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 proceedingConference paperpeer-review

17 Downloads (Pure)


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 languageEnglish
Title of host publicationAequitas 2023: Workshop on Fairness and Bias in AI | co-located with ECAI 2023, Kraków, Poland
PublisherCEUR Workshop Proceedings
Number of pages6
Publication statusAccepted/In press - 21 Jul 2023


Dive into the research topics of 'Recommendations for Bias Mitigation Methods: Applicability and Legality'. Together they form a unique fingerprint.

Cite this