Open Access
| Issue |
SHS Web Conf.
Volume 179, 2023
2023 6th International Conference on Humanities Education and Social Sciences (ICHESS 2023)
|
|
|---|---|---|
| Article Number | 04024 | |
| Number of page(s) | 7 | |
| Section | Community Management and Public Affairs Service | |
| DOI | https://doi.org/10.1051/shsconf/202317904024 | |
| Published online | 14 December 2023 | |
- F. Li, N. Ruijs, and Y. Lu, “Ethics & AI: A systematic review on ethical concerns and related strategies for designing with AI in healthcare,” AI, 4(1), 28–53 (2022). [CrossRef] [Google Scholar]
- A. Jobin, M. Ienca, and E. Vayena, “The global landscape of AI ethics guidelines,” Nature machine intelligence, 1(9), 389–399 (2019). [CrossRef] [Google Scholar]
- B. C. Stahl, J. Antoniou, M. Ryan et al., “Organisational responses to the ethical issues of artificial intelligence,” AI & SOCIETY, 37(1), 23–37 (2022). [CrossRef] [Google Scholar]
- M. K. Kamila, and S. S. Jasrotia, “Ethical issues in the development of artificial intelligence: recognizing the risks,” International Journal of Ethics and Systems, (2023). [Google Scholar]
- L. Gustafson, C. Rolland, N. Ravi et al., “FACET: Fairness in Computer Vision Evaluation Benchmark.” 20370–20382. [Google Scholar]
- B. Pickering, “Trust, but verify: informed consent, AI technologies, and public health emergencies,” Future Internet, 13(5), 132 (2021). [CrossRef] [Google Scholar]
- V. C. Müller, “Ethics of artificial intelligence and robotics,” (2020). [Google Scholar]
- C. Wilson, “Public engagement and AI: A values analysis of national strategies,” Government Information Quarterly, 39(1), 101652 (2022). [CrossRef] [Google Scholar]
- Y. Tian, S. Wang, J. Xiong et al., “Robust and privacypreserving decentralized deep federated learning training: Focusing on digital healthcare applications,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, (2023). [Google Scholar]
- A. Fernandez-Quilez, “Deep learning in radiology: ethics of data and on the value of algorithm transparency, interpretability and explainability,” AI and Ethics, 3(1), 257–265 (2023). [CrossRef] [Google Scholar]
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