“Among those who pay close attention to big technology platforms and misinformation, the frustration over the platforms’ repeated failures to do something that any remotely savvy news consumer can do with minimal effort is palpable: Despite countless articles, emails with links to violating content, and viral tweets, nothing changes. The tactics of YouTube shock jocks and Facebook conspiracy theorists hardly differ from those of their analog predecessors; crisis actor posts and videos have, for example, been a staple of peddled misinformation for years.
This isn’t some new phenomenon. Still, the platforms are proving themselves incompetent when it comes to addressing them — over and over and over again. In many cases, they appear to be surprised by that such content sits on their websites. And even their public relations responses seem to suggest they’ve been caught off guard with no plan in place for messaging when they slip up.”
All of this raises a mind-bendingly simple question that YouTube, Google, Twitter, and Facebook have not yet answered: How is it that the average untrained human can do something that multibillion-dollar technology companies that pride themselves on innovation cannot? And beyond that, why is it that — after multiple national tragedies politicized by malicious hoaxes and misinformation — such a question even needs to be asked?
Because they wan’t to use algorithms; they don’t want to have to pay humans.
Source: Why Can Everyone Spot Fake News But The Tech Companies?
Tiny, half-hearted point in their defense: if they hire real people to identify fake news, they’ll face constant criticism about bias in those people – and whoever has that job will face the constant risk of being revealed and hounded by one side of the political spectrum or the other. On the other hand, if Big Tech can use an algorithm, they’ll be able to shrug their shoulders and claim that “The computer did it, there’s no bias!”
But yeah, employing as few people as possible works out well for them too.
That’s certainly a valid point, but I think it’s not that hard to make sure that no one person makes a decision on a specific issue. With the exception of truly malicious or abusive articles, they would have to develop a database of what is true, perhaps partnering with some fact checking websites who can validate things with sources and citations.
Tiny, half-hearted point in their defense: if they hire real people to identify fake news, they’ll face constant criticism about bias in those people – and whoever has that job will face the constant risk of being revealed and hounded by one side of the political spectrum or the other. On the other hand, if Big Tech can use an algorithm, they’ll be able to shrug their shoulders and claim that “The computer did it, there’s no bias!”
But yeah, employing as few people as possible works out well for them too.
That’s certainly a valid point, but I think it’s not that hard to make sure that no one person makes a decision on a specific issue. With the exception of truly malicious or abusive articles, they would have to develop a database of what is true, perhaps partnering with some fact checking websites who can validate things with sources and citations.
Wired has a long article on Facebook’s problems with fake news. Apparently their problems really began when they switched from people to algorithms for detecting suspect stories. https://www.wired.com/story/inside-facebook-mark-zuckerberg-2-years-of-hell/
Wired has a long article on Facebook’s problems with fake news. Apparently their problems really began when they switched from people to algorithms for detecting suspect stories. https://www.wired.com/story/inside-facebook-mark-zuckerberg-2-years-of-hell/