Philosophy

This is a method, a hypothesis about what progress is and how to measure it. Not a manifesto to agree with, but a question to test.

“We now face the danger, which in the past has been the most destructive to the humans: Success, plenty, comfort, and ever-increasing leisure. No dynamic people has ever survived these dangers.”

John Steinbeck

Social health is the answer

Social networks and other internet communication have complex and distorted incentives. To borrow a term from political philosophy, consumer internet is now a large part of our modern social fabric, the interconnectedness and interdependence of people within a society. But the patterns of that fabric are set by market forces that serve human nature, not always human needs. Content that triggers a fear response, outrage especially, is an effective engagement strategy. Polarization creates toxicity, and it is already weaponized.

AI will amplify everything, for better or worse. To express something to AI may let us finally see it in the world.

Social health is the measurement of collective intelligence and happiness over time. It is not only the connection between individuals; it is also visible in the effectiveness and trustworthiness of our institutions, and in our commitment to ourselves and our identities as we interact with social constructs.

Social health is our answer to the question that names this site: What is progress?

Progress requires healthy conflict

Progress is not the absence of conflict; it depends on conflict being healthy.

“Honest differences are often a healthy sign of progress.”

Mahatma Gandhi

The aim is not to suppress disagreement but to move it from zero-sum toward cooperative: from withheld information to revelation, from hidden agendas to explicit needs, from coercion to mutual commitment. That movement is what we try to measure.

Why conflict breaks us

Conflict resolution is constrained by neurobiology. Under threat, the brain shifts from reflective to reflexive control: as amygdala activation rises, prefrontal activation falls. The prefrontal cortex, which governs working memory, judgment, emotional regulation, perspective-taking, and the capacity for genuine consent, goes quiet exactly when we need it. fMRI studies show this inverse relationship, and even mild, uncontrollable stress produces what researchers call a “rapid and dramatic loss of prefrontal cognitive abilities.”

Recovery takes time, not willpower. The brain’s fast threat pathway fires before conscious appraisal catches up, the basis for the popular “six-second pause” before reacting, while the slower surge of stress hormones takes roughly 20 to 90 minutes to subside, with wide individual variation. Working memory is impaired within the first 10 minutes, and again near 25 minutes as cortisol peaks. The practical implication is blunt: you cannot think your way through conflict while your brain is in threat mode. Good mediation works with that timing instead of against it.

Sources

Built on established science

The following is a base the approach stands on; roughly a century of research across six fields.

• Game Theory and Economics. That adversaries can cooperate is a formal result, not a hope. Aumann showed that “peaceful cooperation is often an equilibrium solution in a repeated game, even between parties with strong short-run conflicts of interest,” work for which he and Schelling shared the 2005 Nobel “for having enhanced our understanding of conflict and cooperation through game-theory analysis” (Nobel, 2005 ). Earlier, Nash’s Bargaining Problem derived a unique, fair division of the joint gains in a nonzero-sum game (Nash 1950 ). More than 15 Nobel laureates in all have worked in game theory and mechanism design (prize list ).
• Neuroscience and Psychology. Under acute stress the brain shifts control from the prefrontal cortex toward the amygdala, impairing judgment and working memory for roughly 20 to 90 minutes. (The often-quoted “30–40% drop” is an approximation drawn from stress studies, not a single measured value (see the table above).)
• Negotiation and Mediation. The cooperative-versus-zero-sum distinction is a long-standing one in interest-based negotiation (Fisher and Ury, Getting to Yes) and the integrative-versus-distributive bargaining literature (Walton and McKersie). It reflects the negotiator’s dilemma: disclosure is the cooperative move where a conflict admits joint gains, not an unconditional good in purely distributive bargaining.
• Computational Social Science. LLM-based agents can reproduce aggregate patterns of human survey and behavioral responses in controlled studies, though fidelity varies by task (Argyle et al. 2023 ; Park et al. 2023 ). Larger, newer work points the same way, though both are preprints: agents built from interviews with 1,000 people matched their subjects’ survey answers about 85% as well as those people matched their own answers two weeks later (Park et al. 2024 ), and simulations of 10,000+ agents qualitatively reproduced known patterns such as opinion polarization (Piao et al. 2025 ).
• International Relations. Peace and conflict studies have been a formal academic discipline since the world’s first chair of International Politics was endowed at Aberystwyth in 1919 , with dedicated peace research institutionalized a generation later when Galtung founded the Peace Research Institute Oslo in 1959 . Historically most armed conflicts ended in military victory, but since the end of the Cold War a growing share have ended through negotiated settlement, and many simply cease without a decisive outcome (Kreutz 2010 ).
• Dispute Resolution. Decades of research on structured conflict-resolution and peer-mediation programs, including Johnson and Johnson’s review of school-based programs (1996 ), find that trained parties reach agreement in most disputes. “Agreement reached” is a process result, not a guarantee of a durable resolution.

The limits matter as much as the foundations. Game theory and simulation are powerful but partial. They abstract away the irrational, contextual, human core of conflict, so we treat them as inputs and measure real behavior rather than only models of it.

Foundational works and further reading

Beyond the studies cited above, the approach draws on foundational works that inform the whole rather than any single claim: Schelling’s The Strategy of Conflict (1960) and Axelrod’s The Evolution of Cooperation (1984) on how cooperation emerges among adversaries (Axelrod via simulation of the iterated Prisoner’s Dilemma); Brams and Taylor’s Fair Division: From Cake-Cutting to Dispute Resolution (1996) on procedures for splitting contested value; and the established professional practice of alternative dispute resolution (mediation, arbitration, negotiation) as documented by the Harvard Program on Negotiation and Cornell’s Legal Information Institute .

Why this matters now

Everything above is the research base. What follows is the bet we are placing on it.

For about ten years these ideas have circled HAI.AI, and the idea of using AI to resolve conflict for twice that long. In the abstract, the function of HAI.AI is to generate and maintain good interpersonal commitments, and to make cooperation possible where it was hard before.

Like many people who dedicate their careers to change, the founder has worked at startups in education technology, mental health care, and environmental air-quality data, building new technologies, validating their efficacy, and running into the same wall every time: the effectiveness of the institutions we rely on. How do you serve an institution that cannot function sufficiently? Institutions full of good people doing good work, where, inside and out, no one is as happy or as effective as they could be. We understandably want to keep our jobs and our identities, but change is constant.

We may need new institutions for large, critical human services. The bigger the institution, the bigger the disruption needed. AI will bring that disruption, and an arms race with it. We are only beginning to understand the challenges ahead. Meanwhile, we have to build what we will be fighting for.

The world we see coming

Foundation models are powerful and will become more so. In the everyday world, at home and at work, people will increasingly use AI running on smaller, distributed computers, serving as personal assistants. Even in a world of very powerful models, individuals need their own AI and their own representation. Where today we have email, in the future agents will talk, argue, exchange, and transact on our behalf. That world needs infrastructure. It needs a harness, and it needs to be observable and trustworthy, held to high standards of personalization.

What we measure

If social health is a measurement, then progress is something we can track. HAI.AI’s benchmarks measure how cooperation happens: not just whether a conflict ends, but whether it moves from zero-sum toward cooperative, the movement described above. That how is the construct the benchmark scores.

That measurement is published openly here. The methods are documented; the test set stays closed so results cannot be gamed. See the results for the scores and how they are produced .

A note on “social fabric”

The term is used widely in social and political philosophy to describe the interdependence of individuals within a society. Threads run through Rousseau’s social contract, Locke on civil society, Marx on class relations and solidarity, Durkheim on social cohesion and the collective conscience, Charles Taylor on identity and the social framework, and Michael Sandel on community and moral values. Together they describe how individuals and communities depend on one another, the fabric this project tries to measure.

Some initial features at HAI.AI center on email. Email is one channel where commitments can happen, but Human Assisted Intelligence does not exist to make email better; it exists to make cooperation possible where it was hard before.