Abstractions: the benefits and dangers

Why is abstraction such a powerful technique in computer science, but a potentially befuddling one in the social sciences? In computer science, abstractions permit one to:

  1. increase the scope of the construct being abstracted
  2. hide unnecessary details
  3. cleanly define object/functions and their interfaces

Yet, in social science it:

  1. increase the scope of the construct being abstracted
  2. hides details — but how do we know whether those details were important?
  3. often has muddled definitions with few cleanly define interfaces

The potential danger is that abstraction in the social sciences — often spoken of as “theory” though I prefer to think of theory in this context as a metaphysic or framework — is that it increases the scope of action while possibly becoming muddled and detached from reality. With greater scope, comes a greater responsibility to clarity.

Consider, that one rarely hears of a computer abstraction being overly broad because it is necessarily grounded in the reflexive practice of usage. (If it’s broken, it’ll get fixed.) For example, the Python sort function takes an object to be sorted and returns a similar, sorted, object. We need not be overly concerned with the algorithm or its implementation. Furthermore, as new data structures are developed, one can pass it a specific compare function relative to that data structure. We get to re-use the concept of “sort” with enough specificity as needed — but no more.

Social science “theorists” tend to resist attempts to cleanly define words, to explicitly model a construct, or be “reduced” by attempts at clarity and coherence. When I asked a student about the meaning of a word he used because I could not find it in the dictionary he replied, “that’s your mistake, don’t look these words up.” Oddly enough, Bourdieu’s most useful work is in an extended interview — as is McLuhan’s Playboy interview — though they both fear being overly reduced by this form of discourse. Consider how this differs from the following well-known anecdote:

Richard Feynman, the late Nobel Laureate in physics, was once asked by a Caltech faculty member to explain why spin one-half particles obey Fermi Dirac statistics. Rising to the challenge, he said, “I’ll prepare a freshman lecture on it.” But a few days later he told the faculty member, “You know, I couldn’t do it. I couldn’t reduce it to the freshman level. That means we really don’t understand it.”

If only we were so humble in the social sciences — and Feynman was not known as a humble man; perhaps he figured that if he couldn’t do it, then no one could.

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