A2 Refereed review article in a scientific journal
Ethics-based AI auditing : A systematic literature review on conceptualizations of ethical principles and knowledge contributions to stakeholders
Authors: Laine Joakim, Minkkinen Matti, Mäntymäki Matti
Publisher: Elsevier
Publication year: 2024
Journal: Information and Management
Journal name in source: Information & Management
Article number: 103969
Volume: 61
Issue: 5
ISSN: 0378-7206
eISSN: 1872-7530
DOI: https://doi.org/10.1016/j.im.2024.103969
Web address : https://doi.org/10.1016/j.im.2024.103969
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/393422189
This systematic literature review synthesizes the conceptualizations of ethical principles in AI auditing literature and the knowledge contributions to the stakeholders of AI auditing. We explain how the literature discusses fairness, transparency, non-maleficence, responsibility, privacy, trust, beneficence, and freedom/autonomy. Conceptualizations vary along social/technical- and process/outcome-oriented dimensions. The main stakeholders of ethics-based AI auditing are system developers and deployers, the wider public, researchers, auditors, AI system users, and regulators. AI auditing provides three types of knowledge contributions to stakeholders: 1) guidance; 2) methods, tools, and frameworks; and 3) awareness and empowerment.
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