Every chess player who follows the debate on cheating has heard of Kenneth (or Ken) Regan. He is an Associate Professor at the Department of Computer Science and Engineering at the University of Buffalo and himself a 2372-rated International Master. Regan has developed statistical methods to prove cheating in a series of scientific papers which are accessible on his homepage.
His approach was explained in a Chess Life cover story and, more concisely, on the website of the Downend & Fishponds Chess Club in Bristol. As Regan himself points out, “statistical evidence is secondary to physical or observational evidence of cheating when judging a case” and “statistical evidence is much easier to obtain where it is supplemented and supported by other evidence, such as suspicious behaviour.”
Chess.com, Lichess and FIDE are applying his methods, but there is no shortage of criticism. Alexander Grischuk considers Regan’s approach completely unsuitable, as it exposes “only the very stupid ones who stubbornly play the computer’s first line”. Evgeny Gleizerov, another Russian grandmaster, suspects that behind the “smoke screen” of a supposedly effective algorithm-based cheater investigation, really clever cheaters could be all the better hidden. If FIDE continues to rely on statistical methods like Regan’s in times of Covid-19, Gleizerov oracles, chess is poised “to become a version of the shell game”.
Such radical criticism is less of a challenge for Regan than the near absence of technical or scientific criticism. Even though there is not the slightest doubt about the expertise and integrity of the American professor, his de facto monopoly in the narrow research area of “cheater recognition in chess using statistical methodology” is far from optimal.
This security by obscurity approach, as we have seen in so many other security fields, is destined to fail in the long term.
One article published in 2015 put Regan’s approach to the test and urged caution. Its authors David J. Barnes and Julio Hernandez-Castro also sent a message to platform operators: “An additional obstacle for researchers and progress in this area is that the numerous online chess servers that have developed their in-house techniques for detecting cheating have, in all cases, kept their methodology secret and seem unprepared to disclose any information publicly. This security by obscurity approach, as we have seen in so many other security fields, is destined to fail in the long term.”
In addition to statistics and information technology, there is another area of cheating research which has developed fast over the last two decades, but has so far received little attention from the chess community. Located at the interface of economics and psychology, behavioural economics is interested in the topic of “cheating”, not least to avert economic damage to communities, economies and companies. Of particular interest for chess should be the human factor in this research:
- What makes someone a cheater?
- Which factors favour cheating?
- What works against cheating?
- Which social contexts need to be considered?
One of the best known representatives of this research field is Dan Ariely, Professor of Psychology and Behavioural Economics at Duke University. Ariely is fascinated by the irrationality of human decisions and penned the bestseller “The (Honest) Truth About Dishonesty”. A short look at the factors involved should convince chess players that behavioural economics helps to better understand cheating in chess.
In the middle (“No effect”) Ariely put two factors which are often named as decisive in anti-cheating discussions in chess: The extent of monetary gain and the probability of being caught. On the right (rather than of factors that “decrease dishonesty” I would speak of “honesty enhancers”), alongside good old ways of surveillance, whether by humans or technology, are forms of reminders and voluntary commitment, which both presuppose that the possibility of cheating is openly discussed in advance.
It gets more exciting on the left side of the graphic (“dishonesty enhancers”), where you will find social factors from the classic slippery slope after a “first mistake” to motives like following the perception that others do it, too, up to do it for the benefit of others. Labeling chess cheaters as pure egoists who simply accept the possible damage for their club falls short. On the contrary, the desire to help one’s own group can be a motive for resorting to illegal means. Ariely has pointed out how cheating can become contageous and how self-control mechanisms fail when a person is too tired.
The finding that cheaters feel happy, at least in the short term, was picked up under the buzzword cheater’s high.
His work has received wide attention and is not without critics. Another interesting scientific author is Francesca Gino, Professor of Business Administration at Harvard and author of “Rebel Talent: Why it Pays to Break the Rules at Work and in Life”. On her website, Gino not only makes available a bundle of her own publications that illuminate the topic of cheating from various perspectives, but also suggests possible prevention strategies. Gino was a member of a research group that broke with the dogma that cheating does not make you happy. The study's finding that cheaters feel happy, at least in the short term, was picked up under the buzzword “cheater's high”.
Other fields where chess can learn are studies on cheating in gaming contexts and on doping and match fixing in sports. My conclusion is that the chess community should pay much more attention to the human and social aspects of the problem.
A longer German version of this article was published on the blog Grumbeerschach.
Sessions related to cheating at ChessTech 2020:
- Saturday 11–12 The Hidden Costs of Cheating and Anti-Cheating (with Wolfgang Grünstäudl)
- Saturday 13–14.30 Best Practices in Anti-Cheating
- Saturday 15–16 How to Detect Cheating (professional or VIP ticket required, with Ken Regan)