It's terrifyingly easy for reporters to exploit Google's News algorithms - The Next Web

I’ve spent the last eight months turning Google News into my personal playground. I manipulated the algorithm and made it surface my stories whether they were relevant to specific topics or not. This is a big problem.

I’m a regular reporter — a writer. I have no programming skills or formal education in computer science.

Google’s arguably the most technologically-advanced AI company in Silicon Valley. It also happens to be worth more than two trillion dollars.

Google News reaches almost 300 million users. And I was able to game its algorithms by changing a single word on a web page. Scary isn’t it?

We have “reinforcement learning” (RL) to thank for this particular nightmare.

Stupid in, stupid out

As Neural’s Thomas Macaulay recently wrote:

[The reinforcement learning] technique provides feedback in the form of a “reward” — a positive number that tells an algorithm that the action it just performed will benefit its goal.

Sounds simple enough. It’s an idea that works with children (you can go outside and play once you’ve finished your chores) and animals (doggo does a trick, doggo gets a treat).

Let’s use Netflix as an example. If you watch The Karate Kid, there’s a pretty good chance the algorithm will recommend Cobra Kai. And if 10 million people watch The Tiger King, there’s a pretty good chance you’ll get a recommendation for it whether you’ve watched related titles not.

Even if you never take one of the algorithm’s suggestions, it’s going to keep surfacing results...

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