The Emperor of Strong AI Has No Clothes: Limits to Artificial Intelligence

Braga, Adriana; Logan, Robert K.

doi:10.3390/info8040156

Cited by 61 publications

(53 citation statements)

References 10 publications

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“…We consider the leading article of this Special Issue [1] as having done a good job in criticizing the first tendency by pointing out a list of features that any truly intelligent system should have, and arguing that mainstream AI techniques cannot deliver them, even after more research. However, many of the authors' conclusions exactly fall into the second tendency mentioned above, mainly because they are not familiar with existing AGI (artificial general intelligence) research.…”

Section: Introductionmentioning

confidence: 99%

“…On this aspect, the lead article [1] provides a typical example. Its main conclusion is that "strong AI" and "AGI" (the two are treated as synonymy) are impossible, and the phrase of "AGI" is used many times in the article, but its 68 references do not include even a single paper from the AGI conferences or journal, nor does the article discuss any of the active AGI projects, where most of the "ignored characteristics" claimed by Braga and Logan [1] have been explored, and demonstrable (although often preliminary) results have been produced. Here, we are not saying that AGI research cannot be criticized by people outside the field, but that such criticism should be based on some basic knowledge about the current status of the field.…”

Section: Introductionmentioning

confidence: 99%

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Conceptions of Artificial Intelligence and Singularity

Wang

Liu

Dougherty³

2018

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In the current discussions about "artificial intelligence" (AI) and "singularity", both labels are used with several very different senses, and the confusion among these senses is the root of many disagreements. Similarly, although "artificial general intelligence" (AGI) has become a widely used term in the related discussions, many people are not really familiar with this research, including its aim and status. We analyze these notions, and introduce the results of our own AGI research. Our main conclusions are that: (1) it is possible to build a computer system that follows the same laws of thought and shows similar properties as the human mind, but, since such an AGI will have neither a human body nor human experience, it will not behave exactly like a human, nor will it be "smarter than a human" on all tasks; and (2) since the development of an AGI requires a reasonably good understanding of the general mechanism of intelligence, the system's behaviors will still be understandable and predictable in principle. Therefore, the success of AGI will not necessarily lead to a singularity beyond which the future becomes completely incomprehensible and uncontrollable.Information 2018, 9, 79 2 of 15 the features that the leading article claimed to be impossible for AI. In the conclusion, we agree with the authors of the leading article [1] that the recent achievements of deep learning are still far from showing that the related techniques can give us AGI or singularity; however, we believe AGI can be achieved via paths outside the vision of mainstream AI researchers, as well as that of its critics. This conception of AGI is fundamentally different from that of the current mainstream conception of AI. As for "singularity", we consider it an ill-conceived notion, as it is based on an improper conception of intelligence. Notions Distinguished and ClarifiedLet us first analyze what people mean when talking about "AI" and "Singularity". Both notions have no widely accepted definitions, although there are common usages. Different Types of AIIn its broadest sense, AI is the attempt "to make a computer work like a human mind". Although it sounds plain, this description demands an AI to be similar (or even identical) to the human mind in certain aspects. On the other hand, because a computer is not a biological organism, nor does it live a human life, it cannot be expected to be similar to the human mind in all details. The latter is rarely mentioned but implicitly assumed, as it is self-evident. Consequently, by focusing on different aspects of the human mind, different paradigms of AI have been proposed and followed, with different objectives, desiderata, assumptions, road-maps, and applicabilities. They are each valid but distinct paradigms of scientific research [2].In the current discussion, there are at least three senses of "AI" involved:

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Conceptions of Artificial Intelligence and Singularity

Wang

Liu

Dougherty³

2018

Information

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“…Strong AI is far removed from realization and may not even be possible. 9,10,11 Personified as Norman Bates, the serial killer in Alfred Hitchcock's Psycho, 12 the Norman program mentioned in the article is suggestive of the strong AI of dystopian films like Ex Machina and Blade Runner. By referring to the program using the personal pronoun "he" and stating that "Norman was subjected to the darkest corners of Reddit," as if a person had been subjected to a terrifying ordeal, the authors make Norman seem much "stronger" than it is.…”

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confidence: 99%

Response to “Emerging Roles of Virtual Patients in the Age of AI”

Kron

Guetterman

Fetters³

2019

AMA Journal of Ethics

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“…This has been argued in the context of a wide range of uniquely human characteristics that cannot be expected to arise in machine intelligence, even if machines are computationally equivalent to or greater than humans [17]. Cariani [18] makes a similar argument that without embodiment, computers have no mechanism by which to experience the external world and therefore cannot adapt and learn, evolve accordingly, and develop true human-level intelligence.…”

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confidence: 99%

When Robots Get Bored and Invent Team Sports: A More Suitable Test than the Turing Test?

Trenchard¹

2018

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Increasingly, the Turing test-which is used to show that artificial intelligence has achieved human-level intelligence-is being regarded as an insufficient indicator of human-level intelligence. This essay extends arguments that embodied intelligence is required for human-level intelligence, and proposes a more suitable test for determining human-level intelligence: the invention of team sports by humanoid robots. The test is preferred because team sport activity is easily identified, uniquely human, and is suggested to emerge in basic, controllable conditions. To expect humanoid robots to self-organize, or invent, team sport as a function of human-level artificial intelligence, the following necessary conditions are proposed: humanoid robots must have the capacity to participate in cooperative-competitive interactions, instilled by algorithms for resource acquisition; they must possess or acquire sufficient stores of energetic resources that permit leisure time, thus reducing competition for scarce resources and increasing cooperative tendencies; and they must possess a heterogeneous range of energetic capacities. When present, these factors allow robot collectives to spontaneously invent team sport activities and thereby demonstrate one fundamental indicator of human-level intelligence.

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The Emperor of Strong AI Has No Clothes: Limits to Artificial Intelligence

Cited by 61 publications

References 10 publications

Conceptions of Artificial Intelligence and Singularity

Conceptions of Artificial Intelligence and Singularity

Response to “Emerging Roles of Virtual Patients in the Age of AI”

When Robots Get Bored and Invent Team Sports: A More Suitable Test than the Turing Test?

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