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)
Cognitive scientist Donald Hoffman is trying to answer a big question: Do we experience the world as it really is ... or as we need it to be? In this ever so slightly mind-blowing talk, he ponders how our minds construct reality for us.
The Origin of Consciousness in the Breakdown of the Bicameral Mind, when it finally came out in 1976, did not look like a best-seller. But sell it did. It was reviewed in science magazines and psychology journals, Time, The New York Times, and the Los Angeles Times. It was nominated for a National Book Award in 1978. New editions continued to come out, as Jaynes went on the lecture circuit. Jaynes died of a stroke in 1997; his book lived on. In 2000, another new edition hit the shelves. It continues to sell today.
The phenomenal success of certain crowdsourced online platforms, such as Wikipedia, is accredited to their ability to tap the crowd's potential to collaboratively build knowledge. While it is well known that the crowd's collective wisdom surpasses the cumulative individual expertise, little is understood on the dynamics of knowledge building in a crowdsourced environment. Our experiment shows that an important reason for the rapid knowledge building in such an environment is due to variance in expertise. A proper understanding of the dynamics of knowledge building in a crowdsourced environment would enable one in the better designing of wiki styled environments to solicit knowledge from the crowd. We use, as our test bed, a customized Crowdsourced Annotation System (CAS) which provides a group of users the facility to annotate a given document. Our results show the presence of different genres of proficiency which accelerate the process of knowledge building by the synergetic interaction amongst the users. We observe that the crowdsourced knowledge ecosystem comprises of four categories of contributors, namely: Probers, Solvers, Articulators and Explorers. We infer from our experiment that the knowledge garnering mainly happens due to the synergetic interaction across these categories.
Brains Vs. Artificial Intelligence: Carnegie Mellon Computer Faces Poker Pros in Epic No-Limit Texas Hold’Em Competition
80,000 Hands Will Be Played in Two-Week Contest at Rivers Casino in Pittsburgh
In a contest that echoes Deep Blue's chess victory over Garry Kasparov and Watson beating two Jeopardy! Champions, computer poker software developed at Carnegie Mellon University will challenge four of the world's best professional poker players in a "Brains Vs. Artificial Intelligence" competition beginning Friday, April 24, at Rivers Casino.
Over the course of two weeks, the CMU computer program Claudico will play 20,000 hands of heads-up no-limit Texas Hold'em with each of the four poker pros. The pros – Doug Polk, Dong Kim, Bjorn Li and Jason Les — will receive appearance fees derived from a prize purse of $100,000 donated by Microsoft Research and Rivers Casino. The Carnegie Mellon scientists will compete for something more precious.
"Poker is now a benchmark for artificial intelligence research, just as chess once was," said Tuomas Sandholm, a professor of computer science at Carnegie Mellon who has led development of Claudico. "It's a game of exceeding complexity that requires a machine to make decisions based on incomplete and often misleading information, thanks to bluffing, slow play and other decoys. And to win, the machine has to outsmart its human opponents."
"Computing the world's strongest strategies for this game was a major achievement — with the algorithms having future applications in business, military, cybersecurity and medical arenas."
This question begins Alan Turing's paper 'Computing Machinery and Intelligence' (1950). However he found the form of the question unhelpful, that even the process of defining 'machines' and 'think' in common terms would be dangerous, as it could mistakenly lead one to think the answer can be obtained from some kind of statistical survey.
Did you know that 63-65 percent of Americans think we're spending too little on welfare? Well, as long as the polls calls it "assistance to the poor." Use the word "welfare", and that number drops to 20-25 percent. Yeah, as we've mentioned before, just the way you word a question can change people's opinion on important matters, but, at least, this isn't a U.S.-only problem: The entire human race sucks at democracy. And we can't even help it because ...
Magic illusions provide the perceptual and cognitive scientist with a toolbox of experimental manipulations and testable hypotheses about the building blocks of conscious experience. Here we studied several sleight-of-hand manipulations in the performance of the classic “Cups and Balls” magic trick (where balls appear and disappear inside upside-down opaque cups). We examined a version inspired by the entertainment duo Penn & Teller, conducted with three opaque and subsequently with three transparent cups. Magician Teller used his right hand to load (i.e. introduce surreptitiously) a small ball inside each of two upside-down cups, one at a time, while using his left hand to remove a different ball from the upside-down bottom of the cup. The sleight at the third cup involved one of six manipulations: (a) standard maneuver, (b) standard maneuver without a third ball, (c) ball placed on the table, (d) ball lifted, (e) ball dropped to the floor, and (f) ball stuck to the cup. Seven subjects watched the videos of the performances while reporting, via button press, whenever balls were removed from the cups/table (button “1”) or placed inside the cups/on the table (button “2”). Subjects’ perception was more accurate with transparent than with opaque cups. Perceptual performance was worse for the conditions where the ball was placed on the table, or stuck to the cup, than for the standard maneuver. The condition in which the ball was lifted displaced the subjects’ gaze position the most, whereas the condition in which there was no ball caused the smallest gaze displacement. Training improved the subjects’ perceptual performance. Occlusion of the magician’s face did not affect the subjects’ perception, suggesting that gaze misdirection does not play a strong role in the Cups and Balls illusion. Our results have implications for how to optimize the performance of this classic magic trick, and for the types of hand and object motion that maximize magic misdirection.
Can we learn without being aware of what we’re learning? Many psychologists say that ‘unconscious’, or implicit, learning exists. But in a new paper, London-based psychologists Vadillo, Konstantinidis, and Shanks call the evidence for this into question. Vadillo et al. focus on one particular example of implicit learning, the contextual cueing paradigm. This involves a …
Author Summary It is well known that the hippocampus, a mammalian brain region, has a crucial role in memory formation. Furthermore, it has a remarkable anatomical structure and can be divided into several subregions based on physiological properties. Over the last decades a widely accepted model has evolved suggesting individual roles for each subregion in memory storage. The central idea is that region CA3, with its remarkably many synapses that project into the region itself again, stores the memories within these synapses. In this model a memory is impressed onto the hippocampus by neuronal activation in the hippocampal input region. Recently it has been found that such activations have a certain regularity instead of being random as assumed in the standard model. Here we investigate how well the model performs when storing memories of regular inputs. We find that the proposed function of CA3 actually harms memory performance. Moreover, we show that this function is redundant even in the case of random inputs. These findings call the standard model into question and support an alternative view of how the hippocampus may store memories.
The sociotechnological system is a system constituted of human individuals and their artifacts: technological artifacts, institutions, conceptual and representational systems, worldviews, knowledge systems, culture and the whole biosphere as a volutionary niche. In our view the sociotechnological system as a super-organism is shaped and determined both by the characteristics of the agents involved and the characteristics emergent in their interactions at multiple scales. Our approach to sociotechnological dynamics will maintain a balance between perspectives: the individual and the collective. Accordingly, we analyze dynamics of the Web as a sociotechnological system made of people, computers and digital artifacts (Web pages, databases, search engines, etc.). Making sense of the sociotechnological system while being part of it, is also a constant interplay between pragmatic and value based approaches. The first is focusing on the actualities of the system while the second highlights the observer's projections. In our attempt to model sociotechnological dynamics and envision its future, we take special care to make explicit our values as part of the analysis. In sociotechnological systems with a high degree of reflexivity (coupling between the perception of the system and the system's behavior), highlighting values is of critical importance. In this essay, we choose to see the future evolution of the web as facilitating a basic value, that is, continuous open-ended intelligence expansion. By that we mean that we see intelligence expansion as the determinant of the 'greater good' and 'well being' of both of individuals and collectives at all scales. Our working definition of intelligence here is the progressive process of sense-making of self, other, environment and universe. Intelligence expansion, therefore, means an increasing ability of sense-making.
Cognitive bias describes the inherent thinking errors that humans make in processing information. Some of these have been verified empirically in the field of psychology, while others are considered general categories of bias. These thinking errors prevent one from accurately understanding reality, even when confronted with all the needed data andevidence to form an accurate view. Many conflicts between science and religion are due to cognitive biases preventing people from coming to the same conclusions with the same evidence. Cognitive bias is intrinsic to human thought, and therefore any systematic system of acquiring knowledge that attempts to describe reality must include mechanisms to control for bias or it is inherently invalid.
The best known system for vetting and limiting the consequences of cognitive bias is the scientific method, as it places evidence and methodology behind the idea under open scrutiny. By this, many opinions and separate analyses can be used to compensate for the bias of any one individual. It is important to remember, however, that in every day life, just knowing about these biases doesn't necessarily free you from them.
Peer review is ubiquitous in modern science: from the evaluation of publications to the distribution of funding. While there is a long tradition of, and many arguments for, peer review as a beneficial and necessary component of scientific processes, the exponential growth of the research community, the 'publish or perish' pressures and increasing insecurity and competition for research grants have led to an increasing number of voices describing the weaknesses of the system. One of the most frequent accusations against the peer review system is that it inhibits true innovation. The availability of better data mining tools allows interested stakeholders, in principle, to monitor many aspects of the process and to promote a better understanding of the interplay of various factors. 'In principle' – because a lot of information is hidden behind the screens of anonymity and confidentiality. Our work presents an attempt at a theoretical understanding of some aspects of the process via an idealized agent-based model, which describes the effects of the peer review done by 'imperfect' agents, in particular with respect to promotion of mediocrity and to formation of self-serving cliques. The results of the model suggest that both phenomena can be quite robust and require careful monitoring of the system to combat their negative effects. Some mitigating measures are simulated and discussed.
Stop me if you’ve heard this one. A trolley carrying five school children is headed for a cliff. You happen to be standing at the switch, and you could save their lives by diverting the trolley to another track. But there he is – an innocent fat man, picking daisies on that second track, oblivious to the rolling thunder (potentially) hurtling his way. Divert the trolley, and you save the kids and kill a person. Do nothing, and you have killed no one but five children are dead. Which is the greater moral good?
Most of us think we know some basic facts about how time works. The facts we believe we know are based on a few intuitions about time, which are, in turn, based on our conscious waking experiences. As far as I can tell, these intuitions about time are something like this: 1) There is a physical world in which events occur, 2) These events are mirrored by our perceptual re-creation of them in essentially the same order in which they occur in the physical world, 3) This re-creation of events occurs in a linear order based on our conscious memory of them (e.g., event A is said to occur before event B if at some point we do remember event A but we don not yet remember event B, and at another point we remember both events), 4) Assuming we have good memories, what we remember has occurred in the past and what we don not remember but we can imagine might: a) never occur, b) occur when we are not conscious, or c) occur in the future. These intuitions are excellent ones for understanding our conscious conception of ordered events. However, they do not tell us anything about how the non-conscious processes in our brains navigate events in time. Currently, neuroscientists assume that neural processes of which we are unaware, that is, non-conscious processes, create conscious awareness as a reflection of physical reality (Singer, 2015). Thus, if we wish to understand how events unfold in time in the physical world, we would do well to attempt to get some hints about how these events are navigated by non-conscious processes.
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