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


The impact of bias on individuals and society is significant, leading to both obvious and subtle forms of discrimination and stereotyping (Steele, 2010). This impact can be seen in many aspects of people’s lives. These aspects are presented below: By restricting their possibilities, skewing their perspectives, and maintaining inequity, bias may harm individuals. When someone is biased, they could experience exclusion, discrimination, or unjust treatment because of their colour, gender, religion, sexual orientation, or other traits. This may result in low self-esteem, a sense of exclusion, and an awareness of unfairness. Additionally, bias may influence people's attitudes and beliefs, which can result in the internalization of stereotypes and biases that serve to reinforce bias. Furthermore, prejudice can affect how decisions are made, resulting in less-than-ideal results in processes including employment, promotion, policy-making, and media portrayal. It can bolster preconceptions, propagate stereotypes, and obstruct the quest of justice, fairness, and equality. This is an excerpt from Learning material for topic: Impact of Bias.

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

Congratulations on completing Module 2! Now you can
deepen your knowledge in Quiz 2. Keep up the good work!