Artificial intelligence

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{{cquote|What do such machines really do? They increase the number of things we can do without thinking. '''Things we do without thinking—there's the real danger'''.|||Frank Herbert, ''God Emperor of Dune''<ref>''God Emperor of Dune'' by Frank Herbert (1981) G.P. Putnam's Sons.</ref>{{rp|332}}}}
{{cquote|We are told that machines will become like us, but in many ways they demand we become more like them. To let that happen is to lose something immeasurably valuable. That immeasurability is what makes this struggle difficult, but what cannot be measured can be described or at least evoked and valued. It cannot be boiled down to simple metrics such as efficiency and profitability.|||Rebecca Solnit<ref>[https://www.theguardian.com/news/ng-interactive/2026/jan/29/what-technology-takes-from-us-and-how-to-take-it-back What technology takes from us – and how to take it back: Decisions outsourced, chatbots for friends, the natural world an afterthought: Silicon Valley is giving us life void of connection. There is a way out – but it’s going to take collective effort] by Rebecca Solnit (29 Jan 2026 05.20 EST) ''The Guardian''.</ref>}}
'''Artificial intelligence''' ('''AI''') is a somewhat [[vague]] concept, but answering three questions can narrow what is and is not AI:<ref name=narayanan>''AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference'' by Arvind Narayanan & Sayash Kapoor (2024) Princeton University Press. {{isbn|069124913X}}.</ref>{{rp|12-13}}
#"…does the task require creative effort or training for a human to perform?"
#"Does the behavior of the system directly specified in code by the developer or did it indirectly emerge, say by learning from examples or searching through a database?"
#Does the system make decisions more or less autonomously and possess some degree of flexibility and adaptability to the environment?
Because of question #2, that there is no fixed result from AI, AI computer programs rely on [[Bayesian]] [[probability]] networks.<ref>[https://www.turing.com/kb/an-overview-of-bayesian-networks-in-ai An Overview of Bayesian Networks in AI] ''Turing''.</ref>

There are many types of AI, but most AI programs fall into two general categories, generative and predictive. Generative AI encompasses chatbots and image generators, whereas predictive AI encompasses programs that try to predict future outcomes and are used in decision making.<ref name=narayanan/>{{rp|2}} Each type has its own set of potential problems, but predictive AI has a [[Reproducibility|replication]] crisis with research paper results not being reproducible by other researchers, and also has a problem with products that often do not work as claimed.<ref name=narayanan/>{{rp|9-12,245}}<ref>[https://www.nature.com/articles/s41586-020-2766-y.epdf Transparency and reproducibility in artificial intelligence] by Transparency and reproducibility in artificial intelligence] by Benjamin Halbe-Kains et al. (2020) ''Nature'' 586:E14-E18. doi:10.1038/s41586-019-1799-6 (2020).</ref><ref>[https://dl.acm.org/doi/fullHtml/10.1145/3531146.3533158 The Fallacy of AI Functionality] by Inioluwa Deborah Raji et al. (2022) ''2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 2022''. doi:10.1145/3531146.3533158.</ref><ref>[https://www.technologyreview.com/2020/11/12/1011944/artificial-intelligence-replication-crisis-science-big-tech-google-deepmind-facebook-openai/ AI is wrestling with a replication crisis: Tech giants dominate research but the line between real breakthrough and product showcase can be fuzzy. Some scientists have had enough.] by Will Douglas Heaven (November 12, 2020) ''MIT Technology Review''.</ref><ref>[https://www.sciencedirect.com/science/article/pii/S2666389923001599 Leakage and the reproducibility crisis in machine-learning-based science] by Sayash Kapoor and Arvind Narayanan (2003) ''Patterns'' 4(9). doi:Sayash Kapoor and Arvind Narayanan.</ref>The lumping together of predictive and generative AI models under the under the umbrella of "AI" has served as a useful corporate tool for obscuring the harm caused by the the intensive energy use of generative AI regarding climate change.<ref>[https://www.theguardian.com/technology/2026/feb/17/tech-companies-traditional-ai-generative-climate-breakdown-report Claims that AI can help fix climate dismissed as greenwashing. Industry using ‘diversionary’ tactics, says analyst, as energy-hungry complex functions such as video generation and deep research proliferate] by Ajit Niranjan (17 Feb 2026 00.00 EST) ''The Guardian''.</ref>

An underlying problem with predictive AI it is predicated on correlations of past data, and [[correlation does not imply causation]].<ref name=narayanan/>{{rp|44}} This is particularly evident when predictive AI is used on human behavior: humans are notoriously hard to predict<ref name=narayanan/>{{rp|60-98}} but also people try to manipulate outcome results (gaming the system) once they realize likely AI behavior.<ref name=narayanan/>{{rp|46-48}} The problem of failed predictions is exacerbated by AI companies frequent failure to make the expensive investment in verifying real-world implementations are accurate. Predictive AI has caused serious real-world problems for people (wrongly accusing 30,000 parents of welfare fraud in the [[Netherlands]], wrongly collecting $71 million from taxpayers in [[Michigan]] and $721 million from taxpayers in [[Australia]]). These types of AI errors are known as "overautomation", and eventually led to AI developers to add fine print saying that the programs should always have human supervision (analogous to the [[Quack Miranda Warning]], which also often gets ignored). But what is the point of using potentially cost-saving but unreliable AI when it also requires expensive expert human supervision?<ref name=narayanan/>{{rp|48-51}}

The history of the field of AI research spans great dreams, and more than half a century of failure to realize "strong AI" (an artificial mind of more general capability).{{efn|Strong AI has been dreamed of and vaguely imagined to be possible throughout the history of the electronic computer.}} Eventually, research and development refocused on the productive goal of making systems with some specific skill each, such as analyzing data to classify objects, navigating robotic equipment, strategic decision-making within the framework of a particular "game" (e.g. chess) or situation, etc. In the early 2020s, the chatbot (earlier mostly a toy) was reinvented on the foundation of the [[large language model]], producing something with a greater range of skills, yet still far from the old dream of strong AI.

Older AI ambitions were often rather anthropocentric, e.g. the striving for an {{wpl|artificial brain}} which may replace the human organ. Anthropocentric thinking also underlies the old [[Turing test]] proposed by [[Alan Turing]] for evaluating a device as intelligent: (roughly) ''If a ''conversation'' with the device cannot be differentiated from a similar conversation with a human being then the device can be called intelligent.'' Such a test is based on the response of an audience to a performance, similarly to how an audience may respond to a stage magician, and as such tests the discernment of the audience more than the device.

==Strong AI==
{{cquote|Without a concrete notion of [[general intelligence]], it's not clear what would constitute an "intelligence explosion," nor what it would mean for one computer to be twice as intelligent as another. Defining AGI in the first place looks shaky too.|||Adam Becker<ref name=becker>''More Everything Forever: AI Overlords, Space Empires, and Silicon Valley's Crusade to Control the Fate of Humanity'' by Adam Becker (2025) Basic Books. ISBN 1541619595.</ref>{{rp|70}}}}
{{cquote|My roommate was the smartest person I ever met in my life. He was incredibly brilliant, and all he did was lie around and play World of Warcraft between [[Cannabis|bong rips]]. The assumption that any intelligent agent will want to recursively self-improve, let alone conquer [[Milky Way|the galaxy]], to better achieve its goals makes unwarranted assumptions about the nature of motivation. It's perfectly possible an AI won't do much of anything, except use its powers of hyperpersuasion to get us to bring it brownies.|||{{wpl|Maciej Cegłowski}}<ref>[https://idlewords.com/talks/superintelligence.htm Superintelligence: The Idea That Eats Smart People] by Maciej Cegłowski (October 29, 2016) ''Idle Words''.</ref><ref>[https://pbfcomics.com/comics/zuthulus-resurrection/ Zuthulus Resurrection] (2017) ''The Perry Bible Fellowship''.</ref>}}
'''Artificial general intelligence''' ('''AGI'''), also called '''strong AI''',<ref name="Kurzweil 2005-08-05">,[https://web.archive.org/web/20060217035702/https://www.forbes.com/home/free_forbes/2005/0815/030.html Long Live AI] by Ray Kurzweil (15 August 2005) ''Forbes''. Ray Kurzweil described strong AI as "machine intelligence with the full range of human intelligence."</ref><ref>[https://crnano.typepad.com/crnblog/2005/08/advanced_human_.html Advanced Human Intelligence]. Responsible Nanotechnology, 10 August 2005.</ref> is a hypothetical, ill-defined type of artificial intelligence that would not be limited to a specific task (as opposed to current AI, which is called specialized or "weak"), but would rather possess a general capability of thinking, learning, and improving much like an organic mind (though not necessarily working like an organic [[brain]]). It differs from a collection of specialized weak AIs, which is what e.g. {{wpl|Amazon Alexa}} and Siri are; intelligent human-like marketeers can include as many such specialized tools as they want in a package, analogously to the parts of a Swiss army knife, without that package gaining the ability to develop new tools in a self-directed way. The use of AGI rather than "strong AI" directly references the psychology term "general intelligence" in humans, which is purportedly measured by [[IQ]] and is associated with [[eugenics]].<ref name=becker/>{{rp|130-131}}<ref>[https://davidgolumbia.medium.com/the-great-white-robot-god-bea8e23943da The Great White Robot God: Artificial General Intelligence and White Supremacy] by David Golumbia (Jan 21, 2019) ''Medium''.</ref>

With the generative AI boom of the 2020s and systems such as the large language-model [[ChatGPT]], confusion about the meaning of strong AI or AGI has spread, allegedly deliberately on the part of some AI vendors, who hope to be able to more easily claim having achieved AGI.<ref>[https://www.fastcompany.com/90968623/why-everyone-seems-to-disagree-on-how-to-define-artificial-general-intelligence Why everyone seems to disagree on how to define Artificial General Intelligence] by Mark Sullivan (18 October 2023) ''Fast Company''.</ref> For example, AGI has at times been defined by ChatGPT maker OpenAI as an AI surpassing humans in a majority of economically valuable tasks&nbsp;– so that if it sells and can profitably replace many types of human workers, it counts as AGI. This need not imply a fluid intelligence, and could hypothetically be achieved through the machine-learning version of large-scale rote memorization and brute force&nbsp;– particularly if commercial use values quantity and superhuman speed above quality and originality in arts and intellectual crafts where applicable.

The older, more established AGI idea of a "full artificial mind" (and often in addition some kind of artificial body accompanying it) is a basis of the [[transhumanism]] and [[singularity]] lore. It is also commonly portrayed in [[science fiction]] in diverse ways. Without it, neither will the wondrous things transhumanists often expect to happen in the future be possible, nor will the fearsome [[cybernetic revolt]]s (robot uprisings and AI [[doomsday scenario]]s) they sometimes warn about and many sci-fi works include.

The use of the term 'artificial general intelligence' has a direct connection to the pseudoscientific term '[[general intelligence]]' as well as to [[racism]] that references American [[slavery]]:<ref name=becker/>{{rp|129-138}}
*the development and the use of the term 'general intelligence' by racists, and eugenicists such as statistician R. A. Fisher
*[[Isaac Asimov]]'s use of racially-charged language in his novel ''The Naked Sun'' (robots are called 'boy' and call humans 'master')<ref>''The Naked Sun'' by Isaac Asimov (1957) Doubleday.</ref>
*AI researcher {{wpl|I. J. Good}} referring to a hypothetical future AI as 'docile'
*{{wpl|Vernor Vinge||,}} who popularized the term "[[Singularity#Technological singularity|technological singularity]]", referred to Asimov's concept of a robot as a "willing slave"<ref>[https://edoras.sdsu.edu/~vinge/misc/singularity.html  The Coming Technological Singularity: How to Survive in the Post-Human Era] by Vernor Vinge (1993) ''San Diego State University''.</ref>

===Its possibility===
Despite immense amounts of money, research, and a broad range of specialized or "weak" AI products having been created, a general artificial intelligence&nbsp;— a sentient [[computer]], capable of initiative, general reasoning, and seamless human interaction&nbsp;— has yet to come to fruition. (Some argue that a sentient computer might be more appropriately referred to as artificial ''[[consciousness]]'' than as artificial intelligence.) The boom in generative AI however pushes stochastic machine imitation to the limits,{{efn|Emily M. Bender ''et al.'' have labeled probabilistic imitation machines that parrot things with random variation without understanding as "[[stochastic parrot]]s".<ref name=parrot-paper>[https://dl.acm.org/doi/pdf/10.1145/3442188.3445922 On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜] by Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, Shmargaret Shmitchell (2021) ''Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency''. Association for Computing Machinery. ISBN 978-1-4503-8309-7. doi=10.1145/3442188.3445922.</ref>}} showing that larger quantity in model size and training data leads to broader canned skills. This leads to new debates about how to distinguish the presence or absence of intelligence, and the relation of such canned skills to general intelligence, with skepticism expressed by a broader range of researchers including in cognitive science.<ref>{{cite news|last=Clark|first=Lindsay|title=Artificial General Intelligence remains a distant dream despite LLM boom|url= https://www.theregister.com/2023/07/04/agi_llm_distant_dream/|access-date=9 July 2023|work=The Register|date=4 July 2023|language=en}}</ref>

In 2023, some researchers argued that the most powerful [[Large language model|LLMs]] already constituted AGI.<ref>[https://www.noemamag.com/artificial-general-intelligence-is-already-here/ Artificial General Intelligence Is Already Here] by Blaise Agüera y Arcas & Peter Norvig (October 10, 2023) ''Noema''.</ref> Yet, as of 2025 their claims that LLMs can be competent at nearly any human information task is still very much lacking in evidence, as LLMs have trouble dealing with questions such as what the word "it" in a sentence refers to, and otherwise evince lack of abstract thought. It may be that, outside of the points made by such "LLMs lead to AGI" debaters, there are other large differences in understanding between them and their critics than the questions about the AI itself, namely questions about human intelligence and intelligence in general and how it works. It wouldn't be the first time such a gap in understanding leads to failing to deliver on the AGI front after AI researchers assumed they were almost already there.

{{wpl|Hubert Dreyfus's views on artificial intelligence|Hubert Dreyfus's critique of artificial intelligence research|,}} made back in the era when AI research tried to create AGI through symbol-manipulation systems, has been especially enduring.<ref>[https://doi.org/10.1007/s11023-008-9093-7 Hubert L. Dreyfus’s Critique of Classical AI and its Rationalist Assumptions] by Setargew Kenaw (2008) ''Minds & Machines'' 18:227–238.</ref><ref>''What Computers Can't Do'' by Hubert Dreyfus (1972) MIT Press. {{isbn|978-0-06-090613-9}}</ref> Dreyfus does not explicitly deny the possibility of strong AI, but  asserts that the fundamental assumptions of AI researchers at the time were either baseless or misguided. Because Dreyfus's critique draws on [[philosopher]]s such as [[Heidegger]] and Maurice Merleau-Ponty, it was largely ignored (and lampooned) at the time of its arrival. However, as the fantastic predictions of early AI researchers continually failed to pan out (which included the solution to all philosophical problems!), his critique has largely been vindicated, and even incorporated into modern AI research. But this has arguably only happened piecemeal, problem by problem, and in response to the problems rather than in response to Dreyfus.<ref>{{Cite book | year = 2004 | title = Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence | isbn = 1-56881-205-1 | publisher = A.K. Peters | location = Natick, Mass. | edition = 2nd | url=http://www.pamelamc.com/html/machines_who_think.html}}</ref>

Some commentators question more categorically whether or not a computer can even qualify in principle. John Searle proposed his "[[Chinese room]]" [[thought experiment]] to demonstrate that a computer program merely shuffles symbols around according to simple rules of syntax, but no ''semantic'' grasp of what the symbols really mean is obtained by the program.<ref>[https://home.csulb.edu/~cwallis/382/readings/482/searle.minds.brains.programs.bbs.1980.pdf Minds, brains, and programs] by John Searle (1980) ''The Behavioral and Brain Sciences'' 3:417-457. {{quotebox|"Could a machine think?" On the argument advanced here only a machine could think, and only very special kinds of machines, namely brains and machines with internal causal powers equivalent to those of brains. And that is why strong AI has little to tell us about thinking, since it is not about machines but about programs, and no program by itself is sufficient for thinking.}}</ref> Proponents of "strong AI", who believe an awareness can exist within a purely algorithmic process, have put forward various critiques of Searle's argument. Ultimately, Searle's argument seems inconclusive.

There are also [[woo]] objections to the possibility of strong AI, or objections at any rate on [[unfalsifiable]] grounds. These can&nbsp;- for example&nbsp;- be [[religious]], based on ideas of [[quantum consciousness]], or espouse some idea about biology (or maybe humanity in particular) being special. Some LLM and AGI [[Hyperbole|hypers]] tend to lump all critics into this category.

Some apparently sensible people are taking the threat of AGI seriously and started the Stop AI organization in 2024.<ref>[https://www.stopai.info/donate Stop AI]</ref> They have called for the banning of the development of AGI.<ref>[https://docs.google.com/document/d/1IgTaTMTZuY3kRLZ5JDFhwqQLATWVVGLOHVulbBY5O6g/ Stop AI Proposal] ''Stop AI''.</ref>

===Transhumanist dreams===
Dreams of replacing the human brain with a device equal to or greater in capacity than it are central to [[transhumanism]], a staple of science fiction, and have long accompanied ideas of strong AI. Much like strong AI in general, such dreams may or may not become possible with future technology, going by what is known today. This is in contrast to functions separate from the need for strong AI, e.g. prosthetic limbs and implants related to sensory processing, where some types are known to be possible or are even in use by people.

Brains and cognition are not currently well understood, and the scale of computation for an artificial brain is unknown. The power consumption of computers however leads to speculation that for an artificial brain, it would have to be orders of magnitude greater than its biological equivalent. The human brain consumes about 20 W of power (and most of it seems used just to keep it permanently up and running, plus basically energy being uselessly leaked away<ref>[https://www.livescience.com/why-does-the-brain-use-so-much-energy We finally know why the brain uses so much energy]</ref>) whereas current supercomputers may use as much as 1 MW or an order of 100,000 more, suggesting that AI may be a staggeringly energy-inefficient form of intelligence. Critics of {{wpl|brain simulation}} believe that artificial intelligence can be modeled without imitating nature, using the analogy of early attempts to construct flying machines modeled after birds.<ref>{{cite journal |last= Goertzel|first= Ben |date= December 2007 |title= Human-level artificial general intelligence and the possibility of a technological singularity: a reaction to Ray Kurzweil's ''The Singularity Is Near'', and McDermott's critique of Kurzweil|journal=Artificial Intelligence |volume=171 |issue=18, Special Review Issue |pages=1161–1173 |url=https://scholar.google.com/scholar?hl=sv&lr=&cluster=15189798216526465792 |accessdate=April 1, 2009}}</ref><ref>Fox and Hayes quoted in Nilsson, Nils (1998), Artificial Intelligence: A New Synthesis, p581 Morgan Kaufmann Publishers </ref>

As part of transhumanism, AGI falls within the [[futurist]] constellation of fantasies of billionaires, [[oligarchic escapes]], a [[utopia]] for the rich an powerful, but a dystopia for everyone else. "If you want a picture of the future, imagine a billionaire's [[Nineteen Eighty-Four|digital boot stamping on a human face]]."<<ref name=becker/>{{rp|249}}

An {{wpl|artificial brain}} would not fall under the current biological definition of life any more than a kidney-dialysis machine. An example of a fictional character with this kind of prosthetic is {{wpl|Cyborg (comics)|Cyborg}} from the ''{{wpl|Teen Titans}}'' comics.

==Machine learning==
{{main|Machine learning}}
In the field of artificial intelligence, [[machine learning]] is a set of techniques that make it possible to train a computer model so that it behaves according to some given sample inputs and expected outputs. For example, machine learning can recognize objects in images or perform other complex tasks that would be too complicated to be described with traditional procedural code.

[[Large language model]]s are [[neural network]]s for language modeling that are large (at least tens of millions of "parameters", or artificial neurons). These include [[ChatGPT]], which sparked a great, renewed interest in chatbots, reinvented to be based on LLMs.

==Risks of AI==

{{cquote|
Critics have already written thoroughly about the environmental<ref>Lex McMenamin, [https://www.teenvogue.com/story/chatgpt-is-everywhere-environmental-costs-oped ChatGPT Is Everywhere — Why Aren't We Talking About Its Environmental Costs?] ''TeenVogue'', 7 May 2025.</ref> harms,<ref>Michelle Fleury & Nathalie Jimenez, [https://www.bbc.com/news/articles/cy8gy7lv448o 'I can't drink the water' - life next to a US data centre]. ''BBC'', 10 July 2025.</ref> the reinforcement<ref>Garance Burke and Hilke Schellmann, [https://apnews.com/article/ai-artificial-intelligence-health-business-90020cdf5fa16c79ca2e5b6c4c9bbb14 Researchers say an AI-powered transcription tool used in hospitals invents things no one ever said]. ''AP News''.</ref> of bias<ref>Adrienne Williams, Milagros Miceli and Timnit Gebru, [https://www.noemamag.com/the-exploited-labor-behind-artificial-intelligence/ The Exploited Labor Behind Artificial Intelligence]. ''Noema'', 13 October 2022.</ref> and generation of racist output,<ref>Lisa Hagen, Huo Jingnan, and Audrey Nguyen, [https://www.npr.org/2025/07/09/nx-s1-5462609/grok-elon-musk-antisemitic-racist-content Elon Musk's AI chatbot, Grok, started calling itself 'MechaHitler']. ''NPR'', 9 July 2025.</ref> the cognitive harms<ref>Harry Black, [https://archive.ph/whVMI AI Eroded Doctors’ Ability to Spot Cancer Within Months in Study]. Archived from ''Bloomberg'', 12 August 2025.</ref> and AI supported suicides,<ref>Kashmir Hill, [https://archive.ph/rdL9W A Teen Was Suicidal. ChatGPT Was the Friend He Confided In.] Archived from ''The New York Times'', 26 August 2025.</ref> the problems with consent<ref>Samatha Cole, [https://www.404media.co/deepfake-harassment-ohio-undress-clothoff-nudify-apps/ A Deepfake Nightmare: Stalker Allegedly Made Sexual AI Images of Ex-Girlfriends and Their Families]. ''404 Media'', 26 June 2025.</ref> and copyright,<ref>David Carson, [https://jskfellows.stanford.edu/theft-is-not-fair-use-474e11f0d063 Theft is not fair use: Artificial Intelligence companies have a copyright problem, and they know it.] jskfellows.stanford.edu, 21 April 2025.</ref> the way AI tech companies further the patterns of empire,<ref>[https://karendhao.com/ Karen Hao, ''Empire of AI'']. karendhao.com.</ref> how it’s a con<ref>[https://thecon.ai/ Emily M. bender and Alex Hanna, ''The AI Con: How To Fight Big tech's Hype and Create the Future We Want'']. thecon.ai.</ref> that enables fraud<ref>Jakob McWhinney, [https://voiceofsandiego.org/2025/04/14/as-bot-students-continue-to-flood-in-community-colleges-struggle-to-respond/ As ‘Bot’ Students Continue to Flood In, Community Colleges Struggle to Respond]. ''Voice of San Diego'', 14 April 2025.</ref> and disinformation<ref>Tate Ryan-Mosley, [https://www.technologyreview.com/2023/10/04/1080801/generative-ai-boosting-disinformation-and-propaganda-freedom-house/ How generative AI is boosting the spread of disinformation and propaganda]. ''Technology Review'', 4 October 2023.</ref> and harassment<ref>Raphael Satter, [https://www.reuters.com/world/us/fbi-says-artificial-intelligence-being-used-sextortion-harassment-2023-06-07/ FBI says artificial intelligence being used for 'sextortion' and harassment]. ''Reuters'', 8 June 2023.</ref> and surveillance,<ref>Jay Stanley, [https://www.aclu.org/news/privacy-technology/machine-surveillance-is-being-super-charged-by-large-ai-models Machine Surveillance is Being Super-Charged by Large AI Models]. ''American Civil Liberties Union'', 21 March 2025.</ref> the exploitation of workers,<ref>Niamh Rowe, [https://archive.ph/Nqx2h Millions of Workers Are Training AI Models for Pennies]. Archived from ''Wired'', 16 October 2023.</ref> as an excuse to fire workers<ref>Emma Roth, [https://www.theverge.com/news/688679/amazon-ceo-andy-jassy-ai-efficiency Amazon CEO says it will cut jobs due to AI’s ‘efficiency’]. ''The Verge'', 17 June 2025.</ref> and de-skill work, how they don’t actually reason<ref>Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, Maxwell Horton, Samy Bengio, and Mehrdad Farajtabar, [https://machinelearning.apple.com/research/illusion-of-thinking The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity]. Machine Learning Research at Apple, June 2025.</ref> and probability and association are inadequate to the goal of intelligence,<ref>Walid S. Saba, [https://thegradient.pub/machine-learning-wont-solve-the-natural-language-understanding-challenge/ Machine Learning Won't Solve Natural Language Understanding]. ''The Gradient'', 7 August 2021.</ref> how people think it makes them faster when it makes them slower,<ref>Joel Becker, Nate Rush, Elizabeth Barnes, and David Rein, [https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/ Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity]. ''METR'', 10 July 2025.</ref> how it is inherently mediocre and fundamentally conservative, how it is at its core a fascist technology<ref>Gareth Watkins, [https://newsocialist.org.uk/transmissions/ai-the-new-aesthetics-of-fascism/ AI: The New Aesthetics of Fascism]. ''New Socialist'', 9 February 2025.</ref> rooted in the ideology of supremacy,<ref>Mandy Brown, [https://aworkinglibrary.com/writing/toolmen Toolmen]. ''A Working Library'', 30 May 2025.</ref> defined not by its technical features but by its political ones.<ref>Ali Alkhatib, [https://ali-alkhatib.com/blog/defining-ai Defining AI]. ali-alkhatib.com, 6 December 2024.</ref>|||moser's frame shop, August 2025<ref>[https://anthonymoser.github.io/writing/ai/haterdom/2025/08/26/i-am-an-ai-hater.html I Am An AI Hater]. moser's frame shop, 26 August 2025.</ref>
}}

Some science fiction has highlighted the risk of an [[Cybernetic_revolt|AI takeover]] of human society. Most risks of this type are unrealistic and, even if they weren't, do not have relevance in today's society for us to worry about them (though [[Eliezer Yudkowsky]] disagrees and will not tire of letting people know it).

However, there are also many more prosaic potential downsides of AI that may necessitate cautious use of the technology, changes in regulations, or political action – way before hypothetical future AI technology reaches Terminator-like levels of general intelligence. These include:

===Black box nature===
One issue is that [[Black box|Black-box]] AIs making decisions that affect people, but whose reasoning is completely opaque and essentially undiscoverable by customers, judges and juries, and even by the organisations that own them. An implication is that these algorithms could be [[hacker|hacked]] for pecuniary advantage, or to literally "get out of jail free", without others noticing. 

Combine this with the tendency of some politicians and bureaucrats with little understanding of technology to simply say "computer says no" when confronted with disagreements about computer-generated decisions, even in the absence of any machine intelligence at all, and this could be a recipe for special interests to do "regulatory capture" in a ''whole new way''.

Some [[Tesla]] fans have theorised that self-driving cars will in the not-too-distant-future also mean that new cars become unaffordable for all but the very wealthy, as car manufacturers focus on selling highly-profitable and expensive autonomous vehicles to [[Uber]] and Lyft, or simply start their own autonomous taxi operations (as Tesla plans to do).

===Plagiarism and spam===
Another issue is that AI can proliferate junk information, harmful messages, or works infringing on rights. From [[spam]], to [[plagiarism]] and forgeries, to psychological warfare, various machine learning approaches can be used to produce either remarkable quality, quantity, or even both, of bogus information of some chosen kind&nbsp;– text, images, audio, videos, etc. [[Deepfake]]s are fabrications made to have convincing qualities, e.g. using a {{wpl|generative adversarial network}} (GAN). In terms of quantity, LLMs like [[ChatGPT]] led to new fears of both mass plagiarism and automated disinformation sweeping the world.

[[Copyright]] concerns are common with generative AIs, because they use training data that includes copyrighted works without asking the artists,{{efn|See, for example, [https://rationalwiki.org/wiki/File:Lord_Cernunnos.png this AI-generated picture] of the god [[Cernunnos]] and that garbled watermark at bottom left}} and also because it's unclear who owns the image.<ref>[https://www.theverge.com/23961021/ai-art-copyright-training-ownership-fair-use Who owns AI art?] by Adi Robertson (Nov 15, 2023, 7:12 AM PST) ''The Verge''.</ref>

===Racism and sexism===

Some AIs are programmed to learn from any internet users. Unfortunately, much of the content on the internet is loaded with [[racism]], [[sexism]], and misinformation, which the AIs parrot&nbsp;– this has happened with older types of chatbot.<ref>[https://techcrunch.com/2016/03/24/microsoft-silences-its-new-a-i-bot-tay-after-twitter-users-teach-it-racism/ Microsoft silences its new A.I. bot Tay, after Twitter users teach it racism] by Sarah Perez (7:16 AM PDT · March 24, 2016) ''TechCrunch''.</ref> Similarly, generative AIs like LLMs soak up expressions of [[bigotry]], and other [[bias]]es and flaws in its data set (sourced in large part from the web) when the model is trained, and imitates it. While work can be done on the model to reduce the issue, large models are inscrutable and all problems can't reasonably be weeded out.<ref name=parrot-paper/>

Some AI algorithms inadvertently make racist or [[sexist]] decisions about matters such as mortgages and other loans, or even about criminal-justice matters such as crime detection, sifting through large amounts of evidence, bail or probation decisions&nbsp;– this has also already happened.<ref>[https://www.theguardian.com/inequality/2017/aug/08/rise-of-the-racist-robots-how-ai-is-learning-all-our-worst-impulses Rise of the racist robots – how AI is learning all our worst impulses] by Stephen Buranyi (8 Aug 2017 02.00 EDT) ''The Guardian''.</ref>

AIs used by [[Social media|social-media]] systems and platforms (for example [[YouTube]]) can create [[filter bubble]]s – potentially inadvertently increasing political polarisation and [[extremism]].

===Technological unemployment===
Successive waves of {{wpl|technological unemployment||.}} [[Self-driving cars]] and trucks may eventually take over the work of professional drivers.{{efn|Self-driving vehicle technology is slowly improving, though as of the early 2020s the hype remains overly optimistic about the rate of progress.}} Various white collar workers who handle boilerplate text, or chat with people, may be replaced by chatbots.{{efn|In roles of technical or work support, psychological counseling, etc., LLM chatbots are poor substitutes for skilled human guidance, but they're cheaper to operate, making the transition profitable.}} Online "influencers" can be replaced by generative AI, creating artificial social media personalities.<ref>[https://arstechnica.com/ai/2023/12/ai-created-virtual-influencers-are-stealing-business-from-humans/ AI-created “virtual influencers” are stealing business from humans] by Christina Criddle (2023-12-29) ''Financial Times'' (on ''Ars Technica'').</ref> Business leaders also dream of replacing software developers with chatbots, though without AGI this cannot go far.{{efn|Human developers may use LLM assistants to speed up some tasks, but can't generally be replaced by LLMs for the thinking involved in design, innovation, security expertise, to name some key areas.}} New jobs involving the use and supervision of AI tools can be expected, but how many? No one can yet be sure how employment will be affected on the whole. Some, notably including 2020 US Presidential candidate [[Andrew Yang]], have advocated a [[universal basic income]] to act as a buffer against technological unemployment, though [[Post-Keynesian economics|others]] have argued instead for a return to the 20<sup>th</sup>-century idea of government full-employment programs.

===Miscellaneous problems===
In addition to the above problems, data leakage is a well-known but ever common problem with 
AI. Leakage is where an AI program is tested on similar or even identical problems that it was trained on. This leads to exaggerated claims about accuracy for AI programs both in academia and industry. The leakage problem can have cascading repercussions when for example scientific research relies on an AI program that turns out to have a leakage problem.<ref name=narayanan/>{{rp|22,244}}

A major problem with AI is [[Environmental]] concerns, given how energy-intensive generative AIs are even for trivial tasks such as chatting or generating images, especially as artificial intelligence becomes more widely adopted<ref>[https://www.scientificamerican.com/article/the-ai-boom-could-use-a-shocking-amount-of-electricity/ The AI Boom Could Use a Shocking Amount of Electricity] by Lauren Leffer (October 13, 2023) ''Scientific American''.</ref><ref>[https://www.extremetech.com/energy/generating-just-a-few-ai-images-consumes-as-much-energy-as-charging-your Generating Just a Few AI Images Consumes As Much Energy As Charging Your Smartphone]</ref>.

Most disturbingly of all, flying [[drone]]s controlled by autonomous AIs could be used by rogue states or [[terrorist]] groups (or even by ordinary states in [[war]] scenarios) to injure or assassinate individuals, or even to target large groups of people with pinpoint accuracy, like political opponents of an authoritarian leader, without it necessarily being traceable back to the people giving the orders. This [[dystopian]] scenario was vividly explored in a disturbing video titled "Slaughterbots", produced by the campaign to stop killer robots (yes, they are actually called that).<ref>[https://www.youtube.com/watch?v=9CO6M2HsoIA Slaughterbots] by Stop Autonomous Weapons (Nov 12, 2017) ''YouTube''.</ref>

==See also==
{{fun}}
{{fun|AI}}
{{fun|AI bro bingo}}
{{fun|Artificial stupidity}}
*[[AI-box experiment]]
*[[CAIMEO]]
*[[Enshittification]]
*[[Killer robot]]
*[[Psychology#Psychology in crisis]]
*[[Singularity]]
*[[Transhumanism]]

{{otherlang
|pt=Inteligência artificial}}

==Further reading==
*George Johnson, ''Machinery of Mind: Inside the New Science of Artificial Intelligence''. Time Books, 1986. {{isbn|0812912292}}
*[[Roger Penrose]], ''The Emperor's New Mind: Concerning Computers, Minds and The Laws of Physics''. Oxford University Press, 1989. {{isbn|0198519737}}
*[[Douglas Hofstadter]], ''Gödel, Escher, Bach: An Eternal Golden Braid''. Basic Books, 1999. {{isbn|0465026567}}

==External links==
*[https://www.propublica.org/series/machine-bias ProPublica's series on Machine Bias]
*[https://scout.ai/story/the-rise-of-the-weaponized-ai-propaganda-machine The Rise of the Weaponized AI Propaganda Machine]
*[https://www.wired.com/2017/02/keep-ai-turning-racist-monster/ How to Keep Your AI From Turning Into a Racist Monster]
*[https://www.aisnakeoil.com/ AI Snake Oil] — a blog by computers scientists Sayash Kapoor and Arvind Narayanan, authors of a 2024 book by the same name
*[https://archive.ph/DCm1E How to argue with an AI Booster]

==Notes==
{{reflist|group=note|2}}

==References==
{{reflist|2|80%}}

[[Category:Artificial intelligence| ]]
[[Category:Technology]]
[[Category:Transhumanism]]

Categories: Artificial intelligence, Technology, Transhumanism