A Fuzzy Approach to the Specification, Verification and Validation of Risk-Based Ethical Decision Making Models

2025-07-02

AI Summary

Establishing robust evaluation criteria for moral machine decision-making remains challenging due to ontological ambiguity and cognitive complexity inherent in ethical domains. Method: This paper proposes a formal framework for ethical risk–driven decision modeling, introducing fuzzy Petri nets (FPNs) to ethical decision modeling for the first time. By integrating fuzzy logic and fuzzy rule systems, the framework enables formal representation, verification, and validation of uncertain ethical scenarios. Contribution/Results: The approach yields an interpretable, verifiable, risk-aware moral decision model that supports dual validation—qualitative analysis and quantitative risk control. Empirical evaluation on medical ethics cases demonstrates significant improvements in model credibility, robustness, and practical adaptability within real-world fuzzy environments.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Machine Learning: Ethics, Bias, and Fairness
• Reasoning under Uncertainty: Other Foundations of Reasoning under Uncertainty

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

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.

Problem

• Establish standards for evaluating moral machine performance
• Formalize ethical decision models using risk assessment
• Verify and validate fuzzy rule-based models with Petri nets

Innovation

• Fuzzy rules for Ethical Decision Making models
• Fuzzy Petri nets for verification and validation
• Ethical risk assessment formal method