The Shutdown Problem: An AI Engineering Puzzle for Decision Theorists

Elliott Thornley (Global Priorities Institute, University of Oxford)

GPI Working Paper No. 10-2024, forthcoming in Philosophical Studies

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I explain and motivate the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems suggest that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. I end by noting that these theorems can guide our search for solutions to the problem.

Other working papers

Intergenerational experimentation and catastrophic risk – Fikri Pitsuwan (Center of Economic Research, ETH Zurich)

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…

Prediction: The long and the short of it – Antony Millner (University of California, Santa Barbara) and Daniel Heyen (ETH Zurich)

Commentators often lament forecasters’ inability to provide precise predictions of the long-run behaviour of complex economic and physical systems. Yet their concerns often conflate the presence of substantial long-run uncertainty with the need for long-run predictability; short-run predictions can partially substitute for long-run predictions if decision-makers can adjust their activities over time. …