DataRobot Predicts the Grammy Awards’ Song of the Year Is…
Summary
With everyone worrying that a robot or artificial intelligence model will take their jobs someday, why shouldn’t The Recording Academy fear its annual task of doling out the Grammy Awards is safe? DataRobot, a Boston-based startup whose machine-learning platform helps companies use algorithms for data analysis without hiring a data science team, is taking a first swipe at predicting how likely it is that each nominee for Song of the Year will walk away with that gramophone award. DataRobot’s Taylor Larkin wrote in a blog post that the data included “genre of the song, amount of profanity, general sentiment, total word count in the song, and various audio features derived by Spotify.” These audio factors are listed by the music service as duration, key, time signature, “acousticness,” “danceability,” “energy,” “instrumentalness,” “liveliness,” “loudness,” “speechiness,” “valence,” and “tempo.” (Of course, anyone can make predictions—we’ll see how accurate it turns out to be. (One wonders how the fact that Childish Gambino, Drake, and Kendrick Lamar turned down offers to perform at the Grammy’s would impact their likelihood of winning, but that might be beyond the abilities of a machine learning model.
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