CNN's resident fact checker has been waiting his whole life for Trump's RNC speech

CNN's resident fact checker has been waiting his whole life for Trump's RNC speech
Screenshot: CNN

Last night, when Donald Trump accepted his nomination at the all-clown circus of the Republican National Convention with a lengthy speech, CNN fact checker Daniel Dale must have felt something stir deep inside him. Years of careful reading and listening—of sorting the bullshit from the truth—have honed his mind into a purpose-built weapon, ready to be deployed at a moment’s notice. After so long spent defeating lies in regular skirmishes, the RNC’s final evening gave him the war he’s spent a lifetime preparing for.

Watch Dale as Anderson Cooper sets him up to fact-check the speech. Obviously humming with pent-up information, Dale says he identified, on a first listen, “more than 20 false or misleading claims” then breathlessly runs through a bunch of them for several minutes straight. His brain downloading an encyclopedia of political data, Dale speeds through a torrent of Trump lies as if he’s been turned into the human vessel for some alien consciousness, supernatural entity, or supercomputer.

“Oh, that’s it?” Cooper says when he’s done. Dale replies that he has plenty more to talk about if the broadcast has time for him to get into it. Later in the same clip, Dale talks to Don Lemon and Chris Cuomo and launches into another of the fact-checking routines he appears able to rattle off in his sleep. Unfortunately, Lemon and Cuomo decide to discuss the speech in general with Dale rather than let him continue his life-giving work of spotting and correcting lies without any interruption.

“I’m sure, Daniel, you could go on even more,” Lemon says at one point. Dale smiles, knowing that, yes, he could go on until the sun burns out. Trump’s acceptance speech is what he’s trained for. It’s the final battle that’s inspired him as he’s sweated over articles and statistics, knowing that one day his vast stores of knowledge would need to be deployed all at once.

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