The Contribution of Computers to the Study of Cognitive Psychology

Cognitive psychology in the last years has produced impeccable data concerning specific elements of the structure of the mind. Scientists from many disciplines, including physical science, life science, mathematics, chemical science, and neuroscience, contribute to the study of cognition. Cognitive psychology, the scientific study of the human mind and information processing, is at the core of empirical investigations into the nature of thoughts and behaviour. Earlier cognitive scientists viewed the mind as a processor, like the newly known digital computer (Miller, 2003).

The mind was known to be a passive recipient of information, which registered information into the short-term memory and encoded it to the long-term memory. The comparison of the human mind and computer information processing approach was made to point out that the mind is a parallel processor and has emphasized that mental structures of the mind are active, and they all are occupied by specific context (Whitworth & Ryu, 2012). Hence, cognitive psychologist contributed to science by using models which are tested in an orderly manner.

Furthermore, they become increasingly involved in the design of new computer systems and in research and theory aimed at understanding the components of the human brain. The future contribution of cognitive psychology to the study of computer science is especially seen as illustrative and interesting. In addition, the consideration of artificial intelligence and computer simulation are one of the main topics that covered by cognitive psychology in computer science. Therefore, a brief history that follows the contribution of computers to the study of cognitive psychology from the start of cognitive revolution to the beginning of the twenty-first century, will be discussed.

Cognitive Revolution of Computer Science

The cognitive revolution was a start of the modern scientific study of the mind. Since the beginning of human experimental psychology in the nineteenth century, there has been high interest in the study of cognitive psychology concerned with the mental processes (Leary, 1994). The arrival of cognitive revolution and computer science was illustrated from the study of behaviourism. During the early nineteenth century, psychology was dominated by behaviourism. Behaviourism, the study of stimulus-response relationship, claimed that all mental states can be reduced to statements of observable behaviour (Leary, 1994). The development of behaviourism was viewed by a group of experimental psychologists, which were influenced by Ivan Pavlov, John B. Watson and B. F. Skinner, who proposed to redefine psychology as the science of behaviour. The study of behaviourism was invested in the study of perception, memory, language, and intelligence, and was particularly concerned with the learned association in human and nonhuman species (Miller, 2003). However, soon after psychologists rejected the model of behaviourism, stating that “the relationship of the stimulus-response formula disregards the fact that between the stimuli certain patterns of association occurs, mainly in a stage of group-units in which they require new characteristics”, (Leary, 1994). In addition, something psychologically must have been happening on the inside of the organism. Hence this something become the focus of cognitive psychology.

Cognitive psychology emerged in the 1950’s during the so called “cognitive revolution”. The emphasis of psychology shifted away from the study of conditioned behaviour and psychoanalytical ideas about the study of the mind, towards the understanding of mental processes and internal mental states (Klahr, 1988). The process of human information processing was said to resemble that of a computer system, and based on transforming, storing and retrieving information (Klahr, 1988). The records of revolutionary events concerning the development of computers and their application in cognitive psychology was accounted for. In the early 3000 BC, the Chinas abacus was one of the first machines that was ever created to be used for counting and calculating. During the late 1600s, Gottfried Leibniz, a pioneer in many fields and the first computer scientists, created his own calculating machine, which was able to perform arithmetic operations. Leibniz was also the first to establish the concept of binary arithmetic on how all technology in our days communicate and he envision a machine that can be used in a binary code. Processing to the 1800s, Charles Babbage, was known as the father of the computer, with the design of his mechanical calculating engines. In the early 1820, Babbage observed that many computations consisted of operations that were regular repeated and theorized that these operations can be done automatically. Hence, he created a so-called difference engine and later an analytic engine, which elaborates on the difference engine on executing operation in non-numeric orders through the addition of conditional control, store memory, and read instructions from punch cards. However, Babbage inventions were never created due to the lack of fundings back then. Ada Lovelace, Babbage’s follower, was considered the first programmer who created an algorithm that would calculate Bernoulli numbers and that was designed to work with Babbage’s machine. Long after Herman Hollerith an American inventor, designed one the first successful electromechanical machines, referred to as the census tabulator (the first iteration of a keyboard). The tabulator could read U.S. census data from punched cards, up to 65 at a time and tally up the results. In addition, the 1800s were a period where the theory of computing began to evolve, and machines were used for calculation. However, the 1900s is the core investigation of where the development of computers and their application to cognitive psychology is revealed through Alan Turing.

The Advancement of Computer Science in Cognitive Psychology

Artificial Intelligence

Artificial intelligence has been a topic of growing prominence in the media and mainstream culture since 2015, as well as in the investment world, with companies that even mention the word in their business model, gaining massive amounts of funding (Russell & Norvig, 2016). However, while to many, the hype around artificial intelligence has appeared sudden. The concept of modern artificial intelligence has been around for a century and extending further. For over thousands of years, philosophers have tried to understand how the human mind operates. The arrival of usable computers in the early 1950s turned the mental process into a real experimental and theoretical discipline (Sperry, 1993). Alan Turing during the 1950s pondered the dilemma of true versus imitated intelligence in section 1 of his paper, Computing Machinery and Intelligence, titled the Limitation Game. In this paper he lays the foundations for what is now referred to as the, Turing Test, the first series proposal in the philosophy of a computing based artificial intelligence (Russell & Norvig, 2016). The Turing Test state that, if a machine acts as intelligent as a human being, then it is as intelligent as a human being. An example is the online chatroom, in which if we are talking to an artificial intelligent bot but aren’t told this before and we believe during the conversation that is was a human, then the bot passes Turing Test and is deemed intelligent. Around the same time as Turing proposal, another titan of the field of computing, the father of the information age, Claude Shannon, published the basics of information theory, in his landmark paper called Mathematical Theory of Communication, in 1948. Information theory is said to be backbone of all digital systems today and a very complex topic. In layman’s terms and in relation to computing, Shannon’s theory states that all information in the entire universe can be represented in binary. This has profound implication for artificial intelligence, meaning we could break down human logic and more so the human brain can replicate its processes with computing technology. This was demonstrated a few years later in 1955 by what is named as the first artificial intelligence program, called, Logic Theorists. A program able to prove 38 of the first 52 theorems in Principia Mathematics, a three-volume work on the foundations of Mathematics. This program was written by Allan Newell, Herbert Simon and Cliff Shaw, who like philosophers and mathematics before them also believed that human thoughts could be broken down , with them stating, “the mind can be viewed as a device operating on bits of information according to formal rules”. That being is was realized that a machine that can manipulate numbers can also manipulate symbols and that symbols manipulation is the essence of human thought. Also, during this time-period, in 1951, Marvin Minsky, one of the founding fathers of the field of artificial intelligence, He built the first machine incorporating a neural net, the stochastic neural analogy reinforcement calculator. In addition, it can be seen that during the mid-nineteen centuries, with computers becoming more comparable every year, increasing research into abstracting human logic and behaviour, and development of the various neural net and other various innovation are the first of modern computing based on artificial intelligence. Henceforth, artificial intelligence currently covers a variety of subfields in studies of perception and logical reasoning.

Computer Simulation

In conclusion cognitive science is a multidisciplinary field. A computational view emphasizes that, ‘cognitive science, tries to explain the structure of the mind by treating them as components. The start and use of computers in the study of cognitive psychology allowed psychologists to better understand the complexity of the human mind and its characteristics. This context known as computer analogy, is the use of a computer as a tool of thinking to how the human mind processes information. Basically, the human brain like a computer retrieves, restores and processes information. Hence, computer analogy gave powerful thoughts about the representations, and in addition the processes that operate on these structures. The subsequent idea of human information processing as sequences of computational processes operating on mental representations remains the cornerstone of modern cognitive psychology.

References

  1. Aaronson, D., Grupsmith, E., & Aaronson, M. (1976). The impact of computers on cognitive psychology. Behavior Research Methods & Instrumentation, 8(2), 129-138.
  2. De Jong, T., & Van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of educational research, 68(2), 179-201.
  3. [bookmark: _Hlk17073629]Klahr, D. (1988). Characterizing information-processing approaches. Information Processing Approaches to Cognitive Development (pp. 1-21). Pittsburgh.
  4. Landauer, T. K. (1987). Relations between cognitive psychology and computer system design. Interfacing thought: cognitive aspects of human-computer interaction, 1-25.
  5. Leary, D. E. (Ed.). (1994). Metaphors in the history of psychology. Cambridge University Press.
  6. Mahoney, M. S. (1988). The history of computing in the history of technology. Annals of the History of Computing, 10(2), 113-125.
  7. Miller, G. A. (2003). The cognitive revolution: a historical perspective. Trends in cognitive sciences, 7(3), 141-144.
  8. Russell, S. J., & Norvig, P. (2016). Artificial intelligence. Artificial Intelligence: A Modern Approach. (pp. 1-29). Malaysia; Pearson Education Limited.
  9. Sperry, R. W. (1993). The impact and promise of the cognitive revolution. American psychologist, 48(8), 878.
  10. [bookmark: _Hlk17067152]Whitworth, B., & Ryu, H. (2012). A comparison of human and computer information processing. In Machine Learning: Concepts, Methodologies, Tools and Applications (pp. 1-12). IGI Global.
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