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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