Humans actually are extremely cooperative. We help strangers without thinking — in fact, we are even more likely to help if we don’t think much about it. We live and work with people we are in competition with, yet most of the time we treat them decently. The research described here is part of a larger research programme in cognitive science. The AmonI group at Bath works to both build cognitive systems and understand cognition in nature. In humans (and probably other species) much of the power of cognition (thinking) comes from our ability to reuse what others have already thought. Thus, understanding social behaviour is also key to understanding human cognition.

Science is often advanced by comparing two things and asking why they are different. So we look at cooperation, especially information sharing, in a variety of species. Since 2010, we’ve also been looking at cultural variation in human economic behaviour. The data we originally worked to explain comes from a type of behavioural economics experiment called “public goods games.” Our research has lead us to look at understanding cooperation more broadly, and to look at group formation, culture and identity, the evolution of culture, contracts and ethics.

Altruism, Punishment and Public Goods

Altruism is technically defined as paying a cost in order to benefit another individual. A cost can be anything — time, money, effort, reputation, or a risk of injury. Altruism can include contributing to a public good — something that everyone (or at least some other people) can use without necessarily asking for permission.

Evolution can easily account for altruism. That is because evolution is driven by genes trying to reproduce themselves, and all species share the vast majority of their genes. Altruism is even easier to explain in families, because families share even more genes. In humans at least, our behaviour isn’t only influenced by our genes, but also by our own individual experience, and by our culture. One thing scientists study is whether culture works like genes: whether ideas (memes) can also work to make copies of themselves, and in doing that bring people that share them together to cooperate.

Another theory of cooperation is more negative — that keeping high levels of cooperation requires policing people who would cheat. Altruistic punishment is paying a cost to punish someone who is not contributing as much as you would to a public good. When economists doing experiments discovered that some people will altruistically punish, they thought they had discovered the reason humans were so cooperative. But in fact punishment can go either way. Punishing those who give more to the public good than the punisher is called anti-social punishment. Herrmann, Thöni & Gächter (Science, 2008) showed that the reason the economists hadn’t noticed anti-social punishment at first was because in some places there isn’t very much of it, but in other places there are. So now we have something to explain, and places to compare.

Herrmann and his collaborators showed that rates of anti-social punishment vary not just by place but by global region. There seems to be more anti-social punishment where people have less money (lower GDP) and where you can’t always trust laws to be enforced (low rule of law). We’ve since shown that in every city in their data, some people never punish anyone, and some people only punish altruistically. It seems like what varies is how many people in a society will punish anyone, and anti-social punishment is just a side effect of that.

Hypotheses

  • Individuals need to invest in their own individual welfare to survive, but they also on average do better in life if they invest in public goods.

  • Striking the “right” (optimal) balance between these two strategies is difficult, because optimality depends on changing opportunities and other factors such as how reliable the rule of law is. Also, tradeoffs mean there are many possible good solutions.

  • Given varying costs and benefits, a population as a whole can wind up tracking these changing optima by being composed of members that over- and under-invest in public goods. The socioeconomic dynamics will drive the balances of costs and benefits (which depend partly on how many people exploit each strategy) such that approximately appropriate numbers of people will exploit the different strategies.

  • One of the proximate mechanism for deciding whether to be so competitive that you punish even altruists is your sense of in-group or out-group identity. Most people won’t punish altruists with whom they identify.

Public Goods, Political Polarization, and Wealth Inequality

One of the models we developed in trying to understand the dynamics of social learning underlying the system of hypotheses just described exhibited an odd gap in public goods investment between sub populations. We came to discover that human populations also sometimes show significant divergence in opinions concerning ideal investment in a particular public, or put another way, split into two publics. This process is known as political polarization. This has led us to other hypotheses, concerning in-group and out-group formation.

Hypotheses

  • Humans are extraordinarily, perhaps uniquely successful at dominating our ecosystem partly because we are able to rapidly adjust the size of our groups, or even hold multiple conflicting concepts of identity (complete with identity indicators such as skills and memories) allowing us to rapidly alternate between publics in which we invest.

  • When individuals seem to be losing status within one public, they tend to form a new, smaller sub group of that public in which they invest more heavily.

  • Membership of these new groups may be flagged by classic identity indicators such as ethnicity, but also more flexible indicators such as unusual beliefs. This could account for both early, imagistic religions (which tend to be highly dynamic) and contemporary “post factualism.”

Key Related Publications

Featured
Polarization Under Rising Inequality and Economic Decline

Alexander J. Stewart, Nolan McCarty, and Joanna J. Bryson, Science Advances, 6(50), Dec 2020.

This project came out of my work on cultural variation in public goods investment, crossed with getting asked on live TV whether AI was increasing inequality. I thought I’d better find out and went to talk by Nolan and learned about the correlation between inequality and polarization. I’ve been talking about this project for a couple years, but the model in the paper is entirely Alex. (I did replicate his work with an ABM, but that’s harder to analyze ... ). This has been my main research focus personally since 2016 and I’ve spoken about it a few times as a contribution to academic meetings, including EHBEA, APSA, and ICSD (well, Alex spoke about it there, I watched :-)

Expectations of Fairness and Trust Co-Evolve in Environments of Partial Information

Paul Rauwolf & and Joanna J. Bryson, Dynamic Games and Applications, 8(4):891-917, 2018.

Highly relevant to information technology policy: The more you know, the less you need to trust, though if you know nothing or don’t have a choice of who you work with, people have no reason to be trustworthy. Trust comes with PARTIAL information, AND at least some freedom. Open access because Bath+Springer

Trust Communication, and Inequality

Joanna J. Bryson & Paul Rauwolf, from The 38th Annual Meeting of the Cognitive Science Society, 10-13 August 2016 in Philadelphia, PA.

Reviews Paul’s awesome work on understanding why it’s adaptive to both have blind faith in others in your community, yet refuse to cooperate with those making unfair but mutually-beneficial offers.

Value Homophily Benefits Cooperation But Motivates Employing Incorrect Social Information

Paul Rauwolf, Dominic Mitchell, and Joanna J. Bryson, Journal of Theoretical Biology, 367:246–261, 2015.

Preferring to cooperate with those with a similar cooperation style supports the evolution of cooperation. Reputations spread through gossip supports this strategy. But now that you are spreading two kinds of information (reputations of others, and your own style of cooperation) you can have a conundrum when these conflict. When there is such a conflict, signalling honestly about your cooperation strategy can be more beneficial to your community than telling the truth about someone else. Free open access draft is here. Software is coming soon. Draft is from October 2014, yet the work originally derived from On the Reliability of Unreliable Information: Gossip as Cultural Memory, which came out in 2016. Such is academia.

Understanding and Addressing Cultural Variation in Costly Antisocial Punishment (pdf)

Joanna J. Bryson, James Mitchell, Simon T. Powers, and Karolina Sylwester, in Applied Evolutionary Anthropology: Darwinian Approaches to Contemporary World Issues, Gibson & Lawson (eds.), Springer, 2014.

This book follows from a workshop. Here is a free version of the chapter, the revised draft from May 2013. See further our Cultural Variation in Costly Punishment project page. Note: Google Scholar managed to find a USAF white paper derived from our final report by the same title which has a lot of irrelevant detail and a couple theoretical errors we’ve since discovered. The book chapter is 15 months more recent.

Homo Homini Lupus? Explaining Antisocial Punishment

Karolina Sylwester, Benedikt Herrmann, and Joanna J. Bryson, Journal of Neuroscience, Psychology, and Economics, 6(3): 167-188, 2013.

A review article; see further our Cultural Variation in Costly Punishment project page. If you don’t have access to APA, here is the revised final version submitted to the publisher (May 2013).

The Role for Simulations in Theory Construction for the Social Sciences: Case Studies Concerning Divergent Modes of Religiosity

Harvey Whitehouse, Ken Kahn, Michael E. Hochberg, and Joanna J. Bryson, Religion, Brain & Behaviour, 2(3):182-224 (including commentaries and response), 2012.

I’m particularly pleased about this paper because it shows clearly how models can advance even well-established social-scientific theories provided that we work directly with domain experts who really understand the theory and data. There are some very pithy, quotable text about this in our response to commentaries, From the Imaginary to the Real: The Back and Forth Between Reality and Simulation. Open access pre-proof version of the target article, and of the response to commentaries. Associated software is available from the AmonI software page, and also in the electronic appendix. Oxford Anthropology have made a web page about our simulation of religion work.

Punishment Can Promote Defection in Group-Structured Populations

Simon T. Powers, Daniel J. Taylor and Joanna J. Bryson, The Journal of Theoretical Biology, 311:107-116, 2012.

Penultimate version on arXiv. This paper shows that punishment alone can’t explain altruism, the papers that thought it could didn’t take into account the well-documented behaviour of anti-social punishment. Basically, some people punish those that contribute to the public good. This is the first article of at least five we expect to publish explaining this phenomenon, and why it varies by culture. See our Cultural Variation in Costly Punishment project page.

 

About the Study

The beginning of this study was commissioned and sponsored by the US Air Force Office of Scientific Research, Air Force Material Command, USAF, under grant number FA8655-10-1-3050. The Artificial Models of Natural Intelligence (Amoni) research group was funded on a collaboration with the Nottingham Centre for Decision Research and Experimental Economics (CeDEx) specifically to address questions at two very different levels of abstraction:

Substantial: to better understand why there should be geographic variation in what at least superficially appears to be a maladaptive economic behaviour (anti-social punishment).

Methodological: to improve the current methodologically state of the art in collaboration between social simulation / agent based modelling and the social sciences.