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Why general artificial intelligence will not be realized

Author

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  • Ragnar Fjelland

    (University of Bergen)

Abstract

The modern project of creating human-like artificial intelligence (AI) started after World War II, when it was discovered that electronic computers are not just number-crunching machines, but can also manipulate symbols. It is possible to pursue this goal without assuming that machine intelligence is identical to human intelligence. This is known as weak AI. However, many AI researcher have pursued the aim of developing artificial intelligence that is in principle identical to human intelligence, called strong AI. Weak AI is less ambitious than strong AI, and therefore less controversial. However, there are important controversies related to weak AI as well. This paper focuses on the distinction between artificial general intelligence (AGI) and artificial narrow intelligence (ANI). Although AGI may be classified as weak AI, it is close to strong AI because one chief characteristics of human intelligence is its generality. Although AGI is less ambitious than strong AI, there were critics almost from the very beginning. One of the leading critics was the philosopher Hubert Dreyfus, who argued that computers, who have no body, no childhood and no cultural practice, could not acquire intelligence at all. One of Dreyfus’ main arguments was that human knowledge is partly tacit, and therefore cannot be articulated and incorporated in a computer program. However, today one might argue that new approaches to artificial intelligence research have made his arguments obsolete. Deep learning and Big Data are among the latest approaches, and advocates argue that they will be able to realize AGI. A closer look reveals that although development of artificial intelligence for specific purposes (ANI) has been impressive, we have not come much closer to developing artificial general intelligence (AGI). The article further argues that this is in principle impossible, and it revives Hubert Dreyfus’ argument that computers are not in the world.

Suggested Citation

  • Ragnar Fjelland, 2020. "Why general artificial intelligence will not be realized," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-9, December.
  • Handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-0494-4
    DOI: 10.1057/s41599-020-0494-4
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    Cited by:

    1. Sayed Fayaz Ahmad & Heesup Han & Muhammad Mansoor Alam & Mohd. Khairul Rehmat & Muhammad Irshad & Marcelo Arraño-Muñoz & Antonio Ariza-Montes, 2023. "Impact of artificial intelligence on human loss in decision making, laziness and safety in education," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    2. Gilbert Giacomoni, 2022. "Towards a general framework for innovation shaped with AI to create and transform market offerings [Vers un cadre général d’innovation façonné par l’IA pour créer et transformer les offres du march," Post-Print hal-04083376, HAL.
    3. Luca M. Possati, 2021. "Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-19, December.
    4. Dydrov, Artur (Дыдров, Артур), 2023. "Artificial Intelligence: Mythologies Of Western Scientific Content [Искусственный Интеллект: Мифологемы Западного Научного Контента]," Sotsium i vlast / Society and power, Russian Presidential Academy of National Economy and Public Administration, pages 16-25.

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