Feeding the machine: We give an AI some headlines and see what it does

Enlarge / Turning the lens on ourselves, as it were.

There's a moment in any foray into new technological territory when you realize you may have embarked on a Sisyphean task. Staring at the multitude of options available to take on the project, you research your options, read the documentation, and start to work-only to find that actually just defining the problem may be more work than finding the actual solution.

Reader, this is where I found myself two weeks into this adventure in machine learning. I familiarized myself with the data, the tools, and the known approaches to problems with this kind of data, and I tried several approaches to solving what on the surface seemed to be a simple machine-learning problem: based on past performance, could we predict whether any given Ars headline will be a winner in an A/B test?

Things have not been going particularly well. In fact, as I finished this piece, my most recent attempt showed that our algorithm was about as accurate as a coin flip.

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