EC Library Guide on artificial intelligence, ethics, bias and fairness: Introduction
Introduction
About this Library Guide
This Library Guide has been compiled to support the work of the European Commission. It may also be of interest to students, researchers and the wider public.
The Library Guide presents a curated selection of relevant sources on the topic: websites, EU publications, EU law, international publications, EU research results, peer-reviewed research journals and articles, books, think tank reports and news updates.
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AI, ethics, bias and fairness
How does the AI Act address racial and gender bias in AI? It is very important to underline that AI systems do not create or reproduce bias. Rather, when properly designed and used, AI systems can contribute to reducing bias and existing structural discrimination, and thus lead to more equitable and non-discriminatory decisions (e.g. in recruitment).
The new mandatory requirements for all high-risk AI systems will serve this purpose. AI systems must be technically robust to ensure they are fit for purpose and do not produce biased results, such as false positives or negatives, that disproportionately affect marginalised groups, including those based on racial or ethnic origin, sex, age, and other protected characteristics.
Source: European Commission
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