Tyler Cowen is worried about our matching technology. We have algorithms which tell us what TV shows to watch, which books to read, what wine to drink, and what shoes to wear. We can be matched with romantic partners and music, and very often our matching gives us exactly what we wanted and were hoping for. But, in the eyes of Cowen, all this matching has a dark side. It can make us complacent and can lead to greater segregation between people with different backgrounds, experiences, and interests.
In his book The Complacent Class Cowen writes, “Better matching for all its pleasures and virtues, is also in some regards uncomfortably close to the concept of more segregation … Very often we match to what we already like, or what is already like us. Matching brings many new and varied delights into our lives, but in a lot of spheres, the like-to-like effects of matching outweigh the ability of matching to shake us up. That is partly why matching can make us so happy.”
We like matching. We like knowing that other people like us already like the restaurant we are going to, or the show that is on tv, or the song that is about to play. We like when things are similar to what we already know. It reduces our cognitive burden and eliminates the stress of picking something and spending money on something we ultimately do not like. We are all risk averse to losing money, and hate the feeling of sunk costs. Matching makes us happy by making decisions more simple and helping us avoid the feeling of loss. It reduces our worries and in many instances, such as auto-playing shows online, we don’t even have to make a decision at all.
At the same time, matching technology reduces the chances for us to find something new. Up-and-coming artists with a new take on an old style can have trouble breaking through if the algorithms don’t match them with our tastes. We might miss out on great new content because our matching technology put us in a certain silo. When we reduce opportunities for new experiences, we stagnate, leading to the complacency that Cowen feared as we lose a belief that we could be something better than what we are and currently have.
A further downside to the matching technology we use is the potential for extreme segregation. If we really like one sport, then we can be pushed ever further into the specifics of that sport. Our algorithms can provide more and more specific content, advertisements, and connections to that single sport, eliminating things unrelated to the sport from our orbit. As we get further along, we might find that all the people we interact with are also obsessed with our particular team from one particular sport, and we will lose some ability to be with people who are not also living in the same bubble.
The sports example is a relatively harmless side of segregation, but it can be worse. Racial, political, and religious segregation are also possible with our matching technology. As we burrow down in our own communities, in real life or online, we may alienate those who do not look, think, and hold the same preferences that we do, leading to situations where we cannot have meaningful interactions with diverse people. This type of segregation is not healthy in a democracy because it makes shared visions and understandings of society and culture impossible across different isolated bubbles.
Our matching might make us happy and reduce our cognitive load, but it certainly comes with dangerous downsides. We can embrace the matching technology we have, but we should also be aware of what can happen if we let it make too many decisions in our lives. We should also find ways, times, and spaces where we can get beyond the matching to try something new and experience something beyond our typical bubble.
Novel Learning 