This short whitepaper aims to create the beginnings of a framework for best practices standards by focusing on specific privacy and security vulnerabilities within ML systems. At present, we view these vulnerabilities as warning signs—either of a future in which the benefits of ML are not fully embraced, or a future in which ML’s liabilities are insufficiently protected.
Norways DPA and FCA joins forces to combat cybercrime
Datatilsynet and Finanstilsynet invite banks to join a sandbox project to enhance data sharing solutions while ensuring compliance with privacy […]