Fairness & Bias
Group and individual criteria, impossibility results, measurement under missing attributes, and mitigation costs.
11concepts
97flashcards
87minutes of reading
- 01 Discrimination in LLM-Mediated Decisions The correspondence-study design adapted to prompted models, what Anthropic's discrim-eval and the realistic-context follow-up measured, and why an anti-bias prompt that passes a clean evaluation fails once the prompt looks like production.
- 02 Disparate Impact and the Legal Frame How US anti-discrimination doctrine actually assigns liability, why the four-fifths rule is a screening heuristic rather than a standard, and the places where a passing fairness metric and a successful legal defence come apart.
- 03 Where Bias Enters the Pipeline The six distinct points at which disparity is introduced, why calling them all "biased data" prevents fixing them, and which stage each mitigation actually addresses.