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Good Old-Fashioned Artificial Consciousness and the Intermediate Level Fallacy.

Riccardo Manzotti1, Antonio Chella2,3

  • 1Department of Business, Law, Economics and Consumer Behavior, Università di Comunicazione e Lingue (IULM), Milan, Italy.

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Researchers explore robot consciousness, identifying a key flaw in current artificial consciousness models. An alternative framework is proposed for developing conscious robots and advancing AI.

Keywords:
artificial consciousnessmachine consciousnessrobot consciousnessrobot self-awarenesssynthetic phenomenology

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Area of Science:

  • Artificial Intelligence
  • Robotics
  • Cognitive Science

Background:

  • Growing interest in creating conscious robots with subjective experiences.
  • Current approaches, termed Good Old-Fashioned Artificial Consciousness (GOFAC), share a common conceptual framework.
  • GOFAC encompasses theories like global workspace, information integration, enaction, cognitive mechanisms, and embodiment.

Purpose of the Study:

  • To critically examine the fundamental principles of GOFAC.
  • To analyze the implications of GOFAC for Artificial Intelligence (AI) and Robotics.
  • To identify and discuss the central issue within the GOFAC framework.

Main Methods:

  • Conceptual analysis of existing artificial consciousness theories.
  • Identification of the core tenets of the Good Old-Fashioned Artificial Consciousness (GOFAC) framework.
  • Critique of GOFAC, focusing on a specific identified fallacy.

Main Results:

  • The study identifies the 'intermediate level fallacy' as a central problem hindering GOFAC.
  • GOFAC's basic tenets and their limitations for achieving robot consciousness are discussed.
  • The limitations of current GOFAC approaches for AI and robotics are highlighted.

Conclusions:

  • The 'intermediate level fallacy' presents a significant obstacle for current artificial consciousness models.
  • A new conceptual framework is needed to advance the development of robot consciousness.
  • This research suggests a path toward more effective AI and robotics development for conscious machines.