Human trust in technology is based on our understanding of how it works and our assessment of its safety and reliability. To trust a decision made by an algorithm, we need to know that it is reliable and fair, that it can be accounted for, and that it will cause no harm.

This talk explores diverse approaches to achieve fairness, robustness, explainability, accountability, value alignment, and how to integrate them throughout the entire lifecycle of an AI application.