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Intelligence has been defined in many ways: the capacity for abstraction, logic, understanding, self-awareness, learning, emotional knowledge, reasoning, planning, creativity, critical thinking, and problem-solving. It can be described as the ability to perceive or infer information; and to retain it as knowledge to be applied to adaptive behaviors within an environment or context.

The term rose to prominence during the early 1900s. Most psychologists believe that intelligence can be divided into various domains or competencies.

Intelligence has been long-studied in humans, and across numerous disciplines. It has also been observed in the cognition of non-human animals. Some researchers have suggested that plants exhibit forms of intelligence, though this remains controversial.

Intelligence in computers or other machines is called artificial intelligence.

Etymology

The word intelligence derives from the Latin nouns intelligentia or intellēctus, which in turn stem from the verb intelligere, to comprehend or perceive. In the Middle Ages, the word intellectus became the scholarly technical term for understanding and a translation for the Greek philosophical term nous. This term, however, was strongly linked to the metaphysical and cosmological theories of teleological scholasticism, including theories of the immortality of the soul, and the concept of the active intellect (also known as the active intelligence). This approach to the study of nature was strongly rejected by early modern philosophers such as Francis Bacon, Thomas Hobbes, John Locke, and David Hume, all of whom preferred "understanding" (in place of "intellectus" or "intelligence") in their English philosophical works. Hobbes for example, in his Latin De Corpore, used "intellectus intelligit", translated in the English version as "the understanding understandeth", as a typical example of a logical absurdity. "Intelligence" has therefore become less common in English language philosophy, but it has later been taken up (with the scholastic theories that it now implies) in more contemporary psychology.

Definitions

There is controversy over how to define intelligence. Scholars describe its constituent abilities in various ways, and differ in the degree to which they conceive of intelligence as quantifiable.

A consensus report called Intelligence: Knowns and Unknowns, published in 1995 by the Board of Scientific Affairs of the American Psychological Association, states:

Individuals differ from one another in their ability to understand complex ideas, to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, to overcome obstacles by taking thought. Although these individual differences can be substantial, they are never entirely consistent: a given person's intellectual performance will vary on different occasions, in different domains, as judged by different criteria. Concepts of "intelligence" are attempts to clarify and organize this complex set of phenomena. Although considerable clarity has been achieved in some areas, no such conceptualization has yet answered all the important questions, and none commands universal assent. Indeed, when two dozen prominent theorists were recently asked to define intelligence, they gave two dozen, somewhat different, definitions.

Psychologists and learning researchers also have suggested definitions of intelligence such as the following:

Researcher	Quotation
Alfred Binet	Judgment, otherwise called "good sense", "practical sense", "initiative", the faculty of adapting one's self to circumstances ... auto-critique.
David Wechsler	The aggregate or global capacity of the individual to act purposefully, to think rationally, and to deal effectively with his environment.
Lloyd Humphreys	"...the resultant of the process of acquiring, storing in memory, retrieving, combining, comparing, and using in new contexts information and conceptual skills".
Howard Gardner	To my mind, a human intellectual competence must entail a set of skills of problem solving—enabling the individual to resolve genuine problems or difficulties that he or she encounters and, when appropriate, to create an effective product—and must also entail the potential for finding or creating problems—and thereby laying the groundwork for the acquisition of new knowledge.
Robert Sternberg & William Salter	Goal-directed adaptive behavior.
Reuven Feuerstein	The theory of Structural Cognitive Modifiability describes intelligence as "the unique propensity of human beings to change or modify the structure of their cognitive functioning to adapt to the changing demands of a life situation".
Shane Legg & Marcus Hutter	A synthesis of 70+ definitions from psychology, philosophy, and AI researchers: "Intelligence measures an agent's ability to achieve goals in a wide range of environments", which has been mathematically formalized.
Alexander Wissner-Gross	F = T ∇ S${\displaystyle _{\tau }}$ "Intelligence is a force, F, that acts so as to maximize future freedom of action. It acts to maximize future freedom of action, or keep options open, with some strength T, with the diversity of possible accessible futures, S, up to some future time horizon, τ. In short, intelligence doesn't like to get trapped".

Human

Human intelligence is the intellectual power of humans, which is marked by complex cognitive feats and high levels of motivation and self-awareness. Intelligence enables humans to remember descriptions of things and use those descriptions in future behaviors. It gives humans the cognitive abilities to learn, form concepts, understand, and reason, including the capacities to recognize patterns, innovate, plan, solve problems, and employ language to communicate. These cognitive abilities can be organized into frameworks like fluid vs. crystallized and the Unified Cattell-Horn-Carroll model, which contains abilities like fluid reasoning, perceptual speed, verbal abilities, and others.

Intelligence is different from learning. Learning refers to the act of retaining facts and information or abilities and being able to recall them for future use. Intelligence, on the other hand, is the cognitive ability of someone to perform these and other processes.

Intelligence quotient (IQ)

There have been various attempts to quantify intelligence via psychometric testing. Prominent among these are the various Intelligence Quotient (IQ) tests, which were first developed in the early 20th century to screen children for intellectual disability. Over time, IQ tests became more pervasive, being used to screen immigrants, military recruits, and job applicants. As the tests became more popular, belief that IQ tests measure a fundamental and unchanging attribute that all humans possess became widespread.

An influential theory that promoted the idea that IQ measures a fundamental quality possessed by every person is the theory of General Intelligence, or g factor. The g factor is a construct that summarizes the correlations observed between an individual's scores on a range of cognitive tests.

Today, most psychologists agree that IQ measures at least some aspects of human intelligence, particularly the ability to thrive in an academic context. However, many psychologists question the validity of IQ tests as a measure of intelligence as a whole.

There is debate about the heritability of IQ, that is, what proportion of differences in IQ test performance between individuals are explained by genetic or environmental factors. The scientific consensus is that genetics does not explain average differences in IQ test performance between racial groups.

Emotional

Emotional intelligence is thought to be the ability to convey emotion to others in an understandable way as well as to read the emotions of others accurately. Some theories imply that a heightened emotional intelligence could also lead to faster generating and processing of emotions in addition to the accuracy. In addition, higher emotional intelligence is thought to help us manage emotions, which is beneficial for our problem-solving skills. Emotional intelligence is important to our mental health and has ties to social intelligence.

Social

Social intelligence is the ability to understand the social cues and motivations of others and oneself in social situations. It is thought to be distinct to other types of intelligence, but has relations to emotional intelligence. Social intelligence has coincided with other studies that focus on how we make judgements of others, the accuracy with which we do so, and why people would be viewed as having positive or negative social character. There is debate as to whether or not these studies and social intelligence come from the same theories or if there is a distinction between them, and they are generally thought to be of two different schools of thought.

Moral

Moral intelligence is the capacity to understand right from wrong and to behave based on the value that is believed to be right. It is considered a distinct form of intelligence, independent to both emotional and cognitive intelligence.

Book smart and street smart

Concepts of "book smarts" and "street smart" are contrasting views based on the premise that some people have knowledge gained through academic study, but may lack the experience to sensibly apply that knowledge, while others have knowledge gained through practical experience, but may lack accurate information usually gained through study by which to effectively apply that knowledge. Artificial intelligence researcher Hector Levesque has noted that:

Given the importance of learning through text in our own personal lives and in our culture, it is perhaps surprising how utterly dismissive we tend to be of it. It is sometimes derided as being merely "book knowledge", and having it is being "book smart". In contrast, knowledge acquired through direct experience and apprenticeship is called "street knowledge", and having it is being "street smart".

Nonhuman animal

Although humans have been the primary focus of intelligence researchers, scientists have also attempted to investigate animal intelligence, or more broadly, animal cognition. These researchers are interested in studying both mental ability in a particular species, and comparing abilities between species. They study various measures of problem solving, as well as numerical and verbal reasoning abilities. Some challenges include defining intelligence so it has the same meaning across species, and operationalizing a measure that accurately compares mental ability across species and contexts.

Wolfgang Köhler's research on the intelligence of apes is an example of research in this area, as is Stanley Coren's book, The Intelligence of Dogs. Non-human animals particularly noted and studied for their intelligence include chimpanzees, bonobos (notably the language-using Kanzi) and other great apes, dolphins, elephants and to some extent parrots, rats and ravens.

Cephalopod intelligence provides an important comparative study. Cephalopods appear to exhibit characteristics of significant intelligence, yet their nervous systems differ radically from those of backboned animals. Vertebrates such as mammals, birds, reptiles and fish have shown a fairly high degree of intellect that varies according to each species. The same is true with arthropods.

g factor in non-humans

Evidence of a general factor of intelligence has been observed in non-human animals. First described in humans, the g factor has since been identified in a number of non-human species.

Cognitive ability and intelligence cannot be measured using the same, largely verbally dependent, scales developed for humans. Instead, intelligence is measured using a variety of interactive and observational tools focusing on innovation, habit reversal, social learning, and responses to novelty. Studies have shown that g is responsible for 47% of the individual variance in cognitive ability measures in primates and between 55% and 60% of the variance in mice (Locurto, Locurto). These values are similar to the accepted variance in IQ explained by g in humans (40–50%).

Plant

It has been argued that plants should also be classified as intelligent based on their ability to sense and model external and internal environments and adjust their morphology, physiology and phenotype accordingly to ensure self-preservation and reproduction.

A counter argument is that intelligence is commonly understood to involve the creation and use of persistent memories as opposed to computation that does not involve learning. If this is accepted as definitive of intelligence, then it includes the artificial intelligence of robots capable of "machine learning", but excludes those purely autonomic sense-reaction responses that can be observed in many plants. Plants are not limited to automated sensory-motor responses, however, they are capable of discriminating positive and negative experiences and of "learning" (registering memories) from their past experiences. They are also capable of communication, accurately computing their circumstances, using sophisticated cost–benefit analysis and taking tightly controlled actions to mitigate and control the diverse environmental stressors.

Artificial

Scholars studying artificial intelligence have proposed definitions of intelligence that include the intelligence demonstrated by machines. Some of these definitions are meant to be general enough to encompass human and other animal intelligence as well. An intelligent agent can be defined as a system that perceives its environment and takes actions which maximize its chances of success. Kaplan and Haenlein define artificial intelligence as "a system's ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation". Progress in artificial intelligence can be demonstrated in benchmarks ranging from games to practical tasks such as protein folding. Existing AI lags humans in terms of general intelligence, which is sometimes defined as the "capacity to learn how to carry out a huge range of tasks".

Mathematician Olle Häggström defines intelligence in terms of "optimization power", an agent's capacity for efficient cross-domain optimization of the world according to the agent's preferences, or more simply the ability to "steer the future into regions of possibility ranked high in a preference ordering". In this optimization framework, Deep Blue has the power to "steer a chessboard's future into a subspace of possibility which it labels as 'winning', despite attempts by Garry Kasparov to steer the future elsewhere." Hutter and Legg, after surveying the literature, define intelligence as "an agent's ability to achieve goals in a wide range of environments". While cognitive ability is sometimes measured as a one-dimensional parameter, it could also be represented as a "hypersurface in a multidimensional space" to compare systems that are good at different intellectual tasks. Some skeptics believe that there is no meaningful way to define intelligence, aside from "just pointing to ourselves".

See also

• Active intellect
• Cattell–Horn–Carroll theory
• Extraterrestrial intelligence, also referred to as Non-Human Intelligence
• Intellect
• Intelligence (journal)
• Knowledge
• Neuroscience and intelligence
• Outline of human intelligence
• Passive intellect
• Superintelligence
• Sapience

References

1. Sharma, Radha R. (2008). Emotional Intelligence from 17th Century to 21st Century: Perspectives and Directions for Future Research. Sage Journals. Vol. 12.
2. White, Margaret B. & Hall, Alfred E. (1980). An overview of intelligence testing. Phi Delta Kappa International. Vol. 58, No. 4, pp. 210-216
3. Buxton, Claude E. (1985). Influences in Psychology: Points of View in the Modern History of Psychology. Academic Press.
4. ^ Stanek, Kevin C.; Ones, Deniz S. (2018), "Taxonomies and Compendia of Cognitive Ability and Personality Constructs and Measures Relevant to Industrial, Work and Organizational Psychology", The SAGE Handbook of Industrial, Work and Organizational Psychology: Personnel Psychology and Employee Performance, 1 Oliver's Yard, 55 City Road London EC1Y 1SP: SAGE Publications Ltd, pp. 366–407, doi:10.4135/9781473914940.n14, ISBN 978-1-4462-0721-5, retrieved 8 January 2024{{citation}}: CS1 maint: location (link)
5. Shettleworth SJ (2010). Cognition, Evolution and Behavior (2ND ed.). New York: Oxford Press.
6. Parise, André Geremia; Gaglianob, Monica; Souza, Gustavo Maia (3 January 2020). "Extended cognition in plants: is it possible?". Plant Signaling & Behavior. 15 (2).
7. ^ Goh, C. H.; Nam, H. G.; Park, Y. S. (2003). "Stress memory in plants: A negative regulation of stomatal response and transient induction of rd22 gene to light in abscisic acid-entrained Arabidopsis plants". The Plant Journal. 36 (2): 240–255. doi:10.1046/j.1365-313X.2003.01872.x. PMID 14535888.
8. ^ Volkov, A. G.; Carrell, H.; Baldwin, A.; Markin, V. S. (2009). "Electrical memory in Venus flytrap". Bioelectrochemistry. 75 (2): 142–147. doi:10.1016/j.bioelechem.2009.03.005. PMID 19356999.
9. Maich, Aloysius (1995). A Hobbes Dictionary. Blackwell. p. 305.
10. Nidditch, Peter. "Foreword". An Essay Concerning Human Understanding. Oxford University Press. p. xxii.
11. Hobbes, Thomas; Molesworth, William (15 February 1839). "Opera philosophica quæ latine scripsit omnia, in unum corpus nunc primum collecta studio et labore Gulielmi Molesworth ." Londoni, apud Joannem Bohn. Archived from the original on 5 November 2013 – via Internet Archive.
12. This paragraph almost verbatim from Goldstein, Sam; Princiotta, Dana; Naglieri, Jack A., eds. (2015). Handbook of Intelligence: Evolutionary Theory, Historical Perspective, and Current Concepts. New York, Heidelberg, Dordrecht, London: Springer. p. 3. ISBN 978-1-4939-1561-3.
13. ^ S. Legg; M. Hutter (2007). "A Collection of Definitions of Intelligence". Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms. Vol. 157. IOS Press. pp. 17–24. ISBN 978-1586037581.
14. Neisser, Ulrich; Boodoo, Gwyneth; Bouchard, Thomas J.; Boykin, A. Wade; Brody, Nathan; Ceci, Stephen J.; Halpern, Diane F.; Loehlin, John C.; Perloff, Robert; Sternberg, Robert J.; Urbina, Susana (1996). "Intelligence: Knowns and unknowns" (PDF). American Psychologist. 51 (2): 77–101. doi:10.1037/0003-066x.51.2.77. ISSN 0003-066X. Archived (PDF) from the original on 28 March 2016. Retrieved 9 October 2014.
15. Binet, Alfred (1916) . "New methods for the diagnosis of the intellectual level of subnormals". The development of intelligence in children: The Binet-Simon Scale. E.S. Kite (Trans.). Baltimore: Williams & Wilkins. pp. 37–90. Archived from the original on 19 June 2010. Retrieved 14 August 2010. originally published as Méthodes nouvelles pour le diagnostic du niveau intellectuel des anormaux. L'Année Psychologique, 11, 191–244
16. Wechsler, D (1944). The measurement of adult intelligence. Baltimore: Williams & Wilkins. ISBN 978-0-19-502296-4. OCLC 219871557.
17. Humphreys, L. G. (1979). "The construct of general intelligence". Intelligence. 3 (2): 105–120. doi:10.1016/0160-2896(79)90009-6.
18. Frames of mind: The theory of multiple intelligences. New York: Basic Books. 1993. ISBN 978-0-465-02510-7. OCLC 221932479.
19. Sternberg RJ; Salter W (1982). Handbook of human intelligence. Cambridge, UK: Cambridge University Press. ISBN 978-0-521-29687-8. OCLC 11226466.
20. Feuerstein, R., Feuerstein, S., Falik, L & Rand, Y. (1979; 2002). Dynamic assessments of cognitive modifiability. ICELP Press, Jerusalem: Israel; Feuerstein, R. (1990). The theory of structural modifiability. In B. Presseisen (Ed.), Learning and thinking styles: Classroom interaction. Washington, DC: National Education Associations
21. S. Legg; M. Hutter (2007). "Universal Intelligence: A Definition of Machine Intelligence". Minds and Machines. 17 (4): 391–444. arXiv:0712.3329. Bibcode:2007arXiv0712.3329L. doi:10.1007/s11023-007-9079-x. S2CID 847021.
22. "TED Speaker: Alex Wissner-Gross: A new equation for intelligence". TED.com. 6 February 2014. Archived from the original on 4 September 2016. Retrieved 7 September 2016.
23. Tirri, Nokelainen (2011). Measuring Multiple Intelligences and Moral Sensitivities in Education. Moral Development and Citizenship Education. Springer. ISBN 978-94-6091-758-5. Archived from the original on 2 August 2017.
24. Colom, Roberto (December 2010). "Human intelligence and brain networks". Dialogues Clin. Neurosci. 12 (4): 489–501. doi:10.31887/DCNS.2010.12.4/rcolom. PMC 3181994. PMID 21319494.
25. ^ Kaufman, Alan S. (2009). IQ Testing 101. Springer. ISBN 978-0-8261-0629-2.
26. Richardson, John T. E. (2003). "Howard Andrew Knox and the origins of performance testing on Ellis Island, 1912-1916". History of Psychology. 6 (2): 143–70. doi:10.1037/1093-4510.6.2.143. PMID 12822554.
27. Schlinger, Henry D. (2003). "The myth of intelligence". The Psychological Record. 53 (1): 15–32.
28. ^ Weiten W (2016). Psychology: Themes and Variations. Cengage Learning. p. 281. ISBN 978-1305856127. IQ tests are valid measures of the kind of intelligence necessary to do well in academic work. But if the purpose is to assess intelligence in a broader sense, the validity of IQ tests is questionable.
29. Bouchard, Thomas J. (1982). "Review of The Intelligence Controversy". The American Journal of Psychology. 95 (2): 346–349. doi:10.2307/1422481. ISSN 0002-9556. JSTOR 1422481.
30. Bouchard, Thomas J. (7 August 2013). "The Wilson Effect: The Increase in Heritability of IQ With Age". Twin Research and Human Genetics. 16 (5): 923–930. doi:10.1017/thg.2013.54. PMID 23919982. S2CID 13747480.
31. Bouchard, Thomas J.; McGue, Matt (January 2003). "Genetic and environmental influences on human psychological differences". Journal of Neurobiology. 54 (1): 4–45. doi:10.1002/neu.10160. PMID 12486697.
32. Bird, Kevin; Jackson, John P.; Winston, Andrew S. (2024). "Confronting Scientific Racism in Psychology: Lessons from Evolutionary Biology and Genetics". American Psychologist. 79 (4): 497–508. doi:10.1037/amp0001228. PMID 39037836. Recent articles claim that the folk categories of race are genetically meaningful divisions, and that evolved genetic differences among races and nations are important for explaining immutable differences in cognitive ability, educational attainment, crime, sexual behavior, and wealth; all claims that are opposed by a strong scientific consensus to the contrary.
33. Nisbett, Richard E.; Aronson, Joshua; Blair, Clancy; Dickens, William; Flynn, James; Halpern, Diane F.; Turkheimer, Eric (2012). "Group differences in IQ are best understood as environmental in origin" (PDF). American Psychologist. 67 (6): 503–504. doi:10.1037/a0029772. ISSN 0003-066X. PMID 22963427. Archived (PDF) from the original on 23 January 2015. Retrieved 22 July 2013.
34. Ceci, Stephen; Williams, Wendy M. (1 February 2009). "Should scientists study race and IQ? YES: The scientific truth must be pursued". Nature. 457 (7231): 788–789. Bibcode:2009Natur.457..788C. doi:10.1038/457788a. PMID 19212385. S2CID 205044224. There is an emerging consensus about racial and gender equality in genetic determinants of intelligence; most researchers, including ourselves, agree that genes do not explain between-group differences.
35. ^ Salovey, Peter; Mayer, John D. (March 1990). "Emotional Intelligence". Imagination, Cognition and Personality. 9 (3): 185–211. doi:10.2190/DUGG-P24E-52WK-6CDG. hdl:10654/36316. ISSN 0276-2366. S2CID 219900460.
36. Mayer, John D.; Salovey, Peter (1 October 1993). "The intelligence of emotional intelligence". Intelligence. 17 (4): 433–442. doi:10.1016/0160-2896(93)90010-3. ISSN 0160-2896.
37. Walker, Ronald E.; Foley, Jeanne M. (December 1973). "Social Intelligence: Its History and Measurement". Psychological Reports. 33 (3): 839–864. doi:10.2466/pr0.1973.33.3.839. ISSN 0033-2941. S2CID 144839425.
38. The Step-By-Step Plan to Building Moral Intelligence. Retrieved 28 April 2016.
39. Beheshtifar, M., Esmaeli, Z., & Moghadam, M. N. (2011). Effect of moral intelligence on leadership. European Journal of Economics, Finance and Administrative Sciences, 43, 6-11.
40. Hector J. Levesque, Common Sense, the Turing Test, and the Quest for Real AI (2017), p. 80.
41. Zentall, Thomas R. (2019). "Animal Intelligence". The Cambridge Handbook of Intelligence. pp. 397–427. doi:10.1017/9781108770422.018. ISBN 978-1-108-75581-8.
42. Coren, Stanley (1995). The Intelligence of Dogs. Bantam Books. ISBN 978-0-553-37452-0. OCLC 30700778.
43. Childs, Casper (27 May 2020). "Words With An Astronaut". Valenti. Codetipi. Retrieved 14 March 2021.
44. Roth, Gerhard (19 December 2015). "Convergent evolution of complex brains and high intelligence". Philos Trans R Soc Lond B Biol Sci. 370 (1684): 20150049. doi:10.1098/rstb.2015.0049. PMC 4650126. PMID 26554042.
45. ^ Reader, S. M., Hager, Y., & Laland, K. N. (2011). "The evolution of primate general and cultural intelligence". Philosophical Transactions of the Royal Society B: Biological Sciences, 366(1567), 1017–1027.
46. Kamphaus, R. W. (2005). Clinical assessment of child and adolescent intelligence. Springer Science & Business Media.
47. Trewavas, Anthony (September 2005). "Green plants as intelligent organisms". Trends in Plant Science. 10 (9): 413–419. Bibcode:2005TPS....10..413T. doi:10.1016/j.tplants.2005.07.005. PMID 16054860.
48. Trewavas, A. (2002). "Mindless mastery". Nature. 415 (6874): 841. Bibcode:2002Natur.415..841T. doi:10.1038/415841a. PMID 11859344. S2CID 4350140.
49. Rensing, L.; Koch, M.; Becker, A. (2009). "A comparative approach to the principal mechanisms of different memory systems". Naturwissenschaften. 96 (12): 1373–1384. Bibcode:2009NW.....96.1373R. doi:10.1007/s00114-009-0591-0. PMID 19680619. S2CID 29195832.
50. Russell, Stuart J.; Norvig, Peter (2003). Artificial Intelligence: A Modern Approach. Englewood Cliffs, N.J.: Prentice Hall. ISBN 978-0-13-790395-5. OCLC 51325314.
51. "Kaplan Andreas and Haelein Michael (2019) Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence, Business Horizons, 62(1)".
52. "How did a company best known for playing games just crack one of science's toughest puzzles?". Fortune. 2020. Retrieved 21 February 2021.
53. Heath, Nick (2018). "What is artificial general intelligence?". ZDNet. Retrieved 21 February 2021.
54. Häggström, Olle (2016). Here be dragons: science, technology and the future of humanity. Oxford: Oxford University Press. pp. 103, 104. ISBN 978-0191035395.
55. Gary Lea (2015). "The Struggle To Define What Artificial Intelligence Actually Means". Popular Science. Retrieved 21 February 2021.
56. Legg, Shane; Hutter, Marcus (30 November 2007). "Universal Intelligence: A Definition of Machine Intelligence". Minds and Machines. 17 (4): 391–444. arXiv:0712.3329. doi:10.1007/s11023-007-9079-x. S2CID 847021.
57. Bostrom, Nick (2014). Superintelligence: Paths, Dangers, Strategies. Oxford: Oxford University Press. "Chapter 4: The Kinetics of an Intelligence Explosion", footnote 9. ISBN 978-0-19-967811-2.
58. "Superintelligence: The Idea That Eats Smart People". idlewords.com. Retrieved 21 February 2021.

Further reading

• Gleick, James, "The Fate of Free Will" (review of Kevin J. Mitchell, Free Agents: How Evolution Gave Us Free Will, Princeton University Press, 2023, 333 pp.), The New York Review of Books, vol. LXXI, no. 1 (18 January 2024), pp. 27–28, 30. "Agency is what distinguishes us from machines. For biological creatures, reason and purpose come from acting in the world and experiencing the consequences. Artificial intelligences – disembodied, strangers to blood, sweat, and tears – have no occasion for that." (p. 30.)
• Hughes-Castleberry, Kenna, "A Murder Mystery Puzzle: The literary puzzle Cain's Jawbone, which has stumped humans for decades, reveals the limitations of natural-language-processing algorithms", Scientific American, vol. 329, no. 4 (November 2023), pp. 81–82. "This murder mystery competition has revealed that although NLP (natural-language processing) models are capable of incredible feats, their abilities are very much limited by the amount of context they receive. This could cause for researchers who hope to use them to do things such as analyze ancient languages. In some cases, there are few historical records on long-gone civilizations to serve as training data for such a purpose." (p. 82.)
• Immerwahr, Daniel, "Your Lying Eyes: People now use A.I. to generate fake videos indistinguishable from real ones. How much does it matter?", The New Yorker, 20 November 2023, pp. 54–59. "If by 'deepfakes' we mean realistic videos produced using artificial intelligence that actually deceive people, then they barely exist. The fakes aren't deep, and the deeps aren't fake. A.I.-generated videos are not, in general, operating in our media as counterfeited evidence. Their role better resembles that of cartoons, especially smutty ones." (p. 59.)
• Press, Eyal, "In Front of Their Faces: Does facial-recognition technology lead police to ignore contradictory evidence?", The New Yorker, 20 November 2023, pp. 20–26.
• Roivainen, Eka, "AI's IQ: ChatGPT aced a test but showed that intelligence cannot be measured by IQ alone", Scientific American, vol. 329, no. 1 (July/August 2023), p. 7. "Despite its high IQ, ChatGPT fails at tasks that require real humanlike reasoning or an understanding of the physical and social world.... ChatGPT seemed unable to reason logically and tried to rely on its vast database of... facts derived from online texts."
• Cukier, Kenneth, "Ready for Robots? How to Think about the Future of AI", Foreign Affairs, vol. 98, no. 4 (July/August 2019), pp. 192–98. George Dyson, historian of computing, writes (in what might be called "Dyson's Law") that "Any system simple enough to be understandable will not be complicated enough to behave intelligently, while any system complicated enough to behave intelligently will be too complicated to understand." (p. 197.) Computer scientist Alex Pentland writes: "Current AI machine-learning algorithms are, at their core, dead simple stupid. They work, but they work by brute force." (p. 198.)
• Domingos, Pedro, "Our Digital Doubles: AI will serve our species, not control it", Scientific American, vol. 319, no. 3 (September 2018), pp. 88–93. "AIs are like autistic savants and will remain so for the foreseeable future.... AIs lack common sense and can easily make errors that a human never would... They are also liable to take our instructions too literally, giving us precisely what we asked for instead of what we actually wanted." (p. 93.)
• Marcus, Gary, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific American, vol. 316, no. 3 (March 2017), pp. 61–63. Marcus points out a so far insuperable stumbling block to artificial intelligence: an incapacity for reliable disambiguation. "irtually every sentence is ambiguous, often in multiple ways. Our brain is so good at comprehending language that we do not usually notice." A prominent example is the "pronoun disambiguation problem" ("PDP"): a machine has no way of determining to whom or what a pronoun in a sentence—such as "he", "she" or "it"—refers.
• Sternberg, Robert J.; Kaufman, Scott Barry, eds. (2011). The Cambridge Handbook of Intelligence. Cambridge: Cambridge University Press. doi:10.1017/9781108770422. ISBN 978-0521739115. S2CID 241027150.
• Mackintosh, N. J. (2011). IQ and Human Intelligence (second ed.). Oxford: Oxford University Press. ISBN 978-0-19-958559-5.
• Flynn, James R. (2009). What Is Intelligence: Beyond the Flynn Effect (expanded paperback ed.). Cambridge: Cambridge University Press. ISBN 978-0-521-74147-7.
  • Lay summary in: C Shalizi (27 April 2009). "What Is Intelligence? Beyond the Flynn Effect". University of Michigan (Review). Archived from the original on 14 June 2010.
• Stanovich, Keith (2009). What Intelligence Tests Miss: The Psychology of Rational Thought. New Haven (CT): Yale University Press. ISBN 978-0-300-12385-2.
  • Lay summary in: Jamie Hale. "What Intelligence Tests Miss". Psych Central (Review). Archived from the original on 24 December 2013.
• Blakeslee, Sandra; Hawkins, Jeff (2004). On intelligence. New York: Times Books. ISBN 978-0-8050-7456-7. OCLC 55510125.
• Bock, Gregory; Goode, Jamie; Webb, Kate, eds. (2000). The Nature of Intelligence. Novartis Foundation Symposium 233. Vol. 233. Chichester: Wiley. doi:10.1002/0470870850. ISBN 978-0471494348.
  • Lay summary in: William D. Casebeer (30 November 2001). "The Nature of Intelligence". Mental Help (Review). Archived from the original on 26 May 2013.
• Wolman, Benjamin B., ed. (1985). Handbook of Intelligence. consulting editors: Douglas K. Detterman, Alan S. Kaufman, Joseph D. Matarazzo. New York: Wiley. ISBN 978-0-471-89738-5.
• Terman, Lewis Madison; Merrill, Maude A. (1937). Measuring intelligence: A guide to the administration of the new revised Stanford-Binet tests of intelligence. Riverside textbooks in education. Boston (MA): Houghton Mifflin. OCLC 964301.
• Binet, Alfred; Simon, Th. (1916). The development of intelligence in children: The Binet-Simon Scale. Publications of the Training School at Vineland New Jersey Department of Research No. 11. E. S. Kite (Trans.). Baltimore: Williams & Wilkins. p. 1. Retrieved 18 July 2010.

External links

• Intelligence on In Our Time at the BBC
• History of Influences in the Development of Intelligence Theory and Testing. Archived 11 November 2007 at the Wayback Machine. Developed by Jonathan Plucker at Indiana University.
• The Limits of Intelligence: The laws of physics may well prevent the human brain from evolving into an ever more powerful thinking machine. By Douglas Fox in Scientific American, 14 June 2011.
• A Collection of Definitions of Intelligence

• Intelligence
• Developmental psychology
• Psychological testing
• Differential psychology