AI effect

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The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not "real" intelligence.[1]

Author Pamela McCorduck writes: "It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'."[2] Researcher Rodney Brooks complains: "Every time we figure out a piece of it, it stops being magical; we say, 'Oh, that's just a computation.'"[3]

Definition

"The AI effect" is that line of thinking, the tendency to redefine AI to mean: "AI is anything that has not been done yet." This is the common public misperception, that as soon as AI successfully solves a problem, that solution method is no longer within the domain of AI. Geist credits John McCarthy giving this phenomenon its name, the "AI effect".[4]

McCorduck calls it an "odd paradox" that "practical AI successes, computational programs that actually achieved intelligent behavior, were soon assimilated into whatever application domain they were found to be useful in, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the 'failures', the tough nuts that couldn't yet be cracked."[5] It is an example of moving the goalposts.[6]

Tesler's Theorem is:

"AI is whatever hasn't been done yet."
—Larry Tesler

Douglas Hofstadter quotes this[7] as do many other commentators.[8]

When problems have not yet been formalised, they can still be characterised by a

human-assisted Turing machine.[9]

AI applications become mainstream

Software and algorithms developed by AI researchers are now integrated into many applications throughout the world, without really being called AI. This underappreciation is known from such diverse fields as

agricultural automation[8] and hospitality.[12]

Michael Swaine reports "AI advances are not trumpeted as artificial intelligence so much these days, but are often seen as advances in some other field". "AI has become more important as it has become less conspicuous", Patrick Winston says. "These days, it is hard to find a big system that does not work, in part, because of ideas developed or matured in the AI world."[13]

According to Stottler Henke, "The great practical benefits of AI applications and even the existence of AI in many software products go largely unnoticed by many despite the already widespread use of AI techniques in software. This is the AI effect. Many marketing people don't use the term 'artificial intelligence' even when their company's products rely on some AI techniques. Why not?"[11]

Marvin Minsky writes "This paradox resulted from the fact that whenever an AI research project made a useful new discovery, that product usually quickly spun off to form a new scientific or commercial specialty with its own distinctive name. These changes in name led outsiders to ask, Why do we see so little progress in the central field of artificial intelligence?"[14]

Nick Bostrom observes that "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labelled AI anymore."[15]

The AI effect on decision-making in supply chain risk management is a severely understudied area.[16]

To avoid the AI effect problem, the editors of a special issue of IEEE Software on AI and software engineering recommend not overselling – not hyping – the real achievable results to start with.[17]

The

applications of AI had already found their way into both US and Soviet militaries during the Cold War.[4] AI tools to advise humans regarding weapons deployment were developed by both sides and received very limited usage during that time.[4] They believe this constantly shifting failure to recognise AI continues to undermine human recognition of security threats in the present day.[4]

Some experts think that the AI effect will continue, with advances in AI continually producing objections and redefinitions of public expectations.[18][19][20] Some also believe that the AI effect will expand to include the dismissal of specialised artificial intelligences.[20]

Legacy of the AI winter

Main article: AI winter

In the early 1990s, during the second "AI winter" many AI researchers found that they could get more funding and sell more software if they avoided the bad name of "artificial intelligence" and instead pretended their work has nothing to do with intelligence at all.[citation needed]

Patty Tascarella wrote in 2006: "Some believe the word 'robotics' actually carries a stigma that hurts a company's chances at funding."[21]

Saving a place for humanity at the top of the chain of being

Michael Kearns suggests that "people subconsciously are trying to preserve for themselves some special role in the universe".[22] By discounting artificial intelligence people can continue to feel unique and special. Kearns argues that the change in perception known as the AI effect can be traced to the mystery being removed from the system. In being able to trace the cause of events implies that it's a form of automation rather than intelligence.[citation needed]

A related effect has been noted in the history of

ability to make tools, or passing the mirror test), the overall importance of that capacity is deprecated.[citation needed
]

Herbert A. Simon, when asked about the lack of AI's press coverage at the time, said, "What made AI different was that the very idea of it arouses a real fear and hostility in some human breasts. So you are getting very strong emotional reactions. But that's okay. We'll live with that."[23]

Mueller 1987 proposed comparing AI to human intelligence, coining the standard of Human-Level Machine Intelligence.[24] This nonetheless suffers from the AI effect however when different humans are used as the standard.[24]

Game 6

Deep Blue defeats Kasparov

When IBM's chess-playing computer Deep Blue succeeded in defeating Garry Kasparov in 1997, public perception of chess playing shifted from a difficult mental task to a routine operation.[25]

The public complained that Deep Blue had only used "brute force methods" and it wasn't real intelligence.[10] Notably, John McCarthy, an AI pioneer and founder of the term "artificial intelligence", was disappointed by Deep Blue. He described it as a mere brute force machine that did not have any deep understanding of the game. McCarthy would also criticize how widespread the AI effect is ("As soon as it works, no one calls it AI anymore"[26][27]: 12 ), but in this case did not think that Deep Blue was a good example.[26]

On the other side, Fred A. Reed writes:

"A problem that proponents of AI regularly face is this: When we know how a machine does something 'intelligent,' it ceases to be regarded as intelligent. If I beat the world's chess champion, I'd be regarded as highly bright."[28]

See also

Notes

  1. S2CID 199866730
    .
  2. ^ McCorduck 2004, p. 204
  3. ^ Kahn, Jennifer (March 2002). "It's Alive". Wired. Vol. 10, no. 30. Retrieved 24 Aug 2008.
  4. ^
    S2CID 151967826. Bulletin of the Atomic Scientists
    .
  5. ^ McCorduck 2004, p. 423
  6. S2CID 259041703
    .
  7. ^ As quoted by Hofstadter (1980, p. 601). Larry Tesler actually feels he was misquoted: see his note in the "Adages" section of [1].
  8. ^
    ISBN 9781119823339
    .
  9. ^ Dafna Shahaf and Eyal Amir (2007) Towards a theory of AI completeness. Commonsense 2007, 8th International Symposium on Logical Formalizations of Commonsense Reasoning.
  10. ^ a b McCorduck 2004, p. 433
  11. ^ a b Stottler Henke. "AI Glossary". Archived from the original on 2008-05-09. Retrieved 2009-02-23.
  12. S2CID 242136095
    .
  13. ^ Swaine, Michael (September 5, 2007). "AI - It's OK Again! Is AI on the rise again?". Dr. Dobbs.
  14. ^ Marvin Minsky. "The Age of Intelligent Machines: Thoughts About Artificial Intelligence". Archived from the original on 2009-06-28.
  15. ^ Quoted in "AI set to exceed human brain power". CNN.com. July 26, 2006.
  16. S2CID 237807857
    .
  17. S2CID 220325485
    .
  18. Stanford, CA: Stanford University
    . Retrieved September 6, 2016.
  19. Forbes Magazine
    .
  20. ^
    S2CID 238851395
    .
  21. ^ Patty Tascarella (August 11, 2006). "Robotics firms find fundraising struggle, with venture capital shy". Pittsburgh Business Times.
  22. Philadelphia Inquirer
    . available from Philly.com
  23. ^ Reuben L. Hann. (1998). "A Conversation with Herbert Simon". Gateway. IX (2): 12–13. Archived from the original on February 25, 2015. (Gateway is published by the Crew System Ergonomics Information Analysis Center,
    Wright-Patterson AFB
    )
  24. ^
    S2CID 228718653
    .
  25. Stanford, CA: Stanford University
    . Retrieved September 6, 2016.
  26. ^
    S2CID 21144816
    .
  27. LCCN 2013955152
    .
  28. Washington Times
    .

References

Further reading

External links
A
Wikidata Q58188053
.
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