Intelligence Operations By Type

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 both non-human animals and plants despite controversy as to whether some of these forms of life exhibit intelligence. 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

The definition of intelligence is controversial, varying in what its abilities are and whether or not it is quantifiable.

In 1994 the "Mainstream Science on Intelligence" was published, as an op-ed statement in the ''Wall Street Journal'', as a response to controversy over the book ''The Bell Curve'' which proposed policy changes based on purported connections between race and intelligence. It was signed by fifty-two researchers, out of 131 total invited to sign, with 48 explicitly refusing to sign. The op-ed described intelligence thus:

From '' Intelligence: Knowns and Unknowns'' (1995), a report published by the Board of Scientific Affairs of the American Psychological Association, also in response to controversy over ''The Bell Curve'':

Besides those definitions, psychology and learning researchers also have suggested definitions of intelligence such as the following:

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 enables humans to experience and think.

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. There have been various attempts to quantify intelligence via testing, such as the Intelligence Quotient (IQ) test. However, many people disagree with the validity of IQ tests; stating that they cannot accurately measure intelligence.

There is debate about if human intelligence is based on hereditary factors or if it is based on environmental factors. Hereditary intelligence is the theory that intelligence is fixed upon birth and does not grow. Environmental intelligence is the theory that intelligence is developed throughout life depending on the environment around the person. An environment that cultivates intelligence is one that challenges the person's cognitive abilities.

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.'
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.

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''. 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. The general factor of intelligence, or ''g'' factor, is a psychometric construct that summarizes the correlations observed between an individual's scores on a wide range of cognitive abilities. 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 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

References

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 ifficultiesfor 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 tandard intelligencetest 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. " rtually every sentence hat people generateis 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.
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External links

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History of Influences in the Development of Intelligence Theory and Testing
– 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

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Developmental psychology
Psychological testing
Differential psychology