Variable Selection in the Context of AI Fairness
Fairness in AI systems has become more important with recent regulatory demands, such as the EU AI Act. Traditional approaches often do not take into account philosophical ethics and social awareness. Variable selection processes, in particular, can introduce implicit bias, affecting equity across different subgroups. We discuss a mathematical approach that evaluates fairness in AI, aligning mathematical methodologies with ethical considerations and regulatory requirements. Our aim is to advocate for interdisciplinary collaboration to address fairness, emphasizing the importance of understanding broader ethical and societal contexts. Our approach emphasizes maintaining all potentially rel...
| Authors | Ivan Luciano Danesi, Chiara Frigerio, Fabio Maccaferri et al. |
|---|---|
| Primary category | cs.CY |
| Published | 4 August 2026 |
| Last updated at source | 4 August 2026 |
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