It Only Takes One: The Psychology of Unilateral Decisions
Joshua Lewis (New York University), Carter Allen (UC Berkeley), Christoph Winter (ITAM, Harvard University and Institute for Law & AI) and Lucius Caviola (Global Priorities Institute, Oxford University)
GPI Working Paper No. 14-2024
Sometimes, one decision can guarantee that a risky event will happen. For instance, it only took one team of researchers to synthesize and publish the horsepox genome, thus imposing its publication even though other researchers might have refrained for biosecurity reasons. We examine cases where everybody who can impose a given event has the same goal but different information about whether the event furthers that goal. Across 8 experiments (including scenario studies with elected policymakers, doctors, artificial-intelligence researchers, and lawyers and judges and economic games with laypeople, N = 1,518, and 3 supplemental studies, N = 847) people behave suboptimally, balancing two factors. First, people often impose events with expected utility only slightly better than the alternative based on the information available to them, even when others might know more. This approach is insufficiently cautious, leading people to impose too frequently, a situation termed the unilateralist’s curse. Second, counteracting the first factor, people avoid sole responsibility for unexpectedly bad outcomes, sometimes declining to impose seemingly desirable events. The former heuristic typically dominates and people unilaterally impose too often, succumbing to the unilateralist’s curse. But when only few people can impose, who know the stakes are high, responsibility aversion reduces over-imposing.
Other working papers
A paradox for tiny probabilities and enormous values – Nick Beckstead (Open Philanthropy Project) and Teruji Thomas (Global Priorities Institute, Oxford University)
We show that every theory of the value of uncertain prospects must have one of three unpalatable properties. Reckless theories recommend risking arbitrarily great gains at arbitrarily long odds for the sake of enormous potential; timid theories recommend passing up arbitrarily great gains to prevent a tiny increase in risk; nontransitive theories deny the principle that, if A is better than B and B is better than C, then A must be better than C.
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…
In defence of fanaticism – Hayden Wilkinson (Australian National University)
Consider a decision between: 1) a certainty of a moderately good outcome, such as one additional life saved; 2) a lottery which probably gives a worse outcome, but has a tiny probability of a far better outcome (perhaps trillions of blissful lives created). Which is morally better? Expected value theory (with a plausible axiology) judges (2) as better, no matter how tiny its probability of success. But this seems fanatical. So we may be tempted to abandon expected value theory…