Much is being written about ideological echo chambers. In particular, I’m enjoying Ethan Zukerman’s REWIRE, published in 2013, in advance of this seemingly sudden revelation after the 2016 US presidential election. Zukerman perfectly predicts (maybe it’s more accurate to say he observed) the phenomenon years ago. The idea that the great wondrous world of the internet has actually shrunk the points of view and differing ideals many of us are exposed to is counterintuitive, frustrating, and initially seems shocking. But it also makes perfect sense. We know that, left to our own devices, most of us seek out comfort, not challenge. We choose familiar ideas instead of ones that run contrary to our own. In short, we choose the easy path, not the hard one.
This is not unique to the media we consume, the people we follow on social media, or the neighborhoods we choose to live in. It also occurs when we look at the efforts put into political engagement (low), actions to mitigate climate change (low), and, perhaps most personally, the work most of us put into our own health and fitness. That latter category has had a great amount R&D devoted to it by researchers – mostly employed by, corporations who felt there was a way to make money by addressing this need. Weight-loss and fitness have been perennial money makers for generations, after all. When companies realized there was a way to add expensive tech to an established business model, the marketing campaigns practically wrote themselves.
Fitness trackers have boomed over the last few years. At their core, they serve as an easier way to quantify and visualize our physical activity over a given amount of time. Certainly they have helped me to better realize some of my bad habits, and to keep me more honest about the patterns in my exercise routine. This quantification is, most often, presented as a goal to reach each day/week/month and the awarding of virtual prizes and praise is nearly ubiquitous in these models. This is, clearly, the gamification of fitness. While the long-term effects are unclear, it is undeniable that some have benefited from this model.
I wonder what will happen if we apply this concept of gamifying a behavior that we generally dislike to encourage exposure to media that presents ideologies that we may not subscribe to ourselves?
The general idea behind a lot of gamification is to make an unpleasant activity fun, or at least to provide motivation for performing the activity. There are a great number of ways that rewards and motivations can present, but they are obviously effective for some. Getting in our step goal for the day, for instance, can result in a flashy animation and message of congratulations from our fitness apps, and even virtual medals for specific achievements. Even if the activity never becomes fun, if we can be motivated by these progress trackers, we can make progress towards our goals.
When it comes to exposure to dissimilar ideologies, goals are not nearly so clear or easy to quantify as for fitness. While I think that echo chambers are bad for everyone, I think it’s unlikely for most people to move too far beyond, say, a “reverb room” of ideological exposure very quickly. However, even that much of a move on the part of even a moderate portion of the population could have profound effects on our civic society. So, if our goals cannot be specific, how do we gamify exposure to ideologies? I think that measuring activity against a set of anti-goals may be useful. While it’s hard to say that “50% of your weekly reading should be outside your reverb room” it’s easier to say “less than 100% of your reading should come from within it.” It’s the extreme of the echo chamber that we need to avoid, not necessarily a perfect balance in all exposure.
But how do we even measure such things? That’s tough, to be sure. We have a general idea that some news sources lean one way or another (if you want to use the simplistic liberal/conservative spectrum for a measure) and we could, simply, categorize all stories from a specific outlet to be some percentage left or right of center. (see here and here) We could also use crowdsourcing to evaluate articles, provided enough people participating rate a specific story to avoid mischief. We could even use machine learning systems, trained on pre-scored corpora of material to evaluate individual news stories. (Seethe work of Marek Rei. I’m frustrated trying to find another researcher who trained a machine learning system to evaluate conservative vs liberal sources. I’ll update when I eventually find her again!)
If we have a reasonable way to score arbitrary content between the (again, much simplified but still useful) conservative and liberal extremes, then, much like counting steps and calories burned, we can tabulate an average for any set of stories. This could certainly be implemented in the form of a browser plugin, and could likely take other forms as well. For a responsible citizen of the US, making sure their browser bar contains, say, a purple dot, rather than a blue or red one, could become a personal goal.
We know that, for most of us, it is human nature to avoid hard things, especially when it seems we are the only ones to suffer from that avoidance. But accountability is an extremely important motivator, as are rewards. An automated system that tracks what we read, and gives us a reasonable estimate of its diversity, could assist a great many people in opening up their echo chambers, even if it is just a simple first step.