Addressing the need for AI systems free from discrimination requires a multidisciplinary approach that combines social, legal, and technical perspectives. Despite significant advancements in research and technical solutions, a gap remains between socio-legal and technical approaches. This paper proposes a meta-methodology - namely, FAIRBRIDGE - to bridge this gap, offering a reference for defining AI fairness methodologies that integrate all three perspectives. The meta-methodology utilizes a questionnaire-based system where socio-legal and technical domain experts iteratively refine questions and responses, supported by automation.
Ciatto, G., Matteini, M., Sartori, L., Rebrean, M., Muller, C., Borghesi, A., et al. (2025). AI-fairness: the FAIRBRIDGE approach to practically bridge the gap between socio-legal and technical perspectives. Piscataway, NJ : IEEE Computer Society.
AI-fairness: the FAIRBRIDGE approach to practically bridge the gap between socio-legal and technical perspectives
Ciatto G.
;Matteini M.;Sartori L.;Muller C.;Borghesi A.;Calegari R.
2025
Abstract
Addressing the need for AI systems free from discrimination requires a multidisciplinary approach that combines social, legal, and technical perspectives. Despite significant advancements in research and technical solutions, a gap remains between socio-legal and technical approaches. This paper proposes a meta-methodology - namely, FAIRBRIDGE - to bridge this gap, offering a reference for defining AI fairness methodologies that integrate all three perspectives. The meta-methodology utilizes a questionnaire-based system where socio-legal and technical domain experts iteratively refine questions and responses, supported by automation.| File | Dimensione | Formato | |
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