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Speculative Diction

The policy of happy accidents

BY MELONIE FULLICK | SEP 16 2013

This post is about one of my favourite issues in education and various areas of knowledge policy: the attempt to use policy to reliably generate the unpredictable.

As an example, one of the themes that recurs in certain kinds of policy design is the idea of creating a geographic hub of innovation, a golden patch of tech turf that connects universities with businesses and governments, and generates technological change that pays off for all involved: in other words, a new “Silicon Valley”, which is the touchstone for these kinds of discussions. Re-creating Silicon Valley has become a policy goal, with the desired result that economic competitiveness will follow; hence the appearance of “science/research parks” and “innovation districts”.

There’s plenty of research about innovation, organizations, and technological discovery and development, that strives to provide explanations about why we see these much-lauded historical irruptions of creativity, innovation, and of course commercial success. The idea is to be able to make this happen in a deliberate way by adding the right ingredients into the socio-political-economic mix.

For example, I think there’s an implicit understanding that space and physical proximity have effects on eventual outcomes in “discovery” when creativity and innovation are the goals. At a time when we’re hearing so much praise about online spaces and their possibilities, I think this is another sign that certain configurations of place and space are scarce commodities in research and higher education. The value of these commodities is such that they’re assumed to be part and parcel in the construction of conditions where “innovation” will flourish, and in elite contexts they’re accommodated as such.

Serendipity in teaching and learning, too, depends partly on the unpredictable outcomes of social contact. Creative sparks can fly when we’re bumping up against other people and their diverse ideas and perspectives, the eclectic combinations of knowledge they’ve built up over time. Each person who takes in knowledge also changes it through the process of knowing. In this way, it could be said that all education is built on a series of chance encounters.

Of course we can’t really plan for chance, which is possibly why it’s the one ingredient left out of most of the formulae we see being applied. Chance is inefficient per se, problematic in terms of the actual goals of planning, which require the assumption of at least some form of certainty. Better to make sure that other things happen, the things we can guarantee, speaking in those terms instead of the nebulous shades produced by the idea of serendipity, accident, and so on. The power of the serendipitous lies in its very unpredictability, but try explaining that in a grant proposal.

Here in Canada, the federal government isn’t much into chance, unless you count the gamble we take by developing policy without sufficient evidence available to inform it. This government is unlikely to solve Canada’s perennial “innovation” problems by targeting large amounts of funding to those projects it deems most meritorious. Nor will students find answers for themselves – or for the much-lamented “skills gap” – by trying to engage in the kind of advanced futurology that is now expected of them as they prepare to enter the job market.

To return to Silicon Valley and its clone zones: where knowledge is tied to governance, where policy must make predictions, we place bets on future success by attempting to emulate success seen elsewhere in the past and present. The historical analysis is in some cases a selective one; rarely if ever do we see calls for military involvement in new innovation hubs, yet Silicon Valley’s prosperity was built more on US military funding than on venture capital, as is pointed out by Steve Blank.

For good education and research to happen, even for those eventual economic benefits to materialize, we need place/spaces where we can allow for possibilities and work through failure and permit experimentation, where we can learn how to take chances and follow our noses – while encountering others – rather than just building on an assumed formula for success. After all, it doesn’t matter how high the stakes are; we can’t know the future, and if we can’t imagine a new model of success, we won’t be able to deal with whatever changes the future brings our way.

ABOUT MELONIE FULLICK
Melonie Fullick
Melonie Fullick is a PhD candidate at York University. The topic of her dissertation is Canadian post-secondary education policy and its effects on the institutional environment in universities.
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  1. David Fernandez / October 3, 2013 at 13:43

    I just wonder why would they want to recreate Silicon Valley… doesn’t Canada has already something quite similar in Waterloo? (just a thought, although I’m aware it’s not the main point that you’re making)

    • Melonie Fullick / June 16, 2014 at 13:14

      It seems like the idea is to look to the places that have experienced “success” in terms of innovation and economic development, and then try to create the conditions for the same thing to happen elsewhere. Silicon Valley is just the most obvious example of this. So while we have Waterloo for example, that’s only one region where development is happening; if it can be done in other places as well, even better–more economic development.

      The MaRS project in Toronto is a good example of this attempt (I’m assuming there are other examples too!). So I think it’s like a formula that we imagine we know, and can apply elsewhere, not just in Waterloo but in as many places as possible. Obviously there’s a problem with this idea (e.g. military/defence funding not mentioned) but it’s extremely popular anyway.

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