Formalisation and Evaluation of Properties for Consequentialist Machine Ethics

Raynaldio Limarga; Yang Song; Abhaya Nayak; David Rajaratnam; Maurice Pagnucco

IJCAI 2024poster1 citations

Formalisation and Evaluation of Properties for Consequentialist Machine Ethics

Raynaldio Limarga, Yang Song, Abhaya Nayak, David Rajaratnam, Maurice Pagnucco

Abstract

As artificial intelligence (AI) technologies continue to influence our daily lives, there has been a growing need to ensure that AI enabled decision making systems adhere to principles expected of human decision makers. This need has given rise to the area of Machine Ethics. We formalise several ethical principles from the philosophical literature in the situation calculus framework to verify the ethical permissibility of a plan. Moreover, we propose several important properties, including some of our own that are intuitively appealing, and a number derived from the social choice literature that would appear to be relevant in evaluating the various approaches. Finally we provide an assessment of how our various situation calculus models of Machine Ethics that we examine satisfy the important properties we have identified.

AI Ethics, Trust, Fairness: ETF: Moral decision makingKnowledge Representation and Reasoning: KRR: Reasoning about actionsKnowledge Representation and Reasoning: KRR: Common-sense reasoningKnowledge Representation and Reasoning: KRR: Other

BibTeX

@inproceedings{ijcai2024p49,
  title     = {Formalisation and Evaluation of Properties for Consequentialist Machine Ethics},
  author    = {Limarga, Raynaldio and Song, Yang and Nayak, Abhaya and Rajaratnam, David and Pagnucco, Maurice},
  booktitle = {Proceedings of the Thirty-Third International Joint Conference on
               Artificial Intelligence, {IJCAI-24}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Kate Larson},
  pages     = {440--448},
  year      = {2024},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2024/49},
  url       = {https://doi.org/10.24963/ijcai.2024/49},
}