Misjudgment Exacerbates Collective Action Problems
Joshua Lewis (New York University), Shalena Srna (University of Michigan), Erin Morrissey (New York University), Matti Wilks (University of Edinburgh), Christoph Winter (Instituto Tecnológico Autónomo de México and Harvard Univeristy) and Lucius Caviola (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 2-2024
In collective action problems, suboptimal collective outcomes arise from each individual optimizing their own wellbeing. Past work assumes individuals do this because they care more about themselves than others. Yet, other factors could also contribute. We examine the role of empirical beliefs. Our results suggest people underestimate individual impact on collective problems. When collective action seems worthwhile, individual action often does not, even if the expected ratio of costs to benefits is the same. It is as if people believe “one person can’t make a difference.” We term this the collective action bias. It results from a fundamental feature of cognition: people find it hard to appreciate the impact of action that is on a much smaller scale than the problem it affects. We document this bias across nine experiments. It affects elected policymakers’ policy judgments. It affects lawyers’ and judges’ interpretation of a climate policy lawsuit. It occurs in both individualist and collectivist sample populations and in both adults and children. Finally, it influences real decisions about how others should use their money. These findings highlight the critical challenge of collective action problems. Without government intervention, not only will many individuals exacerbate collective problems due to self-interest, but even the most altruistic individuals may contribute due to misjudgment.
Other working papers
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Morally speaking, what matters the most is the far future – at least according to Longtermism. The reason why the far future is of utmost importance is that our acts’ expected influence on the value of the world is mainly determined by their consequences in the far future. The case for Longtermism is straightforward: Given the enormous number of people who might exist in the far future, even a tiny probability of affecting how the far future goes outweighs the importance of our acts’ consequences…
Economic growth under transformative AI – Philip Trammell (Global Priorities Institute, Oxford University) and Anton Korinek (University of Virginia)
Industrialized countries have long seen relatively stable growth in output per capita and a stable labor share. AI may be transformative, in the sense that it may break one or both of these stylized facts. This review outlines the ways this may happen by placing several strands of the literature on AI and growth within a common framework. We first evaluate models in which AI increases output production, for example via increases in capital’s substitutability for labor…
Prediction: The long and the short of it – Antony Millner (University of California, Santa Barbara) and Daniel Heyen (ETH Zurich)
Commentators often lament forecasters’ inability to provide precise predictions of the long-run behaviour of complex economic and physical systems. Yet their concerns often conflate the presence of substantial long-run uncertainty with the need for long-run predictability; short-run predictions can partially substitute for long-run predictions if decision-makers can adjust their activities over time. …