Project Maia

Maia is a human-oriented chess engine that tries to understand human play, rather than optimal play. Whereas existing chess engines ask: “What is the best move to play in this position?”, Maia instead asks: “What would a human play in this position?” Maia can answer this question for humans of a particular skill level, or even for the specific individual who is playing. By understanding human decisions at a granular level, Maia can help identify a player’s strengths and weaknesses, with the goal of helping them learn and improve their gameplay.

To learn how Maia works, a good starting point is this blog post. For more technical details, please refer to our papers. For an overview of Maia’s capabilities and a more hands-on experience, check out this deep dive. Because of its fundamentally different approach, Maia feels more human-like than any other chess engine.

Maia grew out of a simple conversation between MSR researcher Siddhartha Sen and Professor Ashton Anderson (lead PI of the Maia project, and former postdoc in the Microsoft Research New York City lab), who both shared a passion for chess. Given that chess AI has surpassed human abilities since 2005, Ashton and Siddhartha wondered if humans could have a more productive relationship with this AI, rather than simply being beaten by it all the time and being told what move to make without any explanation. In particular, they wondered if this AI could be redirected to help humans, by understanding how they play and showing them how to improve.

Maia is the first step towards a much larger vision of creating AI that is compatible with humans and synergistic with their goals. We believe that AI can be a partner in advancing human education. To learn more about this vision, listen to this podcast (opens in new tab). Maia researchers are also active in the chess education (opens in new tab)community and have been working with chess educators and pioneers to amplify and diversify chess outreach in primary education.