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The fork in the road.

Robert J Sternberg1

  • 1Department of Human Development,College of Human Ecology,Cornell University,Ithaca,NY 14853.robert.sternberg@cornell.eduwww.robertjsternberg.com.

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Summary
This summary is machine-generated.

Artificial intelligence research should better simulate human cognition by integrating rational and emotional thinking. Current AI models often neglect the complex, emotional aspects of human decision-making, hindering true human-like intelligence.

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Area of Science:

  • Cognitive Science
  • Artificial Intelligence

Background:

  • The field of artificial intelligence (AI) initially explored two distinct approaches to simulating human thought.
  • One path focused on abstract, idealized rational processing.
  • The other path concentrated on emotionally charged, motivationally complex human situations.

Purpose of the Study:

  • To highlight the divergence in AI research paths.
  • To advocate for the integration of rational and emotional aspects in AI development.
  • To emphasize the missed opportunity for AI to more accurately simulate human cognition.

Main Methods:

  • Conceptual analysis of AI research trajectories.
  • Historical review of AI development paradigms.
  • Comparative examination of rational versus emotional processing in AI.

Main Results:

  • AI research historically divided into two main streams: rational and emotional/motivational.
  • These two streams, which represent key aspects of human cognition, failed to converge.
  • A significant gap remains in AI's ability to model the full spectrum of human thought.

Conclusions:

  • AI development has not adequately integrated the simulation of human emotional and motivational complexity.
  • The convergence of rational and emotional AI approaches is crucial for creating more human-like intelligent systems.
  • The continued separation of these approaches represents a limitation in achieving true artificial general intelligence.