Don’t you just hate how vile some people are on the Internet? How easy it’s become to say horrible and hurtful things about other groups and individuals? How this tool that was supposed to spread knowledge, amity, and good cheer is being use to promulgate hate? No need to worry anymore: Google’s on it.
Earlier this year, Silicon Valley’s overlords introduced Perspective API, the latter being nerd-speak for Application Program Interface, or a set of tools for building software. The idea behind it is simple: because it’s impossible for an online publisher to manually monitor all the comments left on its website, Perspective will use advanced machine learning to help moderators track down comments that are likely to be “toxic.” Here’s how the company describes it: “The API uses machine learning models to score the perceived impact a comment might have on a conversation.”
That’s a strange sentiment. How do you measure the perceived impact of a conversation? And how can you tell if a conversation is good or bad? The answers, in Perspective’s case, are simple: machine learning works by giving computers access to vast databases, and letting them figure out the likely patterns. If a machine read all the cookbooks published in the English language in the last 100 years, say, it would be able to tell us interesting things about how we cook, like the peculiar fact that when we serve rice we’re very likely to serve beans as well. What can machines tell us about the way we converse and about what we may find offensive? That, of course, depends on what databases you let the machines learn. In Google’s case, the machines learned the comments sections of The New York Times, the Economist, and the Guardian.
What did the machines learn? Only one way to find out. I asked Perspective to rate the following sentiment: “Jews control the banks and the media.”