Skip to main content

Extension

Extension
Complete

Why keep learning?

AI adoption is accelerating alongside scrutiny from regulators, civil society and customers. Organisations that treat ethics as a product requirement—not an afterthought—ship more durable systems and recover faster when issues arise.

Extension illustration

Dive deeper: additional learning materials

Understanding AI bias and fairness

Article:

The hidden biases in AI decision-making — real-world bias cases and mitigation directions.

Research:

Gender Shades: intersectional accuracy disparities in commercial gender classification — foundational work on performance gaps across demographic groups.

Ethical AI governance and regulation

Suggested stretch activity

Pick one live system in your organisation and draft a one-page “ethical risk brief”: data sources, stakeholders, failure modes, current controls and three testable mitigations.

In progress