The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Responsible Artificial Intelligence. Challenges in Research, University, and Society
Abstract
Modern AI is mainly machine learning. And machine learning is dramatically changing our civilization. We rely more and more on efficient algorithms, because otherwise the complexity of our civilizing infrastructure would not be manageable: Our brains are too slow and hopelessly overwhelmed by the amount of data we have to deal with. But how secure are AI algorithms? In a first part, we will consider the current challenges of AI research and, in the second part, ask for a research strategy leading to responsible AI on the background of an AI-roadmap of Standardization of the German Government. Finally, responsible AI is considered as an example of modern cross-over research which will be typical for future universities. The author, as former head of the Carl von Linde Academy and founding director of the Munich Center for Technology in Society (MCTS), reminds the reader of the beginning of this kind of research at the Technical University of Munich and recently at the Eberhard Karls University of Tübingen.
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“In the development and implementation of norms for AI governance, academic institutions responded by establishing centers for the study of AI governance, engaging in basic research, and influencing AI norms through academic expertise and collaborations [8,9].”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [9]
Citations
Cites
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(2019) · Springer Reference Geisteswissenschaften · doi:10.1007/978-3-658-23715-8 · Cited by 44
Artificial intelligence - When do machines take over?
Mainzer, K. (2019) · Technik im Fokus · doi:10.1007/978-3-662-59717-0 · Cited by 27
Self-citationMainzer, K., Schuster, P. M., & Schwichtenberg, H. (2018) · WORLD SCIENTIFIC eBooks · doi:10.1142/11005 · Cited by 4
Self-citation
Research works printed but not linked: 2
- Bourque P; Dupuis R (2004) SWEBOK. Guide to the Software Engineering Body of Knowledge. IEEE Computer Society: Los Alamitos.
- Peters J, Janzing D, Schölkopf B (2017) Elements of Causal Inference. Foundations and Learning Algorithms. The MIT Press, Cambridge MA.
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AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities
Wu, C., Zhang, H., & Carroll, J. M. (2024) · Future Internet · doi:10.3390/fi16100354 · Cited by 99
Oncioiu, I., & Bularca, A. R. (2025) · Societies · doi:10.3390/soc15060144 · Cited by 64
Metadata
- Authors
- Mainzer, K.
- Affiliations
- Technical University of Munich (DE)
- Corresponding author
- Mainzer, Klaus
- ORCID
- Mainzer, Klaus
- Venue
- Wirtschaftsethik in der globalisierten Welt
- Publisher
- J.B. Metzler
- Published
- 2022
- Pages
- 117-127
- ISSN
- 2524-3802 (ISSN-L)
- 2524-3810
- OpenAlex
- W4289209766
- Cited by
- 4
- References
- 6
- Citations by year
- 2025: 2 · 2024: 2
- FWCI
- 3.57
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Wirtschaftsethik in der globalisierten Welt (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Law › Digitalization, Law, and Regulation
- Keywords
- responsible AI, machine learning, AI security, research strategies, standardization, interdisciplinary research, universities, technology and society, AI ethics
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