When I speak with student groups, which I do as often as possible, I count it as an extra-successful engagement when I’m asked a question I haven’t thought of — and even more so if it’s one for which I need to really think through my answer.
The other evening I Zoomed with the students at Kent State’s highly-regarded program in Knowledge Management. I was the guest of Prof. Kendra Albright, who not only shares my interest in the economics of information, she has designed a comprehensive required course covering the subject.
Her student’s question went something like this: “You claim the Knowledge Economy (KE) began in 1962, when Fritz Machlup defined it as such. But wasn’t knowledge equally important in the industrial era — the age of steam and other labor-saving inventions — or even earlier than that?”
My immediate thought was that “everybody knows” (who cares about such things) that the KE began in the 1960s — that’s the modern consensus view. But, before I spoke, I realized that “it ain’t necessarily so.” Consensus does not equal truth. (Napoleon Bonaparte’s aphorism, “History is a set of lies, agreed upon,” comes to mind.)
My own research shows that the analog era KE began much earlier than this — around the time of written language (3200 BCE). There is ample evidence that writing was invented in order to facilitate economic transaction — not merely as a by-product. Analog electronic technologies from the 19th and 20th centuries — including game-changers the telegraph, the telephone, radio, and television — were every bit as impactful in their time as the internet is in ours. This implies that Machlup’s 1962 benchmark more accurately represents the beginning of the digital era KE — what we usually think of today as “the” KE.
Another similar example recently came to my attention. “Everybody knows” that the Scientific Revolution occurred somewhere around 1600. But did you know that the term Scientific Revolution was not coined until the 1950s? (I didn’t.) We typically realize that something has happened — especially with big, slow, intangible changes such as these — after they have happened, sometimes long after. That is to say, there is a time lag between when something occurs in the real world, and the time we realize it and document it.
In a more modern example, it was not until March 11, 2020 that the World Health Organization declared the Covid-19 outbreak a global pandemic. This was several months after cases were first reported, and most likely even longer after the first cases occurred but went unreported or even unrecognized.
In short, there is latency between a phenomenon’s occurring and somebody knowing that it has happened. To make things sound appropriately serious, let’s call this phenomenal-epistemic latency (PEL).
The process works like this: some event happens —> somebody realizes (i.e., “knows”) that it has happened —> somebody talks about it —> somebody writes about it —> more people realize it has happened. Each of these steps adds to the latency.
In effect, PEL governs the speed of knowledge; the lower the latency, the faster the speed. Note that by this we do not mean the speed at which an individual learns — a different construct altogether — but rather the speed at which knowledge moves through a given network.
There has been much said around the observation that “knowledge is social.” (There is, for example, a sub-field focusing on the sociology of knowledge.) Knowledge travels in social networks. Knowledge transmission within a network is not instantaneous; it travels at some finite velocity. Knowledge spreads through a network incrementally, and typically with increasing speed — virally, that is to say.
When the novelist Willian Gibson famously said, “The future is here already — it’s just unevenly distributed,” something like this could be what he had in mind.
All the above begs the questions: How can we advance the speed of knowledge? How can we measure and reduce latency (PEL)? How can we identify and remove the barriers to knowledge flow? More on these soon…
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