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Trustworthy artificial intelligence

Thiebes, Scott ORCID iD icon 1,2; Lins, Sebastian 1,2; Sunyaev, Ali 1,2
1 Fakultät für Wirtschaftswissenschaften (WIWI), Karlsruher Institut für Technologie (KIT)
2 Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Karlsruher Institut für Technologie (KIT)

Abstract:

Artificial intelligence (AI) brings forth many opportunities to contribute to the wellbeing of individuals and the advancement of economies and societies, but also a variety of novel ethical, legal, social, and technological challenges. Trustworthy AI (TAI) bases on the idea that trust builds the foundation of societies, economies, and sustainable development, and that individuals, organizations, and societies will therefore only ever be able to realize the full potential of AI, if trust can be established in its development, deployment, and use. With this article we aim to introduce the concept of TAI and its five foundational principles (1) beneficence, (2) non-maleficence, (3) autonomy, (4) justice, and (5) explicability. We further draw on these five principles to develop a data-driven research framework for TAI and demonstrate its utility by delineating fruitful avenues for future research, particularly with regard to the distributed ledger technology-based realization of TAI.


Verlagsausgabe §
DOI: 10.5445/IR/1000124221
Veröffentlicht am 06.10.2020
Originalveröffentlichung
DOI: 10.1007/s12525-020-00441-4
Scopus
Zitationen: 190
Dimensions
Zitationen: 236
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 06.2021
Sprache Englisch
Identifikator ISSN: 1019-6781, 1422-8890
KITopen-ID: 1000124221
Erschienen in Electronic markets
Verlag Springer
Band 31
Heft 2
Seiten 447–464
Vorab online veröffentlicht am 01.10.2020
Schlagwörter Trustworthy artificial intelligence, Artificial intelligence, Trust, Framework, Distributed ledger technology, Blockchain
Nachgewiesen in Dimensions
Web of Science
Scopus
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