In my last post, The Headlong Rush Into Analytics, I dabbled with several analytics tools to graph the undergraduate majors of law school attendees over a recent 14-year period. Ask a real data scientist if “dabbling” is the right word for describing my little experiment and the response will probably be some combination of rolled eyes, grumbling and sighs. That’s what experts in any field of endeavor tend to do when they come across a layperson dabbling in their specialty. Each and everyone of us has done our share of dabbling, and we’ve all probably reacted with disdain when viewing the dabbling of others in our own areas of expertise. I know for certain that I’ve often enough snorted at the amateurish efforts of others who ignorantly comment on KM or, worse yet, roll out some application and call it a knowledge management initiative.

What is it about dabbling that makes it so irritating and yet so strangely irresistible to those of us involved in knowledge management? Think about it. Dabbling is in some respects a precursor or catalyst for KM. You might even say that the purpose of KM is to harness the curiosity and confidence that compels one to dabble and to guide it in a structured way toward just-in-time understanding. In short, knowledge management is supervised dabbling!

Left unattended, dabbling sometimes results in genuine knowledge acquisition and even insight but it too often results in unjustified (i.e., lucky) true belief or even false belief. The former will eventually lead to misapplication of the belief and associated expense or embarrassment, and the later will just accelerate that eventuality. Knowledge management, done correctly, constructs an environment in which “dabblers” can achieve successful outcomes and appear to others to have expertise even if the dabblers themselves remain non-experts. Conversely, KM done incorrectly or incompletely can turn ordinarily cautious individuals into disinhibited dabblers who make poor decisions and give inexpert advice. In the absence of a good KM structure, dabbling is constructive only so long as the outcomes are inconsequential and the conclusions drawn are provisional and not promoted to others as knowledge-based. (If you would like to dabble in a bit of related philosophy, click here.)

In this Internet Age when so much content is frictionless and readily accessible (e.g., the Wikipedia link in the preceding paragraph), dabbling becomes something of a social necessity; and with everyone dabbling, our faculty for discriminating between mere dabblers and real experts is over-burdened to the point of exhaustion. We too easily accept the pseudo-knowledge of dabblers who toss around impressive jargon and too readily reject the guidance of experts just because we’ve turned to generalized skepticism and rejection of traditional authorities. I was reminded of this problem at LegalTech last week. It’s exhausting to go booth-to-booth, session-to-session and event-to-event trying to converse intelligently with friends and strangers alike on so many technical products and topics. Let’s face it, most of us there were often just dabbling and that includes many of the individuals staffing the vendor booths (and a good share of the session panelists I’d presume).

Am I being too cynical here? Consider this: a LegalTech News article covering one of the sessions described a blockchain as “based on an algorithm that records data in a hatch…” It doesn’t require much dabbling in blockchain technology to know that the term is “hash,” not “hatch.” The error is now corrected in the article, but it’s still obvious that the writer simply wasn’t familiar with this fairly obscure corner of technology. To be fair, the legal technology community (including the press) has only very recently begun to consider the potential for smart contracts and other blockchain-based legal applications. I didn’t attend the session itself, but I wonder just how much genuine understanding of this specialized and rapidly evolving topic was present in the room and how much of it was just a generalized exercise in dabbling? How many of these conference events are more than excuses for collective dabbling by attendees, self-promotion or product marketing by presenters and socializing for all?

So, yes, we’ve become a society of dabblers and without proper adult supervision – i.e., access to real subject matter experts, formal education or the kinds of authoritative knowledge resource KMers are often involved in managing – we are all at risk of ever-wider but ever-shallower intellects. I see this as the next great challenge (or opportunity, depending on your perspective) of the emerging (post) Web 3.0 era. Dabbling is on the rise and reliance and trust of traditional modes of authority is on the wane. As the various forms of artificial and augmented intelligence are added to the Web 3.0 mix, will dabbling itself become even more compelling and useful or will it just scale up collective expectations and magnify the detrimental consequences when our dabbling goes awry?

Dabble on it and let me know what you think…

[Note: My apology for anyone expecting this post to be the previously promised one about a major BigLaw metadata challenge. Stay tuned for that upcoming post.]