What power-seeking theorems do not show
David Thorstad (Vanderbilt University)
GPI Working Paper No. 27-2024
Recent years have seen increasing concern that artificial intelligence may soon pose an existential risk to humanity. One leading ground for concern is that artificial agents may be power-seeking, aiming to acquire power and in the process disempowering humanity. A range of power-seeking theorems seek to give formal articulation to the idea that artificial agents are likely to be power-seeking. I argue that leading theorems face five challenges, then draw lessons from this result.
Other working papers
Longtermist political philosophy: An agenda for future research – Jacob Barrett (Global Priorities Institute, University of Oxford) and Andreas T. Schmidt (University of Groningen)
We set out longtermist political philosophy as a research field. First, we argue that the standard case for longtermism is more robust when applied to institutions than to individual action. This motivates “institutional longtermism”: when building or shaping institutions, positively affecting the value of the long-term future is a key moral priority. Second, we briefly distinguish approaches to pursuing longtermist institutional reform along two dimensions: such approaches may be more targeted or more broad, and more urgent or more patient.
Do not go gentle: why the Asymmetry does not support anti-natalism – Andreas Mogensen (Global Priorities Institute, Oxford University)
According to the Asymmetry, adding lives that are not worth living to the population makes the outcome pro tanto worse, but adding lives that are well worth living to the population does not make the outcome pro tanto better. It has been argued that the Asymmetry entails the desirability of human extinction. However, this argument rests on a misunderstanding of the kind of neutrality attributed to the addition of lives worth living by the Asymmetry. A similar misunderstanding is shown to underlie Benatar’s case for anti-natalism.
Towards shutdownable agents via stochastic choice – Elliott Thornley (Global Priorities Institute, University of Oxford), Alexander Roman (New College of Florida), Christos Ziakas (Independent), Leyton Ho (Brown University), and Louis Thomson (University of Oxford)
Some worry that advanced artificial agents may resist being shut down. The Incomplete Preferences Proposal (IPP) is an idea for ensuring that doesn’t happen. A key part of the IPP is using a novel ‘Discounted REward for Same-Length Trajectories (DREST)’ reward function to train agents to (1) pursue goals effectively conditional on each trajectory-length (be ‘USEFUL’), and (2) choose stochastically between different trajectory-lengths (be ‘NEUTRAL’ about trajectory-lengths). In this paper, we propose evaluation metrics…