{"slug": "ai-effect", "title": "AI Effect", "summary": "The AI effect describes how advances in artificial intelligence lead to a redefinition of intelligence, with successful AI systems reclassified as routine computation. Historian Pamela McCorduck noted in her 2004 book 'Machines Who Think' that once a problem is solved, it is no longer considered evidence of intelligence, and researcher Rodney Brooks observed in 2002 that understood systems are often regarded as 'just computation'. The phenomenon is exemplified by IBM's Deep Blue defeating Garry Kasparov in 1997, which critics attributed to brute-force methods rather than genuine understanding.", "body_md": "# AI effect\n\n| Part of\n|\n\n[Artificial intelligence (AI)](https://en.wikipedia.org/wiki/Artificial_intelligence)\n\n[Glossary](https://en.wikipedia.org/wiki/Glossary_of_artificial_intelligence)The **AI effect** is a phenomenon in which advances in [artificial intelligence](https://en.wikipedia.org/wiki/Artificial_intelligence) lead to a redefinition of what is considered intelligence, such that capabilities achieved by AI systems are no longer regarded as examples of \"real\" intelligence.[[1]](#cite_note-haenlein-1)\n\nThe concept has been used to describe both a cognitive tendency and a sociotechnical pattern, in which successful AI techniques are reclassified as routine computation or absorbed into other domains.[[2]](#cite_note-henke-2)\n\nHistorian [Pamela McCorduck](https://en.wikipedia.org/wiki/Pamela_McCorduck) described this as a recurring feature of AI research, noting in her 2004 book *Machines Who Think* that once a problem is solved, it is no longer considered evidence of intelligence. [3] Researcher\n\n[Rodney Brooks](https://en.wikipedia.org/wiki/Rodney_Brooks)similarly observed in 2002 that once systems are understood, they are often regarded as \"just computation\".\n\n[[4]](#cite_note-4)## Definition\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=1)]\n\nThe AI effect refers to a shift in how intelligence is defined as machines acquire new capabilities. Tasks such as playing chess, [recognizing speech](https://en.wikipedia.org/wiki/Speech_recognition), or interpreting images were historically considered indicators of intelligence, but after successful automation they are often reclassified as routine computation.[[1]](#cite_note-haenlein-1)\n\nMcCorduck described this as an \"odd paradox\", in which successful AI systems are assimilated into other domains, leaving AI researchers to focus on unsolved problems. [5] The phenomenon is often interpreted as an instance of\n\n[moving the goalposts](https://en.wikipedia.org/wiki/Moving_the_goalposts).\n\n[[6]](#cite_note-nadin-6)A commonly cited formulation is **Tesler's theorem**, often expressed as \"AI is whatever hasn't been done yet\".[[7]](#cite_note-7)\n\nWhen problems are not fully formalised, they may be described using models involving [human computation](https://en.wikipedia.org/wiki/Human_computation), such as human-assisted [Turing machines](https://en.wikipedia.org/wiki/Turing_machine).[[8]](#cite_note-8)\n\n## Historical examples\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=2)]\n\n### Game playing\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=3)]\n\nEarly AI systems capable of playing games such as checkers and chess were initially regarded as demonstrations of machine intelligence. As these systems improved and became better understood, their achievements were often reinterpreted as examples of computation rather than intelligence.[[9]](#cite_note-mcc3-9)\n\nThe victory of IBM's [Deep Blue](https://en.wikipedia.org/wiki/Deep_Blue_(chess_computer)) over [Garry Kasparov](https://en.wikipedia.org/wiki/Garry_Kasparov) in 1997 is a frequently cited example. Critics argued that the system relied on brute-force methods rather than genuine understanding.[[9]](#cite_note-mcc3-9)\n\n### Pattern recognition\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=4)]\n\nTechnologies such as [optical character recognition](https://en.wikipedia.org/wiki/Optical_character_recognition) and [speech recognition](https://en.wikipedia.org/wiki/Speech_recognition) were once considered core problems in artificial intelligence. As these systems became reliable and widely deployed, they were increasingly treated as standard engineering solutions.[[1]](#cite_note-haenlein-1)\n\n### Integration into applications\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=5)]\n\nMany techniques originally developed within AI research have been incorporated into broader technological systems, including marketing, automation, and software applications.[[2]](#cite_note-henke-2)\n\n[Michael Swaine](https://en.wikipedia.org/wiki/Michael_Swaine_(technical_author)) reported in 2007 that AI advances are often presented as developments in other fields.[[10]](#cite_note-10)\n\n[Marvin Minsky](https://en.wikipedia.org/wiki/Marvin_Minsky) observed that successful AI innovations often evolve into separate disciplines.[[11]](#cite_note-11)\n\n[Nick Bostrom](https://en.wikipedia.org/wiki/Nick_Bostrom) noted in 2006 that widely adopted technologies are often no longer labeled as AI.[[12]](#cite_note-12)\n\n## Contemporary discussion\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=6)]\n\nThe AI effect continues to be discussed in the context of recent advances in [machine learning](https://en.wikipedia.org/wiki/Machine_learning), particularly [large language models](https://en.wikipedia.org/wiki/Large_language_models) and other [generative AI](https://en.wikipedia.org/wiki/Generative_AI) systems. As these systems have become more widely used, some researchers and commentators have noted that their capabilities are frequently described as statistical or mechanical once understood, rather than as intelligence. [13] For instance, different combinations of human and AI action in workflows can be considered \"augmented intelligence\" and specific weights within various combinations of augmentation should be used to define ethical and practical considerations contextually for those workflows.\n\n[[14]](#cite_note-14)A 2016 survey of artificial intelligence also noted that AI systems are increasingly embedded in everyday applications, reinforcing earlier observations that successful AI technologies tend to become normalized and no longer identified as AI.[[15]](#cite_note-15)\n\nAt the same time, the widespread commercial use of artificial intelligence has led to greater visibility of the field, contrasting with earlier periods in which AI techniques were often present but unacknowledged.[[1]](#cite_note-haenlein-1)\n\n## Interpretations\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=7)]\n\n### Cognitive bias\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=8)]\n\nSome authors describe the AI effect as a cognitive bias in which expectations of intelligence shift as machines achieve new capabilities.[[2]](#cite_note-henke-2)\n\n### Sociotechnical perspective\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=9)]\n\nAnother interpretation emphasizes how technologies are reclassified over time as they become widespread and commercially successful.[[1]](#cite_note-haenlein-1)\n\n### Philosophical debate\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=10)]\n\nSome philosophers argue that reclassification reflects genuine conceptual distinctions rather than bias.[[6]](#cite_note-nadin-6)\n\n## Historical context\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=11)]\n\nDuring periods such as the [AI winter](https://en.wikipedia.org/wiki/AI_winter), researchers sometimes avoided the term \"artificial intelligence\" due to negative perceptions.[[1]](#cite_note-haenlein-1)\n\nIn the 21st century, however, the term \"AI\" has become widely used in public discourse and marketing.[[1]](#cite_note-haenlein-1)\n\n## Broader implications\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=12)]\n\nThe AI effect has been linked to broader questions about human uniqueness and the nature of intelligence. [Michael Kearns](https://en.wikipedia.org/wiki/Michael_Kearns_(computer_scientist)) suggested that people may seek to preserve a special role for humans.[[16]](#cite_note-16)\n\nSimilar patterns have been observed in studies of [animal cognition](https://en.wikipedia.org/wiki/Animal_cognition).\n\n[Herbert A. Simon](https://en.wikipedia.org/wiki/Herbert_A._Simon) noted that artificial intelligence can provoke strong emotional reactions.[[17]](#cite_note-17)\n\n## See also\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=13)]\n\n## References\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=14)]\n\n[1](#cite_ref-haenlein_1-0)[2](#cite_ref-haenlein_1-1)[3](#cite_ref-haenlein_1-2)[4](#cite_ref-haenlein_1-3)[5](#cite_ref-haenlein_1-4)[6](#cite_ref-haenlein_1-5)[7](#cite_ref-haenlein_1-6)Haenlein, Michael; Kaplan, Andreas (2019). \"A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence\".*California Management Review*.**61**(4): 5–14.[doi](https://en.wikipedia.org/wiki/Doi_(identifier)):[10.1177/0008125619864925](https://doi.org/10.1177%2F0008125619864925).[1](#cite_ref-henke_2-0)[2](#cite_ref-henke_2-1)[3](#cite_ref-henke_2-2)[\"AI Glossary\"](https://web.archive.org/web/20080509132655/http://www.stottlerhenke.com/ai_general/glossary.htm). Stottler Henke Associates. Archived from[the original](http://www.stottlerhenke.com/ai_general/glossary.htm)on 2008-05-09. Retrieved 20 March 2026.[↑](#cite_ref-mcc1_3-0)McCorduck, Pamela (2004).*Machines Who Think*(2nd ed.). A. K. Peters. p. 204.[↑](#cite_ref-4)Kahn, Jennifer (March 2002).[\"It's Alive\"](https://www.wired.com/2002/03/everywhere/).*Wired*. Retrieved 20 March 2026.[↑](#cite_ref-mcc2_5-0)McCorduck, Pamela (2004).*Machines Who Think*(2nd ed.). A. K. Peters. p. 423.[1](#cite_ref-nadin_6-0)[2](#cite_ref-nadin_6-1)Nadin, Mihai (2023). \"Intelligence at any price? A criterion for defining AI\".*AI & Society*.**38**(5): 1813–1817.[doi](https://en.wikipedia.org/wiki/Doi_(identifier)):[10.1007/s00146-023-01695-0](https://doi.org/10.1007%2Fs00146-023-01695-0).[↑](#cite_ref-7)Hofstadter, Douglas (1980).*Gödel, Escher, Bach: an Eternal Golden Braid*. Basic Books. p. 601.[↑](#cite_ref-8)Shahaf, Dafna; Amir, Eyal (2007).[\"Towards a theory of AI completeness\"](https://wayback.archive-it.org/all/20070824040343/http://www.cs.uiuc.edu/~eyal/papers/ai-complete-commonsense07.pdf)(PDF).*Proceedings of the 8th International Symposium on Logical Formalizations of Commonsense Reasoning (Commonsense 2007)*. Archived from[the original](http://www.cs.uiuc.edu/~eyal/papers/ai-complete-commonsense07.pdf)(PDF) on 2007-08-24. Retrieved 2026-03-20.[1](#cite_ref-mcc3_9-0)[2](#cite_ref-mcc3_9-1)McCorduck, Pamela (2004).*Machines Who Think*(2nd ed.). A. K. Peters. p. 433.[↑](#cite_ref-10)Swaine, Michael.[\"AI – It's OK Again!\"](http://philippe.ameline.free.fr/techtreads/070905_AiOkAgain.htm). Retrieved 20 March 2026.[↑](#cite_ref-11)Minsky, Marvin.[\"The Age of Intelligent Machines: Thoughts About Artificial Intelligence\"](https://web.archive.org/web/20090628081048/http://www.kurzweilai.net/articles/art0100.html?printable=1). Archived from[the original](http://www.kurzweilai.net/articles/art0100.html?printable=1)on 2009-06-28. Retrieved 20 March 2026.[↑](#cite_ref-12)[\"AI set to exceed human brain power\"](https://edition.cnn.com/2006/TECH/science/07/24/ai.bostrom/).*CNN*. 2006-08-09. Retrieved 2026-04-27.[↑](#cite_ref-13)Bommasani, Rishi (2021).[On the Opportunities and Risks of Foundation Models](https://arxiv.org/abs/2108.07258)(Report). Stanford Center for Research on Foundation Models.[↑](#cite_ref-14)Wells, Joshua; VanderVeen, James (2026).[\"An Anthropological Understanding of Artificial Intelligence Transformations in Civic and Domestic Life, Labor, and Higher Education Through the Cybernetic Organism (Cyborg) Concept\"](https://www.proquest.com/openview/639ef067e3f8c2598a88bcf491d198b1).*Maguare*.**40**(1): 157–184 – via ProQuest.[↑](#cite_ref-15)Stone, Peter (2016).[Artificial Intelligence and Life in 2030](https://ai100.stanford.edu/2016-report)(Report). Stanford University.[↑](#cite_ref-16)Flam, Faye (January 15, 2004). \"A new robot makes a leap in brainpower\".*Philadelphia Inquirer*.[↑](#cite_ref-17)Hann, Reuben L. (1998). \"A Conversation with Herbert Simon\".*Gateway*.\n\n## Further reading\n\n[[edit](/w/index.php?title=AI_effect&action=edit§ion=15)]\n\n- McCorduck, Pamela (2004).\n*Machines Who Think*. - Hofstadter, Douglas (1980).\n*Gödel, Escher, Bach*. - Phillips, Everard M. (1999).\n(PDF) (Thesis). MIT.*If It Works, It's Not AI*", "url": "https://wpnews.pro/news/ai-effect", "canonical_source": "https://en.wikipedia.org/wiki/AI_effect", "published_at": "2026-08-30 08:32:36+00:00", "updated_at": "2026-08-30 08:52:10.104472+00:00", "lang": "en", "topics": ["artificial-intelligence"], "entities": ["Pamela McCorduck", "Rodney Brooks", "IBM", "Deep Blue", "Garry Kasparov"], "alternates": {"html": "https://wpnews.pro/news/ai-effect", "markdown": "https://wpnews.pro/news/ai-effect.md", "text": "https://wpnews.pro/news/ai-effect.txt", "jsonld": "https://wpnews.pro/news/ai-effect.jsonld"}}