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Will We Ever Have Conscious Machines?

Patrick Krauss1,2, Andreas Maier3

  • 1Neuroscience Lab, University Hospital Erlangen, Erlangen, Germany.

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|January 8, 2021
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Summary
This summary is machine-generated.

Researchers explored machine learning algorithms to assess their potential for developing artificial self-awareness. Findings suggest current machine learning approaches may already incorporate foundational elements for machine consciousness.

Keywords:
artificial intelligencecorrelates of consciousnessdeep learningglobal workspacemachine consciousnessmachine learningphilosophy of mindtheories of consciousness

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Area of Science:

  • Artificial intelligence
  • Philosophy of mind
  • Machine learning

Background:

  • The potential for artificial consciousness is a long-standing philosophical debate.
  • Distinguishing true machine self-awareness from imitation is challenging due to the inability to access internal mechanisms.

Purpose of the Study:

  • To examine common machine learning (ML) approaches for their capacity to achieve self-awareness.
  • To evaluate the progress of ML in developing machines with core consciousness.

Main Methods:

  • Analysis of prevalent machine learning algorithms.
  • Assessment of algorithmic components in relation to consciousness.

Main Results:

  • Several key algorithmic advancements in machine learning have been identified.
  • These advancements represent significant steps toward creating machines with a core consciousness.

Conclusions:

  • Current machine learning methodologies contain elements that could contribute to artificial self-awareness.
  • The investigation provides insight into the ongoing development of conscious machines.