EC Library Guide on artificial intelligence, algorithms and the risk of discrimination: Introduction
Introduction
About this Library Guide
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AI, algorithms and the risk of discrimination
It is very important that AI systems do not create or reproduce bias. Rather, when properly designed and used, AI systems can contribute to reduce 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 guarantee that the technology is fit for purpose and false positive/negative results are not disproportionately affecting protected groups (e.g. racial or ethnic origin, sex, age etc.).
High-risk systems will also need to be trained and tested with sufficiently representative datasets to minimise the risk of unfair biases embedded in the model and ensure that these can be addressed through appropriate bias detection, correction and other mitigating measures.
They must also be traceable and auditable, ensuring that appropriate documentation is kept, including of the data used to train the algorithm that would be key in ex post investigations.
Compliance system before and after they are placed on the market will have to ensure these systems are regularly monitored and potential risks are promptly addressed.
Source: European Commission
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