Machines are Writing Clickbait

This is slightly terrifying. In a post earlier this week, I joked that clickbait headlines and not CAPTCHA will be the one thing that helps separate man from machine.

Well, developer Lars Eidnes has created a recurrent neural network (RNN) that tests the idea that clickbait headlines are unoriginal and easy to write.

[Clickbait in potentia] Left: RNNs have connections that form a cycle. Right: The RNN unrolled over three timesteps. By unrolling over time we can train an RNN like a standard neural network.

We can show an RNN a bunch of sentences, and get it to predict the next word, given the previous words. So, given a string of words like “Which Disney Character Are __”, we want the network to produce a reasonable guess like “You”, rather than, say, “Spreadsheet”. If this model can learn to predict the next word with some accuracy, we get a language model that tells us something about the texts we trained it on. If we ask this model to guess the next word, and then add that word to the sequence and ask it for the next word after that, and so on, we can generate text of arbitrary length. During training, we tweak the weights of this network so as to minimize the prediction error, maximizing its ability to guess the right next word. Thus RNNs operate on the opposite principle of clickbait: What happens next may not surprise you.

Auto-Generating Clickbait With Recurrent Neural Networks

Eidnes has created a website, Click-o-Tron, and all of its articles are written by the clickbait recurrent neural network. Looking at some of the headlines, I’d say it’s off to a very good start:

  • How The World’s Most Extreme Baby Moms Lost Weight
  • John McCain Speaks Out In His Own Words
  • A Guide For Getting Financial Crisis Out Of Your Career
  • 12 Awesome Ways To Drink Like A Boss
  • Why The National Dog Food Movement Is A Disaster
  • Should We Stop Using The Word ‘Double’?

To crowdsource the RNN’s results, each article can be voted up or down, similar to Reddit. Once it gets good enough? Millenials, y’all better watch out… this machine just might be the one that took your jobs! :mrgreen:

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