The 22-year-old Riley Walz of San Francisco has compiled a numeric system via LooksMapping as to which New York (and SF and LA) restaurants have the hottest clientele based not on actually visiting any restaurants but creating an A.I. model he directed to scrape 2.8 million Google reviews. Red means hot, blue means not, with a 10 signaling the restaurants with the most attractive diners. Carbone is 9.7; Raoul’s is 6.4; no results for Dhamaka or Crevette (lucky for them); and Sarabeth’s on the Upper West Side is 6.8. “The model is certainly biased. It’s certainly flawed. But we judge places by the people who go there [...] This website just puts reductive numbers on the superficial calculations we make every day,” reads the website. LooksMapping “ is more cultural commentary than practical resource,” writes the New York Times, yet, “ its premise speaks to a growing trend of diners prioritizing a restaurant’s clientele over its food or atmosphere.” It also reports that “racial biases in artificial intelligence are baked into the programming.” All of which is to say: One guy looked at 2.8 million reviews and decided the future of dining is Hot or Not, circa 2000.
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