Information Processing

History of Information Processing

IPS theory was inspired by advancements in computer science in the middle of the 20th century that sought to formalize the representation and transmission of information in digital formats. Information theory, primarily driven by mathematician and engineer Claude Shannon’s work on information channels and entropy measures such as the bit, was stimulated in part by the need to correct for transmission losses in telephone lines and interest in ways to recode messages to maximize transmission efficiency.

The notion of a code proved of central importance to the notion of symbol structures in information processing psychology. However, it soon appeared that the information metric, bits of information, would not be the best way to describe how humans processed information. Psychologist George Miller’s work on the role of recoding for human memory led to the view that humans store information in a limited capacity short-term memory in chunks, or matched patterns, rather than bits.

A second influence was the work of neurobiologists investigating brain function. They had traced out cellular mechanisms that supported transmission of information in the brain, particularly axonal firing (neural on–off states similar to bits) and graded responses involving the release of chemical neurotransmitters at synaptic clefts. Brain systems could also be characterized in terms of information transmission processes.

A third influence came from mathematician and philosophers Alfred Whitehead and Bertrand Russell’s work on formal logic and the application of rules to the process of drawing accurate deductions from premises. Logicians such as Alan Turing became aware of the power of newly designed computers (hardware) coupled with programs (software) to serve as universal computing devices. A major insight by computer scientists Allen Newell, Herbert Simon, and others was that higher level programming languages (e.g., Information Processing Language, LISt Processor) could enable computers to perform symbolic operations that mapped to human perceptual (pattern recognition) and cognitive (reasoning and decision making) activities.

Computers could serve not only as numeric (logical and arithmetic) computing devices but also as symbol-manipulating ones. Symbol processing meant that computers could represent the broad range of information that humans processed and simulate human cognition. Such simulation models were superior to previously existing verbal models of how humans perform cognitive tasks because they could actually perform the tasks. Finally, formalization schemes were also developing in parallel in fields such as linguistics, human factors, and developmental psychology.

Researchers in linguistics, particularly Noam Chomsky, advocated for systems of rules working on symbolic representations, such as rewrite rules for parsing syntactic structures in language, as the way to model language competence, including language development. Human factors specialists drew on communication channel models as they sought ways to improve human–machine interaction. In developmental psychology, Swiss psychologist Jean Piaget had advanced the framework of a child progressing in cognitive development according to stages characterized by mathematical operations such as preoperational, operational, and formal operational thinking.

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