Artificial Intelligence Predicts Gambling Behavior

A simulated neural network is able to predict the bets and wins/losses of gamblers. Christie Nicholson reports

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[Below is the original script. But a few changes may have been made during the recording of this audio podcast.]

Artificial intelligence works to replicate our human mind (and a lot more). So scientists need to know how humans make their next moves. And while predicting behavior is inherent in AI, prediction itself is not often an end goal for AI.

But recently scientists have created a system that can predict the bets of gamblers, with an accuracy bordering on spooky.  Their research was published in the Journal of Gambling Studies.


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Researchers used data from a total of 675 online games from six Texas Holdem gamblers. They built a mathematically simulated neural network based on the players’ initial several plays. Meaning the network learns and rewires itself based on guesses that either turn out to be right or wrong.  This method of AI is called propagation of error.

They found that their neural model could predict each of the six gamblers bet amounts with an accuracy to three decimal places of the dollar. Additionally they could also predict with similar accuracy their cumulative wins/losses.

So based on their first few games, the gamblers subsequent behavior, strategy and ultimately their wins and losses, was consistently predictable.

Proves, yet again, sadly there’s no magic in gambling.

—Christie Nicholson

(via Mind Hacks)

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