World's Best Scientists 2026 revealed!

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Computer Science

D-Index
51
Citations
21490
World Ranking
5203
National Ranking
2389

Research.com Recognitions

  • 2019 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2015 - Fellow, National Academy of Inventors
  • 1992 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For his influential knowledge analyses of expert systems and pioneering work in grounding AI research in scientific and engineering modeling.

Overview

William J. Clancey is affiliated with the Florida Institute for Human and Machine Cognition in the United States. Their research primarily spans the fields of Computer Science and Social Sciences, with a focus on subfields such as Artificial Intelligence, Safety Research, Experimental and Cognitive Psychology, Computer Science Applications, and Family Practice.

The scientist's main topics of work include Explainable Artificial Intelligence (XAI), Ethics and Social Impacts of AI, Intelligent Tutoring Systems and Adaptive Learning, Online Learning and Analytics, Topic Modeling, Clinical Reasoning and Diagnostic Skills, and Artificial Intelligence in Healthcare and Education.

Notable recent papers include:

  • Methods and standards for research on explainable artificial intelligence: Lessons from intelligent tutoring systems, 2021, Applied AI Letters
  • Psychology and AI at a Crossroads: How Might Complex Systems Explain Themselves?, 2022, The American Journal of Psychology
  • Increasing the Value of XAI for Users: A Psychological Perspective, 2023, KI - Künstliche Intelligenz
  • Explaining AI as an Exploratory Process: The Peircean Abduction Model, 2020, arXiv (Cornell University)
  • Principles of Explanation in Human-AI Systems, 2021, arXiv (Cornell University)

Frequent coauthors throughout their work include Robert R. Hoffman, Shane T. Mueller, Gary Klein, Tim Miller, and Timothy M. Miller.

Their research has been published in venues such as arXiv (Cornell University), Applied AI Letters, The American Journal of Psychology, KI - Künstliche Intelligenz, and AI Magazine.

William J. Clancey has received several awards, including being named a Fellow of the American Association for the Advancement of Science (AAAS) in 2019, a Fellow of the National Academy of Inventors in 2015, and a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 1992 for influential knowledge analyses of expert systems and pioneering work in grounding AI research in scientific and engineering modeling.

Best Publications

  • Rule-Based Expert Systems

    Bruce G. Buchanan;Edward H. Shortliffe;Barclay Adams;John J. Osborn

  • Heuristic classification

    William J Clancey

  • Situated Cognition: On Human Knowledge and Computer Representations

    William J. Clancey

  • The epistemology of a rule-based expert system: a framework for explanation

    William J. Clancey

  • Tutoring rules for guiding a case method dialogue

    William J. Clancey

  • Situated Action: A Neuropsychological Interpretation Response to Vera and Simon

    William J. Clancey

  • Knowledge-based tutoring: the GUIDON program

    William J. Clancey

  • Antimicrobial selection by a computer, A blinded evaluation by infectious diseases experts.

    Yu Vl;Fagan Lm;Wraith Sm;Clancey Wj

  • Readings in medical artificial intelligence: the first decade

    William J. Clancey;Edward H. Shortliffe

  • A Tutorial on Situated Learning

    William J. Clancey

  • NEOMYCIN: reconfiguring a rule-based expert system for application to teaching

    William J. Clancey;Reed Letsinger

  • Brahms: simulating practice for work systems design

    William J. Clancey;Patricia Sachs;Maarten Sierhuis;Ron Van Hoof

  • From Guidon to Neomycin and Heracles in twenty short lessons

    William J Clancey

  • Classification problem solving

    William J. Clancey

  • Model construction operators

    William J. Clancey

  • Knowledge engineering tool

    Lee D. Erman;William John Clancey;Philip E. London;A. Carlisle Scott

  • Qualitative student models

    William J Clancey

  • Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI.

    Shane T. Mueller;Robert R. Hoffman;William J. Clancey;Abagail K. Emery

  • Viewing knowledge bases as qualitative models

    W.J. Clancey

  • Knowledge based tutor

    William J. Clancey

  • Conceptual structures — Information processing in mind and machine J.F. Sowa, systems programming series (Addison-Wesley, Reading, MA, 1984); 481 pages, indices, appendices

    William J. Clancey

Frequent Co-Authors

Bruce G. Buchanan
Bruce G. Buchanan University of Pittsburgh
Edward H. Shortliffe
Edward H. Shortliffe Columbia University
Robert R. Hoffman
Robert R. Hoffman Florida Institute for Human and Machine Cognition
Jeffrey M. Bradshaw
Jeffrey M. Bradshaw Florida Institute for Human and Machine Cognition
Gary Klein
Gary Klein MacroCognition LLC
Christoph Meinel
Christoph Meinel Hasso Plattner Institute
Alessandro Acquisti
Alessandro Acquisti Carnegie Mellon University
Yorick Wilks
Yorick Wilks Florida Institute for Human and Machine Cognition
Bonnie J. Dorr
Bonnie J. Dorr University of Florida
Stanley N. Cohen
Stanley N. Cohen Stanford University

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