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Machine behaviour

Author

Listed:
  • Iyad Rahwan

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Max Planck Institute for Human Development)

  • Manuel Cebrian

    (Massachusetts Institute of Technology)

  • Nick Obradovich

    (Massachusetts Institute of Technology)

  • Josh Bongard

    (University of Vermont)

  • Jean-François Bonnefon

    (Université Toulouse Capitole)

  • Cynthia Breazeal

    (Massachusetts Institute of Technology)

  • Jacob W. Crandall

    (Brigham Young University)

  • Nicholas A. Christakis

    (Yale University
    Yale University
    Yale University
    Yale University)

  • Iain D. Couzin

    (Max Planck Institute for Ornithology
    University of Konstanz
    University of Konstanz)

  • Matthew O. Jackson

    (Stanford University
    Canadian Institute for Advanced Research
    The Sante Fe Institute)

  • Nicholas R. Jennings

    (Imperial College London
    Imperial College London)

  • Ece Kamar

    (Microsoft Research)

  • Isabel M. Kloumann

    (Facebook AI, Facebook Inc)

  • Hugo Larochelle

    (Google Brain, Montreal)

  • David Lazer

    (Northeastern University
    Northeastern University
    Harvard University)

  • Richard McElreath

    (Max Planck Institute for Evolutionary Anthropology
    University of California, Davis)

  • Alan Mislove

    (Northeastern University)

  • David C. Parkes

    (Harvard University
    Harvard University)

  • Alex ‘Sandy’ Pentland

    (Massachusetts Institute of Technology)

  • Margaret E. Roberts

    (University of California, San Diego)

  • Azim Shariff

    (University of British Columbia)

  • Joshua B. Tenenbaum

    (Massachusetts Institute of Technology)

  • Michael Wellman

    (University of Michigan)

Abstract

Machines powered by artificial intelligence increasingly mediate our social, cultural, economic and political interactions. Understanding the behaviour of artificial intelligence systems is essential to our ability to control their actions, reap their benefits and minimize their harms. Here we argue that this necessitates a broad scientific research agenda to study machine behaviour that incorporates and expands upon the discipline of computer science and includes insights from across the sciences. We first outline a set of questions that are fundamental to this emerging field and then explore the technical, legal and institutional constraints on the study of machine behaviour.

Suggested Citation

  • Iyad Rahwan & Manuel Cebrian & Nick Obradovich & Josh Bongard & Jean-François Bonnefon & Cynthia Breazeal & Jacob W. Crandall & Nicholas A. Christakis & Iain D. Couzin & Matthew O. Jackson & Nicholas , 2019. "Machine behaviour," Nature, Nature, vol. 568(7753), pages 477-486, April.
    • Handle: RePEc:nat:nature:v:568:y:2019:i:7753:d:10.1038_s41586-019-1138-y
    DOI: 10.1038/s41586-019-1138-y
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    • Iyad Rahwan & Manuel Cebrian & Nick Obradovich & Josh Bongard & Jean-François Bonnefon & Cynthia Breazeal & Jacob W. Crandall & Nicholas Christakis & Iain Couzin & Matthew O. Jackson & Nicholas Jennin, 2019. "Machine behaviour," Post-Print hal-04121682, HAL.

    References listed on IDEAS

    as
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    Cited by:

    1. David Pastor-Escuredo, 2021. "Future of work: ethics," Papers 2104.02580, arXiv.org.
    2. March, Christoph, 2021. "Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer players," Journal of Economic Psychology, Elsevier, vol. 87(C).
    3. David Pastor-Escuredo & Philip Treleaven, 2021. "Multiscale Governance," Papers 2104.02752, arXiv.org.

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