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Unraveling the Nuances of AI Accountability: A Synthesis of Dimensions Across Disciplines

Nguyen, Long Hoang 1; Lins, Sebastian 1; Renner, Maximilian 1; Sunyaev, Ali 1
1 Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Karlsruher Institut für Technologie (KIT)

Abstract:

The widespread diffusion of Artificial Intelligence (AI)-based systems offers many opportunities to contribute to the well-being of individuals and the advancement of economies and societies. This diffusion is, however, closely accompanied by public scandals causing harm to individuals, markets, or society, and leading to the increasing importance of accountability. AI accountability itself faces conceptual ambiguity, with research scattered across multiple disciplines. To address these issues, we review current research across multiple disciplines and identify key dimensions of accountability in the context of AI. We reveal six themes with 13 corresponding dimensions and additional accountability facilitators that future research can utilize to specify accountability scenarios in the context of AI-based systems.


Preprint §
DOI: 10.5445/IR/1000170105
Veröffentlicht am 19.04.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2024
Sprache Englisch
Identifikator KITopen-ID: 1000170105
Erschienen in ECIS 2024 Research Papers
Veranstaltung 32nd European Conference on Information Systems (ECIS 2024), Paphos, Zypern, 13.06.2024 – 19.06.2024
Verlag AIS eLibrary (AISeL)
Schlagwörter Artificial Intelligence, Accountability, Dimensions, Conceptualization
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