Using Engineering Design to Achieve Policy Goals
Have you ever wondered why it is so hard to get through the maze that is London Heathrow? Or perhaps you do not understand why all public stalls have blue lights inside of them instead of white ones. Such questions can be answered by looking at the underlying policy motivation for such a design choice. One of the more interesting aspects of policy is exploring how we can build a real, physical system to achieve an abstract goal (Note: I probably sound like a broken record right now to all my friends reading this post, but thinking about how we engineer systems in society to get what we want is something that I frequently return to because it's such a ubiquitous practice). Heathrow may seem like a jumbled mess, but every choice made by its architect was deliberate. Here are a few ways that we can leverage design of a system to achieve policy goals:
To separate populations we do not want to be in contact with one another.
To encourage or discourage certain behaviors.
To virtue signal.
This type of engineering can be more generally classified as a technological solution to a policy problem. In some cases, such a solution is nice because it addresses the symptoms of a policy issue in a sophisticated and easy-to-implement way. But it's not a solution that should be used for every policy problem, because it's often a way of attacking the problem without actually eradicating the underlying issue. For example, blue lights were installed in public restrooms because an individual cannot see their veins under blue light, which is meant to discourage drug addicts from using public restrooms as a place to shoot up. While this is a simple way of partially cleaning up public restrooms, it does not solve the real problem: society has created the conditions that drive an individual to becoming a drug addict in the first place.
In addition to being incorrectly used, an engineering solution can often lead to second and third order consequences not originally intended. This is often cause by a lack of understanding in the scope and complexity of a policy problem. Engineering is a discipline that tends to make assumptions and simplifications about real world systems in order too create understandable solutions. This is generally okay when it is applied in the right context, but can have major consequences when it is not. We need to be better at identifying which situations call for a policy solution and which ones call for a technological solution.
If you are interested in exploring more cases where this happens, the podcast 99% Invisible features a new example of this every week. Check it out here.