Darlene Cavalier has a great piece in Discover about citizen science and reimagining the Office of Technology Assessment. As she explains,

What originally began as Science Cheerleader’s effort to help reopen the Congressional Office of Technology Assessment (an agency, shut down in the 90’s, that helped Congress better understand policy implications of complex, science issues), has evolved into this reincarnation.

Why? It became apparent after two years-worth of numerous discussions with a variety of stakeholders, that reopening the “old” OTA would leave little, if any, opportunities to invoke contemporary applications critical to 21st century governing: decentralized expertise (tapping the knowledge of scientists across the nation) and citizen engagement, to name but two….

Government policymakers, businesses, non-governmental organizations, and citizens rely on analysis to capably navigate the technology-intensive world in which we now live. The new model, described in the report, would provide opportunities to generate input from a diverse public audience, while promoting societal discussions and public education.

This redefines the technology assessment model by recommending the formation of a first-of-its-kind U.S. network to implement the recommendations: Expert and Citizen Assessment of Science and Technology (ECAST).

I'm very interested in systems like this, so I want to take a quick shot at outlining a couple properties that an ECAST would actually have to have to work.

First is a philosophical question. Does this kind of knowledge about the potential impacts of science and technology simply exist somewhere? Or does it need to be created?

Put another way, if you assume the former, your task is to find the person- the orthogonal thinker in a dorm room, the visionary at the startup- who can share a cool insight. If it's the second, then your task is to bring together interesting people, and get them to think together about the future of science and technology.

I've had some clients who were firm believers in the first approach. They wanted me to find the undiscovered visionary: one client more or less told me that my mission was to find the 16 year-old who could become another Steve Jobs, and to find him in China. Wrapped up in this mandate are a couple assumptions: that there's someone out there who sees the future really clearly, and we just need to find them; that such people are the ones who make history (and the future); and that we'll know this person when we find them.

I think each of these three assumptions is faulty. History isn't made by visionaries who spend a lifetime pursuing One Single Vision: I'm not sure that Steve Jobs had a vision for the iPhone that I could have extracted from him in 1973, when he was still- well, before he was Steve. Further, great technologies just aren't made by single people: like all creative endeavours, they're collaborative efforts. Finally, I'm not sure how you'd sort out crackpot from genius ideas about the future in any over-the-transom process.

But this is not say that a simple process that taps the raw "wisdom of the crowds"- say polling people, or opening up a wiki about the implications of science and technology- is a substitute. My experience trying to get experts to contribute to an open future of science platform makes me skeptical that you'll get useful results just by throwing open the doors, however nice they are. (One of the Discover commenters makes this point, too.)

Rather, you need a process that has several properties.

First, it needs to be accessible to just about anyone who wants to participate. There should be some kind of barriers to participation, to discourage people who want to just advocate for their products or talk about how putting microchips in our food will make us all super-geniuses.

Second, it should combine open-ended scanning with events that have clear dates. You need the former because innovation and other interesting things happen all the time; you need the latter because you need mechanisms to encourage concentration and innovative thinking (and hard deadlines and urgency are shown to stimulate more out-of-the-box thinking than leisure and freedom- a fact that many an academic has discovered the hard way).

Third, the system should thoughtfully draw on the wide varieties expertise that can be brought together in a virtual platform. Personally I think talking in terms of "citizens" and "experts" threatens to obscure something important, namely that "expertise" about exceptionally complex phenomena is highly distributed and localized. If you want an opinion about the value of Lie numbers in Garrett Lisi's theoretical physics, there are about a dozen people in the world you want to talk to (mainly this guy); if you want to think about the broad implications of synthetic biology, you want Rob Carlson, but you also want a lot of other people who can contribute expertise in law, engineering, manufacturing, policy, etc. etc. As the history of science shows, sometimes the people least likely to see the long-term implications of ideas or inventions are the scientists and engineers most intimately involved with their creation.

Fourth, you need some real-world events. Virtual meetings can be great- they generally suck, but they can be designed to be great (I make part of my living designing them)- but face-to-face interactions still produce things that you don't get through online itneractions. Even better are events that combine virtual and real interactions and spaces: if properly designed, you get the best of rich social interactions that, as primates, we're so good at, and the virtues of digital scribing and recording and sharing.

Finally, the exercise has to have an obvious payoff. This means two things. First, if it can be designed to provide some immediate benefits to participants- class credit for students, data for grad students, citations for professors, networking opportunities for entrepreneurs, a thousand new Facebook for the rest of us- so much the better. Second, it should be clear that people from NIH (or Merck or CIA or NSF) are actually paying attention to the results of Cubesat Day or Synthetic Biology Week. That raises the stakes, creates more of a sense of urgency, and makes everyone take the event more seriously.

Now, what kind of technology platform would you use?

My answer for now is, try a little of everything. Unless you get caught in the trap of sourcing the whole project to some soul-sucking systems contractor who'll charge your $37 billion and not really ever deliver what you want, you could do a lot of cheap experiments, in lots of cities; so long as you document well and pay close attention, pretty soon you'll see what works and what doesn't, and you can transplant successful efforts to other places. Don't think in terms of a system, in other words: think in terms of an ecosystem, in which you provide some minimal nutrition (seed funding), encourage rapid evolution, have lots of plasmids and transfer RNA around, and quickly reward success. Maybe that sounds like a cop-out, but it's the best way to get a system that's as flexible and interesting as its subject.

Or am I missing something?