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How We’re Predicting AI – or Failing to

  • Chapter
Beyond Artificial Intelligence

Part of the book series: Topics in Intelligent Engineering and Informatics ((TIEI,volume 9))

Abstract

This paper will look at the various predictions that have been made about AI and propose decomposition schemas for analysing them. It will propose a variety of theoretical tools for analysing, judging and improving these predictions. Focusing specifically on timeline predictions (dates given by which we should expect the creation of AI), it will show that there are strong theoretical grounds to expect predictions to be quite poor in this area. Using a database of 95 AI timeline predictions, it will show that these expectations are born out in practice: expert predictions contradict each other considerably, and are indistinguishable from non-expert predictions and past failed predictions. Predictions that AI lie 15 to 25 years in the future are the most common, from experts and non-experts alike.

The authors wish to acknowledge the help and support of the Singularity Institute, the Future of Humanity Institute and the James Martin School, as well as the individual advice of Nick Bostrom, Luke Muelhauser, Vincent Mueller, Anders Sandberg, Lisa Makros, Sean O’Heigeartaigh, Daniel Dewey, Eric Drexler and the online community of Less Wrong.

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Author information

Authors and Affiliations

  1. The Future of Humanity Institute, Faculty of Philosophy, University of Oxford, Oxford, UK

    Stuart Armstrong

  2. The Singularity Institute, Berkeley, CA, USA

    Kaj Sotala

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  1. Stuart Armstrong
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  2. Kaj Sotala
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Corresponding author

Correspondence to Stuart Armstrong .

Editor information

Editors and Affiliations

  1. New Technologies Research Centre & Department of Cybernetics, University of West Bohemia, Plzen, Czech Republic

    Jan Romportl

  2. New Technologies Research Centre, University of West Bohemia, Plzen, Czech Republic

    Eva Zackova

  3. Institute of Computer Science, Silesian University, Opava, Czech Republic

    Jozef Kelemen

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Armstrong, S., Sotala, K. (2015). How We’re Predicting AI – or Failing to. In: Romportl, J., Zackova, E., Kelemen, J. (eds) Beyond Artificial Intelligence. Topics in Intelligent Engineering and Informatics, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-319-09668-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-09668-1_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09667-4

  • Online ISBN: 978-3-319-09668-1

  • eBook Packages: EngineeringEngineering (R0)

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