AI Fairness

The principle that AI systems should not create or reinforce unfair bias against particular groups. Standard AI fairness frameworks primarily address race and gender but are increasingly recognized as inadequate for disability, because disability is often invisible, intermittent, or resists the categorical boundaries that machine learning systems require. Disability-related data collection creates privacy risks since people must disclose disability status to be included, and many disabilities are not captured in training datasets. A comprehensive approach to AI fairness for disability requires consideration of quality of service, allocation harms, denigration, stereotyping, and exclusion from consideration.