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.
Concerns Arise Over Russian Code in Hungary’s New Digital Identification System
Hungary's new Client Gate+ system raises security concerns due to the recommendation of a Russian-developed code generator, prompting scrutiny and […]