The lost art of policymaking

The New Labour Government in the UK has embraced evidence-based policymaking with some fervour. Endless studies inform what Departments decide to do, feeding a generation of policymakers who have been weaned on managerialism as politics.

The New Labour Government in the UK has embraced evidence-based policymaking with some fervour. Endless studies inform what Departments decide to do, feeding a generation of policymakers who have been weaned on managerialism as politics.

The danger is that policy goals are set that can achieve the various targets, be analysed for success by the chosen methods. Policy then becomes uncoupled from the challenges it was initially supposed to address, and Government mandarins end up living out the Kafkaesque contradiction of trying to change the world by delivering outcomes bereft of worldly effect.

Yet the problem is not the evidence-based research itself, but how it is used. Or rather, the organisational structures that use it. In the attempt to be scientific, the policy world has misunderstood how science works.

Take the neuroscience research done here in London at the Wellcome Trust  Centre for Neuroimaging. There are teams of researchers gathering data in order to test theories. And of course the theory construction is closely tied to the data - if the facts don’t ultimately bear the theories out, they will be amended.

But the theory cannot be equated with the data, or with a perfunctory collation of it. At the level of theory - which is the level at which problems get solved - imagination and insight are required. For example, Karl Friston is working on a theory that all information processing done by the brain follows a single mathematical algorithm. This theory did not come from the data, but from thinking about how the brain might work in a similar fashion to other parts of nature, and at bottom, from thinking about how the brain’s information processing is captured by a simple image or metaphor. The hard work lies in cashing the latter out in terms of the data.

This is how great science gets done. Einstein was a brilliant mathematician because he was creative - he had insight into patterns no-one else could see. The same goes for Darwin. On the Galapagos he began to observe strange patterns in things and a whole new metaphor dawned upon him - that of species-level adaptation. True, the data seemed to cash the metaphor out in Darwin‘s own time, and subsequent research has indeed vouchsafed his imaginative leap. But nevertheless, that leap was an essential part of the theory’s construction.

I’m not suggesting policymakers need possess the genius of Einstein or Darwin. Anyone that bright won’t be in the policy world. The lesson is rather that gathering evidence is one thing, solving a problem another. Once the data are in, insight and imagination should be applied to the light they shed on the challenges policies are designed to solve. So good policymaking - like good science - should be a lot like good art.