Compliance and Ethical AI in Practice
Explore how compliance frameworks and ethical AI principles impact system design and governance. Understand key regulations such as GDPR, HIPAA, and FedRAMP, and their influence on data handling, deployment platforms, and audit trails. Learn to distinguish compliance from fairness and transparency to design AI systems that are both legally compliant and ethically sound.
The previous two lessons covered guardrails and escalation, controls that shape how a system behaves once it is already built. This lesson covers something that has to be settled earlier: what a system is even allowed to be built as, given the regulatory environment it operates in, and what it owes the people it makes decisions about beyond whatever the law happens to require. Discovering a compliance requirement after an architecture is already built is expensive in a way discovering it during design is not, since a deployment platform, a data flow, or a logging gap can force a rebuild instead of a patch. In this lesson, we will cover:
GDPR, HIPAA, and FedRAMP as architectural constraints that shape deployment platform, data flow, and logging from the first design decision, well before any review step at the end.
The specific places these regulations bite: data residency, PII and PHI handling, audit trails, and deployment surface.
Bias, fairness, and transparency as a separate, non-regulatory obligation; a fully compliant system can still fail.
Where compliance and ethical AI considerations actually belong in the design process.
Compliance is a constraint on the architecture from the start
A regulatory requirement is not a checklist a legal team runs before launch. It determines which deployment platform is even available, which data is allowed to cross a boundary, and what has to be logged, and it determines these things from the very first architectural decision. Waiting until the system is otherwise finished comes too late. This is the same idea covered earlier in this course when deployment platform and data residency were chosen alongside model selection rather than after it, now extended to the full regulatory ...