What happens when you give your computer a $50 monthly budget and access to your Amazon account? Game designer Darius Kazemi created a program to help escape the predictive you want this, don’t you algorithms of online stores and the first thing it sent him was a CD of Hungarian music and a book by Noam Chomsky.
“I like the idea of being forced to consume things outside of what these large corporations like Amazon think I want to consume,” Kazemi tells The Verge. To that end, he created his own counter-algorithm to try to outfox Amazon, although he limited its purchases to media such as books and CDs so he wouldn’t end up with a bunch of spare parts.
Kazemi says on his blog that the idea was inspired from the delight caused by receiving a backordered item in the mail. Having forgotten you ordered it in the first place, it’s like buying yourself a present. Except he decided to make things more interesting by making that present random.
Genuinely random recommendations are remarkably hard to find on the web right now. Any given Amazon search is filtered by your history on the site, your purchases, the purchases of demographically similar users, a general popularity index, and countless other data sources. Recommendation engines like this are working their magic on most of the web’s big databases, from Google and Amazon to Pandora, Netflix, YouTube, eBay, and so on.
This system is great at sending junk to its rightful place at bottom of your search results, but the top of the list can feel airless and boring. If, based on your first six months of purchasing, Amazon’s algorithm decides you aren’t the kind of person who likes free jazz, you might never know what you’re missing. Apply the same rules over dozens of sites, and it’s easy to see how the experience could get claustrophobic. The buzzword for this is “filter bubble,” what’s left when everything unexpected has been whittled away by algorithms. To put it more simply, these programs just weren’t built for surprises.