Fairness & Bias Mitigation, Transparency, Explainability, and Governance

Illustration by [Johnny Lighthands](https://www.johnnylighthands.co.uk))

Chapter Outline

• Introduction to Fairness
• AI Fairness
• Bias Mitigation
• Accountability
• Governance

Chapter Summary

In this chapter we explore various issues that arise within AI systems. We will look at the elements of AI fairness, and the strategies to conduct bias mitigation. Finally, we will touch upon the concepts of accountability and governance, and how they can be integrated into the AI project lifecycle.

Learning Objectives

In this chapter, you will:

• Learn about the landscape of meanings the concept of fairness has, as well as how to apply it in the context of AI.
• Understand the different elements of AI fairness and how they relate to one another.
• Look at the concept of bias in AI systems, the different kinds of biases which may arise, as well as how to mitigate them.
• Familiarise yourself with AI accountability, its main components, and how it relates to AI governance.