AI Ethics Needs Good Data

Angela Daly, S Kate Devitt, Monique Mann

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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Abstract

In this chapter we argue that discourses on AI must transcend the language of 'ethics' and engage with power and political economy in order to constitute 'Good Data'. In particular, we must move beyond the depoliticised language of 'ethics' currently deployed (Wagner 2018) in determining whether AI is 'good' given the limitations of ethics as a frame through which AI issues can be viewed. In order to circumvent these limits, we use instead the language and conceptualisation of 'Good Data', as a more expansive term to elucidate the values, rights and interests at stake when it comes to AI's development and deployment, as well as that of other digital technologies. Good Data considerations move beyond recurring themes of data protection/privacy and the FAT (fairness, transparency and accountability) movement to include explicit political economy critiques of power. Instead of yet more ethics principles (that tend to say the same or similar things anyway), we offer four 'pillars' on which Good Data AI can be built: community, rights, usability and politics. Overall we view AI's 'goodness' as an explicly political (economy) question of power and one which is always related to the degree which AI is created and used to increase the wellbeing of society and especially to increase the power of the most marginalized and disenfranchised. We offer recommendations and remedies towards implementing 'better' approaches towards AI. Our strategies enable a different (but complementary) kind of evaluation of AI as part of the broader socio-technical systems in which AI is built and deployed.
Original languageEnglish
Title of host publicationAI for Everyone?
Subtitle of host publicationCritical Perspectives
EditorsPieter Verdegem
PublisherUniversity of Westminster Press
Chapter7
Pages103-121
Number of pages19
ISBN (Electronic)9781914386145, 9781914386138, 9781914386152
ISBN (Print)9781914386169
DOIs
Publication statusPublished - 20 Sep 2021

Keywords

  • solutionism
  • machine learning
  • social justice
  • good data
  • algorithms
  • AI

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