Beliefs about the end of humanity: How bad, likely, and important is human extinction?

Matthew Coleman (Northeastern University), Lucius Caviola (Global Priorities Institute, University of Oxford), Joshua Lewis (New York University) and Geoffrey Goodwin (University of Pennsylvania)

GPI Working Paper No. 1-2024

Human extinction would mean the end of humanity’s achievements, culture, and future potential. According to some ethical views, this would be a terrible outcome. But how do people think about human extinction? And how much do they prioritize preventing extinction over other societal issues? Across five empirical studies (N = 2,147; U.S. and China) we find that people consider extinction prevention a societal priority and deserving of greatly increased societal resources. However, despite estimating the likelihood of human extinction to be 5% this century (U.S. median), people believe that the chances would need to be around 30% for it to be the very highest priority. In line with this, people consider extinction prevention to be only one among several important societal issues. People’s judgments about the relative importance of extinction prevention appear relatively fixed and hard to change by reason-based interventions.

Other working papers

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This paper presents a new kind of problem in the ethics of distribution. The problem takes the form of several “calibration dilemmas,” in which intuitively reasonable aversion to small-stakes inequalities requires leading theories of distribution to recommend intuitively unreasonable aversion to large-stakes inequalities—e.g., inequalities in which half the population would gain an arbitrarily large quantity of well-being or resources…

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A principal wants to deploy an artificial intelligence (AI) system to perform some task. But the AI may be misaligned and aim to pursue a conflicting objective. The principal cannot restrict its options or deliver punishments. Instead, the principal is endowed with the ability to impose imperfect recall on the agent. The principal can then simulate the task and obscure whether it is real or part of a test. This allows the principal to screen misaligned AIs during testing and discipline their behaviour in deployment. By increasing the…