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Artificial Intelligence Hits the Barrier of Meaning

Department of Computer Science, Portland State University, Portland, OR 97207-0751, USA
Santa Fe Institute, Santa Fe, NM 87501, USA
This article is reprinted from Mitchell M. Artificial Intelligence Hits the Barrier of Meaning, New York Times, 5 November 2018.
Information 2019, 10(2), 51;
Received: 20 January 2019 / Revised: 31 January 2019 / Accepted: 2 February 2019 / Published: 5 February 2019
(This article belongs to the Special Issue AI AND THE SINGULARITY: A FALLACY OR A GREAT OPPORTUNITY?)
PDF [175 KB, uploaded 19 February 2019]


Today’s AI systems sorely lack the essence of human intelligence: Understanding the situations we experience, being able to grasp their meaning. The lack of humanlike understanding in machines is underscored by recent studies demonstrating lack of robustness of state-of-the-art deep-learning systems. Deeper networks and larger datasets alone are not likely to unlock AI’s “barrier of meaning”; instead the field will need to embrace its original roots as an interdisciplinary science of intelligence. View Full-Text
Keywords: deep neural networks; meaning; understanding deep neural networks; meaning; understanding
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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