AI models struggle to explain chess and Go moves in natural language
In brief
- Current AI models poorly explain moves from chess or Go engines.
- BinProp boosts explainability by uncovering reusable concepts without fine-tuning.
- The method also works for Go, draughts, and shogi without adaptation.
Large language models fail to explain chess or Go engine decisions in a human-understandable way. A new method, BinProp, significantly improves this ability by discovering reusable concepts without additional training.
This summary gives you the essentials. The full article, its figures and quotes are on cs.AI updates on arXiv.org.
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