individual fairness
What It Means
Individual fairness means that when your AI system makes decisions, people who are essentially similar should get essentially similar outcomes. If two loan applicants have nearly identical credit profiles, income levels, and financial histories, the AI should treat them the same way rather than giving one person a loan and rejecting the other for arbitrary reasons.
Why Chief AI Officers Care
This directly impacts legal compliance since discriminatory treatment of similar individuals can violate fair lending, employment, or consumer protection laws. Beyond legal risk, inconsistent AI decisions damage customer trust and brand reputation when people discover they were treated differently than similar peers. It also indicates potential flaws in your AI model that could lead to poor business decisions and lost revenue.
Real-World Example
A hiring AI system evaluates two software engineers with identical experience levels, similar education backgrounds, and comparable skill assessments, but gives one candidate a 95% recommendation score and the other a 60% score. Upon investigation, the difference stems from irrelevant factors like the format of their resume or their college's ranking rather than job-relevant qualifications.
Common Confusion
People often confuse individual fairness with group fairness - individual fairness focuses on treating similar people similarly, while group fairness looks at whether different demographic groups receive proportionally similar outcomes overall. You can have group fairness without individual fairness and vice versa.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare AI, individual fairness requires that patients with similar medical profiles, symptoms, and risk factors r...
Finance: In finance, individual fairness ensures that AI-driven decisions in lending, insurance underwriting, or investment advic...
Premium content locked
Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"The goal of similar individuals receiving similar treatments or outcomes."Source: AI_Fairness_360
"Give similar predictions to similar individuals"Source: Mehrabi,_Ninareh
"A fairness metric that checks whether similar individuals are classified similarly"Source: aime_measurement_2022 citing Machine Learning Glossary by Google
Discuss This Term with Your AI Assistant
Ask how "individual fairness" applies to your specific use case and regulatory context.
Start Free Trial