Intergenerational experimentation and catastrophic risk
Fikri Pitsuwan (Center of Economic Research, ETH Zurich)
GPI Working Paper No. 6 - 2022
I study an intergenerational game in which each generation experiments on a risky technology that provides private benefits, but may also cause a temporary catastrophe. I find a folk-theorem-type result on which there is a continuum of equilibria. Compared to the socially optimal level, some equilibria exhibit too much, while others too little, experimentation. The reason is that the payoff externality causes preemptive experimentation, while the informational externality leads to more caution. Remarkably, for a particular temporal discount rate, there exists an optimal equilibrium in which the behavior of two-period-lived agents align with that of an infinitely-lived social planner. In a model with a political process, unequal political power, biased towards the young, supports an optimal equilibrium most often. Extensions include finite horizon, irreversible catastrophes, and risk-aversion.
Other working papers
How important is the end of humanity? Lay people prioritize extinction prevention but not above all other societal issues. – Matthew Coleman (Northeastern University), Lucius Caviola (Global Priorities Institute, University of Oxford) et al.
Human extinction would mean the deaths of eight billion people and the end of humanity’s achievements, culture, and future potential. On several ethical views, extinction would be a terrible outcome. How do people think about human extinction? And how much do they prioritize preventing extinction over other societal issues? Across six empirical studies (N = 2,541; U.S. and China) we find that people consider extinction prevention a global priority and deserving of greatly increased societal resources. …
Shutdownable Agents through POST-Agency – Elliott Thornley (Global Priorities Institute, University of Oxford)
Many fear that future artificial agents will resist shutdown. I present an idea – the POST-Agents Proposal – for ensuring that doesn’t happen. I propose that we train agents to satisfy Preferences Only Between Same-Length Trajectories (POST). I then prove that POST – together with other conditions – implies Neutrality+: the agent maximizes expected utility, ignoring the probability distribution over trajectory-lengths. I argue that Neutrality+ keeps agents shutdownable and allows them to be useful.
Against Willing Servitude: Autonomy in the Ethics of Advanced Artificial Intelligence – Adam Bales (Global Priorities Institute, University of Oxford)
Some people believe that advanced artificial intelligence systems (AIs) might, in the future, come to have moral status. Further, humans might be tempted to design such AIs that they serve us, carrying out tasks that make our lives better. This raises the question of whether designing AIs with moral status to be willing servants would problematically violate their autonomy. In this paper, I argue that it would in fact do so.