Fairness is the pillar that asks whether your solution works for everyone. We explore accessibility standards, non-discriminatory data and sharing design, privacy architecture, and AI ethics governance. For agents making decisions that affect people, we dig into explainability (why did it act?), contestability (can the decision be challenged?), and right-sized human-in-the-loop oversight. This session turns a principle that is easy to agree with into concrete design choices.