In 2024, the European Union approved the first regulatory framework for AI, the so-called Regulation Act. It says that AI systems that can be used in different applications are analysed and classified according to the risk they pose to users. The various risk levels will mean more or less regulation. The main idea underpinning the EU approach to AI is that artificial intelligence algorithms should incorporate the principles of democracy, the rule of law and fundamental rights from the design stage. The EU guideline on AI Trustworthy realised by a group of experts for the EU Commission, and now recalled by the Regulation Act, defines trustworthy by four (4) ethical issues: (1) the respect for human autonomy; (2) the preservation by damage; (3) the explainability and (4) the Fairness. Fairness and the principle of no discrimination are realisable by correctly selecting the data and personal data used for training and testing AI algorithms. From the juridical point of view, the errors—that could be derived from the training of AI algorithms—become biased towards underrepresented groups or develop some discriminatory characteristics of the patient, exacerbating existing health disparities. The EU legal protection offered by non-discrimination law is called into question when it is the AI, not humans, to discriminate. Still, the increasing use of algorithms disrupts traditional legal remedies and procedures for detecting, investigating, preventing, and correcting discrimination, which have predominantly relied upon intuition.

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EU Guideline on AI Trustworthy and ‘Not Intuitive’ Application of the Principle of Fairness

  • Valentina Colcelli

摘要

In 2024, the European Union approved the first regulatory framework for AI, the so-called Regulation Act. It says that AI systems that can be used in different applications are analysed and classified according to the risk they pose to users. The various risk levels will mean more or less regulation. The main idea underpinning the EU approach to AI is that artificial intelligence algorithms should incorporate the principles of democracy, the rule of law and fundamental rights from the design stage. The EU guideline on AI Trustworthy realised by a group of experts for the EU Commission, and now recalled by the Regulation Act, defines trustworthy by four (4) ethical issues: (1) the respect for human autonomy; (2) the preservation by damage; (3) the explainability and (4) the Fairness. Fairness and the principle of no discrimination are realisable by correctly selecting the data and personal data used for training and testing AI algorithms. From the juridical point of view, the errors—that could be derived from the training of AI algorithms—become biased towards underrepresented groups or develop some discriminatory characteristics of the patient, exacerbating existing health disparities. The EU legal protection offered by non-discrimination law is called into question when it is the AI, not humans, to discriminate. Still, the increasing use of algorithms disrupts traditional legal remedies and procedures for detecting, investigating, preventing, and correcting discrimination, which have predominantly relied upon intuition.