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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.01410 |
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| _version_ | 1866913938776522752 |
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| author | Dyoub, Abeer Lisi, Francesca A. |
| author_facet | Dyoub, Abeer Lisi, Francesca A. |
| contents | The ontological and epistemic complexities inherent in the moral domain make it challenging to establish clear standards for evaluating the performance of a moral machine. In this paper, we present a formal method to describe Ethical Decision Making models based on ethical risk assessment. Then, we show how these models that are specified as fuzzy rules can be verified and validated using fuzzy Petri nets. A case study from the medical field is considered to illustrate the proposed approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_01410 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Fuzzy Approach to the Specification, Verification and Validation of Risk-Based Ethical Decision Making Models Dyoub, Abeer Lisi, Francesca A. Artificial Intelligence The ontological and epistemic complexities inherent in the moral domain make it challenging to establish clear standards for evaluating the performance of a moral machine. In this paper, we present a formal method to describe Ethical Decision Making models based on ethical risk assessment. Then, we show how these models that are specified as fuzzy rules can be verified and validated using fuzzy Petri nets. A case study from the medical field is considered to illustrate the proposed approach. |
| title | A Fuzzy Approach to the Specification, Verification and Validation of Risk-Based Ethical Decision Making Models |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2507.01410 |