Jim Giles has written perhaps the best piece yet on the landscape of fact-checking in a New Scientist piece that published today (archival PDF). He details a range of efforts, both editorial and automated, current and proposed, methodically addressing both the promise as well as the challenges and obvious questions in a remarkably balanced way. It’s very encouraging that the field is getting quality reporting like this early on.
It’s no surprise, then, that a number of organisations are fighting back. They are converging on the idea that new technologies can prevent nonsense from spreading on the internet, and by extension through popular discourse itself. Several groups are about to roll out tools designed to flag up errors in any online content, and so nip them in the in bud before they spread.
In particular, Jim covers Hypothes.is, Dan Schultz’s Truth Goggles and a new effort by our advisor, Paul Resnick, called Fact Spreader. The latter two attempt automated techniques to semantically associate discovered content such as web pages, tweets or even email with fact-checked information as determined by organizations like PolitiFact.
Most importantly, he thoughtfully explores the questions others, such as Rob Ennals (now at Google), raise in terms of overcoming the cold start and how a reputation model might address bias in the community.
By the way, we love being the “most ambitious” project out there.
The solution may be to recruit that army online. Perhaps the most ambitious attempt to use the crowd to purge the internet of falsehoods is a tool called Hypothes.is, which is due to launch next year. Dan Whaley, the founder of the non-profit organisation in San Francisco that is developing it, decided to act after watching the confusion caused by the debates around healthcare legislation and the banking crisis: “Like the rest of us, I feel the pain of trying to understand what is going on and what information to trust.”