Thomas Prehn is a former head of MindLab, an innovation lab established by the Danish government in 2002 to spur creativity and cultural change within government ministries and improve their delivery of public services. Working in numerous policy areas, including education and employment, MindLab became a pioneer in its work both on specific projects and its efforts to make civil servants better risk takers and inventors. It’s mission, which came to an end last year with the creation of the not-dissimilar Disruption Task Force, has been hugely influential, inspiring dozens of similar initiatives by governments around the world. Prehn spoke in on-camera interview to the IDB about the challenges of applying behavioral economics to policymaking in an ever-changing world.
How can governments use behavioral economics tools?
I think behavioral economical tools for governments have the possibility to create a more complex perspective on the challenges that we work with as policymakers. Because the individuals that we work with, even though we like to look at them as a whole, as the public, are very different, and the challenges that they have are very different. So aligning policymaking with that is complex, and I think we need a broader and a different perspective than just desk research and statistics.
How can behavioral economics change policymaking?
The potential of behavioral economics in terms of policymaking is, one, to create initial perspectives that will change the way that we look at policy problems and policy issues. But the world is constantly changing, society is constantly changing, and your policy needs to follow behavioral change among the public.
What obstacles need to be overcome?
I think the big issue for policymaking in relation to behavioral insights is that it introduces a complexity that will be very difficult for governments to handle because they want this evidence-based approach. Even though we call behavioral economics or behavioral insights evidence-based, it’s still on a very small population that we do these tests. And scaling it up in a complex environment is not evidence-based. You must really embrace the idea that you have non-predictive outcomes and (must make) continuous adjustments to your policy. That would definitely be one of the biggest issues for policymaking and politicians.
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