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Chess as a Testing Grounds for the Oracle Approach to AI Safety

Authors :
Miller, James D.
Yampolskiy, Roman
Haggstrom, Olle
Armstrong, Stuart
Publication Year :
2020

Abstract

To reduce the danger of powerful super-intelligent AIs, we might make the first such AIs oracles that can only send and receive messages. This paper proposes a possibly practical means of using machine learning to create two classes of narrow AI oracles that would provide chess advice: those aligned with the player's interest, and those that want the player to lose and give deceptively bad advice. The player would be uncertain which type of oracle it was interacting with. As the oracles would be vastly more intelligent than the player in the domain of chess, experience with these oracles might help us prepare for future artificial general intelligence oracles.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2010.02911
Document Type :
Working Paper