[eg-zap-tey-shuh n], noun
1. The process by which natural features acquire functions for which they were not originally adapted or selected.
2. A cognitive model as well, describing the repurposing of ideas in other fields.
3. The ah-ha moment in which we suddenly realize that something we thought applied in only one context has important implications in a completely different domain.
If you want to learn more about the concept's origin in biology check out Stephen Jay Gould and Elisabeth S. Vrba's "Exaptation - A Missing Term in the Science of Form." To read about the repurposing of the concept to human innovation (exaptation's exaptation), check out Steven Johnson's Where Good Ideas Come From or listen to the talk.
We've curated some of our favorite cognitive exaptations below.
Political scientists and anthropologists used ecological models to understand organized crime in urban settings. Katherine Hirschfeld's "Ganger States" used models from the study of predatory-prey relations to predict the conditions under which crime syndicates evolve and intrude into formal political systems.Brantingham, Tita, Short, and Reid's "The Ecology of Gang Territorial Boundaries" used territorial ecological models to understand how territorial boundaries foment competition and violence among gangs.
Exapted Space Flight
The first private space plane, designed by Burt Ratan, reenters the atmosphere using wings inspired by a badminton birdie. Reentry was a stability problem. The badminton bridie (a.k.a. shuttlecock) immediately orients itself during flight. Interestingly, Ratan trumpets the importance of gut feel as a designer
, alongside training as an engineer.
Gutenberg invented the printing press after visiting a winery and seeing how juice was squeezed from grapes by a wine press. Screw press technology was antiquated even in his day but had been widely employed in agriculture for applying pressure on a flat surface. Gutenberg applied the idea to printing
, while improving the technology for that purpose.
Data visualization created by Martin Wattenberg for visualizing patterns in music
are repurposed to visualize gene sequences, among other string data. Geneticists hearing Wattenberg speak in 2011 quickly realized that gene sequences, like music, are series of letters and asked for help using the technology. Wattenberg expanded his understanding of arc diagrams to encompass visualizing the structure of strings
Oliver Selfridge was one of the most influential thinkers in the field of artificial intelligence. In the 1950s, after graduating from MIT with a degree in math and spending a decade focused on AI, pattern recognition, and neural networks, he re-read Milton's "Paradise Lost". This 17th century poem tells the story of Adam and Eve being cast from the Garden of Eden as part of the war between God and Satan. At one point the poem describes the capital of hell, a place Milton named "Pandaemonium", filled with shrieking demons, and Satan, on the top of a mound, presiding over them. This imagery triggered Selfridge's "ah-ha!" moment regarding artificial intelligence. What if, instead of a bunch of crazy demons shrieking up to Satan, a computer program could be comprised of a bunch of very small, and not so smart, programs shouting their simple realizations to a larger, more powerful demon that could synthesize those "shrieks" into something meaningful? By thinking about AI as a set of chaotic social interactions, Selfridge developed the 4-tier "Pandaemonium Architecture" for visual pattern recognition, comprised of image demons pushing information to feature demons pushing information to cognitive demons pushing information to decision demons. When this architecture was published in 1959 it revolutionized the field and led to Selfridge becoming known as the "Father of Machine Perception".