The Playful System team headed out to Las Vegas, Nevada to create an algorithm that can predict chess moves and enable commentators to tell better stories using predictive technology.
Maurice Ashley learned how to play chess on the streets of deep Brooklyn. There, lively commentary naturally accompanied intergenerational game play, making what is more globally known as a rather stoic, silence-induced game into something more like a spectator sport. So when Ashley became a chess grandmaster, he felt determined to not just play the game well, but to commit himself to finding ways to use the stories generated from a game to inspire others.
In November 2012, MIT Media Lab faculty member Kevin Slavin was attending the Director’s Fellows event in New York City when he witnessed Ashley dramatizing a play-by-play post-tournament debrief with a team of middle school chess players at Hunter College Prep in New York City. “Maurice could see into players minds in ways that other humans can’t,” says Slavin,“he could change the data on a piece of paper into a stories.”
Back at the Media Lab, Slavin tapped student Kevin Borenstein to develop an algorithm that could digitize the kind of dramatization that Ashley was doing from his own head. Borenstein, who has taught machine learning at NYU and is also a seasoned illustrator and storyteller, readily took on the challenge. Over the course of several months, Borenstein patched together some code he had written for previous work, working closely with Ashley to understand the inner workings of chess and how the storytelling component of this intricate game could be interpreted by a machine.
Deep View debuted at Ashley’s Millionaire Chess Open event in October 2014 in Las Vegas, Nevada. The grandmasters who played at the tournament used digital chess boards, which sent information about each move they make in real time to Borenstein’s computer. Borenstein, who was sitting alongside the live video production team backstage, then blasted the information he was getting to the switchboard, and the switchboard operators sent the data Stylized graphics display player statistics and strenghs like a baseball card, while a ticker below each player’s name shows the percentage chance of them winning.
“Deep View can provide analysis on the fly and can help tell stories,” Slavin says. “It will point out when players deviate from their usual play, as well as their strengths and weaknesses.”