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Related Experiment Videos

Decision technology.

W Edwards1, B Fasolo

  • 1Wise Decisions, Inc., Studio City, California, 91604, USA. wedwards@mizar.usc.edu

Annual Review of Psychology
|January 10, 2001
PubMed
Summary
This summary is machine-generated.

Decision technology, including multi-attribute utility and Bayes

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Area of Science:

  • Decision Science
  • Cognitive Psychology
  • Computer Science

Background:

  • Traditional decision technology relies on established rules like multi-attribute utility, Bayes' theorem, and subjective expected utility maximization.
  • These rules guide inference of values and probabilities for improved decision-making.
  • Recent advancements focus on web-based decision-aiding tools for broader accessibility.

Purpose of the Study:

  • To review fundamental principles of decision technology.
  • To explore modern decision-aiding tools, particularly web-based platforms.
  • To discuss challenges and potential of emerging decision technologies.

Main Methods:

  • Review of core decision-making rules (multi-attribute utility, Bayes' theorem, subjective expected utility maximization).

Related Experiment Videos

  • Examination of web-based decision-facilitating sites and their tools.
  • Brief overview of Bayes nets, influence diagrams, and expert probability elicitation.

    • Main Results:

    • A comprehensive 19-step model integrating traditional decision rules is proposed.
    • Web platforms offer sophisticated decision-aiding tools, primarily for consumers.
    • Challenges exist in simplifying complex choices using automated tools.

    Conclusions:

    • Decision technology is evolving, with the web becoming a key distribution channel.
    • Emerging tools like Bayes nets and influence diagrams enhance decision support.
    • Decision tools are poised to be transformative in the 21st century, akin to spreadsheets in the 20th.