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Information 2019, 10(2), 51; https://doi.org/10.3390/info10020051

Artificial Intelligence Hits the Barrier of Meaning

1
Department of Computer Science, Portland State University, Portland, OR 97207-0751, USA
2
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.
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 [193 KB, uploaded 5 February 2019]

Abstract

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.
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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Mitchell, M. Artificial Intelligence Hits the Barrier of Meaning. Information 2019, 10, 51.

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