Where algorithmic bias comes from, how it manifests in justice, work and healthcare, and how we can mitigate it.
Bias is not a technical error but a reflection of social inequalities encoded in data.
Three domains where algorithmic bias has concrete consequences on people's lives.
Technical tools and social approaches to address algorithmic bias: audits, fairness metrics and participatory design.
Test your understanding of Module 02: origins of algorithmic bias, case studies and mitigation strategies.