AI Fairness in Practice

Understand

Reaching consensus on a commonly accepted definition of AI Fairness has long been a central challenge in AI ethics and governance.

• There is a broad spectrum of views across society on what the concept of fairness means and how it should best be put to practice.
• In this workbook, we tackle this challenge by exploring how a context-based and society-centred approach to understanding AI Fairness can help project teams better identify, mitigate, and manage the many ways that unfair bias and discrimination can crop up across the AI project workflow.
• We begin by exploring how, despite the plurality of understandings about the meaning of fairness, priorities of equality and non-discrimination have come to constitute the broadly accepted core of its application as a practical principle.