at Google ScholarTitle data
Kerstan, Sophie ; Baum, Kevin ; Helfer, Thorsten ; Langer, Markus ; Schmidt, Eva ; Sesing-Wagenpfeil, Andreas ; Speith, Timo:
Responsible and Trusted AI : An Interdisciplinary Perspective (2025).
In: Steffen, Bernhard
(ed.):
Bridging the Gap Between AI and Reality : Selected Papers. -
Cham
: Springer Nature Switzerland
,
2026
. - pp. 141-145
. - (Lecture Notes in Computer Science
; 16220
)
ISBN 978-3-032-07132-3
DOI: https://doi.org/10.1007/978-3-032-07132-3_9
Abstract in another language
As Artificial Intelligence (AI) continues to shape individual lives, institutional processes, and societal structures, ensuring its responsible and trusted development has become a critical imperative. However, meeting this imperative is far from straightforward. AI systems frequently lack transparency and are embedded in environments where the distribution of responsibility and accountability is unclear, normative standards are disputed, and system behavior is unpredictable. The Responsible and Trusted AI track at AISoLA 2025 addresses these and similar challenges by fostering interdisciplinary collaboration across philosophy, law, psychology, economics, sociology, political science, and informatics. This introduction outlines the motivation for the track, emphasizing the sociotechnical embeddedness of AI and the need for approaches that go beyond technical performance to consider questions related to trust and responsibility. It highlights three core themes explored in this year's contributions: democratic legitimation and normative alignment, legal compliance and human oversight, and runtime safety in high-risk contexts. Together, these contributions underscore the importance of interdisciplinary discussions to navigate normative ambiguity, regulatory uncertainty, and behavioral unpredictability in AI systems. The track aims to advance dialogue and collaboration that support the development and deployment of AI systems that are not only effective but are also designed and implemented responsibly and can be trusted.
Further data
| Item Type: | Article in a book |
|---|---|
| Refereed: | No |
| Institutions of the University: | Faculties > Faculty of Cultural Studies > Department of Philosophy Research Institutions > Central research institutes > Research Center for AI in Science and Society |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science 100 Philosophy and psychology > 100 Philosophy |
| Date Deposited: | 22 Dec 2025 11:37 |
| Last Modified: | 22 Dec 2025 11:37 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/95491 |