In preparing for a talk next week, I came across this quote from urban planner Pietro Anders Calogero‘s PhD dissertation:
Urban planners usually employ technical rationalities, often assuming that this is the only way to rationally approach a policy problem. Technical rationalities imply a uniform world: indeed, a mobile phone and the chemistry of concrete work the same way regardless of our location on the planet. But political rationalities imply localness, peculiarity, and contingency.
It is possible to substitute virtually any profession for “urban planners” above, even those who work in policy. We all want to find the “right answer” – the optimal solution that we can use over and over again, finding efficiencies and giving us useful points of comparison.
The problem is that the technically correct solution and the one that will actually work in a specific political context are usually very different. That’s why, in international development scholarship, we’ve started to talk about “second-best” solutions – acknowledging that they might not be ideal, but that it’s better to implement something that’s suboptimal on paper than one that’s a flop in practice.
One great way to think about this is the bicycle helmet paradox. Safety experts always recommend wearing a helmet; in many accidents, they save lives. However, in places where helmets are required, fewer people tend to ride, leading to a less safe system overall, with drivers less aware of cyclists. Perversely, discussions over helmet laws also tend to shift the focus toward individual behavior and away from the infrastructure improvements that have a much larger impact on collective safety.
In other words, when dealing with humans, we should be mindful of the gap between the technically correct option (in our eyes) and the one that is likely to work.
I preach about this all the time in my work – the fallacies of big data, the challenges of using technology to solve social problems – but in my own projects, I am just as likely to get stuck pushing for the perfect solution when it simply isn’t possible to get people to behave that way.
None of us get to make decisions in perfect information environments. Even big data is no match for the uncertainty of human behavior. But when we accept political rationalities – the “localness, peculiarity, and contingency” of each place in time – we begin to see opportunities for solutions that we can actually implement, right now.
It’s a good reminder, to me, that it’s okay for some things to be “imperfect.” Real perfection is in the embrace of the possible.