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AI Ethics, Ethics Washing, and the Need to Politicize Data Ethics.

Gijs van Maanen
Published in: Digital society : ethics, socio-legal and governance of digital technology (2022)
Many commercial actors in the tech sector publish ethics guidelines as a means to 'wash away' concerns raised about their policies. For some academics, this phenomenon is reason to replace ethics with other tools and methods in an attempt to make sure that the tech sector does not cross any moral Rubicons. Others warn against the tendency to reduce a criticism of 'ethics washing' into one of ethics simpliciter. In this essay, I argue firstly that the dominant focus on principles, dilemmas, and theory in conventional ethical theories and practices could be an explanation of it lacking resistance to abuse by dominant actors, and hence its rather disappointing capacity to stop, redirect, or at least slow down big tech's course. Secondly, drawing from research on casuistry and political philosopher Raymond Geuss, this essay will make a case for a question, rather than theory or principle-based ethical data practice. The emphasis of this approach is placed on the acquisition of a thorough understanding of a social-political phenomenon like tech development. This approach should be replenished with one extra component to the picture of the repoliticized data ethics drawn so far: the importance of 'exemplars,' or stories. Precisely the fact that one should acquire an in-depth understanding of the problem in practice will also allow one to look in the past, present, or future for similar and comparable stories from which one can learn.
Keyphrases
  • big data
  • public health
  • artificial intelligence
  • machine learning
  • healthcare
  • global health
  • primary care
  • electronic health record
  • mental health
  • deep learning