Digital ethicswashing: a systematic review and a process-perception-outcome framework

Mario D. Schultz, Ludovico Giacomo Conti, Peter Seele
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Abstract

The term “ethicswashing” was recently coined to describe the phenomenon of instrumentalising ethics by misleading communication, creating the impression of ethical Artificial Intelligence (AI), while no substantive ethical theory, argument, or application is in place or ethicists involved. Ethicswashing resembles greenwashing for environmental issues and has become an issue – particularly since 2019 with Thomas Metzinger’s harsh criticisms as a member of the EU panel for developing ethical guidelines for AI, which he called “ethicswashing.” Nowadays, increased ethics washing has changed the perception of AI ethics, leading critics to find a “trivialization” of ethics that may even lead to “ethics bashing.” Considering the scattered literature body and the various manifestations of digital ethicswashing, we recognise the need to assess the existing literature comprehensively. To fill this gap, this research systematically reviews current knowledge about digital ethicswashing stemming from various academic disciplines, contributing to an up-to-date assessment of its underlying characteristics. Applying content analysis to map the field leads us to present five thematic clusters: ethicswashing, ethics bashing, policymaking and regulation, watchdogs, and academia. In conclusion, we synthesise ethicswashing along a process-perception-outcome framework to provide future research to explore the multiple meanings of digital ethicswashing.

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数字伦理清洗:系统回顾与过程-感知-结果框架
“伦理清洗”一词最近被创造出来,用来描述通过误导沟通将伦理工具化的现象,造成道德人工智能(AI)的印象,而没有实质性的伦理理论、论点或应用到位,也没有涉及伦理学家。“洗白”类似于环境问题上的“洗绿”,并已成为一个问题——尤其是自2019年以来,托马斯·梅辛格(Thomas Metzinger)作为欧盟制定人工智能伦理准则小组的成员,提出了严厉的批评,他称之为“洗白”。如今,越来越多的伦理清洗改变了人们对人工智能伦理的看法,导致批评人士发现伦理“庸俗化”,甚至可能导致“伦理抨击”。考虑到文献的分散和数字伦理冲击的各种表现形式,我们认识到有必要对现有文献进行综合评估。为了填补这一空白,本研究系统地回顾了来自不同学科的关于数字伦理清洗的当前知识,有助于对其潜在特征进行最新评估。通过内容分析来绘制这一领域的地图,我们提出了五个主题集群:道德冲击、道德抨击、政策制定和监管、监管机构和学术界。总之,我们沿着过程-感知-结果的框架综合了伦理清洗,为未来的研究提供了探索数字伦理清洗的多重意义。
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