The Adaptable Institution?

While Toby Miller’s focus in his paper Gaming for Beginners is largely concerned with players video games and consumers of media entertainment in general, he also points to the tendency of institutions to reject new media forms for fear of their perceived threat toward “…the established order.” (Miller. 7) By attempting to suppress new media forms in attempt to facilitate their less-relevant business models and/or organizational strategies, these institutions lose their ability to adapt to change. Take for example the position that the music industry circa 1999 took toward Napster and similar other peer-to-peer file sharing networks. Due in part to their resolution not to adopt this highly efficient distribution model, the major record labels – prior to this decision referred to as The Big Six – suffered massive financial losses.

In his forward to Ben Abraham’s Permanent Death – The Complete Saga Clint Hocking asserts that a fear of failure and straying from the familiar “…tends to make players choose a conservative path. It pushes them into the canyons of optimal strategy, rather than seducing them to climb the peaks of glorious idiocy where Roger Federer strides, swatting tennis balls between his legs, widening the eyes of all mankind.” (Hocking)

I am reminded of a software engineering problem that inventor W. Daniel Hillis wrestled with, as described in Steven Johnson’s book Emergence (Johnson. 170). As a common benchmark software challenge, programmers were tasked with creating a program that could arrange 100 random numbers in ascending order in the least number of steps. At the time that Hillis attempted this challenge, the record was 62. (ibid) Hillis approached this challenge by employing a genetic algorithm, wherein he “…instructed the computer to generate thousands of miniprograms, [sic] each composed of random combinations of instructions, creating a kind of digital gene pool. Each program was confronted with a disorderly sequence of numbers, and each tried its hand at putting them in the correct order.” (ibid) The system could quantifiably assess the fitness of each miniprogram’s ability to sort numbers. The genes of the programs that produced the best results became the basis for the next iteration of miniprograms, except that their code would mutate slightly and “…crossbreed with other promising programs.” (ibid) However, Hillis found that the descendant miniprograms could never complete the task in less than approximately 70 steps. He realized that since successful sorting programs would breed only with other successful programs, this created an elitism that tended to reject miniprograms with alternate strategies, which in the end resulted in a population of thinned genetic variance incapable of adaptation. Hillis’ solution was to implement ‘predator’ programs that would threaten the elite miniprograms with deletion if they demonstrated a persistent unwillingness to mix with the seemingly unfit miniprograms. (173) In other words, a choice that might lead to a lower fitness score became preferable over being deleted, thus increasing the potential creativity of the overall population. After implementing this, Hillis’ algorithm generated miniprograms that were able to sort the random numbers in fewer and fewer steps.

(Written by Michael Palumbo)
Works Cited:

Abraham, Ben. “Permanent Death – The Complete Saga.” Forward by Clint Hocking. SLRC – Subterranean Loner Rendered Comatose. December 4, 2009. http://drgamelove.blogspot.ca/2009/12/permanent-death-complete-saga.html

Johnson, Steven. Emergence: The Connected Lives of Ants, Brains, Cities, and Software. New York: Scribner, 2001. Print.

Miller, Toby. “Gaming for Beginners.” Games and Culture. 1.1 (2006): 5-12. Print.

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