Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept
Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept
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DOI：
10.1080/15265161.2022.2040647
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发表时间：
2022-03-15
影响因子：
13.4
通讯作者：
Buyx, Alena
中科院分区：
文献类型：
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作者：
Meier, Lukas J.;Hein, Alice;Buyx, Alena
机器智能已经帮助医务人员完成了许多任务。然而，道德决策并没有交给计算机。在这项概念验证研究中，我们展示了如何使用基于比彻姆和奇尔德里斯的表面原则的算法来对医疗机构中发生的一系列道德困境情况提供建议。我们解释了为什么选择模糊认知图来建立咨询系统，以及我们如何利用机器学习来训练它。我们报告了实施仁慈、不伤害和患者自主原则的困难任务，并描述了我们如何从临床病例的训练数据集中选择合适的输入参数。最初的性能结果是有希望的，但伦理的算法方法也伴随着几个弱点和限制。人们真的应该把临床伦理这一敏感领域委托给机器智能吗？
Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress' prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the difficult task of operationalizing the principles of beneficence, non-maleficence and patient autonomy, and describe how we selected suitable input parameters that we extracted from a training dataset of clinical cases. The first performance results are promising, but an algorithmic approach to ethics also comes with several weaknesses and limitations. Should one really entrust the sensitive domain of clinical ethics to machine intelligence?