Erasing social groups
Accuracy and effectiveness of AI decisions and actions are dependent on group membership, where decisions in AI system design and biased training data lead to unequal outcomes, reduced benefits, increased effort, and alienation of users.
people, attributes, or artifacts associated with specific social groups are systematically absent or under-represented... Design choices [143] and training data [212] influence which people and experiences are legible to an algorithmic system(p. 728)
Part of Representational Harms
Other risks from Shelby et al. (2023) (24)
Representational Harms
1.1 Unfair discrimination and misrepresentationRepresentational Harms > Stereotyping social groups
1.1 Unfair discrimination and misrepresentationRepresentational Harms > Demeaning social groups
1.1 Unfair discrimination and misrepresentationRepresentational Harms > Alienating social groups
1.1 Unfair discrimination and misrepresentationRepresentational Harms > Denying people the opportunity to self-identify
1.1 Unfair discrimination and misrepresentationRepresentational Harms > Reifying essentialist categories
1.1 Unfair discrimination and misrepresentation