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Intelligence assessment is the development of forecasts of behaviour or recommended courses of action to the leadership of an organization, based on a wide range of available information sources both overt and covert. Assessments are developed in response to requirements declared by the leadership in order to inform decision making. Assessment may be carried out on behalf of a state, military or commercial organisation with a range of available sources of information available to each.

An intelligence assessment reviews both available information and previous assessments for relevance and currency, where additional information is required some collection may be directed by the analyst.

Process[link]

The Intelligence Cycle

Intelligence assessment is based on a customer requirement which may be a standing requirement or tailored to a specific circumstance, a Request for Information (RFI). The "requirement" is passed in to the assessing agency and worked through the intelligence cycle, a structured method for responding to the request for information.

The RFI may indicate in what format the requester prefers to consume the product.

The RFI is reviewed by a Requirements Manager who will then direct appropriate tasks to respond to the request. This will involve a review of existing material, the tasking of new analytical product or the collection of new information to inform an analysis.

New information may be collected through one or more of the various collection disciplines; human source, electronic and communications intercept, imagery or open sources. The nature of the RFI and the urgency placed on it may indicate that some collection types are unsuitable due to the time taken to collect or validate the information gathered. Intelligence gathering disciplines and the sources and methods used are often highly classified and compartmentalised with analysts requiring an appropriate high level of security clearance.

The process of taking known information about situations and entities of importance to the RFI, characterising what is known and attempting to forecast future events is termed "all source" assessment, analysis or processing. The analyst uses multiple sources to mutually corroborate, or exclude, the information collected, reaching a conclusion along with a measure of confidence around that conclusion.

Where sufficient current information already exists the analysis may be tasked directly without reference to further collection.

The analysis is then communicated back to the requester in the format directed, although subject to the constraints on both the RFI and the methods used in the analysis may be made available for other uses as well and disseminated accordingly. The analysis will be written to a defined classification level with alternative versions potentially available at a number of classification levels for further dissemination.

Target centric intelligence cycle[link]

Target centric intelligence cycle

Where the subject of the assessment is clearly identifiable and provisions exist to make some form of intervention against that subject the target centric assessment approach may be used. This approach, known as F3EA, is complementary to the intelligence cycle and focussed on the intervention itself.

The subject for action, or target, is identified and efforts are initially made to find the target for further development. This activity will identify where intervention against the target will have the most beneficial effects.

When the decision is made to intervene action is taken to fix the target, confirming that the intervention will have a high probability of success and restricting the ability of the target to take independent action.

During the finish stage the intervention is executed, potentially an arrest or detention or the placement of other collection methods.

Following the intervention exploitation of the target is carried out which may lead to further refinement of the process for related targets. the output from the exploit stage will also be passed into other intelligence assessment activities.

See also[link]

• List of intelligence gathering disciplines
• Military intelligence

Further reading[link]

Surveys

• Andrew, Christopher. For the President's Eyes Only: Secret Intelligence and the American Presidency from Washington to Bush (1996)
• Black, Ian and Morris, Benny Israel's Secret Wars: A History of Israel's Intelligence Services (1991)
• Bungert, Heike et al. eds. Secret Intelligence in the Twentieth Century (2003) essays by scholars
• Dulles, Allen W. The Craft of Intelligence: America's Legendary Spy Master on the Fundamentals of Intelligence Gathering for a Free World (2006)
• Kahn, David The Codebreakers: The Comprehensive History of Secret Communication from Ancient Times to the Internet (1996), 1200 pages
• Lerner, K. Lee and Brenda Wilmoth Lerner, eds. Encyclopedia of Espionage, Intelligence and Security (2003), 1100 pages. 850 articles, strongest on technology
• Odom, Gen. William E. Fixing Intelligence: For a More Secure America, Second Edition (Yale Nota Bene) (2004)
• O'Toole, George. Honorable Treachery: A History of U.S. Intelligence, Espionage, Covert Action from the American Revolution to the CIA (1991)
• Owen, David. Hidden Secrets: A Complete History of Espionage and the Technology Used to Support It (2002), popular
• Richelson, Jeffery T. A Century of Spies: Intelligence in the Twentieth Century (1997)
• Richelson, Jeffery T. The U.S. Intelligence Community (4th ed. 1999)
• Shulsky, Abram N. and Schmitt, Gary J. "Silent Warfare: Understanding the World of Intelligence" (3rd ed. 2002), 285 pages
• West, Nigel. MI6: British Secret Intelligence Service Operations 1909–1945 (1983)
• West, Nigel. Secret War: The Story of SOE, Britain's Wartime Sabotage Organization (1992)
• Wohlstetter, Roberta. Pearl Harbor: Warning and Decision (1962)

World War I

• Beesly, Patrick. Room 40. (1982). Covers the breaking of German codes by RN intelligence, including the Turkish bribe, Zimmermann telegram, and failure at Jutland.
• May, Ernest (ed.) Knowing One's Enemies: Intelligence Assessment before the Two World Wars (1984)
• Tuchman, Barbara W. The Zimmermann Telegram (1966)
• Yardley, Herbert O. American Black Chamber (2004)

World War II

1931–1945

• Babington Smith, Constance. Air Spy: the Story of Photo Intelligence in World War II (1957) - originally published as Evidence in Camera in the UK
• Beesly, Patrick. Very Special Intelligence: the Story of the Admiralty's Operational Intelligence Centre, 1939–1945 (1977)
• Hinsley, F. H. British Intelligence in the Second World War (1996) (abridged version of multivolume official history)
• Jones, R. V. Most Secret War: British Scientific Intelligence 1939–1945 (2009)
• Kahn, David. Hitler's Spies: German Military Intelligence in World War II (1978)
• Kahn, David. Seizing the Enigma: the Race to Break the German U-Boat Codes, 1939–1943 (1991)
• Kitson, Simon. The Hunt for Nazi Spies: Fighting Espionage in Vichy France, Chicago: University of Chicago Press, (2008). ISBN 978-0-226-43893-1
• Lewin, Ronald. The American Magic: Codes, Ciphers and the Defeat of Japan (1982)
• May, Ernest (ed.) Knowing One's Enemies: Intelligence Assessment before the Two World Wars (1984)
• Smith, Richard Harris. OSS: the Secret History of America's First Central Intelligence Agency (2005)
• Stanley, Roy M. World War II Photo Intelligence (1981)
• Stevenson, William. A Man Called Intrepid: The Incredible WWII Narrative of the Hero Whose Spy Network and Secret Diplomacy Changed the Course of History (2009)
• Wark, Wesley K. The Ultimate Enemy: British Intelligence and Nazi Germany, 1933–1939 (1985)
• Wark, Wesley K. "Cryptographic Innocence: the Origins of Signals Intelligence in Canada in the Second World War", in: Journal of Contemporary History 22 (1987)

Cold War Era

1945–1991

• Aldrich, Richard J. The Hidden Hand: Britain, America and Cold War Secret Intelligence (2002).
• Ambrose, Stephen E. Ike's Spies: Eisenhower and the Intelligence Establishment (1981).
• Andrew, Christopher and Vasili Mitrokhin. The Sword and the Shield: The Mitrokhin Archive and the Secret History of the KGB (1999)
• Andrew, Christopher, and Oleg Gordievsky. KGB: The Inside Story of Its Foreign Operations from Lenin to Gorbachev (1990).
• Bogle, Lori, ed. Cold War Espionage and Spying (2001), essays by scholars
• Boiling, Graham. Secret Students on Parade: Cold War Memories of JSSL, CRAIL, PlaneTree, 2005. ISBN 1-84294-169-0
• Dorril, Stephen. MI6: Inside the Covert World of Her Majesty's Secret Intelligence Service (2000).
• Dziak, John J. Chekisty: A History of the KGB (1988)
• Elliott, Geoffrey and Shukman, Harold. Secret Classrooms. An Untold Story of the Cold War. London, St Ermin’s Press, Revised Edition, 2003. ISBN 1-903608-13-9
• Koehler, John O. Stasi: The Untold Story of the East German Secret Police (1999)
• Ostrovsky, Viktor By Way of Deception (1990)
• Persico, Joseph. Casey: The Lives and Secrets of William J. Casey-From the OSS to the CIA (1991)
• Prados, John. Presidents' Secret Wars: CIA and Pentagon Covert Operations Since World War II (1996)
• Rositzke, Harry. The CIA's Secret Operations: Espionage, Counterespionage, and Covert Action (1988)
• Trahair, Richard C. S. Encyclopedia of Cold War Espionage, Spies and Secret Operations (2004), by an Australian scholar; contains excellent historiographical introduction
• Weinstein, Allen, and Alexander Vassiliev. The Haunted Wood: Soviet Espionage in America—The Stalin Era (1999).

External links[link]

• Intelligence Literature: Suggested Reading List (CIA)
• The Relations between the CIA and the Executive Power since 2001, ISRIA, February 5, 2006.
• The Role of Open Sources in Intelligence, ISRIA, December 31, 2005.
• Read Congressonal Research Service (CRS) Reports regarding Intelligence issues
• The Literature of Intelligence: A Bibliography of Materials, with Essays, Reviews, and Comments by J. Ransom Clark, Emeritus Professor of Political Science, Muskingum College
• Proposal for a Privacy Protection Guideline on Secret Personal Data Gathering and Transborder Flows of Such Data in the Fight against Terrorism and Serious Crime
• Intelligence Online Investigative news and reporting on intelligence activities worldwide, including secret service and industrial espionage (subscription required).

Intelligence has been defined in many different ways, including the abilities, but not limited to, abstract thought, understanding, self-awareness, communication, reasoning, learning, having emotional knowledge, retaining, planning, and problem solving.

Intelligence is most widely studied in humans, but has also been observed in animals and plants. Artificial intelligence is the intelligence of machines or the simulation of intelligence in machines.

Numerous definitions of and hypotheses about intelligence have been proposed since before the twentieth century, with no consensus reached by scholars. Within the discipline of psychology, various approaches to human intelligence have been adopted. The psychometric approach is especially familiar to the general public, as well as being the most researched and by far the most widely used in practical settings.^[1]

History of the term[link]

Intelligence derives from the Latin verb intelligere which derives from inter-legere meaning to "pick out" or discern. A form of this verb, intellectus, became the medieval technical term for understanding, and a translation for the Greek philosophical term nous. This term was however 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 entire approach to the study of nature was strongly rejected by the early modern philosophers such as Francis Bacon, Thomas Hobbes, John Locke, and David Hume, all of whom preferred the word "understanding" in their English philosophical works.^[2][3] 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.^[4] The term "intelligence" has therefore become less common in English language philosophy, but it has later been taken up (with the scholastic theories which it now implies) in more contemporary psychology.

Definitions[link]

The definition of intelligence is controversial. Groups of scientists have stated the following:

1. from "Mainstream Science on Intelligence" (1994), an editorial statement by fifty-two researchers:

   A very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, a narrow academic skill, or test-taking smarts. Rather, it reflects a broader and deeper capability for comprehending our surroundings—"catching on," "making sense" of things, or "figuring out" what to do.^[5]

2. from "Intelligence: Knowns and Unknowns" (1995), a report published by the Board of Scientific Affairs of the American Psychological Association:

   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.^[6][7]

Besides the foregoing definitions, these psychology and learning researchers also have defined intelligence as:

What is considered intelligent varies with culture. For example, when asked to sort, the Kpelle people take a functional approach. A Kpelle participant stated "the knife goes with the orange because it cuts it." When asked how a fool would sort, they sorted linguistically, putting the knife with other implements and the orange with other foods, which is the style considered intelligent in other cultures.^[16]

Human intelligence[link]

Psychometrics[link]

The IQs of a large enough population are calculated so that they conform^[17] to a normal distribution.

The approach to understanding intelligence with the most supporters and published research over the longest period of time is based on psychometric testing. It is also by far the most widely used in practical settings. Intelligence quotient (IQ) tests include the Stanford-Binet, Raven's Progressive Matrices, the Wechsler Adult Intelligence Scale and the Kaufman Assessment Battery for Children. There are also psychometric tests that are not intended to measure intelligence itself but some closely related construct such as scholastic aptitude. In the United States examples include the SSAT, the SAT, the ACT, the GRE, the MCAT, the LSAT, and the GMAT.^[1]

Intelligence tests are widely used in educational, business, and military settings due to their efficacy in predicting behavior. IQ and g (discussed in the next section) are correlated with many important social outcomes—individuals with low IQs are more likely to be divorced, have a child out of marriage, be incarcerated, and need long-term welfare support, while individuals with high IQs are associated with more years of education, higher status jobs and higher income.^[18] Intelligence is significantly correlated with successful training and performance outcomes, and IQ/g is the single best predictor of successful job performance.^[1][19]

[edit] General intelligence factor or g

There are many different kinds of IQ tests using a wide variety of test tasks. Some tests consist of a single type of task, others rely on a broad collection of tasks with different contents (visual-spatial, verbal, numerical) and asking for different cognitive processes (e.g., reasoning, memory, rapid decisions, visual comparisons, spatial imagery, reading, and retrieval of general knowledge). The psychologist Charles Spearman early in the 20th century carried out the first formal factor analysis of correlations between various test tasks. He found a trend for all such tests to correlate positively with each other, which is called a positive manifold. Spearman found that a single common factor explained the positive correlations among test. Spearman named it g for "general intelligence factor". He interpreted it as the core of human intelligence that, to a larger or smaller degree, influences success in all cognitive tasks and thereby creates the positive manifold. This interpretation of g as a common cause of test performance is still dominant in psychometrics. An alternative interpretation was recently advanced by van der Maas and colleagues.^[20] Their mutualism model assumes that intelligence depends on several independent mechanisms, none of which influences performance on all cognitive tests. These mechanisms support each other so that efficient operation of one of them makes efficient operation of the others more likely, thereby creating the positive manifold.

IQ tasks and tests can be ranked by how highly they load on the g factor. Tests with high g-loadings are those that correlate highly with most other tests. One comprehensive study investigating the correlations between a large collection of tests and tasks^[21] has found that the Raven's Progressive Matrices have a particularly high correlation with most other tests and tasks. The Raven's is a test of inductive reasoning with abstract visual material. It consists of a series of problems, sorted approximately by increasing difficulty. Each problem presents a 3 x 3 matrix of abstract designs with one empty cell; the matrix is constructed according to a rule, and the person must find out the rule to determine which of 8 alternatives fits into the empty cell. Because of its high correlation with other tests, the Raven's Progressive Matrices are generally acknowledged as a good indicator of general intelligence. This is problematic, however, because there are substantial gender differences on the Raven's,^[22] which are not found when g is measured directly by computing the general factor from a broad collection of tests.^[23]

Historical psychometric theories[link]

Several different theories of intelligence have historically been important. Often they emphasized more factors than a single one like in g

Cattell-Horn-Carroll theory[link]

Many of the broad, recent IQ tests have been greatly influenced by the Cattell-Horn-Carroll theory. It is argued to reflect much of what is known about intelligence from research. A hierarchy of factors is used. g is at the top. Under it there are 10 broad abilities that in turn are subdivided into 70 narrow abilities. The broad abilities are:^[24]

• Fluid Intelligence (Gf): includes the broad ability to reason, form concepts, and solve problems using unfamiliar information or novel procedures.
• Crystallized Intelligence (Gc): includes the breadth and depth of a person's acquired knowledge, the ability to communicate one's knowledge, and the ability to reason using previously learned experiences or procedures.
• Quantitative Reasoning (Gq): the ability to comprehend quantitative concepts and relationships and to manipulate numerical symbols.
• Reading & Writing Ability (Grw): includes basic reading and writing skills.
• Short-Term Memory (Gsm): is the ability to apprehend and hold information in immediate awareness and then use it within a few seconds.
• Long-Term Storage and Retrieval (Glr): is the ability to store information and fluently retrieve it later in the process of thinking.
• Visual Processing (Gv): is the ability to perceive, analyze, synthesize, and think with visual patterns, including the ability to store and recall visual representations.
• Auditory Processing (Ga): is the ability to analyze, synthesize, and discriminate auditory stimuli, including the ability to process and discriminate speech sounds that may be presented under distorted conditions.
• Processing Speed (Gs): is the ability to perform automatic cognitive tasks, particularly when measured under pressure to maintain focused attention.
• Decision/Reaction Time/Speed (Gt): reflect the immediacy with which an individual can react to stimuli or a task (typically measured in seconds or fractions of seconds; not to be confused with Gs, which typically is measured in intervals of 2–3 minutes). See Mental chronometry.

Modern tests do not necessarily measure of all of these broad abilities. For example, Gq and Grw may be seen as measures of school achievement and not IQ.^[24] Gt may be difficult to measure without special equipment.

g was earlier often subdivided into only Gf and Gc which were though to correspond to the Nonverbal or Performance subtests and Verbal subtests in earlier versions of the popular Wechsler IQ test. More recent research has shown the situation to be more complex.^[24]

Controversies[link]

While not necessarily a dispute about the psychometric approach itself, there are several controversies regarding the results from psychometric research. Examples are the role of genetics vs. environment, the causes of average group differences, or the Flynn effect.

One criticism has been against the early research such as craniometry.^[25] A reply has been that drawing conclusions from early intelligence research is like condemning the auto industry by criticizing the performance of the Model T.^[26]

Several critics, such as Stephen Jay Gould, have been critical of g, seeing it as a statistical artifact, and that IQ tests instead measure a number of unrelated abilities.^[25][27] The American Psychological Association's report "Intelligence: Knowns and Unknowns" stated that IQ tests do correlate and that the view that g is a statistical artifact is a minority one.

Other theories[link]

There are critics of IQ, who do not dispute the stability of IQ test scores or the fact that they predict certain forms of achievement rather effectively. They do argue, however, that to base a concept of intelligence on IQ test scores alone is to ignore many important aspects of mental ability.^[1]

On the other hand, Linda S. Gottfredson (2006) has argued that the results of thousands of studies support the importance of IQ for school and job performance (see also the work of Schmidt & Hunter, 2004). IQ also predicts or correlates with numerous other life outcomes. In contrast, empirical support for non-g intelligences is lacking or very poor. She argued that despite this the ideas of multiple non-g intelligences are very attractive to many due to the suggestion that everyone can be smart in some way.^[28]

Multiple intelligences[link]

Howard Gardner's theory of multiple intelligences is based on studies not only of normal children and adults but also by studies of gifted individuals (including so-called "savants"), of persons who have suffered brain damage, of experts and virtuosos, and of individuals from diverse cultures. This led Gardner to break intelligence down into at least eight different components: logical, linguistic, spatial, musical, kinesthetic, interpersonal, intrapersonal, naturalist and existential intelligences. He argues that psychometric tests address only linguistic and logical plus some aspects of spatial intelligence.^[1] A major criticism of Gardner's theory is that it has never been tested, or subjected to peer review, by Gardner or anyone else, and indeed that it is unfalsifiable.^[29] Others (e.g. Locke, 2005) have suggested that recognizing many specific forms of intelligence (specific aptitude theory) implies a political—rather than scientific—agenda, intended to appreciate the uniqueness in all individuals, rather than recognizing potentially true and meaningful differences in individual capacities. Schmidt and Hunter (2004) suggest that the predictive validity of specific aptitudes over and above that of general mental ability, or "g", has not received empirical support.

Howard Gardner mentions in his Multiple Intelligences The Theory in Practice^[30] book, briefly about his main seven intelligences he introduced. In his book, he starts off describing Linguistic and Logical Intelligence because he believed that in society, we have put these two intelligences on a pedestal. However, Gardner believes all of the intelligences he found are equal. Note: At the time of the publication of Gardner's book Multiple Intelligences The Theory in Practice, naturalist and existential intelligences were not mentioned.

Linguistic Intelligence: The kind of ability exhibited in its fullest form, perhaps, by poets.

Logical-Mathematics Intelligence: Is logical and mathematical ability, as well as scientific ability. Howard Gardner believed Jean Piaget may have thought he was studying all intelligence, but in truth, Piaget was really only focusing on the logical mathematical intelligence.

Spatial Intelligence: The ability to form a mental model of a spatial world and to be able to maneuver and operate using that model.

Musical Intelligence: Leonard Bernstein had lots of it; Mozart, presumably, had even more.

Bodily-kinesthetic intelligence: The ability to solve problems or to fashion products using one's whole body, or parts of the body. For example, dancers, athletes, surgeons, craftspeople, etc.

Interpersonal Intelligence: The ability to see things from the perspective of others, or to understand people in the sense of empathy. Strong interpersonal intelligence would be an asset in those who are teachers, politicians, clinicians, religious leaders, etc.

Intrapersonal Intelligence: A correlative ability, turned inward. It is a capacity to form an accurate, veridical model of oneself and to be able to use that model to operate effectively in life.

Triarchic theory of intelligence[link]

Robert Sternberg proposed the triarchic theory of intelligence to provide a more comprehensive description of intellectual competence than traditional differential or cognitive theories of human ability.^[31] The triarchic theory describes three fundamental aspects of intelligence. Analytic intelligence comprises the mental processes through which intelligence is expressed. Creative intelligence is necessary when an individual is confronted with a challenge that is nearly, but not entirely, novel or when an individual is engaged in automatizing the performance of a task. Practical intelligence is bound in a sociocultural milieu and involves adaptation to, selection of, and shaping of the environment to maximize fit in the context. The triarchic theory does not argue against the validity of a general intelligence factor; instead, the theory posits that general intelligence is part of analytic intelligence, and only by considering all three aspects of intelligence can the full range of intellectual functioning be fully understood.

More recently, the triarchic theory has been updated and renamed the Theory of Successful Intelligence by Sternberg.^[32][33] Intelligence is defined as an individual's assessment of success in life by the individual's own (idiographic) standards and within the individual's sociocultural context. Success is achieved by using combinations of analytical, creative, and practical intelligence. The three aspects of intelligence are referred to as processing skills. The processing skills are applied to the pursuit of success through what were the three elements of practical intelligence: adapting to, shaping of, and selecting of one's environments. The mechanisms that employ the processing skills to achieve success include utilizing one's strengths and compensating or correcting for one's weaknesses.

Sternberg's theories and research on intelligence remain contentious within the scientific community.^{[34][35][36][37]}

PASS Theory of Intelligence[link]

Based on A. R. Luria’s (1966)^[38] seminal work on the modularization of brain function, and supported by decades of neuroimaging research, the PASS Theory of Intelligence^[39] proposes that cognition is organized in three systems and four processes. The first is the Planning, which involves executive functions responsible for controlling and organizing behavior, selecting and constructing strategies, and monitoring performance. The second is the Attention process, which is responsible for maintaining arousal levels and alertness, and ensuring focus on relevant stimuli. The next comprise two processes ,Simultaneous and Successive processing to encode, transform, and retain information. Simultaneous processing is engaged when the relationship between items and their integration into whole units of information is required. Examples of this include recognizing figures, such as a triangle within a circle vs. a circle within a triangle, or the difference between ‘he had a shower before breakfast’ and ‘he had breakfast before a shower.’ Successive processing is required for organizing separate items in a sequence such as remembering a sequence of words or actions exactly in the order in which they had just been presented. These four processes are functions of four areas of the brain. Planning is broadly located in the front part of our brains, the frontal lobe. Attention and arousal are combined functions of the frontal lobe and the lower parts of the cortex, although the parietal lobes are also involved in attention as well. Simultaneous processing and Successive processing occur in the posterior region or the back of the brain. Simultaneous processing is broadly associated with the occipital and the parietal lobes while Successive processing is broadly associated with the frontal-temporal lobes. The PASS (Planning/Attention/Simultaneous/Successive) theory is heavily indebted to both Luria (1966^[38], 1973^[40]), and studies in cognitive psychology involved in promoting a better look at intelligence^[41].

Piaget's theory and Neo-Piagetian theories[link]

In Piaget's theory of cognitive development the focus is not on mental abilities but rather on a child's mental models of the world. As a child develops, increasingly more accurate models of the world are developed which enable the child to interact with the world better. One example being object permanence where the child develops a model where objects continue to exist even when they cannot be seen, heard, or touched.

Piaget's theory described four main stages and many sub-stages in the development. Degree of progress through these is correlated with but is not identical with psychometric IQ.^[42][43]

Neo-Piagetian theories of cognitive development expand Piaget's theory in various ways such as also considering psychometric-like factors such as processing speed and working memory, "hypercognitive" factors like self-monitoring, more stages, and more consideration on how progress may vary in different domains such as spatial or social.^[44][45]

Piaget's theory has been criticized for the age of appearance of a new model of the world, such as object permanence, being dependent on how the testing is done (see the article on object permanence). More generally, the theory may be very difficult to test empirically due to the difficulty of proving or not proving that a mental model is the explanation for the results of the testing.^[46]

Latent inhibition[link]

Latent inhibition has been related to elements of intelligence, namely creativity and genius.

Evolution of intelligence[link]

The ancestors of modern humans evolved large and complex brains exhibiting an ever-increasing intelligence through a long evolutionary process (see Homininae). Different explanations have been proposed.

Improving intelligence[link]

Eugenics is a social philosophy which advocates the improvement of human hereditary traits through various forms of intervention.^[47] Conscious efforts to influence intelligence raise ethical issues. Eugenics has variously been regarded as meritorious or deplorable in different periods of history, falling greatly into disrepute after the defeat of Nazi Germany in World War II.^{[citation needed]}

Neuroethics considers the ethical, legal and social implications of neuroscience, and deals with issues such as the difference between treating a human neurological disease and enhancing the human brain, and how wealth impacts access to neurotechnology. Neuroethical issues interact with the ethics of human genetic engineering.

Because intelligence appears to be at least partly dependent on brain structure and the genes shaping brain development, it has been proposed that genetic engineering could be used to enhance the intelligence, a process sometimes called biological uplift in science fiction. Experiments on mice have demonstrated superior ability in learning and memory in various behavioral tasks.^[48]

IQ leads to greater success in education ^[49], but independently education raises IQ scores ^[50]. Attempts to raise IQ with brain training have led to increases on the training tasks – for instance working memory – but it is as yet unclear if these generalise to increased intelligence per se.^[51]

Transhumanist theorists study the possibilities and consequences of developing and using techniques to enhance human abilities and aptitudes, and individuals ameliorating what they regard as undesirable and unnecessary aspects of the human condition.

According to Rosemary Hopcroft, a sociologist at the University of North Carolina at Charlotte, intelligence is negatively linked with sexual frequency (people with higher levels of education often have lower numbers of sexual partners). ^[52]

Animal and plant intelligence[link]

The common chimpanzee can use tools. This chimpanzee is using a stick in order to get food.

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 mathematical and language abilities. Some challenges in this area are defining intelligence so that it means the same thing across species (e.g. comparing intelligence between literate humans and illiterate animals), and then operationalizing a measure that accurately compares mental ability across different species and contexts.

Wolfgang Köhler's pioneering research on the intelligence of apes is a classic example of research in this area. Stanley Coren's book, The Intelligence of Dogs^{[unreliable source?]} is a notable popular book on the topic.^[53] Nonhuman 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. Controversy exists over the extent to which these judgments of intelligence are accurate.^{[citation needed]}

Cephalopod intelligence also provides important comparative study. Cephalopods appear to exhibit characteristics of significant intelligence, yet their nervous systems differ radically from those of most other notably intelligent life-forms (mammals and birds).

It has been argued that plants should also be classified as being intelligent based on their ability to sense the environment and adjust their morphology, physiology and phenotype accordingly.^[54][55]

Artificial intelligence[link]

Artificial intelligence (or AI) is both the intelligence of machines and the branch of computer science which aims to create it, through "the study and design of intelligent agents"^[56] or "rational agents", where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success.^[57] Achievements in artificial intelligence include constrained and well-defined problems such as games, crossword-solving and optical character recognition. General intelligence or strong AI has not yet been achieved and is a long-term goal of AI research.

Among the traits that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception, and the ability to move and manipulate objects.^[56][57] In the field of artificial intelligence there is no consensus on how closely the brain should be simulated.

See also[link]

	Thinking portal
	Logic portal
	Psychology portal

• Active intellect
• Cognitive epidemiology
• Downing effect
• Educational psychology
• Environment and intelligence
• Fertility and intelligence
• Flynn effect
• Health and intelligence
• Height and intelligence
• Heritability of IQ
• History of the race and intelligence controversy
• Individual differences psychology
• Intellectual giftedness
• Intelligence (journal)
• Knowledge
• Malleable intelligence
• Nations and intelligence
• Neuroscience and intelligence
• Passive intellect
• Race and intelligence
• Religiosity and intelligence
• Sex and psychology
• Systems intelligence
• Theory of multiple intelligences

References[link]

Further reading[link]

• 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. http://books.google.com/?id=jEQSAAAAYAAJ&dq=The%20development%20of%20intelligence%20in%20children%20Binet&pg=PA1#v=onepage&q. Retrieved 18 July 2010. 
• Terman, Lewis M. (1916). The Measurement of Intelligence. Boston: Houghton Mifflin. ISBN 0-405-06480-2. http://www.gutenberg.org/etext/20662. Retrieved 26 June 2010. 
• Das, J.P.; Naglieri, J.A.; Kirby, J.R. (1994). Assessment of Cognitive Processes. Needham Heights, MA, USA: Allyn & Bacon. ISBN 0-205-14164-1. http://www.amazon.com/Assessment-Cognitive-Processes-Theory-Intelligence/dp/0205141641 (2 January 1994). 
• Wake, Warren K.; Gardner, Howard; Kornhaber, Mindy L. (1996). Intelligence: Multiple perspectives. Fort Worth, TX: Harcourt Brace College Publishers. ISBN 0-03-072629-8. OCLC 34414874. 
• Khalfa, Jean, ed. (1996). What Is Intelligence?. Darwin College Lectures. Cambridge: Cambridge University Press. ISBN 978-0-521-56685-8. Lay summary (4 July 2010). 
• Sternberg, Robert J., ed. (2000). Handbook of Intelligence. Cambridge: Cambridge University Press. ISBN 978-0-521-59648-0. Lay summary (29 June 2010). 
• Richardson, Ken (2000). The Making of Intelligence. New York (NY): Columbia University Press. ISBN 978-0-231-12005-0. Lay summary (28 June 2010). 
• Bock, Gregory; Goode, Jamie; Webb, Kate, eds. (2000). The Nature of Intelligence. Novartis Foundation Symposium 233. Chichester: Wiley. DOI:10.1002/0470870850. ISBN 978-0-471-49434-8. http://www3.interscience.wiley.com/cgi-bin/bookhome/118964607?CRETRY=1&SRETRY=0. Retrieved 16 July 2010. 
• Blakeslee, Sandra; Hawkins, Jeff (2004). On intelligence. New York: Times Books. ISBN 0-8050-7456-2. OCLC 55510125. 
• Sternberg, Robert J., ed. (2004). International Handbook of Intelligence. Cambridge: Cambridge University Press. ISBN 978-0-521-00402-2. Lay summary (29 June 2010). 
• 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 (18 July 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 (9 August 2010). 
• Garlick, Dennis (2010). Intelligence and the Brain: Solving the Mystery of Why People Differ in IQ and How a Child Can Be a Genius. Burbank (CA): Aesop Press. ISBN 978-0-615-31921-6. Lay summary (23 August 2010). 

External links[link]

Wikimedia Commons has media related to: Intelligence

Look up intelligence in Wiktionary, the free dictionary.

Wikiquote has a collection of quotations related to: Intelligence

• Intelligence on In Our Time at the BBC. (listen now)
• APA Task Force Examines the Knowns and Unknowns of Intelligence - American Psychologist, February 1996
• The cognitive-psychology approach vs. psychometric approach to intelligence - American Scientist magazine
• 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, June 14, 2011.

Scholarly journals and societies

• Intelligence (journal homepage)
• International Society for Intelligence Research (homepage)

The ASCII codes for the word "Wikipedia" represented in binary, the numeral system most commonly used for encoding computer information.

Information, in its most restricted technical sense, is a sequence of symbols that can be interpreted as a message. Information can be recorded as signs, or transmitted as signals. Information is any kind of event that affects the state of a dynamic system. Conceptually, information is the message (utterance or expression) being conveyed. This concept has numerous other meanings in different contexts.^[1] Moreover, the concept of information is closely related to notions of constraint, communication, control, data, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, representation, and especially entropy.

Etymology[link]

The English word was apparently derived from the Latin stem (information-) of the nominative (informatio): this noun is in its turn derived from the verb "informare" (to inform) in the sense of "to give form to the mind", "to discipline", "instruct", "teach": "Men so wise should go and inform their kings." (1330) Inform itself comes (via French informer) from the Latin verb informare, to give form, to form an idea of. Furthermore, Latin itself already contained the word informatio meaning concept or idea, but the extent to which this may have influenced the development of the word information in English is not clear.

The ancient Greek word for form was μορφή (morphe; cf. morph) and also εἶδος (eidos) "kind, idea, shape, set", the latter word was famously used in a technical philosophical sense by Plato (and later Aristotle) to denote the ideal identity or essence of something (see Theory of Forms). "Eidos" can also be associated with thought, proposition or even concept.

Information theory approach[link]

From the stance of information theory, information is taken as a sequence of symbols from an alphabet, say an input alphabet χ, and an output alphabet ϒ. Information processing consists of an input-output function that maps any input sequence from χ into an output sequence from ϒ. The mapping may be probabilistic or determinate. It may have memory or be memoryless.^[2]

As sensory input[link]

Often information is viewed as a type of input to an organism or system. Inputs are of two kinds. Some inputs are important to the function of the organism (for example, food) or system (energy) by themselves. In his book Sensory Ecology, Dusenbery called these causal inputs. Other inputs (information) are important only because they are associated with causal inputs and can be used to predict the occurrence of a causal input at a later time (and perhaps another place). Some information is important because of association with other information but eventually there must be a connection to a causal input. In practice, information is usually carried by weak stimuli that must be detected by specialized sensory systems and amplified by energy inputs before they can be functional to the organism or system. For example, light is often a causal input to plants but provides information to animals. The colored light reflected from a flower is too weak to do much photosynthetic work but the visual system of the bee detects it and the bee's nervous system uses the information to guide the bee to the flower, where the bee often finds nectar or pollen, which are causal inputs, serving a nutritional function.

As representation and complexity[link]

The cognitive scientist and applied mathematician Ronaldo Vigo argues that information is a relative concept that involves at least two related entities in order to make quantitative sense. These are: any dimensionally defined category of objects S, and any of its subsets R. R, in essence, is a representation of S, or, in other words, carries or conveys representational (and hence, conceptual) information about S. Vigo then defines the amount of information that R conveys about S as the rate of change in the complexity of S whenever the objects in R are removed from S. Under "Vigo information", pattern, invariance, complexity, representation, and information—five fundamental constructs of universal science—are unified under a novel mathematical framework.^[3] Among other things, the framework aims to overcome the limitations of Shannon-Weaver information when attempting to characterize and measure subjective information.

As an influence which leads to a transformation[link]

Information is any type of pattern that influences the formation or transformation of other patterns. In this sense, there is no need for a conscious mind to perceive, much less appreciate, the pattern.^{[citation needed]} Consider, for example, DNA. The sequence of nucleotides is a pattern that influences the formation and development of an organism without any need for a conscious mind.

Systems theory at times seems to refer to information in this sense, assuming information does not necessarily involve any conscious mind, and patterns circulating (due to feedback) in the system can be called information. In other words, it can be said that information in this sense is something potentially perceived as representation, though not created or presented for that purpose. For example, Gregory Bateson defines "information" as a "difference that makes a difference".

If, however, the premise of "influence" implies that information has been perceived by a conscious mind and also interpreted by it, the specific context associated with this interpretation may cause the transformation of the information into knowledge. Complex definitions of both "information" and "knowledge" make such semantic and logical analysis difficult, but the condition of "transformation" is an important point in the study of information as it relates to knowledge, especially in the business discipline of knowledge management. In this practice, tools and processes are used to assist a knowledge worker in performing research and making decisions, including steps such as:

• reviewing information in order to effectively derive value and meaning
• referencing metadata if any is available
• establishing a relevant context, often selecting from many possible contexts
• deriving new knowledge from the information
• making decisions or recommendations from the resulting knowledge.

Stewart (2001) argues that the transformation of information into knowledge is a critical one, lying at the core of value creation and competitive advantage for the modern enterprise.

The Danish Dictionary of Information Terms^[4] argues that information only provides an answer to a posed question. Whether the answer provides knowledge depends on the informed person. So a generalized definition of the concept should be: "Information" = An answer to a specific question".

When Marshall McLuhan speaks of media and their effects on human cultures, he refers to the structure of artifacts that in turn shape our behaviors and mindsets. Also, pheromones are often said to be "information" in this sense.

As a property in physics[link]

In 2003 J. D. Bekenstein claimed there is a growing trend in physics to define the physical world as being made of information itself (and thus information is defined in this way) (see Digital physics). Information has a well-defined meaning in physics. Examples of this include the phenomenon of quantum entanglement where particles can interact without reference to their separation or the speed of light. Information itself cannot travel faster than light even if the information is transmitted indirectly. This could lead to the fact that all attempts at physically observing a particle with an "entangled" relationship to another are slowed down, even though the particles are not connected in any other way other than by the information they carry.

Another link is demonstrated by the Maxwell's demon thought experiment. In this experiment, a direct relationship between information and another physical property, entropy, is demonstrated. A consequence is that it is impossible to destroy information without increasing the entropy of a system; in practical terms this often means generating heat. Another, more philosophical outcome is that information could be thought of as interchangeable with energy. Thus, in the study of logic gates, the theoretical lower bound of thermal energy released by an AND gate is higher than for the NOT gate (because information is destroyed in an AND gate and simply converted in a NOT gate). Physical information is of particular importance in the theory of quantum computers.

Technologically mediated information[link]

It is estimated that the world's technological capacity to store information grew from 2.6 (optimally compressed) exabytes in 1986, which is the informational equivalent to less than one 730-MB CD-ROM per person in 1986 (539 MB per person), to 295 (optimally compressed) exabytes in 2007.^[5] This is the informational equivalent of almost 61 CD-ROM per person in 2007.^[6]

The world’s combined technological capacity to receive information through one-way broadcast networks was the informational equivalent of 174 newspapers per person per day in 2007.^[5]

The world's combined effective capacity to exchange information through two-way telecommunication networks was the informational equivalent of 6 newspapers per person per day in 2007.^[6]

As records[link]

Records are a specialized form of information. Essentially, records are information produced consciously or as by-products of business activities or transactions and retained because of their value. Primarily their value is as evidence of the activities of the organization but they may also be retained for their informational value. Sound records management ensures that the integrity of records is preserved for as long as they are required.

The international standard on records management, ISO 15489, defines records as "information created, received, and maintained as evidence and information by an organization or person, in pursuance of legal obligations or in the transaction of business". The International Committee on Archives (ICA) Committee on electronic records defined a record as, "a specific piece of recorded information generated, collected or received in the initiation, conduct or completion of an activity and that comprises sufficient content, context and structure to provide proof or evidence of that activity".

Records may be maintained to retain corporate memory of the organization or to meet legal, fiscal or accountability requirements imposed on the organization. Willis (2005) expressed the view that sound management of business records and information delivered "...six key requirements for good corporate governance...transparency; accountability; due process; compliance; meeting statutory and common law requirements; and security of personal and corporate information."

Information and semiotics[link]

Beynon-Davies^[7][8] explains the multi-faceted concept of information in terms of signs and signal-sign systems. Signs themselves can be considered in terms of four inter-dependent levels, layers or branches of semiotics: pragmatics, semantics, syntax, and empirics. These four layers serve to connect the social world on the one hand with the physical or technical world on the other...

Pragmatics is concerned with the purpose of communication. Pragmatics links the issue of signs with the context within which signs are used. The focus of pragmatics is on the intentions of living agents underlying communicative behaviour. In other words, pragmatics link language to action.

Semantics is concerned with the meaning of a message conveyed in a communicative act. Semantics considers the content of communication. Semantics is the study of the meaning of signs - the association between signs and behaviour. Semantics can be considered as the study of the link between symbols and their referents or concepts; particularly the way in which signs relate to human behaviour.

Syntax is concerned with the formalism used to represent a message. Syntax as an area studies the form of communication in terms of the logic and grammar of sign systems. Syntax is devoted to the study of the form rather than the content of signs and sign-systems.

Empirics is the study of the signals used to carry a message; the physical characteristics of the medium of communication. Empirics is devoted to the study of communication channels and their characteristics, e.g., sound, light, electronic transmission etc..

Nielsen (2008) discusses the relationship between semiotics and information in relation to dictionaries. The concept of lexicographic information costs is introduced and refers to the efforts users of dictionaries need to make in order to, first, find the data sought and, secondly, understand the data so that they can generate information.

Communication normally exists within the context of some social situation. The social situation sets the context for the intentions conveyed (pragmatics) and the form in which communication takes place. In a communicative situation intentions are expressed through messages which comprise collections of inter-related signs taken from a language which is mutually understood by the agents involved in the communication. Mutual understanding implies that agents involved understand the chosen language in terms of its agreed syntax (syntactics) and semantics. The sender codes the message in the language and sends the message as signals along some communication channel (empirics). The chosen communication channel will have inherent properties which determine outcomes such as the speed with which communication can take place and over what distance.

More recently Shu-Kun Lin proposed a simple definition of information: Information is the amount of the data after data compression.

See also[link]

References[link]

Further reading[link]

• Alan Liu (2004). The Laws of Cool: Knowledge Work and the Culture of Information, University of Chicago Press
• Bekenstein, Jacob D. (2003, August). Information in the holographic universe. Scientific American.
• Gleick, James (2011). The Information: A History, a Theory, a Flood. Pantheon, New York, NY.
• Shu-Kun Lin (2008). 'Gibbs Paradox and the Concepts of Information, Symmetry, Similarity and Their Relationship', Entropy, 10 (1), 1-5. Available online at Entropy journal website.
• Luciano Floridi, (2005). 'Is Information Meaningful Data?', Philosophy and Phenomenological Research, 70 (2), pp. 351 – 370. Available online at PhilSci Archive
• Luciano Floridi, (2005). 'Semantic Conceptions of Information', The Stanford Encyclopedia of Philosophy (Winter 2005 Edition), Edward N. Zalta (ed.). Available online at Stanford University
• Sandro Nielsen: 'The Effect of Lexicographical Information Costs on Dictionary Making and Use', Lexikos 18/2008, 170-189.
• Stewart, Thomas, (2001). Wealth of Knowledge. Doubleday, New York, NY, 379 p.
• Young, Paul. The Nature of Information (1987). Greenwood Publishing Group, Westport, Ct. ISBN 0-275-92698-2.

External links[link]

Look up information in Wiktionary, the free dictionary.

Wikiquote has a collection of quotations related to: Information

• Semantic Conceptions of Information Review by Luciano Floridi for the Stanford Encyclopedia of Philosophy
• Principia Cybernetica entry on negentropy
• Fisher Information, a New Paradigm for Science: Introduction, Uncertainty principles, Wave equations, Ideas of Escher, Kant, Plato and Wheeler. This essay is continually revised in the light of ongoing research.
• How Much Information? 2003 an attempt to estimate how much new information is created each year (study was produced by faculty and students at the School of Information Management and Systems at the University of California at Berkeley)
• (Danish) Informationsordbogen.dk The Danish Dictionary of Information Terms / Informationsordbogen

Thomas Bayes
Portrait used of Bayes in the 1936 book History of Life Insurance; it is dubious whether it actually depicts Bayes.[1] No earlier portrait or claimed portrait survived.
Born	c. 1701 London, England
Died	7 April 1761(1761-04-07) (aged 59) Tunbridge Wells, Kent, England
Nationality	English
Signature

Thomas Bayes (/ˈbeɪz/; c. 1701 – 7 April 1761)^{[1][2][note a]} was an English mathematician and Presbyterian minister, known for having formulated a specific case of the theorem that bears his name: Bayes' theorem. Bayes never published what would eventually become his most famous accomplishment; his notes were edited and published after his death by Richard Price.^[3]

Biography[link]

Thomas Bayes was the son of London Presbyterian minister Joshua Bayes^[4] and perhaps born in Hertfordshire.^[5] In 1719, he enrolled at the University of Edinburgh to study logic and theology. On his return around 1722, he assisted his father at the latter's non-conformist chapel in London before moving to Tunbridge Wells, Kent around 1734. There he became minister of the Mount Sion chapel, until 1752.^[6]

He is known to have published two works in his lifetime, one theological and one mathematical:

1. Divine Benevolence, or an Attempt to Prove That the Principal End of the Divine Providence and Government is the Happiness of His Creatures (1731)
2. An Introduction to the Doctrine of Fluxions, and a Defence of the Mathematicians Against the Objections of the Author of the Analyst (published anonymously in 1736), in which he defended the logical foundation of Isaac Newton's calculus ("fluxions") against the criticism of George Berkeley, author of The Analyst

It is speculated that Bayes was elected as a Fellow of the Royal Society in 1742^[7] on the strength of the Introduction to the Doctrine of Fluxions, as he is not known to have published any other mathematical works during his lifetime.

In his later years he took a deep interest in probability. Stephen Stigler feels that he became interested in the subject while reviewing a work written in 1755 by Thomas Simpson,^[8] but George Alfred Barnard thinks he learned mathematics and probability from a book by de Moivre.^[9] His work and findings on probability theory were passed in manuscript form to his friend Richard Price after his death.

By 1755 he was ill and in 1761 had died in Tunbridge. He was buried in Bunhill Fields Cemetery in Moorgate, London where many Nonconformists lie.

Bayes' theorem[link]

Bayes' solution to a problem of "inverse probability" was presented in An Essay towards solving a Problem in the Doctrine of Chances which was read to the Royal Society in 1763 after Bayes's death. Richard Price shepherded the work through this presentation and its publication in the Philosophical Transactions of the Royal Society of London the following year. This was an argument for using a uniform prior distribution for a binomial parameter and not merely a general postulate.^[10]

This essay contains a statement of a special case of Bayes' theorem.

In the first decades of the eighteenth century, many problems concerning the probability of certain events, given specified conditions, were solved. For example, given a specified number of white and black balls in an urn, what is the probability of drawing a black ball? Attention soon turned to the converse of such a problem: given that one or more balls has been drawn, what can be said about the number of white and black balls in the urn? These are sometimes called "inverse probability" problems. The Essay of Bayes contains his solution to a similar problem, posed by Abraham de Moivre, author of The Doctrine of Chances (1718).

In addition to the Essay Towards Solving a Problem, a paper on asymptotic series was published posthumously.

Bayes and Bayesianism[link]

Bayesian probability is the name given to several related interpretations of probability, which have in common the notion of probability as something like a partial belief, rather than a frequency. This allows the application of probability to all sorts of propositions rather than just ones that come with a reference class. "Bayesian" has been used in this sense since about 1950. Since its rebirth in the 1950s, advancements in computing technology have allowed scientists from many disciplines to pair traditional Bayesian statistics with random walk techniques. The use of the Bayes theorem has been extended in science and in other fields.^[11]

Bayes himself might not have embraced the broad interpretation now called Bayesian. It is difficult to assess Bayes' philosophical views on probability, since his essay does not go into questions of interpretation. There Bayes defines probability as follows (Definition 5).

The probability of any event is the ratio between the value at which an expectation depending on the happening of the event ought to be computed, and the value of the thing expected upon its happening

In modern utility theory, expected utility can (with qualifications, because buying risk for small amounts or buying security for big amounts also happen) be taken as the probability of an event times the payoff received in case of that event. Rearranging that to solve for the probability, Bayes' definition results. As Stigler points out,^[8] this is a subjective definition, and does not require repeated events; however, it does require that the event in question be observable, for otherwise it could never be said to have "happened". Stigler argues that Bayes intended his results in a more limited way than modern Bayesians; given Bayes' definition of probability, his result concerning the parameter of a binomial distribution makes sense only to the extent that one can bet on its observable consequences.

See also[link]

• Bayesian inference
• Royal Society – Bayes was elected to membership in the Society in 1742; and his nomination letter has been posted with other membership records at the Royal Society web site here. Those signing that nomination letter were: Philip Stanhope; Martin Folkes; James Burrow; Cromwell Mortimer; John Eames.

Notes[link]

References[link]