Behind every “you might also like” recommendation is an algorithm built on data you’ve provided. This includes the obvious stuff, like your viewing or listening history, but it may also factor in your age, location or gender. These algorithms are all a little different. For example, Netflix considers some surprising factors, like the time of day, the devices you use and how long you tend to watch. Spotify builds its recommendations by logging what you listen to, funneling that through a genre classification system, then pulling in songs from playlists from other users with similar tastes.

Spotify’s complicated algorithm struggles to push the boundaries of your own habits. Listen to a track from Nine Inch Nails and you’ll get more Nine Inch Nails on your algorithm-generated Discover Weekly playlist. Maybe it’ll toss in something similar sounding, but it’s just as likely to throw in a random pop song from the ’90s. If you go too off course and listen to a jazz playlist followed by some metal, the whole thing breaks down and you’re served up a nonsensical playlist for a week. Even in the best-case scenario, the experience is transactional, and without the thrill of self-discovery — part of the appeal of seeking out new media — the recommendations feel cold.

Movie streaming services often use the simple-seeming “people who watched this also watched” algorithm. These formulas are as likely to recommend something new as they are to solidify a stereotype. Netflix does this all the time, and as The Outline points out, it’s terrible at pushing you toward new movies. Most likely because of the feedback loop of movie availability, Netflix always seems to recommend Netflix-produced movies. Netflix at least provides a way to sort movies alphabetically by genre. If you’ve never dialed all the way down to the A-Z listings by genre in Netflix (or anywhere else), I highly recommend it. Almost every time, I find great movies the algorithms ignore.

If you want to see the outcome of too many algorithms, just head over to any Amazon product page, where you’ll get blasted with categories like “Inspired by your recent shopping trends,” “sponsored products related to this item,” “frequently bought together” or “Customers who viewed this item also viewed.” Amazon loves to use popularity-based algorithms, where whatever’s selling well in the moment gets pushed to the top. This has an unexpected effect of sometimes pushing fringe ideas into the spotlight. These popularity-based suggestions don’t improve the shopping experience either, because popularity often has nothing to do with quality.