Module 2: Bias in AI - Understanding Bias

Welcome to our exploration of “Bias in AI." In this module, we'll unravel the intricacies of bias within artificial intelligence, a topic of increasing importance in the development and deployment of AI systems. Bias, both explicit and implicit, can manifest in various forms, influencing decision-making processes and outcomes. Let's embark on a journey to unravel the complexities and foster a more inclusive and equitable AI landscape.

In Module 2, we cover the following Lessons:

Lesson 2.1: Defining Bias in AI Lesson

Lesson 2.2: Types of Bias and Sources of Bias

Lesson 2.3: Impact of Bias


In this exploration, we dissect the various forms of bias, both explicit and implicit, that can affect decision-making processes. Throughout this lesson, we'll identify key types of bias, sources of bias and explore strategies to mitigate its impact. 

Above all, it is important to define what is bias. There are a lot of different understandings of the term, but in AI4Gov project, the following definition has been chosen: Bias is a term used to describe an inclination or prejudice for or against an individual or group in a way that is considered unfair.This is an excerpt from Learning material for topic: Bias and Types of Bias.

Watch the video lecture accompanied with slides to learn more about bias.

In addition, look at this short comics titled All about that Bias, presenting AI, algorithms and predictions.

All about that Bias comic book cover