SAFE-ML

The International Workshop on Secure, Accountable, and Verifiable Machine Learning (SAFE-ML) addresses the critical challenges at the intersection of Machine Learning (ML) and software testing. As ML systems are increasingly adopted across various sectors, concerns about privacy breaches, security vulnerabilities, and biased decision-making have grown. This workshop focuses on developing innovative methods, tools, and techniques to comprehensively test and validate the security aspects of ML systems, ensuring their safe and reliable deployment. SAFE-ML seeks to foster discussion and drive the creation of solutions that streamline the testing of ML systems from multiple perspectives.