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Module 6: Understanding AI Fairness

Site: OpenLearn Create
Course: Trustworthy and Democratic AI - Creating Awareness and Change
Book: Module 6: Understanding AI Fairness
Printed by: Invitado
Date: Friday, 21 November 2025, 6:26 AM

Description

As AI becomes a bigger part of our daily lives, ensuring that these systems are fair is more important than ever. AI fairness means designing systems that treat everyone equally, regardless of their background, identity, or circumstances. Fairness in AI requires diverse, unbiased data, thoughtful design, and ongoing evaluation to ensure systems make equitable and trustworthy decisions. 

In the context of the Horizon Europe MAMMOth project, the “AI Fairness Definition Guide” was developed to help those creating AI understand how to define fairness in the social context of their created systems by working with stakeholders and experts from other disciplines. The guide presents a workflow for gathering fairness concerns of affected stakeholders and using them to derive corresponding formalisms and practices under a combined computer, social, and legal science viewpoint.

In Module 6, we cover:

Lesson 6.1: Understanding AI Fairness

Table of contents

LESSON 6.1: AI FAIRNESS AND PRIVACY

Watch the video lecture “AI fairness and privacy: fundamentals, synergies and conflicts” consisting of 5 parts, that will equip you with the needed knowledge on the topic of AI fairness.

Part 1. Introduction


Part 2. Fairness definitions


Part 3. Fairness methods and limitations


Part 4. Privacy through anonymity


Part 5. Differential privacy and concluding thoughts

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