Data Representativeness

The degree to which a dataset reflects the diversity of the population it is intended to serve, particularly across demographic dimensions such as age, gender, race, ethnicity, disability, and socioeconomic status. In AI and machine learning, unrepresentative training data leads to systems that perform poorly or unfairly for underrepresented groups. For accessibility, data representativeness is a compound challenge: datasets must represent not only diverse disabilities but also demographic diversity within disability communities, as disabled people are not a monolithic group. Intersectional gaps — such as the underrepresentation of autistic women or older adults with developmental disabilities — can perpetuate existing biases through AI systems.