Algorithms trained on biased data reproduce unfair patterns in hiring, evaluations, and customer decisions. This course teaches how to recognise bias in AI systems and take steps to promote fairer outcomes.
Objectives:
- Recognise how biased data creates unfair predictions in AI-driven decisions
- Identify bias patterns in hiring, healthcare, and customer service algorithms
- Question data sources and training methods that may embed unfair assumptions
- Review AI results critically rather than accepting automated outputs as neutral
- Support fairness by flagging questionable AI outcomes and demanding transparency
