Lauren Goode
A few years ago I wrote about how, when planning my wedding, I’d signaled to the Pinterest app that I was interested in hairstyles and tablescapes, and I was suddenly flooded with suggestions for more of the same. Which was all well and fine until—whoops—I canceled the wedding and it seemed Pinterest pins would haunt me until the end of days. Pinterest wasn’t the only offender. All of social media wanted to recommend stuff that was no longer relevant, and the stench of this stale buffet of content lingered long after the non-event had ended.
So in this new era of artificial intelligence—when machines can perceive and understand the world, when a chatbot presents itself as uncannily human, when trillion-dollar tech companies use powerful AI systems to boost their ad revenue—surely those recommendation engines are getting smarter, too. Right?
Maybe not.
Recommendation engines are some of the earliest algorithms on the consumer web, and they use a variety of filtering techniques to try to surface the stuff you’ll most likely want to interact with—and in many cases, buy—online. When done well, they’re helpful. In the earliest days of photo sharing, like with Flickr, a simple algorithm made sure you saw the latest photos your friend had shared the next time you logged in. Now, advanced versions of those algorithms are aggressively deployed to keep you engaged and make their owners money.
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