Lauren Indvik details a prototype from the WaPo:

A software program recognizes and transcribes speech into text, which appears to the right of the video. As statements are transcribed, they are run against WaPo‘s database of facts, matching keywords to determine if an assertion is accurate. If it is, a “true” label will flash above the statement. Misleading statements will likewise be identified.

Hallie Batem ponders the situations in which the Truth Teller will fail and succeed:

[S]ome of the most skilled orators work in the gray areas where figures may be literally true, but misleading in certain contexts. Take Bill Clinton’s speech at the Democratic National Convention …

Clinton didn’t lie when he said, “In the past 29 months, our economy has produced about four and a half million private sector jobs.” But the “29 month” threshold was carefully chosen to reflect positively on President Obama’s leadership. Had that threshold been stretched out by a few months, the economic growth under Obama wouldn’t look so impressive. A robot might not catch that. A person, like FactCheck.org’s Robert Farley, did. …

In the wake of the London riots, the Guardian posted a visualization of how rumors were spread then quickly debunked on social media, and the results showed that Twitter might really be a “truth machine” as some have suggested. If algorithms could harness this data in real time for the sake of fact-checking, could it help journalists avoid potentially devastating reporting errors during breaking news events?