Module 2: AI's Hidden Bias скачать в хорошем качестве

Module 2: AI's Hidden Bias

Mitigating Bias Across the Automated Systems Lifecycle This video outlines a comprehensive framework for identifying and mitigating bias throughout the entire lifecycle of automated systems. It categorises unfairness into data-centric, algorithmic, and societal origins, demonstrating how human prejudice can be inadvertently coded into technology. Through detailed case studies in hiring, lending, and justice, the source illustrates the real-world harm caused by flawed data and feedback loops. To combat these risks, the material provides practical diagnostic tools and technical workflows for correcting models at various stages of development. Ultimately, it advocates for a proactive governance approach using structured audit templates and continuous monitoring to ensure ethical accountability. This systematic overview serves as a guide for transforming responsible AI from a theoretical goal into a functional reality.