Intelligence has been defined in many ways: the capacity for abstraction, logic, understanding, self-awareness, learning, emotional knowledge, , 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.[Sharma, Radha R. (2008). Emotional Intelligence from 17th Century to 21st Century: Perspectives and Directions for Future Research. Sage Journals. Vol. 12.]
The term rose to prominence during the early 1900s.[White, Margaret B. & Hall, Alfred E. (1980). An overview of intelligence testing. Phi Delta Kappa International. Vol. 58, No. 4, pp. 210-216][Buxton, Claude E. (1985). Influences in Psychology: Points of View in the Modern History of Psychology. Academic Press.] Most believe that intelligence can be divided into various domains or competencies.
Intelligence has been long-studied in , and across numerous disciplines. It has also been observed in the Animal cognition.
Etymology
The word
derives from the Latin or
, which in turn stem from the verb , 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
metaphysics and
cosmology theories of
teleology 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.
[This paragraph almost verbatim from ]
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 , published in 1995 by the Board of Scientific Affairs of the American Psychological Association, states:
Psychologists and learning researchers also have suggested definitions of intelligence such as the following:
|
|
| 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-oriented 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".[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] |
| 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", |
| Alexander Wissner-Gross | F = T ∇ S |
Human
Human intelligence is the intellectual power of humans, which is marked by complex
cognition 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
learning,
Concept learning,
understanding, and
reason, including the capacities to recognize patterns, innovate,
planning,
problem solving, 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.
Today, most psychologists agree that IQ measures at least some aspects of human intelligence, particularly the ability to thrive in an academic context.
There is debate about the heritability of IQ, that is, what proportion of differences in IQ test performance between individuals are explained by Genetics or environmental factors.
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
and motivations of others and oneself in social situations. It is thought to be distinct from 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.
[ The Step-By-Step Plan to Building Moral Intelligence . Retrieved 28 April 2016.] It is considered a distinct form of intelligence, independent to both emotional and cognitive intelligence.
[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.]
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:
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.
Cephalopod intelligence provides an important comparative study. appear to exhibit characteristics of significant intelligence, yet their differ radically from those of backboned animals. Vertebrates such as , , and fish have shown a fairly high degree of intellect that varies according to each species. The same is true with .
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.
[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.]
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[Kamphaus, R. W. (2005). Clinical assessment of child and adolescent intelligence. Springer Science & Business Media.]
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,
plant 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.
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."
See also
Further reading
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James Gleick, "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 motivation 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.)
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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 difficulties for researchers who hope to use them to do things such as analyze . In some cases, there are few historical records on long-gone to serve as training data for such a purpose." (p. 82.)
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Daniel Immerwahr, "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 , especially smutty ones." (p. 59.)
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Eyal Press, "In Front of Their Faces: Does facial-recognition technology lead police to ignore contradictory evidence?", The New Yorker, 20 November 2023, pp. 20–26.
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Eka Roivainen, "AI's IQ: ChatGPT aced a standard 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."
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Kenneth Cukier, "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 machine learning are, at their core, dead simple stupid. They work, but they work by brute force." (p. 198.)
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Pedro Domingos, "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 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.)
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Gary Marcus, "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. "Virtually every sentence that is ambiguity, 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.
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