L’impact disparate survient lorsqu’un processus décisionnel produit des résultats disproportionnellement préjudiciables ou bénéfiques pour différents sous-groupes de population, même sans utiliser explicitement des attributs protégés. Dans les systèmes algorithmiques, il est évalué en examinant les disparités de résultats et leur relation avec des caractéristiques sensibles ou juridiquement protégées.
Making decisions about people that impact different population subgroups disproportionately. This usually refers to situations where an algorithmic decision-making process harms or benefits some subgroups more than others. For example, suppose an algorithm that determines a Lilliputian's eligibility for a miniature-home loan is more likely to classify them as "ineligible" if their mailing address contains a certain postal code. If Big-Endian Lilliputians are more likely to have mailing addresses with this postal code than Little-Endian Lilliputians, then this algorithm may result in disparate impact. Contrast with disparate treatment, which focuses on disparities that result when subgroup characteristics are explicit inputs to an algorithmic decision-making process.