Cognitive science is the interdisciplinary scientific study of the mind and its processes. It examines what cognition is, what it does and how it works. It includes research on intelligence and behavior, especially focusing on how information is represented, processed, and transformed (in faculties such as perception, language, memory, reasoning, and emotion) within nervous systems (human or other animal) and machines (e.g. computers). Cognitive science consists of multiple research disciplines, including psychology, artificial intelligence, philosophy, neuroscience, linguistics, and anthropology. The fundamental concept of cognitive science is "that thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures." Wikipedia (en)
Festinger's (1957) cognitive dissonance theory suggests that we have an inner drive to hold all our attitudes and beliefs in harmony and avoid disharmony (or dissonance).
Cognitive dissonance refers to a situation involving conflicting attitudes, beliefs or behaviors. This produces a feeling of discomfort leading to an alteration in one of the attitudes, beliefs or behaviors to reduce the discomfort and restore balance etc.
Prisoner’s Dilemma has been a subject of inquiry for more than 60 years, not just by game theorists but also by psychologists, economists, political scientists, and evolutionary biologists. Yet the game has not given up all its secrets. A startling discovery last year revealed a whole new class of strategies, including some bizarre ones. For example, over a long series of games one player can unilaterally dictate the other player’s score (within a certain range). Or a crafty player can control the ratio of the two scores. But not all the new strategies are so manipulative; some are “generous” rules that elicit cooperation and thereby excel in an evolutionary context.
Squaring recent research suggesting we're "naturally moral" with all the strife in the world.
In 1999, Joshua Greene—then a philosophy graduate student at Princeton, now a psychology professor at Harvard—had a very fertile idea. He took a pretty well-known philosophical thought experiment and infused it with technology in a way that turned it into a very well-known philosophical thought experiment—easily the best-known, most-pondered such mental exercise of our time. In the process, he raised doubts, in inescapably vivid form, about the rationality of human moral judgment.
The thought experiment—called the trolley problem—has over the past few years gotten enough attention to be approaching “needs no introduction” status. But it’s not quite there, so: An out-of-control trolley is headed for five people who will surely die unless you pull a lever that diverts it onto a track where it will instead kill one person. Would you—should you—pull the lever?
When Federal Reserve Chief Ben Bernanke appeared on 60 Minutes to persuade us to bail out the banking system, he didn't bother with charts, figures or lengthy argument. Instead, he used something far more powerful: Analogy and metaphor.
Bernard Ryefield's insight:
Beware of the metaphor ! Actually, just be aware your (or other's) choice of metaphor is framing your arguments
According to the traditional “investment” theory, intelligence can be classified into two main categories: fluid and crystallized. Differences in fluid intelligence are thought to reflect novel, on-the-spot reasoning, whereas differences in crystallized intelligence are thought to reflect previously acquired knowledge and skills. According to this theory, crystallized intelligence develops through the investment of fluid intelligence in a particular body of knowledge.
As far as genetics is concerned, this story has a very clear prediction: In the general population– in which people differ in their educational experiences– the heritability of crystallized intelligence is expected to be lower than the heritability of fluid intelligence. This traditional theory assumes that fluid intelligence is heavily influenced by genes and relatively fixed, whereas crystallized intelligence is more heavily dependent on acquired skills and learning opportunities.
Regardless what you think of infographics (and personally, I think they're largely a pustulent, suppurating boil on the bloated arse of the internet) there are some good, useful ones out there. However, these are vastly outweighed by the thousands of utterly ghastly, misleading, poorly-referenced and pointless ones.
Six years ago, while researching the life of an American psychiatrist who studied the top Nazi leaders during their imprisonment and trial in Nuremberg, I came across a small box among the physician’s possessions. The box held a set of glass photographic transparencies, with each slide showing a cross-section of a brain. Labels on the slides identified the brain’s former owner as Robert Ley...
Computational creativity is an emerging branch of artificial intelligence that places computers in the center of the creative process. Broadly, creativity involves a generative step to produce many ideas and a selective step to determine the ones that are the best. Many previous attempts at computational creativity, however, have not been able to achieve a valid selective step. This work shows how bringing data sources from the creative domain and from hedonic psychophysics together with big data analytics techniques can overcome this shortcoming to yield a system that can produce novel and high-quality creative artifacts. Our data-driven approach is demonstrated through a computational creativity system for culinary recipes and menus we developed and deployed, which can operate either autonomously or semi-autonomously with human interaction. We also comment on the volume, velocity, variety, and veracity of data in computational creativity.
This article sheds light on the important differences in self-declared happiness across countries of similar affluence. It hinges on the different happiness statements of natives and immigrants in a set of European countries to disentangle the influence of objective circumstances versus psychological and cultural factors. The latter turn out to be of non-negligible importance in explaining international heterogeneity in happiness. In some countries, such as France, they are responsible for the best part of the country's unobserved idiosyncratic source of unhappiness. Early schooling plays an important role in shaping these attitudes. I show that these gaps in self-declared happiness have a real emotional counterpart and do not boil down to purely nominal differences.
This article investigates how neuroscience in general, and neuroscience of creativity in particular, can be used in teaching 'applied creativity' and the usefulness of this approach to creativity training. The article is based on empirical data and our experiences from the Applied NeuroCreativity (ANC) program, taught at business schools in Denmark and Canada. In line with previous studies of successful creativity training programs the ANC participants are first introduced to cognitive concepts of creativity, before applying these concepts to a relevant real world creative problem. The novelty in the ANC program is that the conceptualization of creativity is built on neuroscience, and a crucial aspect of the course is giving the students a thorough understanding of the neuroscience of creativity. Previous studies have reported that the conceptualization of creativity used in such training is of major importance for the success of the training, and we believe that the neuroscience of creativity offers a novel conceptualization for creativity training. Here we present two sets of empirical data, suggesting that principles from neuroscience can contribute effectively to creativity training and produce measurable results on creativity tests: 1) an experiment demonstrating how an ANC lecture on the neurobiology of creativity significantly decreased the number of fixations in a creative task, 2) pre/post-training tests showing that ANC students gained more fluency in divergent thinking (a traditional measure of trait creativity) than those in highly similar courses without the neuroscience component. The evidence presented indicates that the inclusion of neuroscience principles in a creativity course can in 8 weeks increase divergent thinking skills with an individual relative average of 28.5%.
Many academics, like Columbia University historian Matthew Connelly, would like to be able to access the information that’s hidden by the government but doesn’t really need to be. That’s why he is leading a project called the Declassification Engine, an effort to find out more from documents that are declassified but have significant portions redacted, with words, phrases, and sometimes whole paragraphs blacked out. Considering that the declassified archive includes hundreds of millions of pages, going through them all by hand isn’t a feasible option. So Connelly is working with computer scientists to try to automatically pull useful information from the documents.
Before Alan Turing made his crucial contributions to the theory of computation, he studied the question of whether quantum mechanics could throw light on the nature of free will. This article investigates the roles of quantum mechanics and computation in free will. Although quantum mechanics implies that events are intrinsically unpredictable, the `pure stochasticity' of quantum mechanics adds only randomness to decision making processes, not freedom. By contrast, the theory of computation implies that even when our decisions arise from a completely deterministic decision-making process, the outcomes of that process can be intrinsically unpredictable, even to -- especially to -- ourselves. I argue that this intrinsic computational unpredictability of the decision making process is what give rise to our impression that we possess free will. Finally, I propose a `Turing test' for free will: a decision maker who passes this test will tend to believe that he, she, or it possesses free will, whether the world is deterministic or not.
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