Cognitive science
Cognitive science is the result of interdisciplinary efforts between psychology, neuroscience, computer science/artificial intelligence, linguistics and philosophy, but also anthropology and sociology. Its central subject is conscious and unconscious experience, which is often located between the sensory and motor systems, as well as the processing of information in the context of human thought and decision-making. This includes, for example, perception, thinking, judgement, memory, learning and language. Its subject area is not limited to cognition, but just as much encompasses emotion, motivation and volition.[1]
Cognitive science partly abstracts from the question of whether cognition is studied in organic systems or living beings, or in artificial systems such as computers or robots, by considering cognitive processes as information processing.
Methodology
Methodologically, cognitive science works on different levels:
- theory building, which serves to form hypotheses,
- cognitive modelling, which simulates cognitive performance with the help of computer models and integrates new hypotheses into these models,
- and the empirical level, which deals with the empirical testing of the models and the concrete implementation of cognitive performance.
Development of cognitive science
History of cognitive science
The development of cognitive science is associated by some with the notion of a so-called "cognitive turn" (c. 1940-1970). Until then, behaviourism had played an authoritative role in psychology and philosophy of mind. Behaviourism had emerged as a reaction to the problems of introspection as a psychological research method. Introspective accounts of the mental inner life were not externally verifiable by scientists. Behaviourism drew the conclusion from this that psychology had to limit itself to a study of behaviour. In the philosophy of mind, Gilbert Ryle, for example, went one step further and claimed that mental states were no more than behavioural dispositions.
In 1956, the Symposium on Information Theory took place at the Massachusetts Institute of Technology, with the participation of AI pioneers Allen Newell, Herbert A. Simon and Marvin Minsky, as well as the linguist Noam Chomsky. Chomsky presented a sharp critique of behaviourism[2], which itself was heavily criticised[3], and introduced his influential transformational grammar. Newell and Simon presented the Logic Theorist, which was the first to independently "prove" a theorem of mathematics. Important precursors of this development were the formulation of cybernetics by Norbert Wiener and the work of Alan Turing, who designed the Turing machine and developed the Turing test.
Cognitive science, which was constituted in the context of the developments described above, was based on a central assumption called the "computer model of mind". This refers to the thesis that the brain is an information-processing system and works in principle like a computer. The distinction between mind and brain can be understood analogously to the distinction between software and hardware. Just as software is determined by data structures and algorithms, the mind is determined by mental representations and computational processes. Just as the abstract description of software is possible without directly examining the hardware, an abstract description of mental abilities should be possible without directly examining the brain. And just as the existence of a software level was easily compatible with materialism, the mental level should also be embedded in a materialist interpretation.
Current developments
The computer model of mind has been subjected to sharp criticism in recent decades. This criticism has two main sources: First, the description of the brain by cognitive neuroscience has developed rapidly. This is reflected, for example, in the increasing importance of medical imaging techniques, which make it implausible not to consider the brain in the study of the mind. On the other hand, other successful approaches have developed, such as connectionism and neural network modelling. Artificial neural networks are programmed, among other things, to simulate the activities of neuron associations. It is doubtful to what extent a distinction between software and hardware level is still possible here.
Other alternative paradigms in cognitive science are, for example, dynamism, artificial life and embodied and situated cognitive science. According to dynamism, dynamical systems theory provides a suitable model of cognitive behaviour because cognitive behaviour always occurs in a temporal context and requires temporal coordination. It is postulated that this temporal aspect of cognition, which is neglected in the computer model of the mind, is essential. On the other hand, this approach questions the centrality of internal representation and symbol manipulation (cf. symbolism), since these concepts are not part of a dynamic explanation.
"Artificial life" is a term that contrasts with artificial intelligence: instead of solving abstract tasks (such as analysing chess positions), which often seems difficult to us humans because of the sheer number of possible solutions, but is easy for computers, we should first understand how to cope with supposedly mundane everyday problems. Many tasks that seem simple to us (such as walking, recognising friends and enemies, catching a ball ...) can currently not be mastered by computers or robots at all or only to a very limited extent.
See also
- Cognition
- Cognitive science - Article in the English Wikipedia
References
- ↑ Cf. Margaret Boden: Mind as Machine. A History of Cognitive Science, Oxford University Press, 2006, p. 10ff.
- ↑ Noam Chomsky: A Review of B. F. Skinner’s Verbal Behavior. In: Language. 35, Nr. 1, New York 1959, ISSN 0097-8507, pS. 26–58, doi:10.2307/411334 online text.
- ↑ Kenneth MacCorquodale: On Chomsky’s Review of Skinner’s Verbal Behavior. In: Journal of the Experimental Analysis of Behavior. 13, Nr. 1, 1970, p. 83-99, PMC 1333660 (free full text)
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