Is human like artificial intelligence a possibility?

This question comes in from an excellent paper in Nature. Surprisingly, it is open access and therefore merits a deeper consideration.

From the 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).

The article summary:

  • 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.
  • This was the birth of artificial intelligence (AI) research.
  • It is possible to pursue this goal without assuming that machine intelligence is identical to human intelligence.
  • For example, one of the pioneers in the field, Marvin Minsky, defined AI as: “… the science of making machines do things that would require intelligence if done by men” (quoted from Bolter, 1986, p.
  • This is sometimes called weak AI.
  • However, many AI researcher have pursued the aim of developing AI that is in principle identical to human intelligence, called strong AI.
  • Because human intelligence is general, human-like AI is therefore often called artificial general intelligence (AGI).
  • Although AGI possesses an essential property of human intelligence, it may still be regarded as weak AI.
  • It is nevertheless different from traditional weak AI, which is restricted to specific tasks or areas.
  • Traditional weak AI is therefore sometimes called artificial narrow intelligence (ANI) (Shane, 2019, p.
  • Although I will sometimes refer to strong AI, the basic distinction in this article is between AGI and ANI.
  • In 1976 Joseph Weizenbaum, at that time professor of informatics at MIT and the creator of the famous program Eliza, published the book Computer Power and Human Reason (Weizenbaum, 1976).
  • Computer power will never develop into human reason, because the two are fundamentlly different.
  • These abilities are not algorithmic, and therefore, computer power cannot—and should not—replace human reason.
  • He got into AI research more or less by accident.
  • Dreyfus therefore thought that computers, who have no body, no childhood and no cultural practice, could not acquire intelligence at all (Dreyfus and Dreyfus, 1986, p.
  • One of the important places for AI research in the 1950s and 1960s was Rand Corporation.
  • However, the leaders of the AI project at Rand argued that the report was nonsense, and should not be published.
  • In the book he argued that an important part of human knowledge is tacit.
  • Although Dreyfus was fiercely attacked by some AI researchers, he no doubt pointed to a serious problem.
  • But during the 1980s another paradigm became dominant in AI research.