Cognitive science

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In its broadest and most ambitious goal, the academic discipline of cognitive science aims to explain the physiological activity of thinking and feeling; of speaking and other ways humans process symbols; of imagining and remembering; of learning and knowing; of experiencing events of reality consciously, non-consciously and unconsciously; of reasoning and problem-solving; of planning and decision-making; of dreaming; and a host of other physiological activities that we associate with the human living system and refer to as mind. Cognitive scientists ask: "How do people accomplish those differing kinds of thinking?"

Scope and definitions of cognitive science

Template:TOC-right The University of California at Berkeley offers an undergraduate degree-granting major in ‘Cognitive Science’, and explains the discipline as follows:

Cognitive Science is an interdisciplinary field that has arisen during the past decade at the intersection of a number of existing disciplines, including psychology, linguistics, computer science, philosophy, and physiology. The shared interest that has produced this coalition is understanding the nature of the mind. This quest is an old one, dating back to antiquity in the case of philosophy, but new ideas are emerging from the fresh approach of Cognitive Science. Previously, each discipline sought to understand the mind from its own perspective, benefiting little from progress in other fields because of different methods employed. With the advent of Cognitive Science, however, common interests and theoretical ideas have overcome methodological differences, and interdisciplinary interaction has become the hallmark of this field.

Notably, though the "….shared interest that has produced this coalition is understanding the nature of the mind", the complete webpage purporting to answer the question, “What is Cognitive Science?”, presumes comprehension of the word (or concept of) "mind".

William Bechtel and George Graham, in the introduction to their multi-authored text, A Companion to Cognitive Science, define cognitive science as follows:

The expression 'cognitive science' names a broadly integrated class of approaches to the study of mental activities and processes, broad not just in the sense of including disciplines as varied as philosophy, cognitive psychology, linguistics, computer science, anthropology, and neuroscience, but in the sense that cognitive scientists tend to adopt certain basic, general assumptions about mind and intelligent thought and behavior. These include assumptions that the mind is (1) an information processing system, (2) a representational device, and (3) [in some sense] a computer. Various relations are possible among each of these assumptions; further, they are not shared by all who dub themselves cognitive scientists. Partly because of such relations and failures of uniformity, cognitive science has generated vigorous dialogues concerning the nature of mental activities and processes as well as over the nature of science and the structure of disciplines.

Harvard University offers a webpage promoting a book by cognitive scientist, Phillip Johnson-Laird that states:

The mind, he says, depends on the brain in the same way as the execution of a program of symbolic instructions depends on a computer, and can thus be understood by anyone willing to start with basic principles of computation and follow his step-by-step explanations.

Margaret Boden’s 2006 book, Mind as Machine: A History of Cognitive Science, views the mind as a machine, though a special one.

In my view, the best way to think about it [cognitive science] is as the study of mind as machine....however, more than one type of machine is relevant here. In a nutshell: some for digital computing, some for cybernetic self-organization or dynamical control. Much of the theoretical—and historical—interest in the field lies in the tension that follows from that fact.

If a 'special' machine, perhaps because mind "emerged" from the interaction of molecular subsystems. Noam Chomsky has stated that "....the evolution of language may involve 'emergence' — the appearance of a qualitatively different phenomenon at a specific stage of complexity of organization."

If so, [Chomsky continues] it would be an interesting, but by no means novel, case of evolution. A similar view is widely held by evolutionary biologists and paleoanthropologists, for example, Ian Tattersall, who suggests more generally that human intelligence is an "emergent quality, the result of a chance combination of factors, rather than a product of Nature's patient and gradual engineering over the eons" [citation]. Still more generally, neuroscientist Vernon Mountcastle, introducing an American Academy of Arts and Sciences collection of essays on the state of the art at the conclusion of "the decade of the brain" that ended the last century, formulates the leading principle of these contributions as the thesis that "Things mental, indeed minds, are emergent properties of brains [my emphasis], . . . produced by principles . . . we do not yet understand" -- and that might derive from laws of nature [citation].

The Stanford Encyclopedia of Philosophy offers these introductory words: Cognitive science is the interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience, linguistics, anthropology, artificial intelligence, artificial life, and control engineering. Its intellectual origins are in the mid-1950s when researchers in several fields began to develop theories of mind based on complex representations and computational procedures. Its organizational origins are in the mid-1970s when the Cognitive Science Society was formed and the journal Cognitive Science began. Since then, more than sixty universities in North America, Europe, Asia, and Australia have established cognitive science programs, and many others have instituted courses in cognitive science.

Cognitive neuroscientists, George Lakoff and Mark Johnson, emphasize the role of the unconscious mind:

Cognitive science is the scientific discipline that studies conceptual systems. It is a relatively new discipline, having been founded in the 1970s. Yet in a short time it has made startling discoveries. It has discovered, first of all, that most of our thought is unconscious, not in the Freudian sense of being repressed, but in the sense that it operates beneath the level of cognitive awareness, inaccessible to consciousness and operating too quickly to be focused on.

It seems that like many other sciences, cognitive science requires an interdisciplinary approach to try to explain the workings of what we commonly recognize as 'mind'. Each discipline includes scholars interested in mental processes, or how the mind/brain works, or how the mind/brain/body works. Cognitive science centrally focuses on explaining exactly what we mean by mind, how we view it, what theories we have about it.

Whatever theories we come up with, it seems that we come up with them with our minds. If minds operate as machines, then as living machines, to explain their workings we must take both a reductionist approach — looking at its parts — and a holistic approach — looking at it as a whole — and integrating the two approaches to yield a satisfying explanation that has explanatory and predictive power, and ultimately controlling power — self-controling power.

We begin, then, with an exploration of the concepts of mind that minds have proposed.

Areas of study by cognitive scientists

The interdisciplinary and multidisciplinary character of modern cognitive science reveals itself in even a greatly abbreviated list of definable 'areas of study' engaged in by cognitive scientists:

The MIT Encyclopedia of the Cognitive Sciences (MITECS), edited by Robert A. Wilson and Frank C. Keil, classifies the cognitive and brain sciences into six domains: (1) computational intelligence (2) culture, cognition, and evolution (3) linguistics and language (4) neuroscience (5) philosophy, and (6) psychology. The following list includes an illustrative selection of topics in those domains:

Analogy Animal Cognition Attention Brain Mapping Cognitive Anthropology Cognitive and Linguistic Development Cognitive Neuroscience Conceptual Change Conceptual Organization Consciousness Decision Making Emotions Imagery and Spatial Representation Language Evolution and Neuromechanisms Language Processing Linguistic Theory Machine Learning Memory Metacognition Perception Problem Solving Reasoning Social Cognition Unconscious Intelligence Understanding Texts Word Meaning Theories of mind Mind as machine Once we had the concept of machine, and built automata that performed manual activities, we had the concept, 'machine as man'. As we built more and more elaborate and complicated machines, machines that could locomote, manipulate objects, compute, operate in response to logical rules, recognize our speech — we began developing, and advancing development of, the concept of 'man as machine'. In keeping with that concept, modern biology continually works out the molecular mechanisms of the diverse physiological activities performed by humans. How could the mind of man exist except as a manifestation of physiological processes. Destroy the brain, destroy the mind. 'Mind as machine', entailed by 'man as machine'. Man as a machine that can think and communicate with other machines like itself, and and think about and communicate with itself. Not just think, but show emotion, social skill, and personality; recognize itself; recognize that it recognizes itself. An autonamously functioning cognition and metacognition machine, intospective and constructive of a detailed representation of aspects of the spatial and temporal reality embedding it. The conscious mind as primary component of reality Some philosophers of mind believe the mind's ability to recognize itself requires a component of reality in addition to those recognized by physicists, specifically something called 'consciousness', fundamental as energy and matter. The conscious mind, a physical machine, but only if physical reality includes 'consciousness' as a fundamental constituent of reality — perhaps a natural "organizing principle informing matter", call it 'soul'. Descartes came close to that notion, seeing the mind as immaterial and separate from the body, influencing the body through a strategy designed and owned by God. Mind as an evolutionary adaptation to Pleistocene lifestyle Others explain cognition as adaptations to achieve fitness for survival, implemented by neurophyiological processes. Mind as neurophysiological processing We learn more and more about the neurophysiology of cognitive processes. We can detect cognitive and emotional adaptations occurring in real-time in the lifetime of individual organisms. The neurophysiology of conscious awareness remains undiscovered, however, explained by competing proposals. Mechanisms of cognition Holding refs: Applied cognitive science and engineering One of the lesser-known branches of psychology, cognitive psychology deals, significantly, with people not in distress, but trying to move to a higher level of functioning. The discipline deals with how people interact with new concepts in their environment, especially with respect to learning, or the mental processes involved in building skills. These topics are also the foundation on which human factors engineering, instructional technology, and user interface design are built. Much of the discipline deals with the conscious processes involved in learning, and in processing information that comes from existing and new sources. Bruning defined the cognitive movement as going beyond Skinner's stimulus-response, reflexive behaviorism into conscious learning. Cognitive psychology is a theoretical perspective that focuses on the realms of human perception, thought, and memory. It portrays learners as active processors of information--a metaphor borrowed from the computer world--and assigns critical roles to the knowledge and perspective students bring to their learning. What learners do to enrich information, in the view of cognitive psychology, determines the level of understanding they ultimately achieve. — Roger H. Bruning While Hofstetter describes a fundamental paradigm shift, experience in gaining certain skills may also draw from the behaviorists. "If faculty members can learn to shift their pedagogical paradigm from teacher-dominated to learner-centered, students will become more actively involved in the teaching and learning process. At the end of a course, instead of having been trained in the digestion of existing knowledge, students will have become able to continue finding, judging, critiquing, synthesizing, and constructing new knowledge... students will have become truly educated, not just trained." Nevertheless, to take the quite different example of flying an advanced combat aircraft, developing the eye-hand coordination to merge the pilot's vision outside supplemented heads-up displays and pilot-selected "glass cockpit" displays, which are controlled from buttons and switches on controls operated without looking at them, can take a year increasingly of simulator and aircraft experience. While this may have behaviorist aspects, it is complemented by highly interactive classroom work on alternative tactics, emergency procedures, and the theory of one's aircrft and weapons. In contrast, cognitive psychologists involved in automobile safety suggest that adding heads-up displays to cars, without a very explicit training program, may cause information overload in the untrained driver. Information and decision flow in the OODA paradigm John Boyd, one of the pioneers of high-speed decisionmaking in the modern military, has a cognitive model at the core of his theories, the decision cycle or OODA Loop, the process by which an entity (either an individual or an organization) reacts to an event. According to this idea, the key to victory is to be able to create situations wherein one can make appropriate decisions more quickly than one's opponent. Boyd theorized that multilevel contexts, such as the tactical, operational, and strategic levels of war, can be modeled with a hierarchy of OODA loops (see below). He also argued that fast OODA loops require a highly decentralized command and control using mission-type orders, or directive control (i.e., what the commander wants to see happen) as opposed to detailed control (i.e., how the commander wants things done. Such a structure, according to Boyd, would create a flexible "organic whole" that would be quicker to adapt to rapidly changing situations. He noted, however, that any such highly decentralized organization would necessitate a high degree of mutual trust and a common outlook that came from prior shared experiences. Headquarters needs to know that the troops are perfectly capable of forming a good plan for taking a specific objective, and the troops need to know that Headquarters does not direct them to achieve certain objectives without good reason. The OODA model of decision and action, originally for air-to-air fighter combat, has four phases. This discussion adds interaction with intelligence and command. Observe: become aware of a threat or opportunity Orient: put the observation into the context of other information; form one's perspective and situational awareness Decide: make the best possible action plan that can be carried out in a timely manner Act: carry out the decision. After the action, the actor observes again, to see the effects of the action. If the cycle works properly, the actor has initiative, and can orient, decide, and act even faster in the second and subsequent iterations of the Boyd loop. Ever-faster Boyd loops Eventually, if the Boyd process works as intended, the actor will "get inside the opponent's loop". When the actor's Boyd cycle dominates the opponent's, the actor is acting repeatedly, based on reasoned choices, while the opponent is still trying to understand what is happening. Modes of learning Individual human beings differ in the way they best learn new information. One common distinction uses: visual: accepting input through vision, testing action through writing and drawing auditory: receiving spoken input and refining it through discussion tactile: absorbing information through highly eye-hand interactive interfaces or developing physical skills, improving the skill by interaction. There is an unfortunate trend, in areas such as industry-specific skills and certification training, to overemphasize the tactile, and insisting that as much learning as possible be "hands on". That may be realistic for computer configuration and troubleshooting, but design skills tend to be visual and collaborative, expressed through drawings, drafting documents, and discussion. Another unfortunate trend is to recognize that some people learn from all these methods, so, whether individual remote instruction or the classroom, multimedia presentation is important -- but, ideally, it should be possible to select the delivery mode. Auditory or visual input may be useless to people with disorders of the ears or eyes. Depending on the topic, however, the learner may need a theoretical base for what is presented in the multimedia experience, but, even there, the learning should be participatory. Lecturers who frequently turn to the class with questions and followup discussion, using their expertise to stay on track, encourage original thought. Such thought is reinforced with frequent individual and team exercises that require synthesis of concepts, often with multimedia or interpersonal interaction. Patterns of creating knowledge Sometimes called a trend to "big science", many fundamental research problems are sufficiently complex to need a team effort. In areas such as particle physics and space science, it will take a mixture of skills simply to conduct the experiments. Collaboration, however, may be a key part of learning and creating. As mentioned above, some classroom experiences deliberately include team exercises. A review of scientific publication showed the greatest growth in research by three authors Cognitive traps Within the United States intelligence community and other areas where decisions must be made on incomplete knowledge, there is ever-growing awareness that cognitive errors come from poorly structured cognition and lack of collaboration. References