Search Results for “Intuition”

April 18, 2013

Michael Leavitt

art army by michael leavitt

Michael Leavitt (b. 1977) is a visual artist based in Seattle, described as “the best caricature sculptor in the city.’ The ‘über-allround-cool-creator’ is most widely known for his ‘Art Army’ series of handmade action figures depicting visual artists, musicians, and entertainers. Through his company, Intuition Kitchen Productions, Leavitt is a ‘jack-of-all-trades’ responsible for a wide variety of conceptual art projects and performance artworks.

From a disinterest in convention, Leavitt proclaims, ‘I’d be afraid not to try other mediums.’ Growing up in the Pacific Northwest, Leavitt was influenced by the wood-craft and engineering of Native American, Scandinavian, and industrial manufacturing in the region. His parents practiced education, graphic design, and environmentalism by trade, formulating Leavitt’s early interests in both art and sociology.

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March 10, 2013


Pseudoarchaeology refers to pseudoscientific theories about the past. Some of these revolve around the idea that prehistoric and ancient human societies were aided in their development by intelligent extraterrestrial life, an idea propagated by Swiss author Erich von Däniken in books such as ‘Chariots of the Gods?’ (1968) and Italian author Peter Kolosimo. Others instead hold that there were human societies in the ancient period that were significantly technologically advanced, such as Atlantis, and this idea has been propagated by figures like Graham Hancock in his ‘Fingerprints of the Gods’ (1995).

Many alternative archaeologies have been adopted by religious groups. Academic archaeologists have heavily criticized pseudoarchaeology, with one of the most vocal critics, John R. Cole, characterizing it as relying on ‘sensationalism, misuse of logic and evidence, misunderstanding of scientific method, and internal contradictions in their arguments.’

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February 25, 2013

Animal Spirits


Animal spirits‘ is the term economist John Maynard Keynes used in his 1936 book ‘The General Theory of Employment, Interest and Money’ to describe emotions which influence human behavior and can be measured in terms of consumer confidence. It has since been argued that trust is also included or produced by ‘animal spirits.’ Several articles and at least two books with a focus on “animal spirits” were published in 2008 and 2009 as a part of the Keynesian resurgence.

According to Keynes: ‘Even apart from the instability due to speculation, there is the instability due to the characteristic of human nature that a large proportion of our positive activities depend on spontaneous optimism rather than mathematical expectations, whether moral or hedonistic or economic. Most, probably, of our decisions to do something positive, the full consequences of which will be drawn out over many days to come, can only be taken as the result of animal spirits – a spontaneous urge to action rather than inaction, and not as the outcome of a weighted average of quantitative benefits multiplied by quantitative probabilities.’

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January 21, 2013

Rational Irrationality

predictably irrational

The concept known as rational irrationality was popularized by economist Bryan Caplan in 2001 to reconcile the widespread existence of irrational behavior (particularly in the realms of religion and politics) with the assumption of rationality made by mainstream economics and game theory. The theory, along with its implications for democracy, was expanded upon by Caplan in his book ‘The Myth of the Rational Voter.’

The original purpose of the concept was to explain how (allegedly) detrimental policies could be implemented in a democracy, and unlike conventional public choice theory, Caplan posited that bad policies were selected by voters themselves. The theory has also been embraced by the ethical intuitionist philosopher Michael Huemer as an explanation for irrationality in politics. The theory has also been applied to explain religious belief.

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January 15, 2013

Dream Interpretation

Dream interpretation is the process of assigning meaning to dreams. In many ancient societies, such as those of Egypt and Greece, dreaming was considered a supernatural communication or a means of divine intervention, whose message could be unravelled by people with certain powers. In modern times, various schools of psychology have offered theories about the meaning of dreams.

One of the earliest written examples of dream interpretation comes from the Babylonian ‘Epic of Gilgamesh.’ Gilgamesh dreamt that an axe fell from the sky. The people gathered around it in admiration and worship. Gilgamesh threw the axe in front of his mother and then he embraced it like a wife. His mother, Ninsun, interpreted the dream. She said that someone powerful would soon appear. Gilgamesh would struggle with him and try to overpower him, but he would not succeed. Eventually they would become close friends and accomplish great things. She added, ‘That you embraced him like a wife means he will never forsake you. Thus your dream is solved.’

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January 13, 2013

Jungian Archetypes

Jungian archetypes

The concept of psychological archetypes [ahr-ki-tahyps] was advanced by the Swiss psychiatrist Carl Jung [yoong], c. 1919. Jung described archetypes as highly developed elements of the collective unconscious (structures of the unconscious mind which are shared among beings of the same species) that can be seen repeated in story, art, myths, religions, and dreams. They are common motifs in human cultures such as ‘the mother,’ ‘the child,’ ‘the trickster,’ and ‘the flood,’ among others.

Carl Jung understood archetypes as universal, archaic patterns and images that derive from the collective unconscious and are the psychic counterpart of instinct. They are inherited potentials which are actualized when they enter consciousness as images or manifest in behavior on interaction with the outside world. They are autonomous and hidden forms which are transformed once they enter consciousness and are given particular expression by individuals and their cultures.

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December 20, 2012

Affective Computing

Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects.

It is an interdisciplinary field spanning computer sciences, psychology, and cognitive science, which originated at MIT with Rosalind Picard’s 1995 paper on affective computing. A motivation for the research is the ability to simulate empathy. The machine should interpret the emotional state of humans and adapt its behavior to them, giving an appropriate response for those emotions.

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December 19, 2012


Autism [aw-tiz-uhm] is a neurological disorder characterized by a profound withdrawal from contact with people, repetitive behavior, and fear of change in the environment. The emotional disorder affects the brain’s ability to receive and process information.

People who have autism find it difficult to act in a way that other people think is ‘normal,’ and they find it difficult to talk to other people, to look at other people, and often do not like being touched by other people. A person who has autism seems to be turned inwards. They may talk only to themselves, rock themselves backwards and forwards, and laugh at their own thoughts. They do not like any type of change and may find it very difficult to learn a new behavior like using a toilet or going to school.

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December 2, 2012


INTJ (introversion, intuition, thinking, judgment) is an abbreviation used in the publications of the Myers-Briggs Type Indicator (MBTI) to refer to one of the sixteen personality types. INTJs are one of the rarest of the sixteen personality types, and account for about 1–4% of the population.

The MBTI assessment was developed from the work of prominent psychiatrist Carl G. Jung in his book ‘Psychological Types.’ Jung proposed a psychological typology based on the theories of cognitive functions that he developed through his clinical observations. From Jung’s work, others developed psychological typologies.

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November 25, 2012

Machine Learning

Bayes' theorem

Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the development of algorithms that take as input empirical data (from sensors or databases), identify complex relationships, and employ these identified patterns to make predictions. The algorithm studies a portion of the observed data (called ‘training data’) to capture characteristics of interest. Optical character recognition, in which printed characters are recognized automatically based on previous examples, is a classic engineering example of machine learning.

In 1959, AI pioneer Arthur Samuel defined machine learning as a ‘Field of study that gives computers the ability to learn without being explicitly programmed.’ Computer scientist Tom M. Mitchell provided a widely quoted, more formal definition: ‘A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.’

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November 12, 2012

Quantum Decoherence

quantum classical boundary

In quantum mechanics, quantum decoherence is the loss of coherence in a quantum superposition. Physical system—such as an electron—exists partly in all its particular, theoretically possible states (or, configuration of its properties) simultaneously; but, when measured, it gives a result corresponding to only one of the possible configurations. The act of observation collapses the multi-state wave function into a single-state particle from the perspective of the observer; and justifies the framework and intuition of classical physics as an acceptable approximation.

Decoherence is the mechanism by which the classical limit emerges out of a quantum starting point and it determines the location of the quantum-classical boundary. It occurs when a system interacts with its environment in a thermodynamically irreversible way. This prevents different elements in the quantum superposition of the system+environment’s wavefunction from interfering with each other. Decoherence has been a subject of active research since the 1980s.

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November 2, 2012

The Structure of Scientific Revolutions

The Structure of Scientific Revolutions by Thomas S. Kuhn, is an analysis of the history of science, published in 1962. Its publication was a landmark event in the history, philosophy, and sociology of scientific knowledge and it triggered an ongoing worldwide assessment and reaction in—and beyond—those scholarly communities. In this work, Kuhn challenged the then prevailing view of progress in ‘normal science’ (the routine work of scientists experimenting within a paradigm).

Scientific progress had been seen primarily as ‘development-by-accumulation’ of accepted facts and theories. Kuhn argued for an episodic model in which periods of such conceptual continuity in normal science were interrupted by periods of revolutionary science. During revolutions in science the discovery of anomalies leads to a whole new paradigm that changes the rules of the game and the ‘map’ directing new research, asks new questions of old data, and moves beyond the puzzle-solving of normal science.

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