Fairness
Absence of unjustified bias or discrimination in AI outputs and equitable treatment and access across individuals and groups.
Definition
Fairness addresses outcomes across individuals or groups, focusing on avoiding systematic disadvantage unless such outcomes are objectively justified and documented; it requires assessment of disparate impacts and implementation of bias mitigation where appropriate.
Related Terms
Bias
A systematic difference in how an AI system treats or represents people, groups, objects, or outcomes that can lead to unfair or discriminatory results....
Algorithmic Discrimination
Unfair or unlawful differential treatment or impact caused by an AI or algorithmic system against individuals or groups, often on protected characteristics....
Non-Discrimination
Requirement that AI systems do not produce unjustified differential treatment or disproportionate adverse impacts against individuals or groups based on protected or analogous characteristics....
Transparency
Providing understandable information about AI systems....
Explainability
The ability to understand and articulate how an AI system reaches its decisions....