Machine Ethics and Artificial Moral Agents

  • Francesco CoreaEmail author
Part of the SpringerBriefs in Complexity book series (BRIEFSCOMPLEXITY)


This final chapter concerns issues that are usually not associated with the business performance but that instead have a profound impact on the company’s financial results. Ethics is indeed a strong component in the algorithmic development and should be managed with care. The chapter will discuss the most common ethics problems and data biases and propose some food for thoughts rather than solutions. It will also talk about the control problem, the accounting and explainability issues, and the development of a safe AI.


Machine Ethics Artificial Moral Agents Machine Intelligence Research Institute Stop Killer Robots Famous Trolley Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., & Mané, D. (2016). Concrete problems in AI safety. arXiv:1606.06565v2.
  2. Dietvorst, B. J., Simmons, J. P., & Massey, C. (2015). Algorithm aversion: People erroneously avoid algorithms after seeing them err. Journal of Experimental Psychology, 144(1), 114–126.CrossRefGoogle Scholar
  3. Dietvorst, B. J., Simmons, J. P., & Massey, C. (2016). Overcoming algorithm aversion: People will use imperfect algorithms if they can (even slightly) modify them. Available at SSRN: or

Copyright information

© The Author(s) 2019

Authors and Affiliations

  1. 1.RomeItaly

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