Over the weekend, I attended the Convergence08 unconference, which focused on future technologies like biotech, nanotech, artificial intelligence, etc. I had to miss the Saturday morning sessions, as I had a chorus rehearsal for this week’s Mahler concerts, but I was there on Saturday afternoon and most of the day Sunday.

The first session I attended was on “Building a better search engine”, which I chose because I work at Google (although on nothing related to search). The attendees speculated about the next big jump in information finding technology, including:

• Personalized agents that know you and just find the right information – I brought up privacy, and the general response was that privacy was overrated and should be ignored for the sake of this discussion as better results would trump privacy.
• Semantic technologies with natural language understanding – somebody from Powerset was there pushing this idea, and somebody else recommended Semantifind. I’m extremely skeptical of such technologies, as I’ve spent most of the past ten years figuring out how to translate between different disciplines as a generalist, and I already understand language. I think it’s going to be a long time before computers can figure out the implicit frames that influence comprehension.
• Social search – leverage our social networks to find more relevant results. If a trusted associate noted something, it’s probably more relevant than a random stranger noting the same thing. The issues I raised is the modelling of the social network – I would trust certain friends to make recommendations about stereo equipment but definitely not about clothes and vice versa. And unless the software can gather enough data to model those subject- and pairwise-specific interactions, it’s not going to get the desired results.

As an aside, it was interesting to me that I’ve gone from being a technological positivist where technology will solve our problems, to being skeptical of most technical solutions, partially because I now think the hardest and most interesting problems are not solvable by technology per se, but instead require the design of new social technologies to coordinate people in new ways.

The next panel I attended was called something like AI and Sense making. I’m fascinated by the question of how we make sense of the world as my continuing obsession with stories makes clear. This was a session where people discussed the idea of sense making (Gary Klein’s work with firefighters was a big influence), how it could be embedded into technology and possible business ideas built on such technology. The discussion was interesting but because sense making is a fuzzy cognitive concept, one attendee afterwards commented that it was difficult to separate sense making from general AI. Two recommendations for further reading I want to record for myself: Perspectives on Sensemaking, an article by Gary Klein, and Sensemaking in Organizations, a book by Karl Weick.

One useful construct from the session was the idea that we create a frame, view everything coming in through that frame, but keep track of whether things are corroborating with reality. Once the discrepancy with reality grows too large, we have to consider junking the existing frame and finding a new one that fits the data better, which I see as yet another form of Bruno Latour’s process.

Then it was time for the keynote speech by Paul Saffo, which I had been eagerly anticipating after having seen him speak several years ago. I was not disappointed – even though it covered many of the same topics as that previous talk, it was entertaining and informative. Tidbits that I wrote down:

• “If you don’t change direction, you’ll end up where you are heading.” (in other words, inaction is a choice with consequences)
• The future will still have a lot of dull parts (riffing on Hitchcock’s claim that “Drama is life with the dull parts cut out of it”). We look forward to all the excitement of the future but forget that amid all that excitement will stlil be dull parts.
• “Change is never linear” (s-curve, s-curve)
• “Cherish failure, especially someone else’s” – this was a theme from the other talk I attended, where he pointed out that the consequences of the s-curve is that the time when everybody decides that a technology is a failure and that it will never work is the time when it might be just about to take off. Which actually made me wonder about my dismissal of semantic technologies in the session earlier, as part of the reason I dismissed it is that it’s been “just around the corner” for 20 years now, which, in Saffo’s world, means it may be just about to finally succeed.
• “Look for indicators” – form a quick opinion, but then look for proof that you’re wrong, which he elaborates in his strong opinions, weakly held blog post.
• “Use forecast techniques until reality gets too complex” – this was an interesting riff where he said that even our forecasting techniques continually get outmoded and need to be updated. He believes that we’re in such a phase transition now, where the old qualitative models are breaking down, but new quantitative models haven’t arrived yet. The four factors that he thinks will drive the next generation of forecasting models are Moore’s law, better forecasting algorithms, more and better data, and more of our lives being stored in digital form thanks to Facebook. My eyes lit up, as that’s a perfect explanation of why I joined a forecasting group at Google.
• Three book recommendations: the novel Daemon, by Daniel Suarez, “A general theory of bureaucracy” by Elliot Jaques, and the “creative destruction” work of Joseph Schumpeter.

Sunday morning started with a panel on synthetic biology. There were a variety of panelists, with backgrounds in physics, software, and biology, but my favorite was Denise Caruso of the Hybrid Vigor institute, as she questioned the assumptions that the optimistic scientists were making. Her focus area has been on risk analysis, especially in new fields where the risks are difficult to quantify, but her point is that the benefits are equally difficult to quantify, so we shouldn’t be going in with the assumption that innovation is automatically good. Her belief is that we need to come up with better processes and methods for assessing risk with interdisciplinary input. You can see why a generalist like me would be a fan (I actually asked a question during Q&A supporting her viewpoint). I chatted with her a bit afterwards, and also attended the breakout session after lunch with her on innovation and risk, which brought together interesting conversations and different perspectives (the work that Etan Ayalon is doing at GlobalTech Research looks particularly interesting to me). I also liked Caruso’s concept of Bayesian regulation, where it’s not black and white, but involves conditional probabilities.

I missed the next session as I ended up chatting with folks from that first after lunch session for about half the next session, and then had to prepare for my session, “How do organizations think?” I threw it open as a discussion forum expanding on the ideas in my post on organizational cognition, and had a good discussion with the eight people who attended. We talked about different people’s experiences with different organizational structures and what might work to improve those. One key concept that was identified was that designing an organizational culture and structure has to first start with the purpose for which the organization is built. Different structures will serve different purposes, and incongruities between the structure and purpose will cause friction. People expressed interest in possibly having a follow up session after the conference was over, but I didn’t get everybody’s contact information, so I hope they get in contact with me.

I ended up bailing out on the end of the conference during the longevity panel, as I had other plans for the evening, but all in all, it was a good experience – I met a couple new interesting people, had some good discussions, and found new food for thought, which were pretty much my goals for the weekend. But now it’s time to get back to my normal life.

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