Evolutionary debunking and value alignment
Michael T. Dale (Hampden-Sydney College) and Bradford Saad (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 11-2024
This paper examines the bearing of evolutionary debunking arguments—which use the evolutionary origins of values to challenge their epistemic credentials—on the alignment problem, i.e. the problem of ensuring that highly capable AI systems are properly aligned with values. Since evolutionary debunking arguments are among the best empirically-motivated arguments that recommend changes in values, it is unsurprising that they are relevant to the alignment problem. However, how evolutionary debunking arguments bear on alignment is a neglected issue. This paper sheds light on that issue by showing how evolutionary debunking arguments: (1) raise foundational challenges to posing the alignment problem, (2) yield normative constraints on solving it, and (3) generate stumbling blocks for implementing solutions. After mapping some general features of this philosophical terrain, we illustrate how evolutionary debunking arguments interact with some of the main technical approaches to alignment. To conclude, we motivate a parliamentary approach to alignment and suggest some ways of developing and testing it.
Other working papers
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Some worry that advanced artificial agents may resist being shut down. The Incomplete Preferences Proposal (IPP) is an idea for ensuring that does not 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…
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