Learning Dougspeak: The Importance of Shared Language

I worked with Doug Engelbart in various capacities from 2000 through 2003, and I often retell lessons and stories from those experiences. My favorite — untold on this blog so far — is how I almost wrote Doug and his ideas off early in my exposure to him. It’s a tale of one of my most significant transformative experiences and of the importance of Shared Language.    (1VF)

I had known of Doug’s inventions for many years because of my interest in Computer History, but my first exposure to his ideas about bootstrapping and organizational improvement occurred in 1998, when I attended a talk he gave at BAYCHI. I was hoping to hear stories about working at SRI in the 1960s and his perspective on usability today. What I got was an abstract lecture on organizational knowledge processes and cognitive frameworks. I walked away very confused.    (1VG)

A year later, Institute for the Future organized a day-long seminar at Stanford to mark the 35th anniversary of the mouse. It consisted largely of testimonial after testimonial from people whose lives and work had been touched by Doug, as well as hints of his larger, more humanistic goals. I was struck by the tremendous intellectual and emotional impact he had had on so many people’s lives, many of whom had gone on to do important work themselves. Both the speakers list and the attendees list read like a who’s who of the history of Silicon Valley.    (1VH)

In 2000, Bootstrap Institute organized a followup colloquium at Stanford. It was a 30-hour (over 10 weeks) seminar on Doug’s ideas, taught by Doug himself and featuring an impressive list of guest speakers. Naturally, I enrolled.    (1VI)

The first week’s session was great. Doug outlined his big picture, which was mind-blowing in and of itself, then marched out several guest speakers who provided some real-world context for Doug’s work.    (1VJ)

The second and third weeks were not as good. Doug began drilling down into some specifics of his framework, and it was starting to feel redundant and irrelevant. I was also getting the feeling that Doug was unaware of what had happened in the world over the past 30 years. “We know all of this already,” I thought. I wasn’t gaining any new insights.    (1VK)

After the fourth session, I had coffee with my friend, Greg Gentschev, who asked me how the colloquium was going. I told him I was going to stop attending, that the content was worthless, and that Doug was a kook. Greg, knowing little of Doug or his work, asked me to explain.    (1VL)

So I did. I started describing Doug’s conceptual universe. I explained his larger motivation regarding the complexity of the world’s problems and mentioned scaling effects and where humans and tools fit in. I translated some of his terminology and threw in some of my own examples.    (1VM)

As I talked, I had an epiphany. I had learned something significant over the past four weeks. I had spent 40 hours mentally processing what I heard, and when I finally had the opportunity to describe this stuff to someone, I realized I had a rich language for describing a powerful conceptual framework at my disposal. Doug wasn’t teaching new facts or force-feeding his opinions. He was rewiring our brains to see the world as he did.    (1VN)

That conversation with Greg convinced me to stick out the colloquium, which led to me getting to know Doug, which eventually led to what I’m doing now.    (1VO)

I recount this story here not out of nostalgia but because of the value it reaffirmed. Language is critical to learning, and Shared Language is critical for collaboration.    (1VP)

The first phase of an MGTaylor workshop is known as a Scan phase. It often consists of explorations of themes that have seemingly nothing to do with the topic at hand. Even worse, those explorations are often kinesthetic and quite playful. People don’t feel like they’re doing work at all, much less the work they think they’re there for. Many people get upset after the first third or half of an MGTaylor workshop.    (1VQ)

That usually changes in the end, though. That first phase is all about developing Shared Language. Once that language has been developed, the work (or “Action” phase) is highly accelerated. People are more productive working together than ever before.    (1VR)

Every effective facilitation technique I’ve seen incorporates this Shared Language phase at the beginning. Allen Gunn‘s tends to be more directed. Jeff Conklin‘s is entirely about developing Shared Language — he comes in for a few hours or a day and facilitates Shared Language via Dialogue Mapping. MGTaylor‘s is particularly effective with large, eclectic groups. However, it’s also critical that people stay for the entire event, despite their frustration. Otherwise, they miss out on the epiphany.    (1VS)

People get frustrated with meetings when they’re all talk, no action. The problem is that people then think that meetings are a waste, that they want all action, no talk. This type of thinking gets you nowhere. The problem is that the talk phase is not effective. People are not going through a conscious Shared Language phase. Once you develop Shared Language, you are now capable of acting collaboratively.    (1VT)

What I Want To Be When I Grow Up

There were two good posts on careers in the blogosphere recently. Ross Mayfield advises future entrepreneurs in a piece entitled “Budding Entrepreneurship.” I liked all of his points, but my favorites were:    (15C)

  • Change your major.    (15D)
  • Take responsibility beyond your years.    (15E)
  • Have fun with failure.    (15F)
  • Do different.    (15G)
  • Be a businessperson.    (15H)

Alex Pang offers a much different, much more personal take in his essay, “Journeyman: Getting Into and Out of Academe.” Alex’s post resonated strongly with me, but before I talk about his essay, I first have to commemorate this moment. We haven’t actually crossed paths physically before (as far as I know; we both happen to be frequent patrons of Cafe Borrone, so it may have happened), but we’ve crossed paths spiritually in many ways, and this will mark the first time we cross paths online.    (15I)

I studied History of Science in college and have continued to pursue my interests in that field in small ways. One of those was an extension school class at Stanford I took in 1998. The class was on postmodernism, but Tim Lenoir, who taught the class, soon learned of my other interests and showed me a project he was involved with. It was called the MouseSite, and it was an online oral history of the mouse (the device, not the rodent). Alex was also involved with that project, and his name stuck with me because his middle name is Korean.    (15J)

Fast forward five years. I accidentally discovered his blog several months ago via GeoURL, and I’ve been enjoying his entries ever since. (I’ve bookmarked at least two of his past entries with the intention of blogging about them, but never got around to doing so.)    (15K)

I didn’t follow the same career path Alex did, but I did some of the same soul-searching that he describes in his essay. I have always loved scholarship, and to this day, I long for the days I used to spend lost in the stacks at the library, taking pleasure in all of the things I didn’t know. As brilliant and as diverse and as intellectual as the Bay Area is, it still does not come close to the experience I had in college of being immersed in scholarship and surrounded by scholars.    (15L)

The flip-side of this is that I’ve also always been interested in entrepreneurship and social change, neither of which are commonly associated with academia. Resolving this schizophrenia has not been easy. Pang suggests that the institutional language (at least in academia) is so narrow, we don’t even know how to think or talk about careers that deviate at all from the “path.”    (15M)

I chose to work in the “real world” and pursue my scholarly interests on the side. This was possible from the beginning because Jon Erickson — the editor-in-chief at Dr. Dobb’s Journal, my first employer, and a good friend — strongly encouraged this. As a curious side note, one of my responsibilities at DDJ was putting together its special issues on software careers, which included writing editorials. Of the five that I wrote, four were about the importance of spreading your wings and extending your learning outside of your given field. My favorite was a piece entitled, “Reading, ‘Riting, and R-Trees.”    (15N)

I loved my work and the people at DDJ, but I eventually left because it only took me 80 percent of where I wanted to go. The boom made it a great time to explore, which I did as an independent consultant for four years. Then the boom became the bust, and I had to start thinking seriously again about what I wanted to do.    (15O)

I did two things simultaneously: I applied to a few Ph.D. programs in History of Science and I started Blue Oxen Associates. I did the latter with the belief that my (and other academically-oriented people’s) skills and interests were valuable in convergent ways and that there was an opportunity to create something that took advantage of this. I was directly inspired by organizations like Institute for the Future (which currently employs Alex).    (15P)

Last spring, a few weeks before we threw our launch party in San Francisco, I received an acceptance letter from one of the programs to which I applied. I decided not to go back to school, a decision that was more gut-wrenching than most people probably realize. Blue Oxen was progressing the way I had hoped it would progress, and a lot of people at that point had begun to jump on the bandwagon. I couldn’t give up on the vision at that point, and more importantly, I couldn’t give up on the people who supported me and were counting on me.    (15Q)

We’re still progressing, but we’re also still several years away from my larger vision for the company. I probably shouldn’t admit this here, given how I rant about being action-oriented and changing the world, but part of that vision has me sitting happily in a corner of the library, following some obscure and fascinating train of thought, and then joining fellow researchers afterwards for coffee and speculation about the life, the universe, and everything.    (15R)

Huberman on Communities of Practices and Forecasting

Bernardo Huberman, the director of the Information Dynamics Lab at Hewlett-Packard, gave a talk at Stanford on January 8 entitled, “Information Dynamics in the Networked World.” Huberman covered two somewhat disparate topics: Automatically discovering Communities Of Practice by analyzing email Social Networks, and a general forecasting technique based on markets.    (TX)

The first part of his talk was a summary of his recent papers. I’ve alluded to this work here many times, mostly in reference to Josh Tyler and SHOCK. The premise of the work is similar to that posed by David Gilmour in his recent Harvard Business Review article.    (TY)

Huberman described a technique for discovering clusters of social networks within an organization by analyzing email. The key innovation is an algorithm for discovering these clusters in linear time. The algorithm, inspired by circuit analysis, treats edges between nodes as resistors. By solving Kirchoff’s equations (which gives “voltage” values for each node), the algorithm determines to which cluster a node belongs.    (TZ)

The second part of Huberman’s talk was enthralling: Predicting the near-term future using markets. This is not a new idea. A very topical example of a similar effort is the Iowa Electronic Markets for predicting the outcome of presidential elections.    (U0)

The methodology Huberman described (developed by Kay-Yut Chen and, Leslie Fine) aggregates the predictions of a small group of individuals. It works in two stages. The first provides behavioral information about the participants, specifically their risk aversion. Huberman remarked that risk aversion is like a fingerprint; an individual’s level of risk aversion is generally constant. In the second stage, participants make predictions using small amounts of real money. The bets are anonymous. Those predictions are adjusted based on risk aversion levels, then aggregated.    (U1)

Huberman’s group set up a toy experiment to test the methodology. There were several marbles in an urn, and each marble was one of ten different colors. Participants were allowed to observe random draws from the urn, and then were asked to bet on the likelihood that a certain color would be drawn. In other words, they were guessing the breakdown of colors in the urn.    (U2)

Although some individuals did a good job of figuring out the general shape of the distribution curve, none came close to predicting the actual distribution. However, the aggregated prediction was almost perfect.    (U3)

The group then tried the methodology on a real-life scenario: predicting HP’s quarterly revenues. They identified a set of managers who were involved in the official forecast, and asked them to make bets. The official forecast was significantly higher than the actual numbers for that quarter. The aggregated prediction, however, was right on target. Huberman noted that the anonymity of the bets was probably the reason for the discrepancy.    (U4)

The discussion afterwards was lively. Not surprisingly, someone asked about the Policy Analysis Market, the much maligned (and subsequently axed) brainchild of John Poindexter’s Information Awareness Office. Huberman responded that the proposal was flawed, not surprisingly suggesting that this technique would have been the right way to implement the market. It was also poorly framed and, because of the vagaries of politics, will most likely never be considered in any form for the foreseeable future.    (U5)

I see many applications for this technique, and I wonder whether the Institute for the Future and similar organizations have explored it.    (U6)

As an aside, I love how multidisciplinary the work at HP’s Information Discovery Lab is. I’ve been following the lab for about a year now, and am consistently impressed by the quality and scope of the research there.    (U7)