Back in the early days of KM, big 4 consulting
firms (I think there were six back then) saw the potential
of KM and started experimenting with various tools and
approaches. And it made sense for them to get onboard
early: their assets were purely knowledge-based and went
down the elevator every night.
Back in 1989, Andersen Consulting hired AI guru
Roger Schank and gave him $30million to play with and
continue his research (he was at Stanford) hoping for some
breakthroughs they could apply to their business.
One KM-related project he worked on involved conducting
and videoing knowledge elicitation interviews with
experts. The thought was that if we could simply interview
people and video it all, it would capture knowledge in a
way that could be then inventoried, tagged and searched
for future retrieval and re-use. I don’t know how much he
spent on it, but word was it was in the millions.
In any case, that didn’t work. When I learned about
this effort I was at IBM, and I knew it wouldn’t work. We
didn’t have the tools to cope with vast amounts of
unstructured data, even when it was in text format, much
less video format.
But maybe now that is about to change. Some MIT
alums are building a startup called Netra around an AI
engine that is supposed to be able to parse video content
and categorize it automagically. Might be a good one to
watch. Who knows? Maybe Schank will be vindicated after
all, and video knowledge elicitations will become a thing
alumnus-founded Netra is using artificial intelligence
to improve video analysis at scale. The company’s system
can identify activities, objects, emotions, locations,
and more to organize and provide context to videos in
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