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An emerging AI mainstream: deepening our comparisons of AI frameworks through rhetorical analysis

A Correction to this article was published on 22 February 2021

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Abstract

Comparing frameworks for AI development allows us to see trends and reflect on how we are conceptualizing, interacting with, and imagining futures for AI. Recent scholarship comparing a range of AI frameworks has often focused methodologically on consensus, which has led to problems in evaluating potentially ambiguous values. We contribute to this scholarship using a rhetorical perspective attuned to how frameworks shape people’s actions. This perspective allows us to develop the concept of an “AI mainstream” through an analysis of five of the highest-profile frameworks, including Asimov’s Three Laws. We identify four features of this emerging AI mainstream shared by most/all of the frameworks: human-centered design focus, abstraction-oriented ethical reasoning, privileged authorship, and ahistorical regulatory justifications. Notably, each of these features permeates each framework, rather than being limited to a single principle. We then evaluate these shared features and offer scholarly alternatives to complement and improve them.

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Notes

  1. 1.

    BAAI does use the word “principles” but is naming actions that must be taken collectively, not abstract values.

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Acknowledgements

Thanks to Lacey Davidson, Kristopher M. Torres, and Mary Glavan for providing us with helpful feedback. Thanks to the Living with AI Fall 2018 seminar for initial feedback and ideas for the direction of this paper. Thanks to Michael Hemenway for pointing us to recently published comparisons of AI frameworks.

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Correspondence to Epifanio Torres.

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The original online version of this article was revised: The error in the affiliation of the co-author “Will Penman” is corrected.

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Torres, E., Penman, W. An emerging AI mainstream: deepening our comparisons of AI frameworks through rhetorical analysis. AI & Soc 36, 597–608 (2021). https://doi.org/10.1007/s00146-020-01073-0

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Keywords

  • Human-centered
  • Abstraction
  • Authorship
  • History