[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.
Data scientist, Matthew Coatney, took algorithms created for music and protein sequences, respectively, and applied them to analyzing global public-health data. Researchers wanted better insight into health outcomes across the world. They needed to break out of the binary, simplistic perspective of "developed" versus "developing" nations. Coatney's work took decades of time-series data and enabled detailed comparison between individual countries based on public policy, living conditions, and health outcomes.
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.
Astronomers at Harvard use MRI software to visualize astronomical data. Surgeons were using the technology for 3D visualization of the brain. The Astronomical Medicine Project was founded on the realization that space phenomena could be visualized using the same sofware, just as highly irregular brains.
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 in general.
Oliver Selfridge, one of the most influential thinkers in AI, had his ah-ha moment while reading Milton's "Paradise Lost." This 17th century epic poem tells the story of Adam and Eve cast from the Garden of Eden in the war between God and Satan. The capital of hell, Pandaemonium, is filled with shrieking demons, with Satan presiding over them. Selfridge developed the four-tier "Pandaemonium Architecture" for visual pattern recognition, comprised of image demons pushing data to feature demons pushing data to cognitive demons pushing data to decision demons. This architecture revolutionized the field, and Selfridge became known as the "Father of Machine Perception."
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.