Intermediate · Safety
Disparate impact
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. When an algorithm's decisions disproportionately affect different population subgroups, even if not intentionally biased.
Technical Definition
When an algorithm's decisions disproportionately affect different population subgroups, even if not intentionally biased.
How it works
Disparate impact occurs when a seemingly neutral algorithm or policy results in different outcomes for various demographic groups. This can happen even if there's no explicit intention to discriminate. The focus is on the real-world effect of the algorithm's decisions, identifying if certain subgroups are consistently disadvantaged or advantaged.
Related Concepts
- Fairness — The principle that AI systems should treat individuals and groups equitably.
- Bias (ethics/fairness) — Unfair prejudice or favoritism towards certain groups or things, which can influence data, system design, and user interactions.
- Responsible AI (RAI) — A holistic framework encompassing the ethical, legal, and societal implications of AI, promoting trustworthy and beneficial systems.