Review of Winograd and Flores' Understanding Computers and Cognition: A Favorable Interpretation.

Abstract

Artificial intelligence researchers and cognitive scientists commonly believe that thinking involves manipulating representations. Thinking involves search, inference, and making choices. This is how we model reasoning and what goes on in the brain is similar. Winograd and Flores present a radically different view. They claim that our knowledge is not represented in the brain at all, but rather consists of an unformalized shared background, from which we articulate representations in order to cope with new situations. In contrast, computer programs contain only pre-selected objects and properties, and there is no basis for moving beyond this initial formalization when breakdown occurs. Winograd and Flores provide convincing arguments with examples familiar to most AI researchers. However, they significantly understate the role of representation in mediating intelligent behavior, specifically in the process of reflection, when representations are generated prior to physical action. Furthermore, they do not consider the practical benefits of expert systems and the extent of what can be accomplished. Nevertheless, the book is crisp and stimulating. It should make AI researchers more cautious about what they are doing, more aware of the nature of formalization, and more open to alternative views.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1986
Accession Number
ADA187092

Entities

People

  • William J. Clancey

Organizations

  • Stanford University

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognition
  • Cognitive Science
  • Computer Programs
  • Computer Science
  • Computers
  • Education
  • Expert Systems
  • Military Research
  • Natural Languages
  • Navy
  • New York
  • Psychology
  • Students
  • Thinking
  • Training
  • United States

Readers

  • Educational Psychology
  • Software Engineering.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML