Crowdsourcing to the users is an interesting alternative. My startup actually considered doing just this in our browser plugin [1]—adding a feature that lets people assign a clickbait rating to a link. We would then get a crowdsourced rating for links, and low-rated links would be grayed out for our plugin users. We ultimately hoped to release the data on rankings publicly, so that a predictive algorithm could be created and used by others as well. This feature aligns moderately with our mission/product, which is about reading efficiently on the web. But we've had other priorities so far and haven't built it yet.

I think the reason that crowdsourcing wouldn't make as much sense for FB is that their audience is less early-adopter than ours. Some people wouldn't know what clickbait is. It's not just about whether you like the article or not—it's specifically about whether the headline mischaracterizes or inappropriately teases the content. FB probably decided that they wanted to train the algorithm carefully, so they used an internal team instead of a crowdsourced solution.

1: https://chrome.google.com/webstore/detail/beeline-reader/ifj...