Recommendations for Bias Mitigation Methods: Applicability and Legality

Madeleine Waller; Odinaldo Rodrigues; Oana Cocarascu

Recommendations for Bias Mitigation Methods: Applicability and Legality

Madeleine Waller^*, Odinaldo Rodrigues, Oana Cocarascu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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Abstract

With AI-based decision-making systems increasingly being deployed in various sectors, research on fairness in AI has become even more important. In this position paper, we highlight a number of significant practical applicability limitations and regulatory compliance issues associated with existing bias mitigation methods. These limitations indicate a pressing need for a change in the approach to their development. In order to address them, we provide a list of recommendations for new bias mitigation methods that are not only effective, but can also be applied in real-world scenarios and comply with legal requirements.

Original language	English
Title of host publication	Aequitas 2023: Workshop on Fairness and Bias in AI \| co-located with ECAI 2023, Kraków, Poland
Publisher	CEUR Workshop Proceedings
Number of pages	6
Publication status	Accepted/In press - 21 Jul 2023

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Recommendations for Bias Mitigation Methods: Applicability and Legality
2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Accepted author manuscript, 230 KBLicence: CC BY

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Recommendations for Bias Mitigation Methods: Applicability and Legality

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