In this day and age, dating apps and websites are nothing new, and the stigma of admitting to be a part of one is becoming virtually non-existent. If anything, we’ll see more and innovative ways people are matched up. Like letting the apps do the driving and using the tech to predict our matches based on our online behaviors.
When it comes to the way we use and interact with social media, we give up a lot about ourselves without even realizing it.
Machine learning algorithms and artificial intelligence have Netflix suggesting an exciting array of “TV Horror” based on shows I’ve watched previously, LinkedIn composed my bio for me, and Amazon’s front page is showing me every movie that Kristen Stewart has ever been in. You know, in case I was curious.
It sure can be convenient, but do predictive algorithms really get us?
How much can really be said about a person based on their viewing habits, website clicks, likes, and tweets? It’s no secret that there’s a common perception that people aren’t always who they present themselves to be online, but different platforms will invite varying forms of participation and thus a certain version of that person. I know I often scroll through my feed and don’t always click ‘Like’ on something I legitimately found interesting, and I don’t always share what I’m thinking or what I’m up to.
With that said, how accurate or reliable can we expect an app to be that will award you with a 28-axis breakdown of your personality based on your tweets? For some, I expect apps that do all the work of weeding out what you don’t want to see and locating more of what it thinks you do want to see would be a godsend of a timesaver. For others, it may invite more skepticism.
If we know we’re participating in a system that determines for us who we would best be paired with, does this not still influence behavior bias somehow? This could prove to be a challenge some might undertake as a sort of “borrowed ladder” just to see if they can.
After all, in a dystopian-like dating app world where one could be barred from participating because they were deemed “high risk” because the algorithm red-flagged them for depression, what’s to stop anyone from finding ways around this? Amy Webb did a TED Talk on a similar idea of how she hacked online dating.
A company that prides itself on having intuitive tech that knows us better than we know ourselves could be in hot water if people are finding ways to cheat the system. Social media profiles specifically curated to be sold to find a more idealized match doesn’t seem too far out of the realm of possibility. After all, social media influencers have been known to purchase fake followers as a way to fluff the appearance of their online fanbase.
Algorithms may be able to pick up on the fact that we may have certain types, but can it also pick up on the fact that these types may be more harmful, than helpful? We may like brunettes covered in tattoos who ride motorcycles, but they could be bad news if there are a series of exes that follow a particular type. When it comes to algorithms and dating services, it feels a lot like leaving one’s fate to percentages of probability, and this could be the future of online dating.
Machine learning algorithms are fascinating and can tell us more about ourselves than we may be aware of, but they’re far from perfect. There is still the problem of being unable to explain why certain things happen when automation is at work, like creepy bot-created content on Kid’s YouTube.
Sexy or not, online dating is taking some interesting turns. I don’t know that we should give our full trust to something automated that we’ve yet to fully understand, but that does require laying out the groundwork for testing while we’re still in the early stages of working with tech that aims to predict what we want.
It would be nice to be able to ask the AI how it came to its conclusions and why, but maybe we’re at a point where we’re more comfortable letting AI take the reigns at the sake of convenience.
Not all algorithms are created equal, so while some apps may be working toward weeding out mismatches, they could also be overlooking more favorable matches by focusing on factors that are irrelevant.