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.
Adult Safeguarding Toolkit
The purpose of this guidance is to assist organisations in their decisionmaking processes when processing the personal data of such […]