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The errors, insights and lessons of famous AI predictions – and what they mean for the future

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  • Additional Information
    • Contributors:
      The Pennsylvania State University CiteSeerX Archives
    • Publication Date:
      2014
    • Collection:
      CiteSeerX
    • Abstract:
      Predicting the development of artificial intelligence (AI) is a difficult project – but a vital one, according to some analysts. AI predictions already abound: but are they reliable? This paper will start by proposing a decomposition schema for classifying them. Then it constructs a variety of theoretical tools for analysing, judging and improving them. These tools are demonstrated by careful analysis of five famous AI predictions: the
    • File Description:
      application/pdf
    • Relation:
      http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.433.2976
    • Online Access:
      http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.433.2976
      http://www.fhi.ox.ac.uk/wp-content/uploads/FAIC.pdf
    • Rights:
      Metadata may be used without restrictions as long as the oai identifier remains attached to it.
    • Accession Number:
      edsbas.9F884ED9