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Many Ways to Think.

B Tversky1

  • 1Stanford University, Stanford, USA. btversky@stanford.edu.

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Summary
This summary is machine-generated.

Human thought and communication involve embodied actions, gestures, and graphics that convey meaning beyond words. These complex interactions pose challenges for current artificial intelligence (AI) systems aiming for multi-modal understanding.

Keywords:
Cognitive toolsEmbodied cognitionGestureSketchingSpatial thinking

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Area of Science:

  • Cognitive Science
  • Human-Computer Interaction
  • Artificial Intelligence

Background:

  • Thinking, collaboration, and communication integrate body, mind, language, and environmental interactions.
  • Embodied actions like gestures and graphics serve as direct representations of thought, surpassing verbal communication.
  • These interactions are often internal, unique, and difficult to decompose, influencing meaning in real-time.

Purpose of the Study:

  • To explore the intricate relationship between embodied cognition, gestures, graphics, and human thought processes.
  • To highlight the challenges these complex, real-time interactions present for artificial intelligence (AI).

Main Methods:

  • Analysis of embodied actions (gestures) and visual representations (graphics) in expressing and shaping thought.
  • Examination of the unique, internal, and dynamic nature of meaning-making through these modalities.

Main Results:

  • Gestures and graphics can represent complex ideas, environments, and action sequences more directly than words.
  • Engaging with gestures and graphics alters cognitive processes for both creators and viewers.
  • Shared and individual meanings emerge dynamically from real-time interactions with these modalities.

Conclusions:

  • The embodied and multimodal nature of human thought, involving gestures and graphics, is not easily captured by current AI.
  • Future multi-modal AI must better account for the dynamic, internal, and context-dependent aspects of human cognition and communication.