AI takeover and human disempowerment
Adam Bales (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 9-2024, forthcoming in The Philosophical Quarterly
Some take seriously the possibility of AI takeover, where AI systems seize power in a way that leads to human disempowerment. Assessing the likelihood of takeover requires answering empirical questions about the future of AI technologies and the context in which AI will operate. In many cases, philosophers are poorly placed to answer these questions. However, some prior questions are more amenable to philosophical techniques. What does it mean to speak of AI empowerment and human disempowerment? And what empirical claims must hold for the former to lead to the latter? In this paper, I address these questions, providing foundations for further evaluation of the likelihood of takeover.
Other working papers
On the desire to make a difference – Hilary Greaves, William MacAskill, Andreas Mogensen and Teruji Thomas (Global Priorities Institute, University of Oxford)
True benevolence is, most fundamentally, a desire that the world be better. It is natural and common, however, to frame thinking about benevolence indirectly, in terms of a desire to make a difference to how good the world is. This would be an innocuous shift if desires to make a difference were extensionally equivalent to desires that the world be better. This paper shows that at least on some common ways of making a “desire to make a difference” precise, this extensional equivalence fails.
Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Rethink Priorities), Jojo Lee and Victor Yaneng Wang (Global Priorities Institute, University of Oxford)
The surrogate index method allows policymakers to estimate long-run treatment effects before long-run outcomes are observable. We meta-analyse this approach over nine long-run RCTs in development economics, comparing surrogate estimates to estimates from actual long-run RCT outcomes. We introduce the M-lasso algorithm for constructing the surrogate approach’s first-stage predictive model and compare its performance with other surrogate estimation methods. …
Tough enough? Robust satisficing as a decision norm for long-term policy analysis – Andreas Mogensen and David Thorstad (Global Priorities Institute, Oxford University)
This paper aims to open a dialogue between philosophers working in decision theory and operations researchers and engineers whose research addresses the topic of decision making under deep uncertainty. Specifically, we assess the recommendation to follow a norm of robust satisficing when making decisions under deep uncertainty in the context of decision analyses that rely on the tools of Robust Decision Making developed by Robert Lempert and colleagues at RAND …