Notes on Chess and AI - by a l - a’s Substack
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Notes on Chess and AI<br>Or How I learned to Stop Worrying and Love the Bomb
a l<br>May 18, 2026
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Inspired by https://www.lesswrong.com/posts/nR3DkyivzF4ve97oM/how-go-players-disempower-themselves-to-ai and how AI interacts with Go players, I thought it would be interesting to share a collection of anecdotes and experiences with chess.<br>I’ve purposefully left this article without any chess diagrams or positions, which may come in a Part II.
In this piece I use ‘engine,’ ‘computer,’ and ‘AI’ somewhat interchangeably.<br>In 1997, Deep Blue defeated then reigning World Champion Garry Kasparov in a match, 3.5-2.5. It was a historic result, although not without controversy, and judging by the quality of the games, perhaps Kasparov still showed superior strategic understanding. Human-computer matches would continue over the next decade. The final human-computer match was played between Deep Fritz and Vladimir Kramnik, with the computer winning 4-2. It has to be said that even there, the machine showed few signs of superhuman ability. The World Champion inexplicably blundered checkmate in one move in Game 2, with 4 of the other 5 games being drawn, and a loss in the final game in a last ditch attempt to win the match.<br>Since then, computers have steadily gotten stronger. Because current engines do not play against humans, it is difficult to get an exact grasp on their rating level (instead, the 1997 and 2006 matches are often used as a bridge to peg down their Elo). In addition, the drawish nature of chess forces developers to use imbalanced opening books to differentiate the skill gap between engines, because a match from the start position would feature almost all draws. We can say that as time goes on, there are fewer positions where engines tend to ‘misplay,’ although the space of all possible positions is enormous.<br>Chess players today grow up in an interesting era where computer dominance is a given. Computer analysis and programs are ubiquitous; any commentary of top level games features an ‘eval bar,’ an indicator that shows exactly how well a player is doing at any given moment. The game notation often features colored commentary indicating which moves are mistakes or blunders. On the now defunct game spectating website Chessbomb.com, chatters would derogatorily mark bad games as ‘rainbow colored.’<br>But the share of top players that use AI has also steadily increased. In the early days, some strong GMs consistently played their pet openings, and for a while, they could get away with it, too. One of my early coaches, a player in the top 100, steadfastly used Rybka 3 even as later versions came out. He liked its feel and how it would approach certain positions.<br>What happened to the players that refused the AI adoption? They gradually stopped becoming top players. Today, of the top 100 players, at least 95, and probably 100, use the latest engines or play opening moves suggested by the top engines.1<br>AI Users Never Find out They Haven’t Got It - But It Probably Doesn’t Matter
The chess world is remarkably inclusionary of all ages. In speaking to any grandmaster from the 80s, there’s an immediate sign of reverence in how they spoke of the top players of the day. Patrick Wolff described analyzing with Vishy Anand as ‘being in the presence of God,’ a sentiment later shared by a young Magnus Carlsen who had already taken the world #1 ranking. Perhaps it is possible that pre-AI, humans demonstrated a superior method of understanding. They just got it.2<br>I think differently. The fundamental problem of getting it is this: The goal of playing chess is not to create art, not to show understanding, not to think or display strategical brilliance. The goal of playing chess is to win chess games.3 The top chess players use whatever resources they can, including copious amounts of computer use to deeply analyze every single variant and position.<br>But if AI is freely available to use for everyone, what is the differentiator? Why are the elite players better than the less elite players?4 Top players go into less explored lines - with a slight twist. In popular culture, people cite Magnus Carlsen ‘purposefully not playing the best moves,’ although perhaps a more apt description would be ‘purposefully not playing the best moves, and then analyzing the next 5-10 moves and memorizing the best moves.’ It is not by accident that Magnus Carlsen rarely, if ever, gets outprepared in the opening, and it is not because he ‘doesn’t use AI.’5<br>While the goal is still to avoid the well-trotted lines, the use of AI has exploded, rather than diminished. It is difficult to know exactly how much analysis has been done, because so much of it is done behind closed doors. But even players on the fringe of the top-100 have thousands of opening files, each with thousands of moves. The top players, who are able to hire teams to analyze for them, surely have significantly...