Can Artificial Intelligence identify your playing style?

by ChessBase
2/4/2022 – Ashton Anderson, a computer scientist at the University of Toronto, wanted to know whether chess players have a unique playing style. To answer that question, he and his team gathered more than "50 million human games played on the Lichess website. They collected games by players who had played at least 1000 times and sampled sequences of up to 32 moves from those games. ... [Then] they gave the system 100 games from each of about 3000 known players, and 100 fresh games from a mystery player. The system ... identified the mystery player 86% of the time." An article in "Science" takes a closer look at the pros and cons of this experiment. | Photo: Xi Jian/ | Source: "Science"

ChessBase 17 - Mega package - Edition 2024 ChessBase 17 - Mega package - Edition 2024

It is the program of choice for anyone who loves the game and wants to know more about it. Start your personal success story with ChessBase and enjoy the game even more.


AI unmasks anonymous chess players, posing privacy risks

Software that identifies unique playing styles could lead to better tutorials and game play

By Matthew Hutson

Think your bishop’s opening, queen’s gambit, and pawn play are unique? A new artificial intelligence (AI) algorithm has got your chess style pegged. AI software can already identify people by their voices or handwriting. Now, an AI has shown it can tag people based on their chess-playing behavior, an advance in the field of "stylometrics" that could help computers be better chess teachers or more humanlike in their game play. Alarmingly, the system could also be used to help identify and track people who think their online behavior is anonymous.

"Privacy threats are growing rapidly," says Alexandra Wood, a lawyer at the Berkman Klein Center for Internet & Society at Harvard University. She says studies like this one, when conducted responsibly, are useful because they "shed light on a significant mode of privacy loss."

Chess-playing software, such as Deep Blue and AlphaZero, has long been superhuman. But Ashton Anderson, a computer scientist at the University of Toronto and principal investigator of the new project, says the chess engines play almost an "alien style" that isn’t very instructive for those seeking to learn or improve their skills. They’d do better to tailor their advice to individual players. But first, they’d need to capture a player’s unique form.

See complete article at "Science" online...


Reports about chess: tournaments, championships, portraits, interviews, World Championships, product launches and more.


Rules for reader comments


Not registered yet? Register