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Who is the fairest of them all? Public attitudes and expectations regarding automated decision-making
Computer Law & Security Review ( IF 2.707 ) Pub Date : 2020-09-08 , DOI: 10.1016/j.clsr.2020.105456
Natali Helberger , Theo Araujo , Claes H. de Vreese

The ongoing substitution of human decision makers by automated decision-making (ADM) systems in a whole range of areas raises the question of whether and, if so, under which conditions ADM is acceptable and fair. So far, this debate has been primarily led by academics, civil society, technology developers and members of the expert groups tasked to develop ethical guidelines for ADM. Ultimately, however, ADM affects citizens, who will live with, act upon and ultimately have to accept the authority of ADM systems.

The paper aims to contribute to this larger debate by providing deeper insights into the question of whether, and if so, why and under which conditions, citizens are inclined to accept ADM as fair. The results of a survey (N = 958) with a representative sample of the Dutch adult population, show that most respondents assume that AI-driven ADM systems are fairer than human decision-makers.

A more nuanced view emerges from an analysis of the responses, with emotions, expectations about AI being data- and calculation-driven, as well as the role of the programmer – among other dimensions – being cited as reasons for (un)fairness by AI or humans. Individual characteristics such as age and education level influenced not only perceptions about AI fairness, but also the reasons provided for such perceptions. The paper concludes with a normative assessment of the findings and suggestions for the future debate and research.



中文翻译:

谁是最公平的?公众对自动化决策的态度和期望

在整个领域中,不断被自动化决策(ADM)系统取代人类决策者的问题提出了一个问题,即是否以及如果可以,在什么条件下ADM是可接受和公平的。到目前为止,这场辩论主要由学者,民间社会,技术开发人员和负责制定ADM道德准则的专家组成员主持。但是,最终,ADM会影响与ADM系统一起生活,采取行动并最终必须接受ADM系统权威的公民。

本文旨在通过提供更深入的见解为公民是否倾向于接受ADM是否公平这一问题提供更深入的见解,从而为这一更大的辩论做出贡献。一项 具有荷兰成年人口代表性样本的调查(N = 958)的结果表明,大多数受访者认为AI驱动的ADM系统比人类决策者更公平。

通过对响应的分析,情感,对AI的期望是数据和计算驱动的,以及程序员的角色(其中包括其他方面)被AI引用为(不)公平的原因,可以得出更为细微的看法。或人类。诸如年龄和受教育程度之类的个人特征不仅影响对AI公平的看法,而且影响这种看法的原因。本文最后对未来的辩论和研究的发现和建议进行了规范性评估。

更新日期:2020-09-09
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