Article 5TZ6Z AI Unmasks Anonymous Chess Players, Posing Privacy Risks

AI Unmasks Anonymous Chess Players, Posing Privacy Risks

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BeauHD
from Slashdot on (#5TZ6Z)
silverjacket shares a report from Science.org: [A]n 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. [...] To design and train their AI, the researchers tapped an ample resource: 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. They coded each move and fed them into a neural network that represented each game as a point in multidimensional space, so that each player's games formed a cluster of points. The network was trained to maximize the density of each player's cluster and the distance between those of different players. That required the system to recognize what was distinctive about each player's style. The researchers tested the system by seeing how well it distinguished one player from another. They gave the system 100 games from each of about 3000 known players, and 100 fresh games from a mystery player. To make the task harder, they hid the first 15 moves of each game. The system looked for the best match and identified the mystery player 86% of the time, the researchers reported last month at the Conference on Neural Information Processing Systems (NeurIPS). "We didn't quite believe the results," says Reid McIlroy-Young, a student in Anderson's lab and the paper's primary author. A non-AI method was only 28% accurate. [...] The researchers are aware of the privacy risks posed by the system, which could be used to unmask anonymous chess players online. With tweaks, McIlroy-Young says, it could do the same for poker. And in theory, they say, given the right data sets, such systems could identify people based on the quirks of their driving or the timing and location of their cellphone use.

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