Shutdownable Agents through POST-Agency
Elliott Thornley (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 5-2025
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.
Other working papers
Is Existential Risk Mitigation Uniquely Cost-Effective? Not in Standard Population Models – Gustav Alexandrie (Global Priorities Institute, University of Oxford) and Maya Eden (Brandeis University)
What socially beneficial causes should philanthropists prioritize if they give equal ethical weight to the welfare of current and future generations? Many have argued that, because human extinction would result in a permanent loss of all future generations, extinction risk mitigation should be the top priority given this impartial stance. Using standard models of population dynamics, we challenge this conclusion. We first introduce a theoretical framework for quantifying undiscounted cost-effectiveness over…
Social Beneficence – Jacob Barrett (Global Priorities Institute, University of Oxford)
A background assumption in much contemporary political philosophy is that justice is the first virtue of social institutions, taking priority over other values such as beneficence. This assumption is typically treated as a methodological starting point, rather than as following from any particular moral or political theory. In this paper, I challenge this assumption.
Exceeding expectations: stochastic dominance as a general decision theory – Christian Tarsney (Global Priorities Institute, Oxford University)
The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk (like Pascal’s Mugging), and intolerably paradoxical in cases like the St. Petersburg and Pasadena games. In this paper I show that, under certain conditions, stochastic dominance reasoning can capture most of the plausible implications of expectational reasoning while avoiding most of its pitfalls…