Trustworthy artificial intelligence

By Scott Thiebes, Sebastian Lins, Ali Sunyaev. 2020

311 citations recorded by the source corpus.

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.

Subfields: Computer Networks and Communications, Information Systems, Safety Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Arun Ross
2. Prabu David
3. Hyesun Choung

In Information Systems

1. Arun Ross
2. Prabu David
3. Hyesun Choung

In Safety Research

1. Arun Ross
2. Christoph Kelp
3. Prabu David
4. Hyesun Choung
5. Mona Simion

Citations in the corpus

• Trustworthy artificial intelligence (2023, background): “If, for example, neither physicians nor patients trust an AI-based system’s diagnoses or treatment recommendations, it is unlikely that either of them will follow the recommendations, even if the treatments may increase the patients’ well-being (Thiebes et al., 2021).”
• Trust in AI and Its Role in the Acceptance of AI Technologies (2022, background): “Such concerns, compounded by the erosion of trust in institutions and governments (Edelman, 2021), underscore the importance of building trustworthy AI system to instill confidence among users (Gillath et al., 2021; Thiebes et al., 2020) and to further our understanding of the social and psychologic”