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

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

Existential risk and growth – Leopold Aschenbrenner (Columbia University)

Human activity can create or mitigate risks of catastrophes, such as nuclear war, climate change, pandemics, or artificial intelligence run amok. These could even imperil the survival of human civilization. What is the relationship between economic growth and such existential risks? In a model of directed technical change, with moderate parameters, existential risk follows a Kuznets-style inverted U-shape. …

The freedom of future people – Andreas T Schmidt (University of Groningen)

What happens to liberal political philosophy, if we consider not only the freedom of present but also future people? In this article, I explore the case for long-term liberalism: freedom should be a central goal, and we should often be particularly concerned with effects on long-term future distributions of freedom. I provide three arguments. First, liberals should be long-term liberals: liberal arguments to value freedom give us reason to be (particularly) concerned with future freedom…

Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Paris School of Economics)

Estimating long-term impacts of actions is important in many areas but the key difficulty is that long-term outcomes are only observed with a long delay. One alternative approach is to measure the effect on an intermediate outcome or a statistical surrogate and then use this to estimate the long-term effect. …