible influence at the level of entire societies isn't new. Religious and political propaganda has been around for a very long time, directing cultural evolution into new directions. It was new technology that enabled the first revolution in agriculture about 12,500 years ago, directly precipitating large demographic and cultural shifts. What cultural changes will our new cognitive tools precipitate?

We need to reopen the conversation about what it means to create our culture. Who shapes it? Who benefits from it? Why? How could this change? As Noah Yuval Harari identified in his book Homo Deus, our accelerating ability to shape our environment, ourselves, and our societies brings with it a responsibility to do so intelligently. We are cultural engineers, whether we like it or not. We debate this today in the religious and political arenas, but there's more to it.

Cultural evolution is open-ended. Where could it go? If we wanted to take it somewhere, how would we do that? We know there are many wrong ways to intervene. The more interesting question is then: Is there a right way to intervene, to take our culture in the direction that leads toward human flourishing? It would have to be transparent, democratic, and meet the ethical standards society agrees upon. If such intervention is possible, what forms might it take? This is the exercise in generating scenarios. We've done that. The things we haven't done: 1) generate all the possible scenarios, 2) generate any single scenario in the fine-grained detail needed to show how it would impact the daily activities of any given individual. For example, if I wanted to ask "How would your scenario for a sustainable future impact my life?" Would I get a broad brush response, or would I get the details I'm most interested in? Would it reflect a new culture, and would I be receptive to making any changes if I knew what they were? For example, what are the socially sanctioned "default behaviors" when confronted by stress? What options does our culture first suggest? Find a distraction, consume food or entertainment, or respond constructively? A change in default behavior patterns that reflects a more constructive approach to stress and problem solving would require a society configured around supporting and encouraging these changes, not just in it's media and public discourse, but the social and material culture as well.

While it is true that many possible scenarios may lead to further entrenchment of bad policies, there remain open avenues to a more prosperous future. A lot of this comes down to communication and information availability, and so far, persuasion tactics based on the truth haven't been nearly as successful as those based on fictions. People need information that communicates the reality of their situation, and we haven't always succeeded there. From a social epidemiologist's point of view, many people are living in unhealthy conditions, in the broadest sense of that term. We need to move beyond the standard measurements of social outcomes and into measuring individual outcomes. The first question any voter asks is "How will this affect me?" That being the case, we should be able to tell them, and in as much detail as they want. If we can do that, then maybe we can also tell them how it will affect their community, region, state, international relations, and planetary health (within certain confidence levels). That's the direction in which we are headed. This is the potential of fine-grained data paired with counterfactual thinking to connect the dots in a new way, to reveal a more attractive future than the current local policies, operating procedures, and cultural context is able to permit.

A Beautiful Landscape: "taking no action contrary to nature," or "why wu wei?" (life, culture, aesthetics)

“Broad ways are extremely even, but people are fond of bypaths.” - TTC 53

Peter Corning said that "life is a process with a purpose" (teleonomy), and that purpose is our collective survival enterprise. Does our aesthetic sense mediate our relationship to that purpose? If Barry Lord was right that the kind of art you make and value reflects your culture, then will our culture reflect the kind of art we make and value? Seigen Ishin implied there are two kinds of people who see "mountains as mountains, and waters as waters," the naïve and the wise. And Karl Schroeder said "any sufficiently advanced technology is indistinguishable from nature." All of this, taken together, would seem to reinforce the view that we should take nature as our inspiration.

It is interesting to note that, in the Mūlamadhyamakakārikā, Nagarjuna uses the theory of "dependent arising" (pratitya-samutpada) to demonstrate the futility of metaphysical speculations, that things are neither empty nor not empty. Contrast this with the concept of non-action (wu wei), which is used to demonstrate that one should act without undue effort and let nature take it's course. This illustrates the characteristic difference in emphasis between early philosophical thought in India and China, the first focusing on the nature of reality and knowledge, and the second concerning the nature of embodied processes and subjective awareness. As we consider our unfolding cultural evolution, indirectly influencing factors such as these will play a role. The aesthetic qualities rooted in our early past can help guide our future course toward a culture that prioritizes health and adaptability.

Natural, Artifactual, Coevolutionary: Algorithmic art, a narrow application of natural aesthetics to factors influencing our social landscape and evolution

“Die jetzt aufgezeigte Handlung ist thetisch, antithetisch und synthetisch zugleich." - Johann Fichte

Architecture is considered a form of art. Why? After all, a building needs to provide some kind of shelter from the elements, but it doesn't need to be especially beautiful. Yet we all admit that some buildings are better looking than others. In like manner, I want to suggest we should view the coding for computer algorithms like architecture. In their basic design, they are just a functional scaffolding, but because of the social settings in which they perform their function, and the end result, there are several examples of algorithms that I believe can be considered genuinely beautiful.

The first example is Origamizer, an algorithm created by Erik Demaine and Tomohiro Tachi that can tell you how to fold a 2 dimensional sheet of paper into any 3 dimensional origami polyhedron. You read that right, ANY polyhedron. Want a paper rabbit? No problem. And now this algorithm is freely available as computer software.

The second example is Impartial Automatic Redistricting, an algorithm created by Brian Olson, a software engineer in Massachusetts, that can create "optimally compact" congressional districts in each state. Algorithm-based districts make so much intuitive sense that there are now many ways to generate them, like Wendy Cho's algorithm, which can do more or less the same thing.

Both of these examples may not be as iconic as the Taj Mahal in India or Sagrada Familia in Barcelona, but I think they qualify as the computer code equivalent of beautiful architecture. And they deserve wider recognition. Perhaps some day we'll have a phylogeny of algorithms, which will be displayed in museum collections or the equivalent of zoological gardens. Or maybe, in some sense (per Noah Harari) we already do.

Digital alter egos and the interpersonal utility comparison problem

"Behavior is the mirror in which everyone shows their image." - Johann Wolfgang von Goethe

A digital alter ego exists for each one of us, and these are engaged in countless virtual evaluations, product pairings, and scenarios to optimize our engagement with other people, service providers, etc. These digital models can also aid in confronting global issues. Here's how they can help us realize our values and aesthetic sense. Also referred to as a "digital double," they explore many "what if" scenarios that we are prevented from investigating in full due to limited time and resources. Often only one of these scenarios can ever become real. The overwhelming majority of them are destined to become unrealized counterfactual possibilities. Think of them as the latent potential that we only have fleeting glimpses of in the normal course of our lives. Some of this potential is the ability to realize, more fully than we do today, an environmentally and ethically responsible way of life that conforms to our aesthetic aspirations.

At this point I hear several objections. "Since we already have an understanding of our goals for social and environmental health, why do we need a digital alter ego to suggest scenarios we already want? And furthermore, if our so-called "leader/decision-makers" can't hear the smartest among us (scientists) why would they listen to digital doubles?" Because, as Pedro Domingos and other AI researchers suggest, a digital double would know you better than anyone else. At the upper limit, it would know you better than you know yourself. Consequently, if it can’t persuade you, nobody can. By comparison, a scientist is hardly persuasive to those who are opposed, on ideological or tribalistic grounds, to the basic assumptions or conclusions offered. This is the big obstacle to effective science communication: bridging the empathy gap, solving the interpersonal utility comparison problem. A digital double could be the perfect device for finding a common language to unite groups at opposing ends of the political divide. By exploring all counterfactual possibilities, a better consensus can be reached, and in less time. With further iterations, these benefits become multiplicative. Here's Domingos describing this future trend that we are already witnessing:

"The next decade is going to be one of accelerating change. Today each company has a little model of you based on just the sliver of your data that it has access to. Netflix has a model to predict your movie tastes based on your movie ratings. Amazon has a model to predict what you're going to buy based on what you've done on their site and so on. But all these little models are quickly coalescing into bigger and bigger ones and soon you'll have a complete 360 degree model of you that learns from all your data and assists you with everything that you're doing in your life, from buying things and making appointments to finding a job or a mate. Our "digital alter egos" will be even more indispensable to us than our smartphones, and the world economy will revolve around them. 

"Our society will become a society of models. Everyone's models will be continually collaborating, competing, and negotiating in cyberspace to determine what happens in the real world. You click on the "find me a job" button on LinkedIn and your model instantly interviews for all the open positions that match your specs at the same time. Another copy of your model can be looking for a car for you, exhaustively researching all the options and haggling with the car dealer so you don't have to. If you're looking for a date your model will go on millions of dates with thousands of other people's models and select the most promising ones to try out in the real world. 

"But your data, and your model, have to be under your control, not owned by some third party that may have a conflict of interest. Sergey Brin says that Google wants to be the third half of your brain, but do you really want part of your brain constantly trying to show you ads? Probably not. We need something different, maybe something like data banks that store your data and use it on your behalf in the same way that regular banks store and invest your money, or maybe we need data unions to even the balance of power between us and large companies in the same way that labor unions even the balance of power between workers and their bosses. And you need to be able to interact with your model, setting its goals, asking it to justify suggestions, telling it where it went wrong and why. All very different from the black boxes that we have today. And finally, as a society we're going to have to decide what kind of society of models we want to have. What's allowed, what's not, how do we make sure that everyone benefits, how do we smooth the transition? There is lots 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 digital models, imitating our individual lives as they do, will reflect both the good and less desirable aspects of our human nature. But just as when we see our faces in a mirror we have the ability to style our appearance to our liking, when we see our behaviors reflected in these computational models, we will have the ability to reinforce those behaviors that promote our common good, and exert greater restraint over those that detract from it.

Partial list of terms:  
無常 (Japanese: mujō, Pali: anicca) meaning: transience, impermanence.
物の哀れ (Japanese: mononoaware) meaning: the pathos of things, an awareness of ephemerality. (Compare with lacrimae rerum, weltschmerz)
侘寂 (Japanese: wabisabi) meaning: traditional Japanese aesthetics - beauty that is "imperfect, impermanent, and incomplete."
無為 (Chinese: wúwéi, Japanese: mui) meaning: non-action
無為而無不為 or 无为而无不为 (Chinese: wúwéi ér wúbù wéi) meaning: "No action is undertaken, and yet nothing is left undone." Tao Te Ching, chapter 37 and 48.
無用の用 (Japanese: muyonoyo) meaning: “without use's use." Zhuangzi's short parables about the use of the useless (Carpenter Shih, Crippled Shu)
もったいない (Japanese: mottainai) meaning: "Do not destroy (or lay waste to) that which is worthy."
道 (Chinese: tao) meaning: As a way of life, it denotes simplicity, spontaneity, tranquility, weakness, and non-action (wúwéi). “Reversion is the action of Tao.”

Additional reading:
Semi-artificial Photosynthesis
Get Ready for your Digital Model by Pedro Domingos

Causality, Counterfactuals, and Possible Worlds

Source: xkcd

“A Causal Revolution has spread like a chain of firecrackers from one discipline to the next: epidemiology, psychology, genetics, ecology, climate science, and so on... With every passing year I see a greater and greater willingness among scientists to speak and write about causes and effects, not with apologies and downcast eyes but with confidence and assertiveness.”
- Judea Pearl, "The Book of Why" (2018)

"Philosophy begins in wonder."
- Socrates

The pursuit of a better future for ourselves and our children begins with asking "Can we do better?" and furthermore, "Could we have done better, had we acted differently?" To both these questions, we must answer in the affirmative. That being the case, I believe we cannot avoid following up with "Why?" According to Judea Pearl, the prototypical "Why?" question is actually a counterfactual question in disguise.

People often imagine how things might have turned out differently "if only." But can counterfactual claims be true? Neil Sinhababu said this question about "possible worlds" is one of the hardest problems in philosophy. Nonetheless, "counterfacutal history," not to be confused with "alternative history" or "historical revisionism" (which has separate popular and academic meanings) can yeild important insights. For example, consider that following the election of President Trump, a lot of people who were disappointed in this outcome were asking "Why?" If Bernie Sanders had won the 2016 presidential primary, would Trump have been elected? If James Comey had not announced his investigation into Hillary's emails just 11 days before the election, would Trump still have won? Of course, we all know that such counterfactual scenarios did not occur, but it's hard not to wonder how things might have turned out differently.

Or consider that in the course of WWII, Alan Turing played a pivotal role in cracking intercepted coded messages that enabled the Allies to defeat the Nazis in many crucial engagements. Counterfactual history is difficult with respect to the effect Ultra intelligence had on the length of the war, but at the upper end it has been estimated that this work shortened the war in Europe by more than two years and saved over fourteen million lives.

A useful analogy is that counterfactual research in history is like chess. Each new move opens up the possibility for roughly thirty-eight times as many positions in the branching tree of analysis. We can ask: What are the most promising "moves?" How might the interaction of these counterfactuals and existing context play out? What is the logic connecting antecedent and consequent and the assumptions on which chains of causation are based? Supercomputers are routinely used to conduct counterfactual simulations in the sciences, where there can be multiple interactions at every move, and the chains set in motion interact with one another simultaneously and continually. (Richard Ned Lebow, "Counterfactual thought experiments: A necessary teaching tool")

Isaiah Berlin (Virtual History by Niall Ferguson)

Another great opportunity to ask some important "what if?" questions is suggested by Hanna Rosin, the author of "The End of Men: And The Rise of Women," where she chronicles the economic and cultural shifts that are upending male dominance. In a recent interview she said "Every time you have forward motion economically, any kind of progress for women, it's accompanied by a giant tidal wave of cultural backlash. And that's exactly the moment we're in right now." So let's ask: What if male dominance is upended? Ensuring women can enjoy the same rights and privileges as men is essential to our future. And yes, that will affect many cultural institutions, including marriage and child-rearing practices. Can we find a healthier response to this forward motion than the socially damaging cultural backlash we see now?

Would a better understanding of social physics and especially cause-and-effect relationships lead to the development of a Fair Society (as outlined in Peter Corning's book of the same name)? Consequentialist ethical theories posit that the consequences of actions should be the primary focus, so it would seem obvious that a clearer view of how cause and effect operates, at both very small and very large scales of space and time, could have significant ethical implications. If Judea Pearl is right when he claims a "causal revolution" has begun, this knowledge may force us to choose whether we will squarely face the ethical dilemmas that confront us, or renege on our responsibility to act given what we know. If we choose the later, our inaction will be rationalized away using the psychological acrobatics of self deception. But if we choose confrontation, it will be because our cumulative cultural evolution is open-ended and able to advance in spite of our individual limitations.

Visions of a better future, whether utopian or merely incremental, always address social problems, and, after the start of the Industrial Revolution these invariably include environmental problems as well. In so doing, we assume the ability to diagnosis our problems and prescribe an appropriate course of treatment. This descriptive/prescriptive dynamic is either explicit or implied. In this light, the fear of an apocalyptic dystopia is just as often the fear of human incompetence in diagnosis and treatment, as often as it is the fear of truly malign forces at work. This should serve to underscore the importance of understanding causal processes.

Our ability to gather information about the world around us, inquire how causal relationships change, and to intervene so we can change our behavior patterns, is critical. None of the answers to a question contain the possibility of asking the question in the first place, as my former philosophy professor, Dr. Benesch, was fond of saying. Scenarios that consider "what if?" questions are useful for both the possibilities and the insights they suggest, but they cannot simply suggest themselves. This is why the ability to ask the "what if?" and "why?" questions is so important. We need more counterfactual thinking today more than at any time in our past. The causal revolution hasn't arrived a moment too late.

Postscript:

Sewall Wright

The possibility of asking questions seems to assume subjective awareness, which seems to assume time asymmetry and therefore causality. If our subjective experience of time was symmetrical (no arrow of time) then the explanatory tool of causation, and the concepts of free will, agency, and intervention would likely be incomprehensible. But because we cannot see the future, the concept of causation is our primary tool to help bring it into focus. Causality is therefore the means, and understanding is the goal. Hence, if some procedure other than causality were discovered that could provide a greater means for understanding the interaction among variable factors across spatial and temporal scales, then that would be used in its place. As Newtonian physics is to general relativity, perhaps causation is to this as yet undiscovered means.

A few unresolved problems remain for me: 1) in the presence of synergistic effects, it may be impossible to perform meaningful causal analysis, and 2) depending on deterministic factors, we may need to reconceptualize our notion of how change occurs - intervention may only be described completely as a property of an entire system, not any single agent within that system.

"Causal inference may be superfluous in some idealised, superhuman version of physics, but if you actually want to find out how the Universe works, it is vital. ...But this doesn’t mean we must believe in a richly metaphysical idea of causal powers, ‘producing’ or ‘bringing about’ causal regularities like muscular enforcers of the laws of nature. We still see only the patterns, the constant conjunctions of different sorts of event."
- Mathias Frisch

But I can't neglect to mention the relationship between causality and feedback (cybernetics), and how that in turn relates to social networks and Alex Pentland's hope to have a transformative impact on our understanding of the dynamics of human society and our ability to plan for the future. And after all, causality and teleonomy may both be inherent biological qualities:

"Cognition is heavily grounded in space. As animals that move in space, we travel both physically and mentally in space and time, reliving past events, imagining future ones, and even constructing imaginary scenarios that play out in stories. Mental exploration of space is extraordinarily flexible, allowing us to zoom, adopt different vantage points, mentally rotate, and attach objects and sense impressions to create events, whether remembered, planned, or simply invented."
- Michael Corballis, "Space, time, and language"

My former history professor, Dr. Cole, identified the importance of looking to the future without being held in the past, a specific reference to The Pattern Problem. “In one sense, I feel sorry for younger people today because they’re trapped by the inability to reinvent themselves, free of the burdens of the past. People who know the past are stuck in it because they love repeating it,” Cole said. “This may sound odd to you, coming from a history professor, but I think history is a trap for many people.” ...You can escape that trap with counterfactual thinking.

Sourced quotes: 

"The ability to reflect on one's past actions and envision alternative scenarios is the basis of free will and social responsibility. Counterfactuals are at the core of the cognitive advances that made us human and the imaginative abilities that have made science possible. ...The rewards of having a causal model that can answer counterfactual questions are immense. Finding out why a blunder occurred allows us to take the right corrective measures in the future. ...The advantage we gained from imagining counterfactuals was the same then as it is today: flexibility, the ability to reflect on and improve upon past actions and, perhaps even more significant, our willingness to take responsibility for past and current actions."
- Judea Pearl, "The Book of Why" (2018)

"The survival of the fittest is a slow method for measuring advantages. The experimenter, by the exercise of intelligence, should be able to speed it up. ...If he can trace a cause for some weakness he can probably think of the kind of mutation which will improve it."
- Alan Turing, “Computing Machinery and Intelligence”(1950)

"We may define a cause to be... if the first object had not been, the second never had existed."
- David Hume (1748)

"Evolutionary events weren't destined to occur in the way that they did..."
- Stephen Jay Gould (1989)

Algorithmic Society

A better understanding of our actions within the context of their proximal and distal causes will enable us to improve health by selectively enhancing factors that promote it and intervening, when appropriate, for those that detract from it. The accompanying view of individuals and collectives at higher levels of temporal and spatial scale this encourages will tend toward an antireductive dissolution of dualisms, like mind/body, nature/artifice, and individual/social. These are a few of the results we can anticipate to see from the relatively new field of computational social science, which is becoming a principle paradigm through which society and culture, and even social contracts, are being viewed.

In "The Rise of the Social Algorithm" David Lazer writes "Humanity is in the early stages of the rise of social algorithms: programs that size us up, evaluate what we want, and provide a customized experience. This quiet but epic paradigm shift is fraught with social and policy implications. ...The fact that human lives are regulated by code is hardly a new phenomenon. Organizations run on their own algorithms, called standard operating procedures. And anyone who has been told that “it’s a rule” knows that social rules can be as automatic and thoughtless as any algorithm. Our friends generally are a lot like us and news media have always had to choose to pay attention to some stories and not others, in part based on financial and cultural imperatives. Social and organizational codes have always resulted in filter bubbles. However, every system of rules and every filtering process has potentially quite different dynamics and normative implications. Therein lies the most important lesson of Bakshy et al.’s report: the need to create a new field around the social algorithm, which examines the interplay of social and computational code."

It's been well established that our early capacities for learning from others enabled culture-driven genetic evolution. To paraphrase Joseph Henrich, genetic evolution is shaping us to be cultural learners, and cultural evolution shapes our genetic evolution. But Pablo Reyes Arellano digs deeper when he states: "The process of cultural evolution occurs through an algorithm." Culture-driven genetic evolution can be described as social "algorithm-driven" genetic evolution. Our many algorithmic innovations (such as fire, cooking, water containers, plant knowledge, and projectile weapons) drove our genetic evolution, altering our physiology, and psychology. These shared algorithms were the earliest sort of intelligence outside our own minds that we created. On a daily basis we interact with them, are affected by them, and can even be destroyed by them. Algorithms have been with us long before our recognition of contemporary artificial intelligence. 

Yuval Harari famously claimed "organisms are algorithms.” He was close. What he probably should've said was "cultures are algorithms," which is a far more consequential statement anyway. The embodiment problem (substrate dependence) makes algorithmic biology very difficult, but algorithmic descriptions of behavior and certain taxonomic characters (insofar as they are superorganic) are common. The field of physics is based on this premise. Animal behaviorists can describe the behavior of single-celled organisms algorithmically. Can we do the same with a mouse? Or how about a human within the sociocultural context? Regardless of our actual ability or stated beliefs, this is the operating assumption within society, where algorithm-driven evolution is happening today. Consider that algorithms mediate many of our relationships with each other. They used for social media, online dating, college admissions, credit scores, and stock trading, to name just a few examples. Over time, these experiences create a social, cultural, and ontological shift.

"Every reform deliberately instituted in the structure of society changes both history and the selective forces that affect evolution - though evolutionary change may be the farthest thing from our minds as reformers. We are not free to avoid producing evolution: we are only free to close our eyes to what we are doing." - Garrett Hardin, 1971

Arellano asks: "Are the systems with which we have approached the management of problems in the past enough to deal with the complex environments we find ourselves in today?" An algorithmic society wouldn't need to be comprehensive, in any sense of the word, to have a profound influence. Ted Striphas echoed this in an article about "algorithmic culture" noting that "Today, culture may only be as good as its algorithms." There is both potential and danger. Jack Balkin writes: "We are moving beyond the Information Age to the Algorithmic Society, where new technologies permit both public and private organizations to govern large populations. This could lead to asymmetries of information, monitoring capacity, and computational power."

When ideas can rapidly recombine with other ideas, algorithmic evolution moves faster and we produce more innovations, and potentially better adaptive bodies of knowledge. Hence, larger and more interconnected societies tend to produce faster algorithmic evolution. Harari again: "Computer scientists have been learning how to create better and better electronic algorithms. [This] will create a tsunami that will wash everything in its way. But technology’s not deterministic. There is no determinism about where this idea would lead us in the coming decades, so we should aim not just to regulate but to somehow guide this tsunami in a better and wiser direction." Merged with Joseph Henrich's expansive description of the significance of culture, the question is: what do social algorithms mean for ethics, healthcare, energy, transportation, heavy industry, agriculture, and materials? What do they mean for environmental and sustainability problems, and our cultural evolution? Who is helping to guide the direction of our coevolutionary process to ensure our Algorithmic Society is responsive to the biological health of the planet? It takes visionaries, like Rachel Armstrong who can see a beneficial fusion of nature and machine, and Lewis, Arista, Pechawis and Kite, who bring Indigenous epistemologies and open new lines of discussion.

There are of course numerous caveats. Some of which have been raised by Ian Bogost and George Zarkadakis. What are the limits to our ability to understand ourselves and our society through the lens of algorithms? To what extent can intuition be said to be algorithmic? And a real human society is so complex that, even assuming we can describe it algorithmically, things may be interconnected in a different way than we think they are. But that said, some rough contours are apparent, and there are many other very real features and behaviors that we can effectively describe as the product of individual and collective algorithmic minds and cultures, with useful results. If we can predict which policies will produce the best outcomes, for example, maybe we’ll end up with a healthier and happier world.

Consider that algorithmic modeling has shown that people tend to secularize when four factors are present: existential security, personal freedom, pluralism, and education. If even one is absent, the whole secularization process slows down. (Incidentally, this likely explains why the U.S. is secularizing at a slower rate than Western and Northern Europe.) This introduces the potential for social engineering, which hasn't escaped the attention of various groups like Cambridge Analytica. Bad actors will do this kind of computational work without transparency or public accountability. LeRon Shults points out “It’s going to be done. So not doing it is not the answer.” Instead, he believes the answer is to do the work with transparency and simultaneously speak out about the ethical danger inherent in it.

There is likely a collection of algorithms that would be able to describe my behavior to an arbitrary level of accuracy (a valuable commodity that is bought and traded by organizations that sell our data). The question is whether, and in what ways, this data can benefit us. Social algorithms should be studied. To reinterpret a well known quote from Jung: "We need more understanding of human algorithms. Our psyche should be studied..." It begins with knowing your personal data and algorithms, and those you share collectively with others. Who is doing this sort of work today? Iyad Rahwan leads the Scalable Cooperation group at the MIT Media Lab. His recent work has been on the topic of algorithmic social contracts. This dovetails into the research neuroscientist Molly Crockett has done on bridging the empathy gap, which is also partially motivated with the goal of creating better social contracts, and the research Peter Corning has done into the topics of society, synergy, and evolutionary transitions. As Rahwan writes: "We need to build new tools to enable society to program, debug, and monitor the algorithmic social contract between humans and governance algorithms."

Elinor Ostrom described how people can manage common-pool resources for centuries with little or no over exploitation. Notably, the answer could not be provided by formal models, but required detailed documentation from history and ethnography. J. D. Trout, in his book The Empathy Gap, wrote that our efforts to improve well-being must be more deliberate, surgical, and fully informed by the subtleties of scientific findings. In case it's not clear, "policy by intuition and and impressionistic judgment has had its run." Alex Pentland said theorists like Adam Smith and Karl Marx only had half the answers. His study of social physics, which he calls "Promethean fire," marks a qualitative change that is taking place in our understanding of human interaction. Managing the commons, bridging the empathy gap, and leveraging social networks are all fundamentally complex global challenges that only become tractable once we begin to look at the details, and get a fine grain understanding of individual interactions. As Vyacheslav Polonski writes, "Computational social scientists can truly make a difference, particularly by engaging with other actors from public policy and strategy in collaborative work, integrating analysis, intervention and implementation."

Key terms: algorithmic society, computational social science, social physics, ethical calculus, ethical algorithm, felicific calculus, stigmergic algorithm, empathy gap, cultural evolution, collective brain, complex systems, memetics

Additional sourced information:
"What potential value might a computational social science, based in an open academic environment, offer society, through an enhanced understanding of individuals and collectives?"
        - Life in the network: the coming age of computational social science (2009)

"Social science is about how people think (psychology), handle wealth (economics), relate to each other (sociology), govern themselves (political science), and create culture (anthropology)... The complex triadic nexus among social, artefactual, and natural systems requires computational investigation within an overall science of complexity."
"Computational social scientists strongly believe that a new era has started in the understanding of the structure and function of our society at different levels. ...characterized by new data at higher levels of temporal and spatial scale, and by new principles and concepts."
"Computational social science is aimed to pay attention to the entities the social world consists primarily of, i.e., people, ideas, human-made artefacts, and their relations within ecosystems. These entities are modelled as computational objects that encapsulate attributes and dynamics ...to both explain phenomena of interest and predict their evolution."
"The role of computational social science is a leading one in addressing the Big Problems of society, avoiding crises and threats to its stability and healthy development... According to the results of the Harvard Symposium on hard social problems in 2010, one of the top-ten problems is how to achieve good collective behaviour... Many bad environmental practices arise when citizens do not coordinate in order to attain a global optimal usage of collective resources, but rather pursue their own profit selfishly – resulting in an even worse long term individual performance."
"The development of Computational Social Science will make it possible to model and simulate social processes on a global scale, allowing us to take full account of the long distance interdependencies that characterise today’s heavily interconnected world. The output of these simulations will be used to support policy makers in their decision making, to enable them to efficiently and effectively identify optimal paths for our society. Similarly, open access to these large scale simulations will support individuals in their evaluation of different policy options in the light of their personal needs and goals, greatly enhancing citizen participation in this decision process. These developments together open the doors to a much safer, more sustainable and fairer global society."
         - Manifesto of computational social science (2012)

"This is the first time in human history that we have the ability to see enough about ourselves that we can hope to actually build social systems that work qualitatively better than the systems we've always had. That's a remarkable change. It's like the phase transition that happened when writing was developed."
"We can potentially design companies, organizations, and societies that are more fair, stable and efficient as we get to really understand human physics at this fine-grain scale. This new computational social science offers incredible possibilities."
        - Alex Pentland (2012)

"Human behavior is determined as much by the patterns of our culture as by rational, individual thinking. These patterns can be described mathematically, and used to make accurate predictions. The new science of “social physics” can build a predictive, computational theory of human behavior, a data-driven operating system for humanity.
"This is the first time in human history that we have the ability to see enough about ourselves that we can hope to actually build social systems that work qualitatively better, more fair, stable and efficient, than the systems we've always had. That's a remarkable change. It's like the phase transition that happened when writing was developed or when education became ubiquitous, or perhaps when people began being tied together via the Internet. This new computational social science offers incredible possibilities.
"A nation with poor measures of justice or inequality normally also has higher levels of corruption, and a nation with a poor record in poverty or sustainability normally also has a poor record of economic stability. Never again should it be possible to say “we didn’t know.” No one should be invisible. This is the world we want—a world that counts.
"If we're going to reinvent what it means to have a human society, one of the questions is: who is this new world going to be for, and what is it going to look like? There's a real focus on building a sustainable future, which means one in which there aren't large chunks of the population left out in the cold.
"You can begin to build a world where infectious pandemics cease to be as much of a threat. Similarly, if you're worried about global warming, you can design cities that are far more efficient, far more human, and burn an awful lot less energy. You could engineer transportation, energy, and health systems that would be dramatically better. We can get down and design things that really work for us on a personal level, rather than just being treated as another consumer.
"But you need to be able to see the people moving around in order to be able to get these results. If you could see everybody in the world all the time, where they were, what they were doing, then you could create an entirely different world. It's everybody contributing his or her data that's going to make a greener world. We need to stop pandemics. We need to make a greener world. We need to make a fairer world.
"There are some elements of this new data driven world that are really promising. For instance, the most efficient and robust architectures tend to be ones that have no central points. It means that there's no single place for a dictator to grab control. Also there is inherent in a society built on data sharing a certain level of transparency and choice for individuals that I believe will tend to mitigate against central control. It tends to dissolve the power of the state and big organizations because you can build things that are far more efficient and robust if they're distributed.
"Today societies' systems are built on big averages and indices, and the ideas of Adam Smith and Karl Marx, but these theorists only had half the answers. They talked about markets and classes, but those are only averages. Social phenomena are really made up of millions of small transactions between individuals. We're at a phase transition, moving from the reasoning of the enlightenment about classes and about markets to a fine grain understanding of individual interactions and systems built on fine grain data sharing. The patterns in those individual transactions are not just averages, but things that are responsible for the flash crash and the Arab spring. You need to get down into these new patterns, these micro-patterns, because they don't just average out to the classical way of understanding society. We're entering a new era of social physics, where it's the details of all the particles — the you and me — that actually determine the outcome. This new capability of looking at the details, and getting to really understand human physics at a fine-grain scale will give us the other half of the story.
"It is the connections between people that are at the core of making systems work well. The challenge is to figure out how to analyze the connections and come to a new way of building systems based on understanding these connections, the causality of connections in the real world.
"George Orwell was not nearly creative enough when he wrote 1984. We can use our understanding of the way things work to screw ourselves up really badly, or we can use it to build a better society. This is Promethean fire.
        - Alex Pentland, Reinventing Society in the Wake of Big Data

"Just as the goal of traditional physics is to understand how the flow of energy translates into changes in motion, social physics seeks to understand how the flow of ideas and information translates into changes in behavior... how people cooperate to discover, select, and learn strategies and coordinate their actions." (5, 16)
"Sustaining a healthy, safe, and efficient society is a scientific and engineering challenge that goes back to the 1800s, when the Industrial Revolution spurred rapid urban growth and created huge social and environmental problems... We have cities jammed with traffic, worldwide outbreaks of diseases, and political institutions that are deadlocked and unable to act. In addition, we face the challenges of global warming; uncertain energy, water, and food supplies... But it doesn't have to be this way. We can have cities that are energy efficient, have secure food and water supplies, and much better government. To reach these goals, however, we need to radically rethink our approaches. Rather than static systems that are separated by function - water, food, waste, transport, education, energy, and so on - we must consider them as dynamic and holistic systems." (138)
"I believe there are three design criteria for our emerging hypernetworked societies: social efficiency, operational efficiency, and resilience. Let us look at each of these in turn and then ask how they might apply to governments and society more generally." (203)
"The most important limitation is that we are attempting to infer causal processes from observational data in which many mechanisms are likely at play. If we find that behaviors between two individuals are correlated, it could be due to influence, but it could also be due to selection or to contextual factors. These mechanisms are generically confounded. However the ability to use time data to test causal ordering, as well as asymmetries in network relationships to test the direction of effects, provides greater confidence when inferring causality..." (249)
"The main point is that the propagation of human action habits by means of social learning can be accurately modeled from easily observable behavior using heterogenous, dynamic, stochastic networks. This capability is transformative for increasing our understanding of the dynamics of human society, and hence our ability to plan for the future." (264)
        - Alex Pentland, "Social Physics" (2014)

"Social Persuasion to influence the actions, beliefs and behaviors of individuals, embedded in a social network, has been widely studied. It has been applied to marketing, healthcare, sustainability, political campaigns and public policy. Traditionally, there has been a separation between physical (offline) and cyber (online) worlds. While persuasion methods in the physical world focused on strong interpersonal trust and design principles, persuasion methods in the online world were rich on data-driven analysis and algorithms. Recent trends including internet of things, `Big data', and smart phone adoption point to the blurring divide between the cyber and the physical worlds in the following ways. Fine grained data about each individual's location, situation, social ties, and actions are collected and merged from different sources. The messages for persuasion can be transmitted through both worlds at suitable times and places. The impact of persuasion on each individual is measurable. Hence, we posit that social persuasion will soon be able to span seamlessly across these worlds and will be able to employ computationally and empirically rigorous methods to understand and intervene in both cyber and physical worlds. Several early examples indicate that this will impact the fundamental facets of persuasion including who, how, where and when, and pave the way for multiple opportunities as well as research challenges."
        - Vivek Singh, Ankur Mani, and Alex (Sandy) Pentland, "Social Persuasion in Online and Physical Networks"

Postscript 1: In my earlier article about algorithms, I explored them primarily through the lens of the physical sciences. In this article, I wanted to take a closer look at them through the humanities and social sciences, to employ the simple but useful division within academia.

Postscript 2: A common misconception is that algorithms are just math. The word does vaguely sound like algebra or logarithm, doesn't it? But it's more useful to think of them as a set of rules that describe how to perform a task, or a flowchart that helps you arrive at a decision. Peter Kassan wrote a very nice article (not available online) titled: "I’ve Got Algorithm. Who Could Ask for Anything More?" He finds today's algorithms wanting in their ability to find causal relationships. The first part of his article provides several useful examples:

"Examples of early classical algorithms include Euclid’s Algorithm, which finds the greatest common divisor of two whole numbers; The Sieve of Eratosthenes, which finds prime numbers; and Binary Search, which finds an item in a sorted list. More prosaic examples are the procedures you learned in elementary school to do arithmetic — the ways you do addition, subtraction, multiplication, and division (if you still do them yourself) are all algorithms."

But as we tend to use the word today, "computer program" is in many cases a more appropriate term to algorithm. Whereas an algorithm (or heuristic) has an actual idea behind it, a computer program may or may not. However a bigger problem, and one which hasn't escaped the attention of researchers like Judea Pearl, is that most computer programs primarily look for correlations within data. If you haven't identified and gathered the metric that's actually causal, no amount of data will help. The fundamental goal of science is to find causal relationships — and this often involves inventing new instruments, tools, and materials to make new observations and measurements guided by new insights and new ideas." 

Source: "I’ve Got Algorithm. Who Could Ask for Anything More?" by Peter Kassan

Skeptical Inquirer, Sept/Oct 2018

Evolution and Culture

Source: Joseph Henrich

There is an area of research in biology called niche construction theory that is focused on how evolution has been shaped by the way living organisms manipulate their environments. For example, consider how beavers and earthworms engineer the ecosystems in which they live. Through a process of reciprocal causation, over time these changes in turn re-shape the selective contexts and the course of evolution itself. In the same way, human nature and human cultures have co-evolved. Our shared objectives facilitated the evolution of cooperative problem solving and cooperative behaviors which enabled our ancestors to prosper and ultimately colonize new environments. Steven Pinker called this the "cognitive niche." Peter Corning returned to the subject of culture-gene coevolution, or culture-driven genetic evolution (also called dual inheritance theory) several times within his book Synergistic Selection and referenced two others on that subject: The Secret of Our Success: How Culture Is Driving Human Evolution, Domesticating Our Species, and Making Us Smarter by Joseph Henrich (2015), and Self-Made Man: Human Evolution From Eden to Extinction? by Jonathan Kingdon (1993). Corning writes:

Henrich's book shows that the secret of our success lies in our collective brains--on the ability of human groups to socially interconnect and learn from one another over generations. He demonstrates how our collective brains have propelled our species' genetic evolution and shaped our biology. Our early capacities for learning from others produced many cultural innovations, such as fire, cooking, water containers, plant knowledge, and projectile weapons, which in turn drove the expansion of our brains and altered our physiology, anatomy, and psychology in crucial ways. Later on, some collective brains generated and recombined powerful concepts, such as the lever, wheel, screw, and writing, while also creating the institutions that continue to alter our motivations and perceptions. Henrich shows how our genetics and biology are inextricably interwoven with cultural evolution, and how culture-gene interactions launched our species on an extraordinary evolutionary trajectory.

In Self-Made Man, Kingdon offers a radical new interpretation of the role that new tools and technologies played in driving human evolution. "Modern humans are truly self-made" argues Kingdon, because even the most strictly biological of adaptations was profoundly influenced by technological innovations, distinguishing our evolutionary path from that of all other animals. "All animals adapt to circumstances, and for humans, by definition tool-making animals, circumstances have become more and more self-made."

Source: Joseph Henrich

Our cultural evolution has had one major unintended side effect: it has created opportunities for exploitative hierarchical systems which have led to greater social inequality, political conflict, and today, the emerging environmental crisis, by undermining the more egalitarian social contract which had sustained our ancestors for millions of years. We have not yet developed the means for dealing with with these consequences. So it is now possible to see how these three things are connected at a deep level: (1) the existential threat posed by an unsustainable economic system, (2) the role of countervailing political powers within a functioning reverse dominance hierarchy, and (3) culture-gene coevolution, which is ultimately foundational to understanding the parts of these systems and provides a toolkit for reconfiguring them as needed.

Lest it be forgotten, the biologists John Maynard Smith and Eörs Szathmáry have argued that the evolutionary dynamic which drove the major transitions in the history of life developed safeguards to prevent one from exploiting the rest to the detriment of the whole. From which Corning deduced, "the next major transition in evolution must sustain and enhance our interdependent collective survival enterprise.” Speculating on the next major transition, Szathmáry writes: "It was language, with its unlimited hereditary potential, that opened up the possibility of open-ended cumulative cultural evolution... The biology of humans has become gradually de-Darwinized. It is culture where the main action is going on [my emphasis]."

There is no sharp line to be drawn between human and animal behavior except that evolution operates in humans overwhelmingly as a cultural process, through the accumulation, organization, and application of experience in a system of shared material, mental, and social constructions. This has allowed us to become the principle agent of the evolutionary process on this planet, and the instrument for realizing new possibilities for its future, at once an inspiring and a sobering conception. In the partnership between humans and nature, a joint enterprise, our futures are interlocked.
Source: Julian Huxley, New Bottles for New Wine (1957)

We get by with less fixed programming because we have added a new twist to the traditional Darwinian machinery of self-replication: a symbiotic relationship with culture that has liberated us from cognitive isolationism.
Source: Merlin Donald, "The central role of culture in cognitive evolution: a reflection on the myth of the isolated mind"

There is a chapter in The Dominant Animal: Human Evolution and the Environment titled "History as Cultural Evolution" (p158). In a separate article titled "Why History and Cultural Evolution Are Natural Allies," Peter Turchin writes "what most people don’t realize is that cultural evolution allied to history has the potential of yielding immense practical benefits." Broadly speaking, this has always been the implicit understanding of historians, but the wider perspective of culture-gene coevolution adds more depth and the possibility of drawing a longer arc with greater explanatory, and possibly, predictive power (as was the hope of E.O. Wilson [1], not to mention a source of creative speculation for Asimov in his Foundation series). Insofar as we are evolving with our planet, it will be increasingly important to understand the dynamic by which this occurs. Joseph Henrich outlines the field of action:

Humans are very dependent on culture and cultural learning for very basic things — like how to find food, how to organise our societies, how to make the tools which allow us to survive. Human invention has always been a product of the interaction of minds. So if you want to energize innovation, you should create larger "collective brains" — in other words, interconnect more minds and allow information to flow more freely among people with diverse areas of knowledge and expertise.

We can think about culture as a genetically evolved cognitive adaptation for learning from other people. Natural selection is operating over generations to make people better at learning from the other members of their social milieu — figuring out who in their environment they should tune in to, what kinds of ideas they should pay attention to, and how they should integrate information across diverse people. Genetic evolution is shaping us to be cultural learners, but then the interesting part is that that turns around, and cultural evolution begins to shape our genetic evolution.

After reading Peter Corning, Maynard-Smith and Szathmáry, and now especially Joseph Henrich, I can't help but think that most of what I typically associate with "me," my personal identity, I owe to numerous other people. Henrich's book The Secret of Our Success really spells out in detail how, as individuals, we are virtually helpless. Our strength comes from our association with countless others, both formerly and now. A month ago when I asked Corning about how the individual parts of the human superorganism relate to one another, I had in mind some sort of theory of mind incorporating elements of enactivism or externalism. Now with Henrich, the extent of our "collective brain," as he calls it, is spelled out. Corning would caution against reifying these notions, emphasizing the synergistic effects as opposed to the means by which they are achieved, but nonetheless the picture that emerges is clear.



7/5/2018:

I believe women will guide our cultural evolution to become more responsive to the biological health of the planet. Carlos Perez recently wrote: "Women have a natural inclination to focus on the important things that make us human. To maximize the benefit of technology we must focus on how it improves our humanity and therefore we need to understand, at the very least, what makes us human and not what makes us machines." I've got some influential people in mind: Molly Crockett, Manuela Veloso, Margaret Boden, Rachel Armstrong, Radhika Nagpal, and Heather Marsh. But before I describe why I agree with Perez, we need to see the symbiotic relationship between culture and biology in the same way that they do. 

As Nicholas Christakis put it, culture is the earliest sort of intelligence outside our own minds that we humans created. We create culture, interact with it, are affected by it, and can even be destroyed by it. Culture applies its own logic, has a memory, endures after its makers are gone, can be repurposed in supple ways, and can induce action. These are also attributes of artificial intelligence, so after a manner of speaking, culture is a kind of "natural artificial intelligence." And seen in this way, culture-gene coevolution can provide a model for AI-gene coevolution. ...Now take a deep breath, because these women are helping to guide the direction of this coevolutionary process into the future, and they see good reasons to believe it will be a very human process. Here's just a few of the reasons they've provided.  

Margaret Boden believes that once we understand how it is possible for a representational system to be embodied, and how representations can be constructed, stored, accessed, compared, and transformed, we will have greater freedom and greater incentive to concentrate on what is most fully human. Manuela Veloso echoes this, "In some sense, the humanism of AI will eventually be what brings us together. ...focus on education, people knowing each other, caring for each other." I believe this is the direction in which our cultural evolution is headed. 

Rachel Armstrong sees a beneficial fusion of nature and machine in synthetic biology and living technologies. She believes that "technology is the way the mind becomes embodied in the process of problem solving. ...Human development is now enabled to synergistically evolve with the biosphere and help us coauthor an ecologically engaged future. Our task in a living culture of materiality will be to remain engaged and 'conversant' with those agencies that we rely on." ...I hope you are asking yourself right now, as I am asking myself: Is our culture engaged and conversant?

Molly Crockett describes some of the possible benefits that this synergy will allow: "Human brains are incapable of solving the interpersonal utility comparison problem. ...Bridging the empathy gap would require a way to quantify preferences and translate them into a common currency that is comparable across individuals [and] could be used to create better social contracts. Machines that can bridge the empathy gap could also help us with self-control. In addition to the empathy gap that resides between self and others, there exists a similar gap between our present and future selves. Self-control problems stem from the never-ending tug-of-war between current and future desires. Perhaps AI will one day end this stalemate by learning the preferences of our present and future selves, comparing and integrating them, and making behavioral recommendations on the basis of these integrated utilities. Think of a diet that is healthy enough to foster weight loss, but just tasty enough so you're not tempted to cheat, or an exercise plan that is challenging enough to improve your fitness, but just easy enough that you can stick with it." 

This reminds me of John Rawls "veil of ignorance" thought experiment, but it combines an objective approach to intimately subjective preferences in a unique way. It also includes elements of proactive (predictive) AI in that it provides "actionable intelligence." If we can predict the three factors of culture, genes, and environment, we will have fulfilled E. O. Wilson's hope of turning ecology into a predictive science.

Marshall McLuhan wrote “We shape our tools, and thereafter our tools shape us.” …And then we repurpose our tools, and share them, and others reconfigure them, and they reshape our sociocultural fabric. And all along, we evaluate their impact for good or ill. But our tools for bridging the empathy gap are still inadequate. We need to be better empathizers. Neuroscientist Molly Crockett knows all about this and how critical it may be for our collective survival enterprise – a term frequently used by Peter Corning. 

If we could bridge the empathy gap, then achieving the level of cooperative relations required for pursuing the great human projects of our time is not out of reach. Philosopher J. D. Trout wrote a book called “The Empathy Gap,” that describes some of these tools and approaches. Crockett could write the sequel. As she says, “We've already built computers that can see, hear, and calculate better than we can, [but] creating machines that are better empathizers is a knottier problem.” Maybe not. We don't necessarily need empathizing machines. The process has already begun with us, aided by the prosthetic devices everyone carries in their pockets. It's still too early to tell, but I think we've already started down the path toward narrowing the empathy gap. The quest to create an interpersonal-intertemporal lingua franca capable of making explicable utility comparisons (an empathic bridge) is a long journey, and an immense project of human culture.

Further Reading:
Robert Boyd 
Nicholas Christakis

[1] In his 2009 book Whole Earth Discipline, Stewart Brand recounts that E.O. Wilson once told him "Ecology needs to be a predictive science." (p267)