Knowledge Retention and the Importance of Forgetting
Three things happened in conjunction this morning that made me wonder whether memory and experience have some underestimated drawbacks. In order,
- I saw Jack's post about Knowledge Retention
- My server stopped working because it was full, and
- I read a paper by Martin Dodge on the ethics of forgetting in an age of pervasive computing
All of which conspired to tinkle a little - well, tiny - bell in my head, because a long time ago I remember being struck by something in Kevin Kelly's book Out of Control [online version], namely that death was an integral part of a healthy complex system.
Jack's post pointed to a Dorothy Leonard article in CIO called "How To Salvage Your Company's Deep Smarts". In it she writes:
The approaching exodus of retiring baby boomers will severely erode the knowledge base of many companies. Fortunately, there are ways to re-create this crucial expertise.The premise of the article is that it is "a bad thing" for a company to lose experienced heads, and on top of the discussion at the end of the article, Jack (and students) ask some great questions, such as has the damage ever been quantified, and how many people actually ever stay long enough at one job to accumulate "deep smarts" about the company?. So that was the first thing.
... But people with deep smarts can be indispensable. Why? Because their particular brand of expertise is based on long, hard-won experience. They are the go-to people known for their swift, seemingly intuitive judgments. Such experts differ from their less experienced colleagues in having the ability to view a problem at a system level and yet dive into the details when necessary - and identify a familiar pattern.
Second was much more mundane. I'd mailed my service provider saying that things weren't working, and they mailed back to say that it was bacause I'd used up all my disk space. And my first reaction was "oh-my-god-that-means-I'm-going-to-have-to-lose-some-of-the-blog-I-wasn't-expecting-that-andwhich-bits-aren't worth-keeping". It was pretty standard squirrel behaviour, or what you might call blind accumulation with no trashing strategy. Panic, albeit short-term, that throwing anything away meant loss for the future.
Third, in this, erm, "unprecedented" chain of events was my reading Martin's paper. It's about life-logging - be that externally generated data about how you shop or blogs - and it's well-worth a read. Martin and Rob Kitchen
want play devil's advocate to the drive to create technologies that store and manage a lifetime's worth of everything - by suggesting that memory should always be complemented by forgetting. We thus posit that forgetting is not a weakness or a fallibility, but is an emancipatory process that will free life-logging from burdensome and pernicious disciplinary effects; as Nietzsche suggests, forgetting will save humans from historyThey point to some interesting work by artists beginning to examine questions about the 'reality' of trying to live in a life-logged world. Lucy Kimbell ("I measure therefore I am"), Ellie Harrison's Eat 22 project, and Stephanie's work at All-Con$uming.com
They go on to suggest the intriguing idea of building forgetfulness into systems.
Perhaps, in the process of designing and implementing life-logging, forgetting should be an integral part of any system. This, we feel should happen from the bottom-up and be a core feature of the life-log, rather than from the top-down wherein legislation or organisational policy is used to regulate 'perfect' life-logs. So, rather than focus on the prescriptive needs for privacy protections, we envisage necessary processes of forgetting, following Schacter (2001) six forms, that should be in-built into the system ensuring a sufficient degree of imperfection, loss and error. The goal is to make the system humane and yet still useful.It's a great idea. And one that, if we're to subsribe to bottom-up systems, emergance and all that jazz, we should perhaps be going for full pelt.
Strong learning methods require smart teachers; that's one type of learning. A smart teacher tells a learner what it should know, and the learner analyzes the information and stores it in memory. A less smart teacher can also teach by using a different method. It doesn't know the material itself, but it can tell when the learner guesses the right answer-as a substitute teacher might grade tests. If the learner guesses a partial answer the weak teacher can give a hint of "getting warm," or "getting cold" to help the learner along. In this way, a weaker teacher can potentially generate information that it itself doesn't own. Ackley has been pushing the edge of weak learning as a way of maximizing computation: leveraging the smallest amount of information in, to get the maximum information out. "I'm trying to come up with the dumbest, least informative teacher as possible," Ackley told me. "And I think I found it. My answer is: death."Without some type of "death" in the (evolving) system, the system doesn't learn. And (also from the link) going for Lamarckian, cherry-picked solutions doesn't necessarily give you the best results. (Perhaps put another way, good teams need variety?)
From all of which overlong ponderings, I thought:
- "churn" may well be a good thing for companies. People with "deep smarts" may not be all they're cracked up to be. Though obviously there are social issues here, too much churn and people get depressed and demotivated etc.
- innovation may well be stifled by spending too much time trying to keep hold of the deep smarts and worrying about what you're losing (as a company or as a blogger)
- Minimum input, maximum output learning sounds great (!)
- How do you identify the people with deep smarts? Age? Or ability to learn? Or cultural fit? Or network position? Or...
In short, there's a danger in focusing too heavily on the individual expertise. Focusing on their being able to share it (as the CIO article suggests), and on (any) others being able to tap into it while those experts are working might be a better, cheaper approach.