Description: The ‘Disparate Impact’ refers to a legal doctrine that addresses how certain practices, policies, or technologies affect different groups of people unevenly. In the context of ethics and bias in artificial intelligence (AI), this concept becomes crucial, as algorithmic decisions can perpetuate or even exacerbate existing inequalities. Disparate impact manifests when a demographic group, whether by race, gender, socioeconomic class, or another characteristic, suffers more severe negative consequences than others due to the implementation of automated systems. This can include discrimination in hiring processes or excessive surveillance in specific communities. The relevance of this concept lies in the need to develop technologies that are fair and equitable, ensuring that all groups have access to the same benefits and opportunities. Identifying and mitigating disparate impact is essential for building AI systems that are not only efficient but also ethically responsible and socially just.
