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

TL;DR

This paper introduces a formal fuzzy method for specifying, verifying, and validating risk-based ethical decision-making models, demonstrated through a medical case study, to address complexities in moral machine evaluation.

Contribution

It presents a novel fuzzy framework for ethical decision models and their verification using fuzzy Petri nets, enhancing moral machine assessment techniques.

Findings

Effective fuzzy verification of ethical models

Successful application to a medical case study

Improved standards for moral machine evaluation

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.