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In some sub-sects of economics, “knowledge spillover” refers to someone making use of someone else’s ideas or know-how to make their own discovery or invention.
The Industrial Revolution arguably happened as rapidly (and regionally, at first) as it did because Britain (and a few other hubs) had immense capacity for knowledge spillover in the mid-18th and mid-19th centuries, which meant one person’s development of a clever new way to utilize steam could be picked up by someone else who wanted to power a spinning contraption, and that would all be combined by a third person (or multiple third-people) into mechanisms capable of upending the global textile industry.
This is a perhaps intuitive idea that’s devilishly difficult to quantify because of how information and concepts are transmitted, how we learn and are inspired, and because ideas often mutate substantially between their broadcast and eventual utility, elsewhere.
In other words, innovation doesn’t travel linearly and it’s not only shared in formal research papers: it’s disseminated widely by individuals at cocktail parties and rumors in newspapers and hints of wisps of concepts mentioned in discussions about something else entirely.
Similarly, we don’t absorb information exclusively in formal settings via work-related mediums—we soak it up without realizing we’re doing so, our “eureka” moments often resulting from a jumble of information and ideas we soaked up, slammed together, and then regurgitated in slightly or dramatically different forms (or in some cases the same form, but in our own, unique voice).
And all of these free-floating concepts can evolve and iterate as they move about, each new brain recontextualizing them, adding and subtracting and rethinking them into distinct shapes with varied utilities.
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Some researchers have attempted to capture this process by looking at patents and attempting to measure the “knowledge flows” they portray.
Others have focused on sources of funding (like grants) and how (and how often) they lead to the publication of research findings in neighboring spaces (more specifically: how often discoveries related to the treatment of one disease spills over to the treatment of other diseases).
All such approaches are generally considered to be flawed and highly limited, capturing—at best—a Xerox of a snapshot of some ultra-specific facet of some individual industry or field of inquiry.
These finite findings can be useful, though, as this knowledge helps us understand which circumstances tend to lead to auras of beneficial knowledge spillover and which tend to artificially limit the same.
Some regulations may incentivize putting up walls around one’s research, for instance, because one might be held liable for someone else’s use of their work, if that work finds its way into something illegal or harmful.
For similar reasons, some entities tailor their R&D infrastructure so that their findings are locked-down and unavailable beyond their walls, not wanting to give their competition a leg-up on their dime.
Other entities spread their formal findings widely, though, the assumption being that while their competitors may learn from the knowledge they paid for, those competitors will tend to do the same for them, in return, and more knowledge and know-how bubbling around the ether is a net-positive for everyone.
One way to think about knowledge spillover is that it’s akin to the creative “scenius”: the collective brilliance of a group of people, often but not always located in the same geographic (or potentially, online social) space, their ideas and work informing and amplifying each other’s, rather than competing in a draining, deflating, zero-sum fashion.
Everyone’s work gets better as a result of being exposed to everyone else’s work, basically, so some sceniuses (or “clusters”) have led to breakthroughs, just as knowledge spillovers have led to the same (though often in a more economically relevant sense, rather than a creative one).
Refining our ability to track and measure these flows, then, even if our capacity remains limited and flawed, could help us adjust the variables of our businesses, organizations, and societies so more amplification occurs, helping these spaces, in turn, become breeding grounds for new understandings, rather than walled-off gardens that disincentivize cross-pollination.