Data, Algorithms, Machines and People
DOI:
https://doi.org/10.5753/compbr.2022.47.4400Keywords:
Data in AI, Algorithm in AI, Algorithms-Data binomial in AI, Risks in AIAbstract
This paper discusses the risks and benefits of the Algorithms-Data binomial in AI and Robotics. Furthermore, it draws attention to the origin of biases and addictions in AI applications, which may be in the data, the algorithms, or both. Finally, it questions the role of the SBC and its associates in the ethics of AI and suggests three roles that the SBC can play in this context.
Downloads
References
ACM. The 2012 ACM Computing Classification System. [link]
B. Friedman, H. Nissembaum. Ethics in Computer Systems. ACM Transactions on Information Systems, 14(3), 330-347, 1996
J. Stoyanovich, S. Abiteboul, B. Howe, H. V. Jagadish, S. Schelter. Responsible Data Management. Communications of the ACM 65(6), pp 64–74, 2022
A. Marchetti, C. Di Dio, F. Manzi, D. Massaro. Robotics in Clinical and Developmental Psychology. Reference Module in Neuroscience and Biobehavioral Psychology. 2022; doi:10.1016/B978-0-12-818697-8.00005-4.
J. Danaher et al (editors). Robot Sex – Social and Ethical Implications. The MIT Press, 2017
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
