Trustworthy AI
Aus Aifbportal
Beteiligte Personen
- Dr. Michael Färber
- M.Sc. Florian Leiser
- Dr. Sebastian Lins
- M.sc. Maximilian Renner
- M.Sc. Helen Schneider
- M.Sc. Helen Schneider/en
- Prof. Dr. Ali Sunyaev
- Philipp Toussaint
Veröffentlichungen zum Forschungsgebiet
Article
Imrana Abdullahi Yari, Tobias Dehling, Felix Kluge, Juergen Geck, Ali Sunyaev, Bjoern EskofierSecurity Engineering of Patient-Centered Health Care Information Systems in Peer-to-Peer Environments: Systematic Review
Journal of Medical Internet Research, 23, (11), Seiten e24460, November, 2021
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Ali Sunyaev
Vertrauenswürdige Systeme mit künstlicher Intelligenz
Wirtschaftsinformatik & Management, März, 2020
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Konstantin D. Pandl, Scott Thiebes, Manuel Schmidt-Kraepelin, Ali Sunyaev
On the Convergence of Artificial Intelligence and Distributed Ledger Technology: A Scoping Review and Future Research Agenda
IEEE Access, 8, Seiten 57075-57095, März, 2020
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Scott Thiebes, Sebastian Lins, Ali Sunyaev
Trustworthy artificial intelligence
Electronic Markets, Oktober, 2020
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inproceedings
Leopold Müller, Lars Böcking, Michael FärberSafety Aware Reinforcement Learning by Identifying Comprehensible Constraints in Expert Demonstrations
Proceedings of the Workshop on Artificial Intelligence Safety 2022 (SafeAI∂AAAI'22), AAAI
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Michael Färber, Frederic Bartscherer
Media Bias Everywhere? A Vision for Dealing with the Manipulation of Public Opinion
Proceedings of the Second International Workshop on Algorithmic Bias in Search and Recommendation (Bias∂ECIR'21), Springer
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Konstantin D. Pandl, Fabian Feiland, Scott Thiebes, Ali Sunyaev
Trustworthy machine learning for health care: scalable data valuation with the shapley value
Proceedings of the Conference on Health, Inference, and Learning, Seiten: 47–57, Association for Computing Machinery (ACM), April, 2021
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proceedings
Maximilian Renner, Sebastian Lins, Matthias Söllner, Sirkka L. Jarvenpaa, Ali SunyaevArtificial Intelligence-Driven Convergence and its Moderating Effect on Multi-Source Trust Transfer
Hawaii International Conference on System Sciences (HICSS), Januar, 2023
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Maximilian Renner, Sebastian Lins, Matthias Söllner, Scott Thiebes, Ali Sunyaev
Understanding the Necessary Conditions of Multi-Source Trust Transfer in Artificial Intelligence
none, 55th, Januar, 2022
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Maximilian Renner, Sebastian Lins, Matthias Söllner, Scott Thiebes, Ali Sunyaev
Achieving Trustworthy Artificial Intelligence: Multi-Source Trust Transfer in Artificial Intelligence-capable Technology
Association for Information Systems, Austin, TX, USA, Dezember, 2021
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