• DocumentCode
    1521337
  • Title

    Building intelligent systems one e-citizen at a time

  • Author

    Hearst, M.A. ; Stork, David G.

  • Author_Institution
    California Univ. Berkeley, LA, USA
  • Volume
    14
  • Issue
    3
  • fYear
    1999
  • Firstpage
    16
  • Lastpage
    20
  • Abstract
    The article comprises two sections. In the first, the author suggests that speculative markets are a neglected way to help Us find out what people know. Such markets pool the information that is known to diverse individuals into a common resource, and have many advantages over standard institutions for information aggregation, such as news media, peer review, trials, and opinion polls. Speculative markets are decentralized and relatively egalitarian, and can offer direct, concise, timely, and precise estimates in answer to questions we pose. In the second section, the author argues that now is the time for computer science and cognitive science to have their big science-one that harvests informal knowledge from a large number of e-citizens for building useful software for next generation systems. Given the conjunction of several forces-the need for natural human-machine interfaces and improved Web searching, the existence of good learning algorithms and Web infrastructure, and the demonstrated success of the Open Source methodology-the time is right for the Open Mind Initiative
  • Keywords
    Internet; information retrieval; knowledge based systems; technological forecasting; Open Mind Initiative; Open Source methodology; Web infrastructure; Web searching; cognitive science; common resource; computer science; e-citizen; informal knowledge; information aggregation; intelligent systems; learning algorithms; natural human-machine interfaces; next generation systems; precise estimates; speculative markets; Guns; Humans; Intelligent structures; Intelligent systems; State estimation;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems and their Applications, IEEE
  • Publisher
    ieee
  • ISSN
    1094-7167
  • Type

    jour

  • DOI
    10.1109/5254.769877
  • Filename
    769877