We propose the use of the hypothetical retrospection argumentation procedure, developed by Sven Ove Hansson to improve existing approaches to machine ethical reasoning by accounting for probability and uncertainty from a position of Philosophy that resonates with humans. Actions are represented with a branching set of potential outcomes, each with a state, utility, and either a numeric or poetic probability estimate. Actions are chosen based on comparisons between sets of arguments favouring actions from the perspective of their branches, even those branches that led to an undesirable outcome. This use of arguments allows a variety of philosophical theories for ethical reasoning to be used, potentially in flexible combination with each other. We implement the procedure, applying consequentialist and deontological ethical theories, independently and concurrently, to an autonomous library system use case. We introduce a preliminary framework that seems to meet the varied requirements of a machine ethics system: versatility under multiple theories and a resonance with humans that enables transparency and explainability.

翻译：我们提出采用Sven Ove Hansson提出的假设性回溯论证程序，从与人类共鸣的哲学视角出发，通过考虑概率和不确定性来改进现有机器伦理推理方法。行为通过一组分支式潜在结果进行表征，每个结果包含状态、效用，以及数值型或诗意的概率估计。行为选择基于比较从各分支（包括那些导向非预期结果的分支）视角支持不同行为的论证集合。这种论证应用方式允许采用多种哲学理论进行伦理推理，并可能实现理论间的灵活组合。我们实现了该程序，将结果主义和道义论伦理理论分别且并行地应用于一个自主图书馆系统用例。我们引入了一个初步框架，该框架似乎满足机器伦理系统的多重需求：在多种理论下具有通用性，以及与人类产生共鸣从而实现透明性和可解释性。