There might not be an app for that: The quest to quantify politics
Posted by David Hamilton
US Ambassador to the United Kingdom, Matthew Barzun recently wrote about a forum on “soft power” – the ability to influence and persuade other nations – in which the idea was proposed that this soft power could be tracked similar to how we track our fitness progress using wearable devices or our social influence using Klout. I respectfully disagree.
I’m a strong believer in changing the status quo in politics, but I don’t really think we should be offloading the work of diplomacy or political decision making to algorithms.
First off, there’s a problem of quantifying qualitative data. Computers today are most able to understand things in terms of numbers. For instance, you might be able to assign a value from 1 to 10 for your feelings about a certain trade negotiation or come up with odds on whether you think a proposal will be passed.
But the problem is that these numbers don’t answer the question: “Why?”
Number ratings and odds might help summarize an opinion or be used in a decision-making model, but they don’t take into account the complexities of actual politics and diplomacy, where decisions are – under the best circumstances – made strategically by experts.
While it would be nice to be able to make a statement like, “There was a 20% improvement in relations with Russia since last year,” this ultimately means very little because it doesn’t take into account why relations have improved and in what ways. It would also be very difficult to come to a consensus on a definition of “improvement”, especially when parties (as they often do) disagree on what’s best for nations.
However, in these initiatives to add numbers to some of the more subjective areas of politics, I see a healthy thirst for data. My issue is that it’s short sighted to see data only in terms of numbers, but qualitative data from a wider segment of individuals.
New tools can help individuals get better qualitative data from a wider range of viewpoints. For instance, blogs and even platforms like Twitter can give officials a sense of what idea and priorities people on the street have in a creative and open-ended way. In contrast, collecting numerical data might actually rein in the multiplicity of viewpoints and options available to decision makers by putting them into clearly-defined boxes.
Perhaps the basis of our idea that machines and data can help us make better decisions is based on the work of theorist cybernetics Norbert Wiener who developed a model of rapid input and feedback. This was developed as a way of solving the problem of how anti-aircraft gunners can predict where their target will be after they pull the trigger. They used a feedback loop of numerical data to attempt try to increase success rates.
In a similar way, politicians and diplomats can get constant qualitative input from a network of experts, colleagues and stakeholders. This helps them make smart, predictive decisions.
The problem with equating politics to closed systems like shooting enemy aircrafts is that the outcomes are much more complex than simply hit or miss. The definition of a hit or miss could change because of one’s political leaning. And the procedures taken by diplomats are more complex than aiming on different axes. Politics isn’t as logical as driven by the cold, hard logic at which computers excel.
In many ways, this is reintroducing an old concept that decision makers should be in a web of influences, but then have the perspective to identify useful patterns. By being able to see the big picture, they can make the best decisions.
Instead of forcing politicians and diplomats to provide inputs to computers that make decisions based on a limited amount of data, perhaps we should treat humans as the informed decision-making mechanism – allowing them to sift through data and use their wisdom to make the most informed decisions.
No algorithm can “solve” political problems, but they can help us humans get closer to something that works.