We propose the use of the hypothetical retrospection argumentation procedure, developed by Sven 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 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 Hansson发展的假设性回顾论证程序，通过从与人类产生共鸣的哲学立场出发考虑概率与不确定性，来改进现有机器伦理推理方法。行动以带分支的潜在结果集合呈现，每个结果包含状态、效用以及数值或诗意的概率估计。行动的选择基于对支持不同行动层次的论证集进行比较——即使那些导致不良结果的分支也在考量之内。这种论证的使用允许灵活组合多种哲学理论进行伦理推理。我们实现了该程序，将后果论与义务论伦理理论独立且并行地应用于一个自主图书馆系统案例。我们提出一个初步框架，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，且能与人类产生共鸣，从而实现透明度和可解释性。