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Meticulous Transparency—An Evaluation Process for an Agile AI Regulatory Scheme

  • David Benrimoh
  • Sonia Israel
  • Kelly Perlman
  • Robert Fratila
  • Matthew Krause
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10868)

Abstract

Artificial intelligence (AI) poses both great potential and risk, as a rapidly developing and generally applicable technology. To ensure the ethical development and responsible use of AI, we outline a new ethical evaluation framework for usage by future regulators: Meticulous Transparency (MT). MT allows regulators to keep pace with technological progress by evaluating AI applications for their capabilities and the intentionality of developers, rather than evaluating conformity to static regulations or ethical codes of the underlying technologies themselves. MT shifts the focus of ethical evaluation from the technology itself to instead why it is being built, and potential consequences. MT assessment is reminiscent of a Research Ethics Board submission in medical research, with required explanation depending on the potential impact of the AI system. We propose the use of MT to transform AI-specific ethical quandaries into more familiar ethical questions, which society must then address.

Keywords

Assessment framework AI ethics Intentionality Meticulous transparency 

Notes

Acknowledgments

We are grateful to Dr. Wendell Wallach (Yale University) and to Dr. Jason Behrmann (aifred health), whose comments improved this article.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • David Benrimoh
    • 1
    • 2
  • Sonia Israel
    • 1
    • 2
    • 3
  • Kelly Perlman
    • 1
    • 2
    • 4
  • Robert Fratila
    • 1
    • 2
    • 4
  • Matthew Krause
    • 1
    • 2
    • 4
  1. 1.McGill UniversityMontrealCanada
  2. 2.aifred healthMontrealCanada
  3. 3.Douglas Mental Health University InstituteMontrealCanada
  4. 4.Montreal Neurological InstituteMontrealCanada

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