TRUSTML

Through interdisciplinary collaborations and partnerships, we aim to build foundations for developing trustworthy ML-based systems, i.e., systems that are reliable, secure, privacy-preserving, explainable, and ethical. Such an effort will help prevent ML failures and biases, improving the trust of professionals and the general public in ML-based decision-making processes... TrustML facilitates development of trustworthy machine-learning-based systems, i.e., systems that are reliable, secure, explainable, and ethical.The cluster examines trust-related requirements in several life-critical domains, including medicine and aerospace, and investigates solutions for building trustw