A few weeks ago, I read a thread on Twitter by a game designer at Riot Games. The thread is about the concept of “celebration” in the world of game design. It refers to the techniques used to reinforce “good” behavior in video games (good not in any objective sense, but simply whatever is desired by the game designer). It was an interesting thread, but I moved on shortly after reading it and didn’t give it much more thought. Until last week when I was reading an article about how social media is designed to be addictive. With the thread still floating around in the back of my mind, what I realized while thinking about the design of social media platforms was that Twitter uses the exact same techniques as video games.
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I am subscribed to Marques Brownlee on YouTube. I watch almost every one of his videos. YouTube is smart. It knows this, it recommends me almost all of his videos. But not this one. No matter how many times I refresh the page. No matter how far down the page I scroll. Despite the fact that the video has gotten 2.3 million views in 16 hours, performing better than a number of his recent videos. Despite the fact that it’s recommending me videos that are from people I am not subscribed to, videos that are years old, videos that I have watched before, videos that are about politics, videos that are about the ongoing Black Lives Matter protests in the wake of George Floyd’s murder.
This is what algorithmic bias looks like. Algorithms are not neutral.
“Algorithm” is a word here used not in the purely computer science sense, but to mean a element of software which operates in a black box, often with a machine learning component, with little or no human supervision, input, or control. ↩