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Investigating sources and effects of bias in AI-based systems – results from an MLR

De Buitlear, Caoimhe, Byrne, Ailbhe, McEvoy, Eric, Camara, Abasse, Yilmaz, Murat orcid logoORCID: 0000-0002-2446-3224, McCarren, Andrew orcid logoORCID: 0000-0002-7297-0984 and Clarke, Paul orcid logoORCID: 0000-0002-4487-627X (2023) Investigating sources and effects of bias in AI-based systems – results from an MLR. In: 30th European Conference on Software Process Improvement (EuroSPI 2023), 30 Aug - 1 Sept 2023, Grenoble, France. ISBN 978-3-031-42306-2

Abstract
AI-based systems are becoming increasingly prominent in everyday life, from smart assistants like Amazon’s Alexa to their use in the healthcare industry. With this rise, the evidence of bias in AI-based systems has also been witnessed. The effects of this bias on the groups of people targeted can range from inconvenient to life-threatening. As AI-based systems continue to be developed and used, it is important that this bias should be eliminated as much as possible. Through the findings of a multivocal literature review (MLR), we aim to understand what AI-based systems are, what bias is and the types of bias these systems have, the potential risks and effects of this bias, and how to reduce bias in AI-based systems. In conclusion, addressing and mitigating biases in AI-based systems is crucial for fostering equitable and trustworthy applications; by proactively identifying these biases and implementing strategies to counteract them, we can contribute to the development of more responsible and inclusive AI technologies that benefit all users.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:AI; bias; artificial intelligence; risks
Subjects:Computer Science > Artificial intelligence
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > Lero: The Irish Software Engineering Research Centre
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: 30th European Conference on Software Process Improvement (EuroSPI 2023). Communications in Computer and Information Science (CCIS) 1890. Springer. ISBN 978-3-031-42306-2
Publisher:Springer
Official URL:https://doi.org/10.1007/978-3-031-42307-9_2
Copyright Information:© 2023 The Authors.
Funders:Science Foundation Ireland grant No SFI 13/RC/2094_P2 to Lero, Science Foundation Ireland (https://www.sfi.ie/) grant No SFI 12/RC/2289_P2 to Insight
ID Code:29092
Deposited On:28 Sep 2023 11:05 by Thomas Murtagh . Last Modified 28 Sep 2023 11:05
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