Re: What is the most challenging question for the KM community? What is our biggest fear? #state-of-KM
Murray Jennex wrote:
All that said, the real point that I agree with Richard on is that we need to focus on socio-technical systems and not separate social and technical systems and I don't have the hang up about codifiying knowledge if we map the sources of knowledge and provide the communication and collaboration tools to ensure users and sources can link and share knowledge. This will probably put more emphasis on the knowledge creation and sharing cultures in organizations than on the technology in the organization. As I recall, we have always said technology is an enabler and not the answer. Of course someone did say that their question is what if technology is the answer. Technology hasn't been the sole answer for centuries so I'm not too worried about technology becoming the KM answer....murray jennex<<<just a quick comment Douglas, you call tacit knowledge personal knowledge while the more traditional definition is knowledge that cannot be well expressed. I can significant overlap with both definitions and not really complaining about that, but I do want to say that frankly I think all knowledge is explicit if we take the time to learn to express it and capture it. I believe the same for implicit knowledge. To me, then, the role of KM is to assist users to articulate and capture their implicit/tacit/personal knowledge and to make that knowledge available. Another way of doing this is to include knowledge maps with our knowledge bases that point to holders of specific tacit/implicit/personal knowledge.
I was just about to post up and say that so far what Doug wrote is about the only reply I’ve seen that made complete sense to me. I don’t know what distinction you are making between tacit knowledge and personal knowledge, though, Murray. I think the point is that much of KM has devolved into a focus on information and documentation management - ie, managing explicit or codified “knowledge”. I’ve watched this play out for the last 25 years or so and reached the conclusion that large enterprises only want to spend their money on scalable solutions with tangible outputs, and IT-based solutions are a natural fit with “managing stuff” part of KM.
Collaboration has come into the scene more lately, but unfortunately real collaboration platforms were co-opted by the likes of Slack, which while more entertaining for workers, produces less in the way of true valuable output and a more legitimate way for workers to socialize without really getting anything done (except perhaps creating and maintaining social capital at distance, which is in fact a benefit, albeit a mostly unrecognized one by most enterprises).
As we now enter into KM’s third or fourth age with the advent of true AI and machine learning, perhaps it would be useful to revisit Nonaka and Takeuchi’s breadmaking example. In fact, Ribeiro and Collins did just that in their 2007 research piece (https://journals.sagepub.com/doi/10.1177/0170840607082228). They talk about the bread making machine along with its operating manual as a “social prosthesis” requiring human intervention to fully replicate the results achieved by a master bread maker. They claim that without that human intervention, the breadmaking machine alone would not produce the same result. In other words, there is still something about the use of human hands in making bread that could not be instantiated in a machine, despite all the study of the master bread maker’s actions and the mechanical prowess of the resulting machine.
Perhaps the notion of a “social prosthesis” is something we might consider incorporating into our thinking about the work we do in KM going forward. The human actor will always be required, and the most valuable tacit knowledge will never be fully codified or otherwise made explicit, desipte how underpowered our puny little wetware CPUs are compared to the AIs with all their gigahertz and terabytes.
So yes, connecting us to each other is going to be where it’s at. Figuring out how to accomplish this on based on contextual cues on a just-in-time basis is going to be the gold standard. Seems like just the thing we might consider ordering our AIs to do - after all, they are here to serve us!