Brain-as-Computer Discourses

AKA

Computational Metaphor

Focus

Interpreting learners and learning in terms of computers and computer functioning

Principal Metaphors

The “brain-as-computer” metaphor is also known as the “computational metaphor.” Other metaphors in this flock of associations include:
  • Knowledge is … information
  • Knowing is … using information
  • Learner is … an information processor
  • Learning is … inputting (and associated computer-based notions, such as processing, storing, and retrieving)
  • Teaching is … transmission (of information)

Originated

1950s

Synopsis

There is a long history of interpreting learning in terms of the latest technologies. Examples include writing on a tablet, taking photographs and films, and making connections on a telephone switchboard. Brain-as-Computer Discourses represent an uncritical continuation of this trend, through which knowledge is reduced to information, learning is cast as inputting, and cognition (which, here, is typically seen as distinct from learning) as computation – that is, manipulating/processing that information. Most Brain-as-Computer Discourses assume the following constructs:
  • Cognitive Modifiability (Cognitive Plasticity) – one's capacity and propensity for learning
  • Encoding – the principal metaphor of learning across Brain-as-Computer Discourses, derived from the act of inputting new information into a digital information processing system. The metaphor of “encoding information” is coupled to the metaphor of “inputting information” – a consequence of which is a variety of encoding types are imagined based on different sensory systems, in a manner that parallels popular Learning Styles Theories. All these types of encoding are suggested to be intermediate to the process of picking up sensations and extracting meaning:
    • Acoustic Encoding – ostensibly, brain-based processes by which information that has been gathered through the ears is converted into usable mental representations
    • Gustatory Encoding – ostensibly, brain-based processes by which information that has been gathered through the tastebuds is converted into usable mental representations
    • Olfactory Encoding– ostensibly, brain-based processes by which information that has been gathered through the nose is converted into usable mental representations
    • Tactile Encoding – ostensibly, brain-based processes by which information that has been gathered through touch is converted into usable mental representations
    • Visual Encoding – ostensibly, brain-based processes by which information that has been gathered through the eyes is converted into usable mental representations
  • Encoding Specificity Hypothesis – extending the Encoding metaphor, the suggestion that “retrieval of information” (i.e., recall) is improved if the cues used to trigger the recall match those that were present during the learning
  • Information Hypothesis – the assertion (and, frequently, assumption) that the “knowledge as information” metaphor is valid – that is, in effect, that Brain-as-Computer Discourses are sound
  • Input-Process-Output Model – any perspective that if founded on an image/metaphor of imputing raw materials or information that are processed by a system and then outputted as new, more-refined materials or information. On the level of personal, the Input-Process-Output Model is typically interpreted in terms of encoding information (input) that is transformed by cognition (process), leading to thoughts and actions (output). On the collective level, situational conditions (input) are socially mediated (process), leading to norms and assumptions (output).
  • Mentalese (Language of Thought; Thought-Ordered Mental Expression) (Jerry Fodor, 1970s) – a hypothetical construct that is used in some theories to explain human cognition. Based on an analogy between the combining of words into sentences and the combining of simple concepts to form more complicated ideas, Mentalese is seen as the set of innate grammatical rules that enables the composition of more and more sophisticated thoughts.
  • Model-Based Reasoning (Philip Johnson-Laird, 1980s) – a theory concerned with the mental processes underlying logical inferences. It assumes a brain-as-computer metaphor and thus posits that formal-logical operations are at work.
  • Neural Code (Spike Code) (Various, 1940s) – a metaphor based on 1–0 logical operations of digital computers that was proposed (to little avail) to describe and explain brain functioning
  • Sandwich Model of Cognition (Susan Hurley, 1990s) – a metaphor used to highlight the tendency of most Brain-as-Computer Discourses to assume a separation of perception (input) and action (output), thus positioning cognition between them as the process of converting perceptions into actions. (See Input-Process-Output Model, above.)
  • Two-Store Memory Model of Information Processing (Dual-Memory Model of Information Processing) – a framing of Short-Term Memory and Long-Term Memory (see Memory Research) in terms of stages, areas, and processes of digital information storage

Commentary

Brain-as-Computer Discourses represent a reversal of a prior metaphor that “computers are brains.” Brain-as-Computer Discourses were in part propelled by the fact that early computers proved to be very effective at tasks that their designers found difficult – namely, highly repetitive ones based on pure logic. Indeed, early successes on complicated mathematical tasks prompted some developers to predict, with confidence, that “electronic brains” would soon surpass their flesh-based counterparts. In spite of their popularity, neither metaphor (i.e., “brains are computers” or “computers are brains”) is tenable. Flatly asserted, brains are not digital computers. As problematical as the orienting metaphor is, however, many popular theories of cognition and/or consciousness (and their critiques) unproblematically assume it. Examples include:
  • Brain in a Vat (BIV; Brain in a Jar) (Gilbert Harman, Hilary Putman, 1970s) – an image involving an artificially sustained, disembodied human brain connected to a computer that simulates all the electrical impulses that brain would normally receive. This construct used in some thought experiments to highlight and problematize common-but-implicit assumptions about learning and cognition – although its implicit assumption of a computer-like brain is not often flagged.

Subdiscourses:

  • Acoustic Encoding
  • Brain in a Vat (BIV; Brain in a Jar)
  • Cognitive Modifiability (Cognitive Plasticity)
  • Encoding
  • Encoding Specificity Hypothesis
  • Gustatory Encoding
  • Information Hypothesis
  • Input-Process-Output Model
  • Mentalese (Language of Thought; Thought-Ordered Mental Expression)
  • Model-Based Reasoning
  • Neural Code (Spike Code)
  • Olfactory Encoding
  • Sandwich Model of Cognition
  • Tactile Encoding
  • Two-Store Memory Model of Information Processing (Dual-Memory Model of Information Processing)
  • Visual Encoding

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Please cite this article as:
Davis, B., & Francis, K. (2024). “Brain-as-Computer Discourses” in Discourses on Learning in Education. https://learningdiscourses.com.


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