I had this vague intuition for years that arguing against an idea still supported the idea. I never was able to fully articulate this intuition until I read George Lakoff’s work on framing, which explained how arguing against a proposition still reinforces the proposition as stated. Lakoff’s classic example is “tax relief” - even arguing against “tax relief” reinforces certain connotations, including the idea that relief implies an affliction. So referencing a worldview, even if one is arguing against it, still reinforces that worldview.

So why do people do it? I have a feeling that we are wired to play finite games, where we are trying to win the game with the rules as stated, rather than infinite games, where part of the challenge is to step back and re-define the rules (James Carse’s book Finite and Infinite Games is obviously a big influence on me). So people get caught up in trying to win the argument within the context that they are given, rather than thinking about their overall picture and whether they are contributing to that. In other words, I agree with Noah’s point that “the best way to fight this kind of behavior is to not talk about it. But most people can’t help themselves.” We want to win the finite game, even when the game as framed will contribute to the other side’s success. To avoid that, we need to be thinking about playing the infinite game instead.

Getting to Yes is another framework for thinking about these sorts of issues, as it emphasizes figuring out your principal interests and focusing on those, rather than getting sucked into zero-sum positional bargaining about specific issues. If we go into a negotiation focused on winning every individual point, we may often fail to actually achieve our interests (much like Internet pundits arguing against certain issues, but only providing them more visibility and respectability in the process).

So when faced with a screed which makes us want to argue and tear down an opposing perspective point by point, we need to step back and figure out if we’re just contributing to their worldview by doing so. We need to concentrate on our overall vision and figure out whether what we’re doing is contributing to that end goal. We need to find opportunities to reframe the discussion to find points of commonality (e.g. both sides of the abortion issue agreeing that they’d like to see fewer unwanted pregnancies) so that everybody can feel like they are moving towards their goals.

Or, sometimes, we just need to accept that the other person is too locked into their viewpoint for us to be able to convince them. If their frames are so strong that all incoming information will be mapped to their frame, such that no facts or arguing will convince them, we need to recognize that and move on rather than continue to futilely waste our time. This is definitely one of the hardest skills to learn on the Internet.

Man. I really need to get back into writing regularly. There’s a whole trove of interesting territory around zero-sum vs. non-zero-sum thinking that I need to explore at some point. It’s fascinating stuff to me, and while it’s a frame that I’m probably over-applying right now, I think it has some explanatory power.

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.

Technorati tag: Convergence08

Last weekend, I was catching up on a couple such talks that I had meant to see but missed for one reason or another (including Nancy Pelosi’s visit), and the one by Philip Zimbardo caught my eye. Zimbardo is infamous for the Stanford Prison Experiment where he simulated a prison with Stanford students and was aghast at how quickly the prison became real to all involved. Within a day, the guards were finding ways to humiliate the prisoners and previously healthy “prisoners” were having mental breakdowns (the images from the experiment were eerily echoed by Abu Ghraib). I’m currently reading Zimbardo’s book The Lucifer Effect, where he discusses the idea that evil is not a dispositional but situational; in other words, people who do bad things are not inherently evil, but instead all of us have the potential to do evil in the right situation (as his Stanford students demonstrated in their “prison”).

His latest book is called The Time Paradox, about the psychology of time, and he came by Google to give a talk on the subject. He started the talk with a discussion of the marshmallow experiment. The subjects were four-year-olds who were given a choice - they were given a marshmallow, but if they could wait a few minutes before eating it, they would be given two marshmallows for their patience. Some of them ate the marshmallow, some of them managed to hold out and wait for the greater reward. Here’s the astounding result: the experimenters returned to their subjects fourteen years later and found that the ones that had the self-control to wait had better grades and better SAT scores by a statistically significant margin. In other words, one brief experiment on a four-year-old was highly correlated with their future performance in life. So what’s going on?

Zimbardo identifies the two types of children as having different time perspectives: the ones that ate the marshmallow have a present time perspective, focusing on the immediate gratification of the marshmallow. The ones who waited have a future time perspective, able to trade off their present gratification for future results. And our culture rewards those who can make those future tradeoffs (e.g. study now rather than play to enhance one’s college test scores).

Zimbardo later extended the classifications of time perspectives to include past-positive (focusing on the good things that have happened in the past), past-negative (focusing on the bad things), and present-fatalistic (feeling unable to influence the events impacting one’s life). You can find out your time perspective tendencies by taking the online test. Zimbardo has done survey work to show that the results of the marshmallow experiment are not isolated - the time perspective of a person is strongly correlated with the results that person achieves in many areas of life.

What I like about this is that it feels right to me as an explanatory mechanism. There are certain areas where I am heavily future-weighted, such as financial planning where I will forgo something I want today for the sake of something I am saving to buy next year. There are other areas where I am past-weighted, such as in my social identity where some part of me still clings to my self-identity from when I was a teenager. There are still other areas where I am present-weighted, with a focus on whatever feels right at the moment (which contributes to my inability to maintain a regular exercise program). I was also able to immediately start classifying other people around me into the various categories.

The sign to me of a powerful classification system is when it breaks open a problem where everything seemed ambiguous before. Back when I was a programmer, I used to love that feeling when I finally hit upon the right way to represent the data and everything suddenly became easy. And I’d been feeling muddled about certain people recently where I just didn’t understand why they behaved the way they did. But when Zimbardo gave me this new template for thinking about how people think, their behaviors immediately fell into place.

The other nice part about Zimbardo’s use of time perspectives is that they are not fixed. A future perspective can be taught. So we could test four-year-olds, identify the ones that have a present perspective and give them the tools to develop a future perspective, thus improving their ability to adapt to adult life where future tradeoffs are always necessary. Zimbardo trashes the idea that success is genetically determined, instead focusing on the idea that the tools for success can be taught with the right system - not surprising from the man who identified that evil is present in all of us in the wrong system.

I recommend watching Zimbardo’s talk if this sounds interesting, as he explains it better and more rigorously than I do. But I wanted to share this idea that had immediate impact on me. I’m curious if others have the same feeling - maybe this is just obvious to others, or maybe it’s a helpful template for thinking about the world. What do you think?

Such conversations are where an organization’s thought processes are made visible (audible?). In other words, if an organization could be perceived as a group mind, then those conversations are the equivalent of watching the synapses between neurons firing. It’s the only way to get insight into how the group mind operates. This may sound a little wacky, but I’m inspired by Edwin Hutchins’s book Cognition in the Wild, where he extracts observations about cognition by watching how a group mind in the form of a navigation team operated. In the best case, meetings can be a reflection of this organizational cognition, an aspect which Peter mentioned in the comments of my meetings post.

So by listening in on such conversations, one can map out how the organization operates. Which assumptions are taken for granted? Who are the stakeholders mentioned regularly as needing to be consulted? How are decisions made in such conversations - is it by consensus, persuasion, or hierarchy? These sorts of observations may not be directly relevant to one’s job, but it’s invaluable to an amateur anthropologist like myself in understanding the different forces that are at work within the organization.

Even better, conversations often arise when new organizational territory is being mapped out, either in the form of current assumptions being questioned, or in the development of a response to a new stimulus. When everything is running smoothly and there’s a defined process for how to do things, there is no need for conversation as everybody knows how to do their job. But when one reaches the limits of one’s understanding, then one has to consult another person, and such consultations are where somebody like me can see how the organization, in the form of its constituents, learns. To use the framework of Latour, conversations are where we can see the organizational Collective perform the Consultation process, where it grapples with an outside influence (what Latour calls “Perplexity”). Seeing the Collective go through a round of growing and learning is exactly what I mean by saying that conversations are a window into the cognitive process of the organization.

This is also exactly the sort of fuzzy stuff that I once would have scorned as a hard scientist and logic-driven engineer. These sorts of ephemeral observations about an organization are difficult to quantify and would not have even been on my radar ten years ago. And now they are the sorts of things that capture the value I bring to an organization, as my ability to attend meetings and listen to passing conversations and extract this sort of organizational knowledge is a testament to my ever-improving observational skills. I liked Rands’s description of it as the culture chart, as opposed to the formal organizational chart. The culture chart isn’t written down anywhere and is supremely fuzzy - it can only be intuited by reading between the lines of conversations.

So that’s my rationalization for why listening in on conversations when starting a new job is important. It’s the best way to understand how an organization operates: which assumptions are stated (and more importantly, not stated), which stakeholders matter and which can be ignored, etc. And, in case you’re wondering, all this listening to conversations is why I have to stay at work until 9pm a couple nights a week to catch up on my individual contributions. Once I am more efficient at my assigned tasks and up to speed on how Google works as an organization, I hope to get my hours down to a more reasonable number.

Despite the help of my readership in brainstorming ideas for the essay, one of the requirements for publication was that I refrain from posting my essay here for six months. So if you just want to see my essay, ping me then.

I’d been meaning to check out Google Reader for months, if not years, but had never gotten around to it, as Bloglines was serving me well enough for what I needed, and I’d gotten used to its quirks.

But over the past couple weeks, Bloglines started failing at its primary purpose, delivering RSS feeds on demand, as it stopped properly updating feeds. It didn’t bother me too much at first as I was busy enough that reading blogs was a luxury, but it was starting to get annoying. And then somebody twittered about a TechCrunch article describing how Bloglines users were fleeing to Google Reader, which provided instructions on making the move. Ten seconds later, I was moved to Google Reader, and now I probably won’t go back.

Let’s parse out what happened here, as I think it’s instructive.

1. A few years ago, I started reading enough blogs that updated infrequently that checking them one by one was becoming ridiculous. So I started looking for an RSS reader, and chose Bloglines as it met my requirements well enough at the time (Barry Schwartz, of The Paradox of Choice, would call this “satisficing” - speaking of which, I need to review that book at some point). In particular, it was web-based so that I could read blogs from work or home without duplication, which was the key differentiator from Thunderbird, the other major contender.
2. I stuck with the choice for several years, even as bits of it started to annoy me, as the perceived switching costs were too high. Given that there are no lock-in effects in this software (no data that I couldn’t export), the switching costs were purely cognitive. In other words, the cognitive effort of switching was the major lock-in for this product. Also, the benefits of switching were minimal - Bloglines was meeting my needs, so it was unclear how other software would be better in that core functionality.
3. Once Bloglines started to fail in its primary purpose (making it easy for me to see the latest in my desired feeds), the benefit of switching became relatively greater (other RSS readers were succeeding where Bloglines was failing).
4. Once I read the TechCrunch article, I had “social proof”, the term Cialdini uses to label our tendency to want to see others doing something before doing it ourselves. Knowing that there were dozens of other people making me the same switch helped convince me to make the jump. That was the critical tipping point.
5. The actual switch took about ten seconds (export from Bloglines, import into Google Reader). To reiterate, the effort of switching had nothing to do with the actual work it would take to switch - it was the cognitive effort of having to re-open a decision that I had already made.

What’s my point here? In the Web world, switching is often fairly painless, as most vendors provide a way to easily get one’s data out of their system (and if they don’t, that’s a bad sign). Companies are generally relying on us to pick a system and get comfortable with it, so that habit and the perceived cognitive effort of making a change is a far greater impediment to switching than other possible lock-in effects. In such a situation, the company has to never make it easier to contemplate the switch; in other words, if the company continues to fulfill its value proposition to the user, users will stick around, but as soon as they lapse, users may leave in droves (as appears to be happening to Bloglines).

Another way of thinking about it is that the game between companies and users is all played in people’s minds. While economists may believe that people are rationally maximizing their potential economic gain, most of us are far less rational in our decision-making. We use brand names over equivalent generics because of advertising or because we “trust” the brand name more. We stick with products or services that are clearly inferior to newer ones because it’s too much effort to re-open the decision we originally made. Companies that understand this game will be telling stories to convince people to use their products or services, rather than trying to convince them with data. For instance, the book Positioning is all about creating new primary needs in the minds of consumers to give them the necessary impetus to switch.

So focus on the value proposition your company offers to its customers. If you can make sure that the value of your product keeps on increasing, you can benefit from the perceived effort of switching and keep customers even in situations where they might rationally choose another product or service. Ideally, of course, your product is the best in class, but every little edge counts, right?

Now I just have to get over the cognitive effort of switching from Windows to Mac…

P.S. I have been at Google for exactly one month as of today. Crazy how the time flies!

I’ve been thinking about this question on and off for weeks, as it keeps on coming up in different contexts. Here are some different possibilities for story metrics: