Before big tech engineers can improve the fairness of recommendation systems, such as social media feeds and online shopping results, they need to define what “fairness” even means. Should an app show people only the content it predicts they will like most, or should it boost newer creators, small businesses or historically underrepresented groups? Should an online store rank products purely by past clicks and sales, or make sure independent sellers can compete with dominant brands?
Making big tech algorithms ‘fair’ is harder than it looks
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