Identifying AI Corporate Governance Principles That Should Be Prevalent in a Governance Framework for Business

Author:

Husain CoovadiaORCID,Benjamin MarxORCID,Botha IlseORCID

Publisher

Springer Nature Switzerland

Reference51 articles.

1. Abraham, R., Schneider, J., & Vom Brocke, J. (2019). Data governance: A conceptual framework, structured review, and research agenda. International Journal of Information Management, 49(1), 424–438.

2. Banerjee, S., Singh, P. K., & Bajpai, J. (2017). A comparative study on decision-making capability between human and artificial intelligence. In B. K. Panigrahi, M. N. Hoda, V. Sharma, & S. Goel (Eds.), Advances in intelligent systems and computing. Nature inspired computing (pp. 203–210). Springer.

3. Bataller, C., & Harris, J. (2016). Turning artificial intelligence into business value, today. Retrieved from https://www.accenture.com/t20160814T215045w/us-en/canmedia/Accenture/Conversion-Assets/DotCom/Documents/Global/PDF/Technology_11/Accenture-Turning-ArtificialIntelligenceinto-Business-Value.pdf.

4. Beauchamp, T. L. (1995). Principalism and its alleged competitors. Kennedy Institute of Ethics Journal, 5(3), 181–198.

5. Binns, R. (2017). Fairness in machine learning: Lessons from political philosophy. Proceedings of Machine Learning Research, 81, 1–11. Retrieved from SSRN: https://ssrn.com/Abstract=3086546

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