The privacy panic around machine learning is overblown

We often hear warnings about how machine learning (ML) models may expose sensitive information tied to their training data. The concern is understandable. If a model was trained on personal records, it may seem reasonable to assume that releasing it could reveal something about the people behind those records. A study by Josep Domingo-Ferrer examines this assumption and finds that the situation is less threatening than current discussions suggest. How regulation frames the issue The … More →

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