Here's what artificial intelligence thinks makes a terrible selfie

A new artificial intelligence system has figured out how not to take a selfie.

Stanford University PhD student Andrej Karpathy built a deep learning system called a ConvNet that studied 2 million selfies and found that the worst selfies share a few things in common with bad photos in general — they’re usually badly lit or too close up.

However, the AI also found that selfies containing more than one person tended to not get very many likes. It’s easy to see why the photos below may not attract a lot of likes — it’s difficult to even make out any faces in many of them. Here’s what the worst of the worst look like:

Kaparthy writes what not to do to take a good selfie in his blog about the project. He writes not to do the following:

  • Take selfies in low lighting. Very consistently, darker photos (which usually include much more noise as well) are ranked very low by the ConvNet.
  • Frame your head too large. Presumably no one wants to see such an up-close view.
  • Take group shots. It’s fun to take selfies with your friends but this seems to not work very well. Keep it simple and take up all the space yourself. But not too much space.

In contrast, the top 100 selfies are very washed out and only featured one person. The best selfies also tended to follow a set of specific rules — had a black and white filter, included white borders, featured a face in the middle third of the photo, and cropped so that the person’s forehead is cut off.

The best selfies are also uniform in other ways — very few women of colour and virtually no men appear in the top 100.

The rules for great selfies change slightly when it comes to men, though many of them are still very washed out and feature white borders. Karpathy writes that the best selfies taken by men also more frequently included the whole head and shoulders.

So if you want your selfie to get a lot of love, make sure to include a lot of light, be on your own, and back up a little. Read more about the program’s creation.

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