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Is a Machine Realization of Truly Human-Like Intelligence Achievable?

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Abstract

Even after more than a half a century of research on machine intelligence, humans remain far better than our strongest computing machines at a wide range of natural cognitive tasks, such as object recognition, language comprehension, and planning and acting in contextually appropriate ways. While progress is being made in many of these areas, computers still lack the fluidity, adaptability, open-endedness, creativity, purposefulness, and insightfulness we associate with the supreme achievements of human cognitive ability. Reasons for this and prospects for overcoming these limitations are discussed.

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Notes

  1. I have heard this story somewhere, but cannot be sure of the source. Perhaps it was in a seminar at MIT in fall of 1982, taught by Jerry Fodor. He certainly would have supported the point that human thought is unlimited in the kind of information it can exploit in reasoning and problem solving.

  2. Only a sub-set of synapses are active during any given millisecond. On the other hand I am leaving out all of the post-synaptic integration, synaptic change, and modulatory influences, not to speak at all of the homeostatic processes continually at play, and so I will stick with the 1018 figure as a useful approximation.

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  1. Department of Psychology, Stanford University, Bldg 420, 450 Serra Mall, Stanford, CA, 94305, USA

    James L. McClelland

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  1. James L. McClelland
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Correspondence to James L. McClelland.

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McClelland, J.L. Is a Machine Realization of Truly Human-Like Intelligence Achievable?. Cogn Comput 1, 17–21 (2009). https://doi.org/10.1007/s12559-009-9015-x

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