At the recent Databricks Spark AI Summit Europe, Swoop co-founder and CTO Sim Simeonov spoke at length on how to build great ML/AI models without sacrificing user privacy, specifically viewed through the lens of learning how to operate under Europe’s General Data Protection Regulation (GPDR). His talk challenges the implicit assumption that more privacy requires worse data.

Watch the presentation as Sim and co-presenter Slater Victoroff detail topics like pseudonymous ID generation, semantic scrubbing, structure-preserving data fuzzing, task-specific vs. task-independent sanitization and ensuring downstream privacy in multi-party collaborations.

Get the slides:

Categories: Data and Privacy

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