AI Ethics and Safety Courses

6 courses that explain the ethics, risks, and regulation of AI — what can go wrong, why, and how society is responding. They're conceptual and need no technical background: the aim is to understand issues like bias, transparency, and the rules now governing AI, not to manage AI systems at work.

As AI spreads into hiring, lending, medicine, and the courts, a set of hard questions comes with it: who is accountable when a model is wrong, whose biases it absorbs, whether its reasoning can be explained, and how it should be regulated. These courses are about understanding those questions. They cover the core ideas of AI ethics and safety — fairness and bias, transparency and explainability, privacy, and the emerging laws and standards meant to keep AI in check — as a subject to grasp rather than a job to perform. The treatment is conceptual and needs no coding. If instead you need to deploy or govern AI responsibly in your own organization, the Use AI track's responsible-AI courses are the practical counterpart; this page is for building a clear, informed understanding of where AI helps, where it harms, and how it is being held to account.