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The imperative of interpretable machines

Nature Machine Intelligence volume 2, pages 197–199 (2020)Cite this article

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As artificial intelligence becomes prevalent in society, a framework is needed to connect interpretability and trust in algorithm-assisted decisions, for a range of stakeholders.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Tandon School of Engineering, New York University, New York, NY, USA

    Julia Stoyanovich

  2. Center for Data Science, New York University, New York, NY, USA

    Julia Stoyanovich

  3. Department of Psychology, College of Arts and Sciences, New York University, New York, NY, USA

    Jay J. Van Bavel & Tessa V. West

  4. Center for Neural Science, New York University, New York, NY, USA

    Jay J. Van Bavel

Authors
  1. Julia Stoyanovich
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  2. Jay J. Van Bavel
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  3. Tessa V. West
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Corresponding authors

Correspondence to Julia Stoyanovich, Jay J. Van Bavel or Tessa V. West.

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The authors declare no competing interests.

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Stoyanovich, J., Van Bavel, J.J. & West, T. The imperative of interpretable machines. Nat Mach Intell 2, 197–199 (2020). https://doi.org/10.1038/s42256-020-0171-8

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