Social Choice for Fair Recommendations

Recommender systems influence nearly every aspect of our digital lives—but what does it mean for those systems to be fair? Robin Burke joins Data Skeptic to discuss the history of recommender systems, the limitations of optimizing purely for accuracy, and how ideas from social choice theory can help balance the needs of users, creators, and society. The conversation explores the future of recommendation algorithms and why fairness is a far more complex challenge than it first appears.

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ethics.ai (27 July 2026), “Social Choice for Fair Recommendations,” evidence record 13999, https://ethics.ai/record/13999 (originally published by Data Skeptic).

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