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The Complex Math of Counterfactuals Could Help Spotify Pick Your Next Favorite Song


by Will Douglas Heaven, Senior editor for AI, MIT Technology Review, April 4, 2023


A new kind of machine-learning model built by a team of researchers at the music-streaming firm Spotify captures for the first time the complex math behind counterfactual analysis, a precise technique that can be used to identify the causes of past events and predict the effects of future ones.


(...) “The basic idea behind counterfactuals is to ask what would have happened in a situation had certain things been different. (...) In Spotify’s case, that might mean choosing what songs to show you or when artists should drop a new album. Spotify isn’t yet using counterfactuals”, says Ciaran Gilligan-Lee, leader of the Causal Inference Research Lab at Spotify. “But they could help answer questions that we deal with every day.”


(...) Spotify is not the only tech company racing to build machine-learning models that can reason about cause and effect. In the last few years, firms such as Meta, Amazon, LinkedIn, and TikTok’s owner ByteDance have also begun to develop the technology.




Illustration by STEPHANIE ARNETT/MITTR | ENVATO


Thanks to Tristra Yeager for sharing this article on LinkedIn.

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