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
How to neglect the long term – Hayden Wilkinson (Global Priorities Institute, University of Oxford)
Consider longtermism: the view that, at least in some of the most important decisions facing agents today, which options are morally best is determined by which are best for the long-term future. Various critics have argued that longtermism is false—indeed, that it is obviously false, and that we can reject it on normative grounds without close consideration of certain descriptive facts. In effect, it is argued, longtermism would be false even if real-world agents had promising means…
Towards shutdownable agents via stochastic choice – Elliott Thornley (Global Priorities Institute, University of Oxford), Alexander Roman (New College of Florida), Christos Ziakas (Independent), Leyton Ho (Brown University), and Louis Thomson (University of Oxford)
Some worry that advanced artificial agents may resist being shut down. The Incomplete Preferences Proposal (IPP) is an idea for ensuring that does not happen. A key part of the IPP is using a novel ‘Discounted Reward for Same-Length Trajectories (DReST)’ reward function to train agents to (1) pursue goals effectively conditional on each trajectory-length (be ‘USEFUL’), and (2) choose stochastically between different trajectory-lengths (be ‘NEUTRAL’ about trajectory-lengths). In this paper, we propose…
Aggregating Small Risks of Serious Harms – Tomi Francis (Global Priorities Institute, University of Oxford)
According to Partial Aggregation, a serious harm can be outweighed by a large number of somewhat less serious harms, but can outweigh any number of trivial harms. In this paper, I address the question of how we should extend Partial Aggregation to cases of risk, and especially to cases involving small risks of serious harms. I argue that, contrary to the most popular versions of the ex ante and ex post views, we should sometimes prevent a small risk that a large number of people will suffer serious harms rather than prevent…