WEBVTT - The Alex Kogan Experience

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<v Speaker 1>Pushkin. I want to start this episode by telling you

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<v Speaker 1>just the very beginning of a story I recently heard about.

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<v Speaker 1>A guy named Alex Cogan born in nineteen eighty six

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<v Speaker 1>into a Jewish family in the Soviet Union. After the

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<v Speaker 1>collapse in nineteen ninety one, the government loses control and

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<v Speaker 1>Jews are even less safe than before. Alex's dad starts

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<v Speaker 1>getting death threats, so he up and moves his entire

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<v Speaker 1>family four generations of Cogan's, to New York City. In

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<v Speaker 1>nineteen ninety four, Alex enter's first grade in a Brooklyn

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<v Speaker 1>public school. He's conspicuous, way taller than the other kids.

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<v Speaker 1>He speaks no English. He's also got a talent from

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<v Speaker 1>math and science. Once his teachers can understand him, they

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<v Speaker 1>think he has the makings of a gifted physicist. Life's

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<v Speaker 1>not hard for him, but as he grows up, he

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<v Speaker 1>begins to see that it isn't always easy for everybody else.

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<v Speaker 1>Six months after they've arrived in the United States, his

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<v Speaker 1>great grandmother had jumped from their apartment window to her death.

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<v Speaker 1>His parents, the loves of each other's lives, split up.

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<v Speaker 1>Alex cries every night until they get back together. He

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<v Speaker 1>enters high school and one of his close friends attempts suicide,

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<v Speaker 1>another becomes clinically depressed. Alex begins to read psychology. He's

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<v Speaker 1>a math and science kid, but he's getting more and

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<v Speaker 1>more curious about human nature. And the first time I

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<v Speaker 1>met him, and I really remember it very distinctly, because

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<v Speaker 1>he almost always wore these giant basketball shorts no matter

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<v Speaker 1>what the weather. You know, he's terribly dressed, like a

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<v Speaker 1>lot of Berkeley undergrads, and you know, and basketball shoes.

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<v Speaker 1>That's Daker Keltner, the psychologist at the University of California,

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<v Speaker 1>Berkeley who runs something called the Greater Good Science Center

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<v Speaker 1>where they study human emotion. We heard from him in

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<v Speaker 1>episode one. Alex Cogan was a shambolic six foot four

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<v Speaker 1>inch freshman back in two thousand and five when he

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<v Speaker 1>knocked on Daker's office door and said he'd like for

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<v Speaker 1>Daker to teach him. Emotions fascinated him. He'd come to

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<v Speaker 1>cal to study physics, but he'd been thinking about love,

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<v Speaker 1>about the distinction between loving and being loved. He wanted

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<v Speaker 1>to study it the way you'd study a quark. And

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<v Speaker 1>Alex came in and he said, you know, I have

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<v Speaker 1>seven kinds of love. That I'm going to put people into.

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<v Speaker 1>I was like, wow, that's interesting. And then there are

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<v Speaker 1>twelve variations of I forgot what the other factor was

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<v Speaker 1>that or set of conditions that he wanted to create,

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<v Speaker 1>And there are eighty four different conditions in his study.

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<v Speaker 1>So he's going to study seven different kinds of love,

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<v Speaker 1>and he's going to study all these different variables that

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<v Speaker 1>would maybe predict the force of the love, the power

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<v Speaker 1>of the love exactly. So he's about to make glove

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<v Speaker 1>more complicated than it's ever been made. So it sounds like, right,

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<v Speaker 1>he was gonna confound our understanding of love. Daker talks

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<v Speaker 1>Alex out of that idea, but this kid is so

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<v Speaker 1>smart and original and full of energy, and so Daker

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<v Speaker 1>takes him in and it isn't long before Alex is

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<v Speaker 1>finding things to do that no one else is doing.

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<v Speaker 1>For instance, the thing that he does after they discover

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<v Speaker 1>a gene it's associated with human kindness. And Alex did

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<v Speaker 1>this cool paper where he showed if you present videotapes

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<v Speaker 1>of people who have that gene or this variant of

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<v Speaker 1>a gene that makes them kind and I am an

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<v Speaker 1>observer and I see one of those people for twenty

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<v Speaker 1>seconds on video. I trust them, right, I'm like this guy.

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<v Speaker 1>I go to battle at this guy, right, I trust

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<v Speaker 1>this guy. By the time Alex graduates from cal he's

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<v Speaker 1>established himself as the most promising student in the entire

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<v Speaker 1>psychology department and the most unusual. Just this big, sweet

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<v Speaker 1>natured guy with a serious talent for math and statistics

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<v Speaker 1>and a desire to study huge questions like what is love?

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<v Speaker 1>When he left and he's so unconventional, Michael, he could

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<v Speaker 1>have gone to any graduate program in the country, and

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<v Speaker 1>he chooses the University of Hong Kong. I'm what because

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<v Speaker 1>he met this woman or got engaged and fell in love? Yeah,

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<v Speaker 1>fell in love. But Daker and Alex stay in touch.

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<v Speaker 1>They collaborate on a few papers. They're both interested in

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<v Speaker 1>big questions about human nature. At the same time, social

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<v Speaker 1>media has started to create a new way to study

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<v Speaker 1>those questions. In late twenty twelve, Facebook invites Daker to

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<v Speaker 1>visit and asks him to create a bunch of new emojis,

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<v Speaker 1>ones that better convey actual emotions. When Daker sees what

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<v Speaker 1>Facebook knows about its users, he's blown away. This could

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<v Speaker 1>be the greatest data source that will ever EXI and

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<v Speaker 1>it would help us answer questions from the scientific perspective,

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<v Speaker 1>like how does disease spread in some neighborhoods but not others?

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<v Speaker 1>What predicts heart attacks? Where does hate crime? Where is

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<v Speaker 1>it likely to happen? Right? That was all tractable with

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<v Speaker 1>the data that they had. Meanwhile, Alex had moved to

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<v Speaker 1>England to teach at Cambridge University. He was still researching

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<v Speaker 1>the same stuff, the positive emotions, and he too was

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<v Speaker 1>seeing possibilities in the new social media data. And I

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<v Speaker 1>was at Facebook doing my consulting work and I saw

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<v Speaker 1>Alex there. I was like, what are you doing here?

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<v Speaker 1>And he's everywhere, you know, So he's like, oh, I'm

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<v Speaker 1>working on this other project and he told me about it.

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<v Speaker 1>Alex Cogan told Daker that he wanted to use Facebook

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<v Speaker 1>to study things like love and happiness. For example, you

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<v Speaker 1>might be able to take a fairly small sample of data,

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<v Speaker 1>say the likes of ten thousand Facebook users, to make

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<v Speaker 1>discoveries about those emotions entire countries. The math was complicated

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<v Speaker 1>enough the Dacker himself didn't fully understand it. He then

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<v Speaker 1>forgot all about it until one day a year or

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<v Speaker 1>so later, when Alex Cogan called him up. He calls

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<v Speaker 1>me after Trump's elected and he says, I think I've

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<v Speaker 1>done something that was part of this election. And I

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<v Speaker 1>was like, okay, well, let's talk what is it? And

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<v Speaker 1>he said, I created this mechanism that was purchased and

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<v Speaker 1>used in the Trump campaign. He was worried that he

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<v Speaker 1>actually had had some effect, or that he'd be perceived

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<v Speaker 1>to have had some effect. I don't think he made

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<v Speaker 1>that distinction. I just think he thought, oh now, Alex

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<v Speaker 1>Cogan sensed that he might have a problem. He just

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<v Speaker 1>had no idea how big it was going to be.

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<v Speaker 1>I'm Michael Lewis, and this is Against the Rules, a

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<v Speaker 1>show about the decline of the human referee in American

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<v Speaker 1>life and what that's doing to our idea of fairness today.

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<v Speaker 1>I want to talk about an entire species of refs,

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<v Speaker 1>one that's nearing extinction, whom no one will miss until

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<v Speaker 1>it's too late. I used to be a referee in

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<v Speaker 1>the big leagues of dictionaries. The American Heritage. You've heard

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<v Speaker 1>of it. The American Heritage has something called the usage Panel,

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<v Speaker 1>and I was on it, along with a couple of

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<v Speaker 1>hundred other word people. Every year we get this mass

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<v Speaker 1>email asking us to judge the latest word controversies how

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<v Speaker 1>certain words should be defined, or spelled or pronounced. English

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<v Speaker 1>is always changing, and the dictionary wanted to keep up

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<v Speaker 1>with the times and sometimes resist them. Was it okay

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<v Speaker 1>to use unique to mean unusual? Should you say banal

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<v Speaker 1>or banal or both? This year I got a different

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<v Speaker 1>sort of email, saying I've been fired. They fired the

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<v Speaker 1>whole panel, so I didn't take it personally, but I

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<v Speaker 1>still want to know why. As far as I could see,

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<v Speaker 1>we've done nothing wrong. Our definitions were still definitive. I

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<v Speaker 1>call the guy who'd been my boss as head of

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<v Speaker 1>the usage panel. What did you do? I advised on

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<v Speaker 1>people to include on the usage panel. Occasionally people die,

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<v Speaker 1>and or occasionally people would simply not respond to the

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<v Speaker 1>questionnaire for several years running, and we'd want to replace them.

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<v Speaker 1>His name is Stephen Pinker. Yes, that's Stephen Pinker, Harvard

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<v Speaker 1>psychologist and author of many best selling books. In the

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<v Speaker 1>case of disputed usage, where people wonder what is the

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<v Speaker 1>correct use? Can I use decimate to mean destroy most of, or,

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<v Speaker 1>as rumor has it should only mean destroy one tenth of?

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<v Speaker 1>Or what's the best way to use epicenter. Is it

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<v Speaker 1>just the center of something or does it have to

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<v Speaker 1>mean propagating outward? Of course, if you want to know

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<v Speaker 1>what a center means, you can now just google it.

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<v Speaker 1>The Internet has been bad for dictionaries. They don't sell

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<v Speaker 1>the way they used to. But the Internet doesn't explain

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<v Speaker 1>why our panel was fired. We didn't cost the dictionary

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<v Speaker 1>a dime. We all work for free. Why did they

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<v Speaker 1>cut it? You know, I haven't gotten to the bottom

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<v Speaker 1>of this. Maybe I'll just let someone else chase this

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<v Speaker 1>one down. I mentioned this whole situation because it's not unique, which,

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<v Speaker 1>by the way, should only be used to mean one

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<v Speaker 1>of a kind. Nothing can be very unique, or most unique,

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<v Speaker 1>or even rather unique. A thing can be either banal

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<v Speaker 1>or banal. But it's either unique or it's not anyway.

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<v Speaker 1>The death of the word referee is not even all

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<v Speaker 1>that unusual. They're a member of the species of refs

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<v Speaker 1>that the world now has no use for. The culture refs,

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<v Speaker 1>the people who referee are most basic interactions how we

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<v Speaker 1>should talk, who we should trust, or whom we should trust.

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<v Speaker 1>No one particularly mourns their death until they really need one.

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<v Speaker 1>Our bags. We are in a suburb of Dallas, at

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<v Speaker 1>the home of Brian Garner, who has set himself up

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<v Speaker 1>as a referee of the English language. When and what

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<v Speaker 1>should you hyphenate? He's the author of M. Garner's Modern

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<v Speaker 1>English Usage. Why people shouldn't use flaunt when they mean flout.

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<v Speaker 1>We've been standing out of here for three or four

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<v Speaker 1>minutes and there's no sign of life. We're gonna go

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<v Speaker 1>knock on his door. All right, all right? What's the

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<v Speaker 1>difference between species and spurious? Does it really matter if you,

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<v Speaker 1>at this very moment are filled with angst or angst?

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<v Speaker 1>We're a weird g. Garner's Usage manual is now more

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<v Speaker 1>than twelve hundred pages long. The late novelist David Foster

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<v Speaker 1>Wallace called it a work of genius. This book is

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<v Speaker 1>so big. Did you bring your copy? No? I have

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<v Speaker 1>xerox those pages that I want, just the front. Yeah,

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<v Speaker 1>it wouldn't fit. You don't really expect to find guardians

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<v Speaker 1>of the English language in Dallas, Texas. Then again, you

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<v Speaker 1>don't really expect to find them anywhere. That's why I've

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<v Speaker 1>bothered to find him. It's like flying to Indonesia to

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<v Speaker 1>see the last of the Sumatran rhinos, and so here

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<v Speaker 1>We are between a giant golf course of a lawn

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<v Speaker 1>and a monticello of red bricks and doric columns. We're

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<v Speaker 1>prank in the right place, Michael Lewis, Ryan Garner, very

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<v Speaker 1>good to meet you. Thank you for letting us in truth.

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<v Speaker 1>Are we welcome? Garner's house does have a kitchen and bathrooms,

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<v Speaker 1>almost like a normal house, but it feels like an

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<v Speaker 1>excuse for him to live in what amounts to a

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<v Speaker 1>massive library. Floors of books with little ladders so you

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<v Speaker 1>can climb up and reach them. Thousands upon thousands of

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<v Speaker 1>mostly very old books about the English language. I've had

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<v Speaker 1>my coffee all round. It looks like a Robber Baron's

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<v Speaker 1>collection of books, except they look like they've been read.

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<v Speaker 1>They look like they aren't. They aren't book spot by

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<v Speaker 1>the yard, and they also have plastic covers on them,

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<v Speaker 1>which is a little unusual. How many Usage Experts books

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<v Speaker 1>do you have in this library? I mean, how many different?

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<v Speaker 1>He published his first Usage Guide back in nineteen ninety eight,

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<v Speaker 1>partly as a protest against the way people talked on TV,

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<v Speaker 1>which sounds a bit snooty, but Gardner's genius was not

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<v Speaker 1>to set himself up as some kind of elite speaking

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<v Speaker 1>down to the illiterate masses. His judgments felt like common sense.

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<v Speaker 1>They were relied on data. He classified any change in

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<v Speaker 1>the language into five stages, ranging from weird new usage

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<v Speaker 1>to a totally accepted new use of the word. He

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<v Speaker 1>had lots of information on how people were actually speaking

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<v Speaker 1>and writing the English language. So this is Webster's first

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<v Speaker 1>dictionary six and this just kind of shows the evolution

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<v Speaker 1>over the nineteenth century. But I have so upstairs. These

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<v Speaker 1>are books on writing, a beginning all the way over here,

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<v Speaker 1>so that this whole, that whole wall is linguistics, and

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<v Speaker 1>look on usage and writing. I think I just assume

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<v Speaker 1>that anybody who went this far out of his way

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<v Speaker 1>to tell other people how to speak and write must

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<v Speaker 1>have something wrong with him. That if you tracked his

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<v Speaker 1>interest back to its source, you'd finally arrive at the

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<v Speaker 1>desire to feel superior. But that's not Garner. His source

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<v Speaker 1>energy isn't snobbery. It's outrage at an idea cooked up

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<v Speaker 1>by academic linguistics, an idea he had encountered back as

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<v Speaker 1>a student at the University of Texas descriptivism. It was

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<v Speaker 1>called a native speaker of English cannot make a mistake,

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<v Speaker 1>and it's so fact though if a native speaker says it,

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<v Speaker 1>it is correct. That is a very extreme position to take,

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<v Speaker 1>and I think an indefensible one, and one that I

0:14:16.956 --> 0:14:20.716
<v Speaker 1>have pretty much set my face against. He set his

0:14:20.756 --> 0:14:24.396
<v Speaker 1>face against descriptivism, and his face is set against it. Still.

0:14:25.196 --> 0:14:33.876
<v Speaker 1>Do you consider yourself a referee? Yes? Yeah, I'm making

0:14:34.036 --> 0:14:38.756
<v Speaker 1>judgment calls about and there is a lot of judgment involved,

0:14:38.916 --> 0:14:43.436
<v Speaker 1>But I'm trying to be a helpful guide to writers

0:14:43.436 --> 0:14:46.836
<v Speaker 1>and speakers of English. We're now up in a balcony

0:14:46.876 --> 0:14:50.796
<v Speaker 1>gazing down at an amphitheater of books about the English language.

0:14:51.356 --> 0:14:53.836
<v Speaker 1>He's got a whole other collection of books out back

0:14:53.996 --> 0:14:56.716
<v Speaker 1>where the poolhouse should be, in a building that's an

0:14:56.716 --> 0:14:59.356
<v Speaker 1>exact replica of the room in England in which the

0:14:59.396 --> 0:15:03.476
<v Speaker 1>Oxford English Dictionary was created. I pulled down an especially

0:15:03.516 --> 0:15:09.556
<v Speaker 1>decrepit looking book by someone I've never heard of, Lindley Murray. Murray,

0:15:09.676 --> 0:15:12.836
<v Speaker 1>but there's kind of a hero of mine. Interesting guy.

0:15:13.396 --> 0:15:16.636
<v Speaker 1>He was a New York lawyer in seventeen eighty four.

0:15:16.676 --> 0:15:20.116
<v Speaker 1>He moved to York, England because he didn't like the Revolution,

0:15:20.716 --> 0:15:25.836
<v Speaker 1>and a lot of Americans actually moved to England because

0:15:25.836 --> 0:15:29.276
<v Speaker 1>they didn't appreciate what was going on. Lynn Manuel and

0:15:29.276 --> 0:15:33.396
<v Speaker 1>Miranda left that out of Hamilton. I guess so, and

0:15:33.476 --> 0:15:37.476
<v Speaker 1>so these two shelves are whole various ambitions of Murray's Grammar. Yeah,

0:15:37.796 --> 0:15:41.076
<v Speaker 1>and Brian Garner seems to have all of them. So Murray.

0:15:41.196 --> 0:15:44.076
<v Speaker 1>In seventeen ninety five he stopped practicing law and he

0:15:44.116 --> 0:15:49.556
<v Speaker 1>wrote Murray's English Grammar for a Quaker girls school in York,

0:15:49.636 --> 0:15:53.676
<v Speaker 1>and it became the best selling book in the English

0:15:53.756 --> 0:15:59.196
<v Speaker 1>language other than the Bible for the first fifty years

0:15:59.196 --> 0:16:03.396
<v Speaker 1>of the nineteenth century. He sold over thirteen million copies

0:16:03.436 --> 0:16:08.116
<v Speaker 1>of his English Grammar. Every household needed an English Grammar

0:16:08.796 --> 0:16:14.836
<v Speaker 1>and a Bible thirteen million copies. The joint population of

0:16:14.876 --> 0:16:17.356
<v Speaker 1>Great Britain in the United States in eighteen hundred was

0:16:17.396 --> 0:16:21.076
<v Speaker 1>only fifteen million, But back then people threw money at

0:16:21.116 --> 0:16:25.276
<v Speaker 1>language refs. Noah Webster got rich from his dictionary, so

0:16:25.396 --> 0:16:28.716
<v Speaker 1>did Fowler and Follet and Partridge and scores of others

0:16:29.116 --> 0:16:32.596
<v Speaker 1>from their grammars and usage guides. Strunk and White have

0:16:32.716 --> 0:16:36.636
<v Speaker 1>sold ten million copies of this style manual. There was

0:16:36.636 --> 0:16:38.756
<v Speaker 1>a time not long ago when a writer could get

0:16:38.796 --> 0:16:41.756
<v Speaker 1>paid to write about how to write, and the American

0:16:41.756 --> 0:16:46.316
<v Speaker 1>Heritage Dictionary used to brag about his usage panel. But

0:16:46.396 --> 0:16:49.836
<v Speaker 1>Brian Garner is in the wrong century. How many copies

0:16:49.836 --> 0:16:54.036
<v Speaker 1>of Garner's Modern English usage is sold, I don't know exactly,

0:16:54.076 --> 0:16:57.596
<v Speaker 1>but it's fewer that hauled and paltry. Brian Garner has

0:16:57.636 --> 0:17:00.716
<v Speaker 1>a really nice house, but his usage manual doesn't pay

0:17:00.716 --> 0:17:05.116
<v Speaker 1>his mortgage. He gives writing seminars for lawyers. The rest

0:17:05.116 --> 0:17:08.956
<v Speaker 1>of his market has mostly vanished. I mentioned Barnes and Noble,

0:17:08.956 --> 0:17:13.036
<v Speaker 1>but I haven't singled anybody out in particular, although I

0:17:13.116 --> 0:17:16.796
<v Speaker 1>kind of did when the first two editions of my

0:17:16.876 --> 0:17:19.636
<v Speaker 1>Usage book came out. Usage Book has passed a we're

0:17:19.636 --> 0:17:22.476
<v Speaker 1>not going to stalk it. I mean that has a

0:17:22.516 --> 0:17:26.036
<v Speaker 1>major effect, and they said, no, we've made the decision

0:17:26.276 --> 0:17:29.716
<v Speaker 1>that really this category is defunct. The usage book is

0:17:29.716 --> 0:17:32.476
<v Speaker 1>a defunct category. I grab another one of his old

0:17:32.476 --> 0:17:36.236
<v Speaker 1>books and flip through it. Some nineteenth century guide to pronunciation.

0:17:37.636 --> 0:17:40.676
<v Speaker 1>The idea that anyone would write, much less pay money

0:17:40.676 --> 0:17:46.756
<v Speaker 1>for a pronunciation guide, well, it's preposterous and preposterous. It

0:17:46.876 --> 0:17:50.076
<v Speaker 1>is an interesting fact, and one not sufficiently realized that

0:17:50.076 --> 0:17:52.356
<v Speaker 1>a person who has a pronunciation of his own for

0:17:52.436 --> 0:17:54.436
<v Speaker 1>a word is very apt to take it for granted

0:17:54.716 --> 0:17:56.676
<v Speaker 1>that he hears all others has pronounced it in the

0:17:56.676 --> 0:18:00.036
<v Speaker 1>same manner, when in fact his own method is entirely

0:18:00.116 --> 0:18:07.036
<v Speaker 1>peculiar to himself. It doesn't make true at Also, talking

0:18:07.036 --> 0:18:10.396
<v Speaker 1>about making people incredibly uncomfortable, fearful of what was coming

0:18:10.396 --> 0:18:13.076
<v Speaker 1>out of their mouths, that's what he's doing. People used

0:18:13.116 --> 0:18:15.556
<v Speaker 1>to feel uneasy about how they use the language. They

0:18:15.556 --> 0:18:19.076
<v Speaker 1>didn't want to sound stupid or uneducated. Now they feel

0:18:19.116 --> 0:18:21.876
<v Speaker 1>uneasy about anyone who would presume to judge how they're

0:18:21.916 --> 0:18:24.996
<v Speaker 1>using the language, and old anxiety has been replaced by

0:18:24.996 --> 0:18:29.516
<v Speaker 1>something else, a suspicion of the individual ref People still

0:18:29.596 --> 0:18:31.516
<v Speaker 1>judge other people by what they say and how they

0:18:31.516 --> 0:18:34.796
<v Speaker 1>say it, but they do it differently, without reference to

0:18:34.836 --> 0:18:38.316
<v Speaker 1>a higher authority, but to the crowd. My own bank

0:18:38.356 --> 0:18:42.436
<v Speaker 1>here in Dallas, every time there would be in any

0:18:42.436 --> 0:18:44.556
<v Speaker 1>activity on one of my accounts, I'd get an email

0:18:44.596 --> 0:18:52.796
<v Speaker 1>message dear dear mister Garner semicohen And I called my

0:18:52.876 --> 0:18:54.836
<v Speaker 1>banker and I said, by the way, you know, you

0:18:54.956 --> 0:18:57.716
<v Speaker 1>got hundreds of these things, presumably thousands going out by

0:18:57.716 --> 0:19:03.636
<v Speaker 1>the day, dear customer, semicolon, And I said, you know,

0:19:03.836 --> 0:19:05.796
<v Speaker 1>it's got to be either comma or a colon. He said,

0:19:05.796 --> 0:19:09.236
<v Speaker 1>could you put that in writing? And I said, or

0:19:09.276 --> 0:19:12.036
<v Speaker 1>I'll even give you some authorities, and I cited Garner's

0:19:12.076 --> 0:19:18.316
<v Speaker 1>Modern English usage and a couple of other authorities on

0:19:18.396 --> 0:19:22.196
<v Speaker 1>this point of punctuation. It's a pretty elementary point. Yep,

0:19:22.276 --> 0:19:25.156
<v Speaker 1>he did that. I mean, who else is there to site?

0:19:25.676 --> 0:19:29.156
<v Speaker 1>But the incorrectly punctuated letters just kept coming. Still. I

0:19:29.196 --> 0:19:32.516
<v Speaker 1>was getting dozens every week of dear mister Garner semicolon

0:19:32.676 --> 0:19:34.956
<v Speaker 1>and and it was I was about to change banks

0:19:34.956 --> 0:19:37.796
<v Speaker 1>over this, because it's it's it's a little upsetting to

0:19:37.836 --> 0:19:44.716
<v Speaker 1>think I'm doing business with people who are doing something

0:19:44.756 --> 0:19:49.356
<v Speaker 1>so egregiously bad. And they didn't change it for about

0:19:49.396 --> 0:19:50.836
<v Speaker 1>a month, and so I called him and I said,

0:19:50.876 --> 0:19:53.716
<v Speaker 1>what's going on? He said, well, you know, I showed

0:19:53.716 --> 0:19:56.156
<v Speaker 1>it to some of the people here at the bank,

0:19:56.236 --> 0:19:58.036
<v Speaker 1>but we have a dispute about whether it should be

0:19:58.036 --> 0:20:01.156
<v Speaker 1>a semicolon or a colon, and so we just left it.

0:20:02.596 --> 0:20:04.836
<v Speaker 1>But that that is a demotic view. Well, your your

0:20:04.836 --> 0:20:07.476
<v Speaker 1>opinion is as good as mine. Anybody's opinion is as

0:20:07.516 --> 0:20:11.796
<v Speaker 1>good as somebody else. Demotic. Now, there is a word

0:20:12.796 --> 0:20:18.116
<v Speaker 1>derived from an ancient Greek word meaning popular. That's how

0:20:18.156 --> 0:20:23.476
<v Speaker 1>the language is generally refereed by popular opinion. Inside Garner's bank,

0:20:23.876 --> 0:20:26.876
<v Speaker 1>by popular opinion, it was okay to send out letters

0:20:26.916 --> 0:20:31.356
<v Speaker 1>teeming with semicolons that didn't belong. It's obviously not that

0:20:31.396 --> 0:20:34.556
<v Speaker 1>big a deal. I mean, you can still understand where

0:20:34.556 --> 0:20:37.676
<v Speaker 1>the bank was trying to say. Plus, it's sort of

0:20:37.716 --> 0:20:42.396
<v Speaker 1>freeing to rid ourselves of this expert language ref this

0:20:42.556 --> 0:20:47.596
<v Speaker 1>annoying little schoolmarmie voice in your head. On the other hand,

0:20:48.156 --> 0:20:51.276
<v Speaker 1>what happens when that little voice ceases to exist? And

0:20:51.356 --> 0:20:54.116
<v Speaker 1>not just that little voice, but the other little voices

0:20:54.196 --> 0:21:03.436
<v Speaker 1>like it. I'm Margaret Sullivan and I was the public

0:21:03.556 --> 0:21:06.316
<v Speaker 1>editor of the New York Times. And what's a public editor?

0:21:06.596 --> 0:21:08.476
<v Speaker 1>I just asked that to loosen her up. I knew

0:21:08.476 --> 0:21:12.836
<v Speaker 1>the answer. The public editor is the ombudsman, the neutral

0:21:12.876 --> 0:21:16.756
<v Speaker 1>party inside the news organization whose job is to make

0:21:16.956 --> 0:21:21.236
<v Speaker 1>judgments about the news in the same possibly irritating way

0:21:21.516 --> 0:21:25.756
<v Speaker 1>that Brian Garner makes judgments about the language, to call

0:21:25.796 --> 0:21:28.836
<v Speaker 1>out the paper when it screws up. Sullivan did that

0:21:28.876 --> 0:21:31.036
<v Speaker 1>at the New York Times from two thousand and twelve

0:21:31.356 --> 0:21:33.796
<v Speaker 1>until the spring of two thousand and sixteen. When she

0:21:33.916 --> 0:21:36.956
<v Speaker 1>left a year later, the Times just got rid of

0:21:36.956 --> 0:21:39.956
<v Speaker 1>its public editor altogether. So I would love for you

0:21:39.996 --> 0:21:44.916
<v Speaker 1>to explain to me the importance of ombudsman why they

0:21:44.956 --> 0:21:48.396
<v Speaker 1>exist in the first place. So, for example, and this

0:21:48.516 --> 0:21:51.396
<v Speaker 1>is not the only role, but let's just say someone

0:21:51.436 --> 0:21:54.036
<v Speaker 1>thinks a correction should be made in a news story

0:21:54.596 --> 0:21:58.596
<v Speaker 1>and the people who are in charge of that say, well, nope,

0:21:58.756 --> 0:22:01.316
<v Speaker 1>we're not going to do that because we're convinced it's right.

0:22:01.676 --> 0:22:05.316
<v Speaker 1>So then they could come to the ombudsman and say,

0:22:06.196 --> 0:22:09.436
<v Speaker 1>what do you think here? The thing about the is

0:22:09.476 --> 0:22:14.116
<v Speaker 1>that it has to be independent. I had no editor.

0:22:14.156 --> 0:22:16.156
<v Speaker 1>I mean I had a copy editor, and I end

0:22:16.156 --> 0:22:18.916
<v Speaker 1>the My copy editor great person would say to me,

0:22:19.036 --> 0:22:20.596
<v Speaker 1>are you sure you want to say it that way?

0:22:20.676 --> 0:22:23.756
<v Speaker 1>Or don't you think going a little too far there?

0:22:24.196 --> 0:22:26.916
<v Speaker 1>But he couldn't tell me not to do it. Sullivan

0:22:27.036 --> 0:22:30.156
<v Speaker 1>was not just a good ombudsman. She was a famously

0:22:30.236 --> 0:22:32.876
<v Speaker 1>good one. She made a big deal about reporters who

0:22:32.956 --> 0:22:36.396
<v Speaker 1>let sources approve their quotes. She called out The Times

0:22:36.396 --> 0:22:40.476
<v Speaker 1>for its policies allowing anonymous sources, especially in stories about

0:22:40.556 --> 0:22:44.196
<v Speaker 1>national politics. Everyone in the news room read and feared her,

0:22:44.956 --> 0:22:47.876
<v Speaker 1>and that probably prevented a lot of distorted or unfair

0:22:48.036 --> 0:22:51.956
<v Speaker 1>stuff from ever getting into print. But the role she

0:22:51.996 --> 0:22:54.716
<v Speaker 1>played is dying. The Washington Post got rid of their

0:22:54.756 --> 0:22:58.236
<v Speaker 1>ombudsman in two and thirteen, and the New York Times

0:22:58.276 --> 0:23:02.956
<v Speaker 1>in twenty seventeen. Even ESPN had one and got rid

0:23:02.956 --> 0:23:06.716
<v Speaker 1>of it. And why so, why has it been in decline?

0:23:07.316 --> 0:23:10.676
<v Speaker 1>If you ask the media organizations, the news organizations who

0:23:10.756 --> 0:23:17.836
<v Speaker 1>have discontinued their ombudsperson rolls, they would say, almost to

0:23:17.916 --> 0:23:21.916
<v Speaker 1>a person, they would say, it's not necessary anymore because

0:23:21.916 --> 0:23:26.396
<v Speaker 1>there's so much criticism in the digital world on Twitter

0:23:26.916 --> 0:23:30.076
<v Speaker 1>and elsewhere. There's so many voices, there's so many ways

0:23:30.116 --> 0:23:32.436
<v Speaker 1>to get a complaint or a point of view out

0:23:32.476 --> 0:23:34.876
<v Speaker 1>there that we don't need to have someone that we

0:23:35.076 --> 0:23:39.836
<v Speaker 1>pay to criticize us. Internally, you don't need a news

0:23:39.876 --> 0:23:43.316
<v Speaker 1>reff anymore because in the new media market, the crowd

0:23:43.396 --> 0:23:46.716
<v Speaker 1>can do the reffing. The Times only created the ombudsman

0:23:46.836 --> 0:23:50.036
<v Speaker 1>roll back in two thousand and three. The reasoning then

0:23:50.156 --> 0:23:54.356
<v Speaker 1>was the modern media market, the Internet, cable TV, the

0:23:54.396 --> 0:23:57.156
<v Speaker 1>speeding up in the news cycle that was all creating

0:23:57.196 --> 0:24:00.236
<v Speaker 1>pressures that led to some really sensational screw ups by

0:24:00.236 --> 0:24:02.996
<v Speaker 1>the New York Times. They printed a bunch of stories

0:24:03.036 --> 0:24:05.716
<v Speaker 1>on the front page by a reporter named Jason Blair.

0:24:06.276 --> 0:24:08.796
<v Speaker 1>He later confessed that he just made up quotes an

0:24:08.916 --> 0:24:12.596
<v Speaker 1>entire scenes. They printed stories saying that Sodom Hussein possessed

0:24:12.636 --> 0:24:16.556
<v Speaker 1>weapons of mass destruction when he didn't. Did you while

0:24:16.596 --> 0:24:19.156
<v Speaker 1>you were there? Was there? Did you have a sense

0:24:19.196 --> 0:24:22.836
<v Speaker 1>that there was a decline in the need for you

0:24:23.116 --> 0:24:25.036
<v Speaker 1>to do this job? Was there? Where? Were there like

0:24:25.236 --> 0:24:28.916
<v Speaker 1>less things coming in? Oh? No more if anything? But

0:24:28.956 --> 0:24:31.796
<v Speaker 1>there was this belief in the air that the crowd

0:24:31.876 --> 0:24:35.956
<v Speaker 1>could do the job. And why pay a genuinely independent

0:24:35.956 --> 0:24:39.316
<v Speaker 1>news referee when you could get the crowd to do

0:24:39.436 --> 0:24:42.876
<v Speaker 1>the job for free? Do you ever read it? Does

0:24:42.956 --> 0:24:46.196
<v Speaker 1>any anything ever cause a story to smell for you?

0:24:46.236 --> 0:24:48.516
<v Speaker 1>You go, there's something wrong. It's the kind of thing

0:24:48.556 --> 0:24:50.756
<v Speaker 1>that if I were there in my job, I'd be

0:24:50.756 --> 0:24:54.036
<v Speaker 1>getting emails about Oh, yes, absolutely, you can see those

0:24:54.116 --> 0:25:01.756
<v Speaker 1>coming a mile away. Now I'm going to finish the

0:25:01.796 --> 0:25:05.116
<v Speaker 1>story of Alex Cogan, the young psychologist born in the

0:25:05.116 --> 0:25:08.316
<v Speaker 1>Soviet Union who started out in physics and ended up

0:25:08.316 --> 0:25:12.596
<v Speaker 1>in love along with a bunch of other researchers and

0:25:12.676 --> 0:25:16.316
<v Speaker 1>app builders. He'd signed an agreement with Facebook to study

0:25:16.356 --> 0:25:20.916
<v Speaker 1>its users. It wasn't cheap to do. Alex paid the

0:25:20.956 --> 0:25:24.436
<v Speaker 1>subjects of his studies through some survey company. He asked

0:25:24.436 --> 0:25:28.076
<v Speaker 1>permission to let him study overall patterns of what they

0:25:28.156 --> 0:25:31.796
<v Speaker 1>liked and how they used emojis. He hoped that the

0:25:31.916 --> 0:25:34.916
<v Speaker 1>data might yield all kinds of insights or help address

0:25:34.956 --> 0:25:37.356
<v Speaker 1>the odd questions that Alex had a talent for raising,

0:25:38.036 --> 0:25:41.836
<v Speaker 1>like what is the difference between loving and being loved?

0:25:44.196 --> 0:25:49.236
<v Speaker 1>Fast forward to i'd say winter of twenty fourteen, and

0:25:49.476 --> 0:25:52.796
<v Speaker 1>one of the PhD students in my department at Cambridge says, Hey,

0:25:52.916 --> 0:25:56.076
<v Speaker 1>I've been consulting for this company. They'd really love to

0:25:56.116 --> 0:25:58.476
<v Speaker 1>meet you and get like a little consulting help from you.

0:25:58.636 --> 0:26:01.876
<v Speaker 1>Would you be interesting? I'm like, sure, meet Alex Cogan,

0:26:02.556 --> 0:26:06.596
<v Speaker 1>student of Love. The big cary for me here was

0:26:06.876 --> 0:26:08.316
<v Speaker 1>that they were going to pay for a really big

0:26:08.396 --> 0:26:12.436
<v Speaker 1>data collection. So they're going to pay something like eight

0:26:12.516 --> 0:26:15.156
<v Speaker 1>hundred thousand dollars so we could get all this data

0:26:15.196 --> 0:26:17.236
<v Speaker 1>and I could keep it to do my research. And

0:26:17.276 --> 0:26:20.076
<v Speaker 1>that was really exciting to me because hey, this was

0:26:20.316 --> 0:26:22.996
<v Speaker 1>a really fast way to get a really nice grant.

0:26:23.996 --> 0:26:25.956
<v Speaker 1>So I set up a meeting with this company called

0:26:26.236 --> 0:26:32.556
<v Speaker 1>cl which would eventually become Cambridge Analytica. Yes, that Cambridge Analytica.

0:26:32.676 --> 0:26:35.916
<v Speaker 1>It has nothing to do with Cambridge University. It was

0:26:35.956 --> 0:26:38.956
<v Speaker 1>just a little known political consulting firm trying to horn

0:26:39.036 --> 0:26:43.316
<v Speaker 1>in on the lucrative business of advising presidential campaigns. Yeah,

0:26:43.356 --> 0:26:46.116
<v Speaker 1>so we're really looking at page legs. And the reason

0:26:46.116 --> 0:26:48.476
<v Speaker 1>we focused it on page likes was there's a few

0:26:48.516 --> 0:26:51.116
<v Speaker 1>papers published at that point that showed that, hey, you

0:26:51.156 --> 0:26:54.716
<v Speaker 1>could take people's page legs and use them to predict

0:26:54.756 --> 0:26:58.876
<v Speaker 1>their personalities with some level of accuracy. The company asked

0:26:58.916 --> 0:27:02.716
<v Speaker 1>Alex if he could classify people by five personality traits

0:27:03.076 --> 0:27:08.476
<v Speaker 1>extra version, agreeableness, openness, and so on use their Facebook

0:27:08.556 --> 0:27:11.796
<v Speaker 1>data to herman which little personality buckets they fell into

0:27:12.556 --> 0:27:16.196
<v Speaker 1>kind of routine stuff for him. Would caught Alex's interest

0:27:16.476 --> 0:27:18.916
<v Speaker 1>was the chance to make other studies of the same people.

0:27:19.396 --> 0:27:21.116
<v Speaker 1>Why do you need that much money to collect the

0:27:21.196 --> 0:27:24.996
<v Speaker 1>data paying participants. So the way we usually recruit participants,

0:27:24.996 --> 0:27:27.956
<v Speaker 1>as would say like, hey, please answer twenty minutes of

0:27:28.036 --> 0:27:30.076
<v Speaker 1>questionnaires for us, and we'll give you a few dollars

0:27:30.116 --> 0:27:33.516
<v Speaker 1>for your time. And in this case we got something

0:27:33.516 --> 0:27:36.756
<v Speaker 1>like two hundred thousand people to go and give us

0:27:36.796 --> 0:27:38.716
<v Speaker 1>twenty minutes of their time, and we paid them around

0:27:38.756 --> 0:27:43.396
<v Speaker 1>four bucks each. He didn't even need to go find

0:27:43.436 --> 0:27:47.356
<v Speaker 1>these people. They found him through websites where people offered

0:27:47.356 --> 0:27:50.716
<v Speaker 1>to be lab rats for researchers in exchange for cash

0:27:50.836 --> 0:27:55.196
<v Speaker 1>or prizes. Alex gave them cash. They gave Alex access

0:27:55.236 --> 0:27:57.556
<v Speaker 1>to their Facebook data, which I guess tells you that

0:27:57.596 --> 0:27:59.116
<v Speaker 1>a lot of people are happy to put a price

0:27:59.116 --> 0:28:03.676
<v Speaker 1>on their privacy. Anyway, Cambridge Analytica's idea wasn't even all

0:28:03.716 --> 0:28:07.036
<v Speaker 1>that original. The Obama campaign claimed to have done the

0:28:07.076 --> 0:28:10.636
<v Speaker 1>same thing with Facebook data back into twelve, though on

0:28:10.636 --> 0:28:14.836
<v Speaker 1>a smaller scale. But Alex figured out pretty quickly just

0:28:14.916 --> 0:28:17.316
<v Speaker 1>how hard it was to do what his client wanted.

0:28:18.236 --> 0:28:22.516
<v Speaker 1>You couldn't really predict much about people using their Facebook data,

0:28:22.676 --> 0:28:26.196
<v Speaker 1>or at least he couldn't. We started asking the question

0:28:26.236 --> 0:28:28.956
<v Speaker 1>of like, well, how often are we right? And so

0:28:28.996 --> 0:28:32.596
<v Speaker 1>there's five personality dimensions, and we said, like, okay, for

0:28:32.756 --> 0:28:36.356
<v Speaker 1>one percentage of people, do we get all five personality

0:28:36.836 --> 0:28:40.156
<v Speaker 1>categories correct? We found it was like one percent. How

0:28:40.156 --> 0:28:41.916
<v Speaker 1>did you even check that? Though? How do you find

0:28:41.956 --> 0:28:46.316
<v Speaker 1>out whether someone is an extrovert? The two hundred thousands

0:28:46.396 --> 0:28:50.276
<v Speaker 1>that provided us to the personality scores, because those terms

0:28:50.276 --> 0:28:52.316
<v Speaker 1>of thousand people to authorize that app filled out the

0:28:52.316 --> 0:28:56.236
<v Speaker 1>personality quiz, and that would be like, okay, let's go

0:28:56.316 --> 0:28:59.076
<v Speaker 1>and see how these people actually answered, and let's see

0:28:59.076 --> 0:29:01.396
<v Speaker 1>what we predicted and we could compare it. So, assuming

0:29:01.436 --> 0:29:04.396
<v Speaker 1>they know their personality and that was right, you got

0:29:04.396 --> 0:29:06.516
<v Speaker 1>it right one percent of the time. One percent of time.

0:29:08.156 --> 0:29:11.316
<v Speaker 1>I'm going to break that down for you. Cambridge Analytica

0:29:11.396 --> 0:29:16.356
<v Speaker 1>had Alex Cogan collecting and compiling Facebook data in a

0:29:16.396 --> 0:29:20.076
<v Speaker 1>way that was incredibly useless. I think we got halfway

0:29:20.116 --> 0:29:23.236
<v Speaker 1>through the project and realize, you know, this probably doesn't

0:29:23.276 --> 0:29:25.916
<v Speaker 1>work that well. But at that point, you know, we're

0:29:25.956 --> 0:29:28.876
<v Speaker 1>contractorally obligated to give them the data and they were

0:29:28.916 --> 0:29:32.636
<v Speaker 1>still interested. But here was the crazy thing. The consulting

0:29:32.676 --> 0:29:35.996
<v Speaker 1>firm didn't care whether it worked or it didn't. They're

0:29:35.996 --> 0:29:39.516
<v Speaker 1>getting paid pots of money by Ted Cruz's presidential campaign,

0:29:39.996 --> 0:29:42.876
<v Speaker 1>who were trying to reach voters on social media. The

0:29:42.956 --> 0:29:45.516
<v Speaker 1>Cruise campaign didn't seem to know that this stuff didn't work.

0:29:46.716 --> 0:29:52.676
<v Speaker 1>With a heavy heart, but with boundless optimism. Then Ted

0:29:52.796 --> 0:29:58.276
<v Speaker 1>Cruz lost the Republican primary to Donald Trump, we are

0:29:58.356 --> 0:30:02.916
<v Speaker 1>suspending our campaign. Cambridge Analytica had used Alex's useless predictions

0:30:03.236 --> 0:30:07.436
<v Speaker 1>to help the loser to lose. Now amazingly, they sold

0:30:07.476 --> 0:30:11.076
<v Speaker 1>their services to the winner. Alex never learned whether the

0:30:11.116 --> 0:30:14.356
<v Speaker 1>Trump campaign actually ever used his data, but in the

0:30:14.476 --> 0:30:18.436
<v Speaker 1>end that didn't matter. And when Donald Trump became president,

0:30:19.356 --> 0:30:22.316
<v Speaker 1>a lot of folks thought incredible had happened. So they

0:30:22.356 --> 0:30:26.716
<v Speaker 1>started looking for incredible explanations. Could the same data have

0:30:26.876 --> 0:30:30.116
<v Speaker 1>been possibly used when this selection? Because like, how else

0:30:30.116 --> 0:30:32.796
<v Speaker 1>could this possibly have happened? So folks are looking for, like,

0:30:33.196 --> 0:30:36.876
<v Speaker 1>where's the evil genius that could have possibly caused all this?

0:30:38.596 --> 0:30:42.396
<v Speaker 1>That was the moment Alex called his old teacher, Daker Keltner,

0:30:42.836 --> 0:30:45.436
<v Speaker 1>who gave him which sounded like good advice. I told

0:30:45.476 --> 0:30:48.516
<v Speaker 1>him like key below profile and just try to stay

0:30:48.556 --> 0:30:52.436
<v Speaker 1>out of the conversation. And that advice mostly worked right

0:30:52.516 --> 0:30:55.956
<v Speaker 1>up until early twenty and eighteen. First, our chief business

0:30:55.996 --> 0:31:00.316
<v Speaker 1>correspondent Rebecca Jarvis has the latest. He's the scientist at

0:31:00.316 --> 0:31:03.236
<v Speaker 1>the heart of the Facebook privacy scandal, and then the

0:31:03.316 --> 0:31:06.916
<v Speaker 1>drama unfolded a researcher at the University of Cambridge. They

0:31:06.956 --> 0:31:10.436
<v Speaker 1>finally realized that I was worn in the Soviet Union

0:31:11.076 --> 0:31:20.036
<v Speaker 1>to collect the data of millions of ali About a

0:31:20.036 --> 0:31:22.836
<v Speaker 1>week before the stories break, the New York Times and

0:31:22.916 --> 0:31:26.156
<v Speaker 1>The Guardian email me with a bunch of questions about

0:31:26.276 --> 0:31:29.036
<v Speaker 1>like the project and also whether I might be a

0:31:29.076 --> 0:31:32.836
<v Speaker 1>Russian spy. Now, I didn't want to ask them, like, guys,

0:31:32.916 --> 0:31:35.036
<v Speaker 1>if I am actually a Russian spy, do you think?

0:31:35.076 --> 0:31:37.276
<v Speaker 1>Like a direct question was going to trip me up,

0:31:37.276 --> 0:31:39.076
<v Speaker 1>And I'm gonna say, you got me, Yes, I'm a

0:31:39.116 --> 0:31:45.076
<v Speaker 1>Russian spy. It's now April twenty and eighteen. Alex Cogan's thinking,

0:31:45.516 --> 0:31:48.556
<v Speaker 1>surely someone will step in and sort this out, some

0:31:48.716 --> 0:31:52.796
<v Speaker 1>neutral third party, some grown up inside the New York Times.

0:31:52.836 --> 0:31:56.476
<v Speaker 1>Maybe someone would just stop and think about it. He

0:31:56.636 --> 0:32:00.876
<v Speaker 1>was an academic using some political consulting money to make

0:32:00.996 --> 0:32:05.236
<v Speaker 1>useless predictions about people's personalities, while also funding his own

0:32:05.276 --> 0:32:09.316
<v Speaker 1>studies on the side. He signed this agreement with Facebook,

0:32:09.556 --> 0:32:11.996
<v Speaker 1>the one that's spelled out how he could interact with

0:32:12.036 --> 0:32:15.156
<v Speaker 1>its users, and the company was okay with everything he'd

0:32:15.196 --> 0:32:18.916
<v Speaker 1>been doing. Facebook had explicitly agreed to let him use

0:32:18.996 --> 0:32:22.196
<v Speaker 1>Facebook data not just for academic research, but for commerce

0:32:22.596 --> 0:32:26.236
<v Speaker 1>if he could find some business use for it. When

0:32:26.276 --> 0:32:30.116
<v Speaker 1>reporters called him, he'd say, look at the agreement. Call Facebook,

0:32:30.196 --> 0:32:33.796
<v Speaker 1>they'll tell you the truth. But it's clear now that

0:32:33.876 --> 0:32:36.396
<v Speaker 1>we didn't do enough to prevent these tools from being

0:32:36.476 --> 0:32:39.716
<v Speaker 1>used for harm as well, and that goes for fake news,

0:32:40.196 --> 0:32:43.516
<v Speaker 1>for foreign interference and elections, and hate speech, as well

0:32:43.556 --> 0:32:47.396
<v Speaker 1>as developers and data privacy. That's Mark Zuckerberg on TV,

0:32:48.596 --> 0:32:50.596
<v Speaker 1>not looking like he wants to tell anybody the truth.

0:32:50.956 --> 0:32:55.276
<v Speaker 1>Facebook goes on the defensive. They do a press release

0:32:55.356 --> 0:32:58.836
<v Speaker 1>basically say like we've banned Kim John Letaca, they we've

0:32:58.876 --> 0:33:02.836
<v Speaker 1>banned Cogan. They basically also say that you know, Cogan

0:33:02.956 --> 0:33:05.436
<v Speaker 1>here told us it was for academocra research and that's

0:33:05.436 --> 0:33:07.356
<v Speaker 1>why we let him do it, which wasn't true at all.

0:33:07.596 --> 0:33:09.356
<v Speaker 1>We need to make sure that people aren't you using

0:33:09.356 --> 0:33:11.756
<v Speaker 1>it to harm other people. Facebook wanted people to believe

0:33:11.756 --> 0:33:14.756
<v Speaker 1>it was a victim of this data thief, when in fact,

0:33:14.836 --> 0:33:17.316
<v Speaker 1>it had given Alex's permission to do exactly what he did.

0:33:18.396 --> 0:33:21.596
<v Speaker 1>But then Facebook was created to be an unrefereed space.

0:33:22.356 --> 0:33:24.716
<v Speaker 1>It allowed its users to do and say pretty much

0:33:24.716 --> 0:33:29.796
<v Speaker 1>whatever they pleased and took no responsibility for the consequences. Now,

0:33:29.836 --> 0:33:33.236
<v Speaker 1>the world was furious with Facebook for not refing itself,

0:33:34.156 --> 0:33:37.316
<v Speaker 1>and so it panicked and look for someone else to blame.

0:33:38.276 --> 0:33:40.436
<v Speaker 1>Alex Cogan had set out in life to study our

0:33:40.476 --> 0:33:43.596
<v Speaker 1>positive emotions. He now got his lesson in the other kind,

0:33:44.516 --> 0:33:48.756
<v Speaker 1>anger mistrust. All these reporters were now calling him to

0:33:48.796 --> 0:33:52.796
<v Speaker 1>ask these very weird, hostile questions, like why it changed

0:33:52.836 --> 0:33:57.076
<v Speaker 1>his last name after he'd gotten married. We wanted to

0:33:57.116 --> 0:34:01.276
<v Speaker 1>find something that symbolize both our religious sides or a

0:34:01.356 --> 0:34:04.836
<v Speaker 1>scientific sites, because we're both scientists and religious, and we

0:34:04.996 --> 0:34:08.596
<v Speaker 1>landed this idea of light and they're like, oh, spectrum

0:34:09.276 --> 0:34:11.156
<v Speaker 1>like and then we heard the last name Specter, and

0:34:11.156 --> 0:34:13.036
<v Speaker 1>I'm like, oh, that's really cool, let's do that. So

0:34:13.076 --> 0:34:17.436
<v Speaker 1>we change your last name to Specter. Bad luck hab it.

0:34:18.076 --> 0:34:22.036
<v Speaker 1>Specter is also the evil organization from James Bond. I

0:34:22.156 --> 0:34:25.356
<v Speaker 1>got a lot of questions from a lot of journalists

0:34:25.356 --> 0:34:28.716
<v Speaker 1>saying like, Hey, this whole Specter thing is mighty suspicious.

0:34:31.116 --> 0:34:33.796
<v Speaker 1>I just say this that if you're planning to do

0:34:33.836 --> 0:34:39.076
<v Speaker 1>something sinister, if you're even vaguely considering the possibility, the

0:34:39.156 --> 0:34:41.916
<v Speaker 1>last thing you should do is change your last name

0:34:41.956 --> 0:34:46.996
<v Speaker 1>to Specter. It's like naming a restaurant sam and Ella.

0:34:47.396 --> 0:34:50.956
<v Speaker 1>Maybe that's just me. All the little details of Alex

0:34:51.036 --> 0:34:56.396
<v Speaker 1>Cogan's life had now become evidence for the prosecution. No

0:34:56.396 --> 0:34:58.476
<v Speaker 1>one even had to come out and say that Alex

0:34:58.556 --> 0:35:02.556
<v Speaker 1>Cogan was a spy. The Guardian ran graphics and little

0:35:02.676 --> 0:35:06.196
<v Speaker 1>arrows pointing from a picture of red Square to a

0:35:06.276 --> 0:35:11.556
<v Speaker 1>picture of Alex Cogan. What the Russia connection? I woke

0:35:11.636 --> 0:35:14.916
<v Speaker 1>up that day too, like two hundred emails from pretty

0:35:14.996 --> 0:35:18.756
<v Speaker 1>much every outlet in the world. CNNs starts trying to

0:35:18.796 --> 0:35:21.996
<v Speaker 1>track me down, Like I started giving phone calls from

0:35:21.996 --> 0:35:24.116
<v Speaker 1>like my old house in San Francisco that CNN is

0:35:24.156 --> 0:35:26.756
<v Speaker 1>like poking around trying to find me, and then they

0:35:26.756 --> 0:35:30.476
<v Speaker 1>show up at my door. The story of Alex Cogan

0:35:30.756 --> 0:35:35.116
<v Speaker 1>and Cambridge Analytica went viral before it ever really got

0:35:35.196 --> 0:35:38.836
<v Speaker 1>checked for whether it made any sense. It was refed

0:35:38.836 --> 0:35:42.356
<v Speaker 1>by the crowd. The crowd just decided that it liked

0:35:42.396 --> 0:35:46.876
<v Speaker 1>the story and ran with it. The US government started

0:35:46.996 --> 0:35:50.236
<v Speaker 1>knocking my door. We got, you know, questions from the

0:35:50.356 --> 0:35:56.116
<v Speaker 1>US Senate, the House, and etc. Etc. The British Parliament

0:35:56.196 --> 0:35:58.596
<v Speaker 1>reached out and I learned you can't really talk to

0:35:58.636 --> 0:36:01.556
<v Speaker 1>the government as a private citizen. So like financially like

0:36:01.676 --> 0:36:04.956
<v Speaker 1>completely wiped me out and like massive debt. Now in

0:36:05.036 --> 0:36:08.716
<v Speaker 1>terms of the legal bills, as far as the academic career,

0:36:09.156 --> 0:36:13.796
<v Speaker 1>pretty much over. A promising academic career went poof, just

0:36:14.156 --> 0:36:17.356
<v Speaker 1>like that. All he's got left is the possibility of

0:36:17.396 --> 0:36:21.676
<v Speaker 1>writing a memoir of the experience and a lawsuit against Facebook,

0:36:21.836 --> 0:36:24.996
<v Speaker 1>accusing the company of defamation, which he filed a few

0:36:24.996 --> 0:36:30.076
<v Speaker 1>months after we spoke. I met with a guy who

0:36:30.956 --> 0:36:33.156
<v Speaker 1>is doing a documentary about all of this, and he's like,

0:36:33.796 --> 0:36:36.236
<v Speaker 1>you know, it's crazy. I was warned, and I'm not

0:36:36.236 --> 0:36:38.316
<v Speaker 1>gonna tell you by who, but it's somebody prominence. But

0:36:38.476 --> 0:36:40.916
<v Speaker 1>I was warned when I'm talking to you to be

0:36:40.956 --> 0:36:44.436
<v Speaker 1>really careful because you're a trained covert agent from Russia

0:36:44.516 --> 0:36:50.636
<v Speaker 1>and you would out my phone. I think of Alex

0:36:50.716 --> 0:36:53.676
<v Speaker 1>Cogan as a curious kind of victim, even if he

0:36:53.756 --> 0:36:57.716
<v Speaker 1>refuses to sound anything but cheery about his situation. He's

0:36:57.716 --> 0:37:00.036
<v Speaker 1>what happens when the refs are banished from the news,

0:37:00.836 --> 0:37:03.276
<v Speaker 1>when people are encouraged to believe whatever it is they

0:37:03.316 --> 0:37:06.516
<v Speaker 1>want to believe. It's not that the news was once

0:37:06.556 --> 0:37:10.116
<v Speaker 1>perfectly refereed and now it's not, or that there weren't

0:37:10.116 --> 0:37:13.076
<v Speaker 1>ever fake stories, or that people haven't always believed all

0:37:13.196 --> 0:37:18.236
<v Speaker 1>kinds of bullshit. But there's an obvious antidote, the neutral

0:37:18.316 --> 0:37:23.596
<v Speaker 1>third party, the independent authority, the referee who makes it

0:37:23.636 --> 0:37:27.236
<v Speaker 1>more difficult, if only just a little bit, for an

0:37:27.276 --> 0:37:32.116
<v Speaker 1>easy lie to replace a complicated truth. Yet the job

0:37:32.196 --> 0:37:36.396
<v Speaker 1>doesn't exist. The market doesn't want some neutral third party

0:37:36.596 --> 0:37:39.876
<v Speaker 1>interfering with our ability to create our own truths, to

0:37:40.036 --> 0:37:45.196
<v Speaker 1>render our own meanings, to construct our own realities as

0:37:45.196 --> 0:38:01.596
<v Speaker 1>we decline, stage by stage against the Rules. Is brought

0:38:01.596 --> 0:38:05.156
<v Speaker 1>to you by Pushkin Industries. The show's produced by Audrey

0:38:05.156 --> 0:38:09.396
<v Speaker 1>Dilling and Catherine Girardote, with research assistance from Zoe Oliver

0:38:09.516 --> 0:38:15.116
<v Speaker 1>Gray and Beth Johnson. Our editor is Julia Barton. Mia

0:38:15.196 --> 0:38:19.276
<v Speaker 1>Lobell is our executive producer. Our theme was composed by

0:38:19.356 --> 0:38:23.556
<v Speaker 1>Nick Burttell, with additional scoring by Seth Samuel, mastering by

0:38:23.636 --> 0:38:28.236
<v Speaker 1>Jason Gambrel. Our show was recorded by Tofa Ruth at

0:38:28.316 --> 0:38:33.036
<v Speaker 1>Northgate Studios at UC Berkeley. Special thanks to our founders,

0:38:33.196 --> 0:38:56.636
<v Speaker 1>Jacob Weisberg and Malcolm Gladwell. Do you mean an example

0:38:56.676 --> 0:39:00.716
<v Speaker 1>of the state something that's at stage one now? Using

0:39:02.116 --> 0:39:08.236
<v Speaker 1>climatic in the sense climactic, this was the climatic point

0:39:08.276 --> 0:39:14.556
<v Speaker 1>of the play. Well climate yeah, they're both words. I

0:39:15.396 --> 0:39:20.276
<v Speaker 1>absolutely u and if you if you take the phrase

0:39:20.436 --> 0:39:24.276
<v Speaker 1>so anti climactic is the word is an anti climax.

0:39:25.196 --> 0:39:31.956
<v Speaker 1>But if you search anti climatic versus anti climactic, the

0:39:32.116 --> 0:39:35.556
<v Speaker 1>ratio and that's the you have to contextualize these searches.

0:39:35.676 --> 0:39:39.556
<v Speaker 1>There's no reason to use anti climatic at all. But

0:39:39.596 --> 0:39:44.036
<v Speaker 1>it's twenty eight to one in print sources anti climactic

0:39:44.356 --> 0:39:47.316
<v Speaker 1>in favor of anti climactic. But the fact that the

0:39:47.356 --> 0:39:51.716
<v Speaker 1>other one appears once every twenty eight times, that yeah,

0:39:51.756 --> 0:39:56.556
<v Speaker 1>it is. So this is like linguistic epidemiology. It begins

0:39:56.596 --> 0:40:00.716
<v Speaker 1>to spread. A lot of us have snakes in the grass.

0:40:01.316 --> 0:40:05.716
<v Speaker 1>We call them garter snakes, and garter snakes have little

0:40:06.116 --> 0:40:08.796
<v Speaker 1>stripes on them that look like garters. But a lot

0:40:08.796 --> 0:40:11.356
<v Speaker 1>of people people misheard that and started saying garden snake.

0:40:11.556 --> 0:40:13.956
<v Speaker 1>They thought it was it's a garden it's a register, regular,

0:40:14.116 --> 0:40:19.556
<v Speaker 1>harmless garden snake. Well it's a garter snake. That is

0:40:21.076 --> 0:40:24.196
<v Speaker 1>uh wow, Well that's a problem. That's eight to one

0:40:24.236 --> 0:40:26.516
<v Speaker 1>because if that snake in the garden is a rattlesnake,

0:40:26.916 --> 0:40:30.036
<v Speaker 1>that's right, there could be a real I've got I've

0:40:30.076 --> 0:40:32.076
<v Speaker 1>got a garden snake out there. Oh good, I don't

0:40:32.116 --> 0:40:35.396
<v Speaker 1>have to wear any protective clothing. I'll go catch it. Well,

0:40:35.476 --> 0:40:38.956
<v Speaker 1>you know that these are problems people would say you

0:40:38.956 --> 0:40:40.996
<v Speaker 1>and I just made that up. Give me an example

0:40:40.996 --> 0:40:45.716
<v Speaker 1>of the stage stage four um misspelling minuscule as if

0:40:45.756 --> 0:40:49.836
<v Speaker 1>it were miniskirt minuscules m I n us culi. But

0:40:49.916 --> 0:40:54.236
<v Speaker 1>that's two to one in print. Now or anti vinin.

0:40:54.516 --> 0:40:58.196
<v Speaker 1>Now here's one anti vinen. If you get bitten by

0:40:58.356 --> 0:41:01.516
<v Speaker 1>not a garter snake, but by a rattlesnake, you need

0:41:01.596 --> 0:41:06.316
<v Speaker 1>anti vinin v E N I N. But the noun

0:41:06.636 --> 0:41:10.196
<v Speaker 1>for what the snake puts into you is them, And

0:41:10.236 --> 0:41:14.476
<v Speaker 1>so a lot of people you know this is is

0:41:14.476 --> 0:41:18.196
<v Speaker 1>it really worth preserving? I don't know. It's traditional English

0:41:18.276 --> 0:41:23.636
<v Speaker 1>anti venin, and it comes from a Latin form. But

0:41:23.836 --> 0:41:28.156
<v Speaker 1>people have started saying anti venom, and that one is

0:41:28.516 --> 0:41:31.396
<v Speaker 1>one point two to one in favor of anti venom.

0:41:31.756 --> 0:41:35.236
<v Speaker 1>But that's one where I continue to recommend the traditional

0:41:35.276 --> 0:41:38.236
<v Speaker 1>form anti vinin. So you go into the garden and

0:41:38.316 --> 0:41:40.036
<v Speaker 1>you pick up the snake because you think it's a

0:41:40.076 --> 0:41:42.116
<v Speaker 1>garden snake, and you're a bit by the rattlesnake, and

0:41:42.156 --> 0:41:44.756
<v Speaker 1>you go you're bitten. You're bitten by the bit, thank

0:41:44.796 --> 0:41:47.276
<v Speaker 1>you very much, bitten by the rattlesnake, and you're taking

0:41:47.316 --> 0:41:49.036
<v Speaker 1>to the hospital and by the time they figure out

0:41:49.036 --> 0:41:50.916
<v Speaker 1>what you're trying to ask for, because you're asking for

0:41:50.956 --> 0:41:54.236
<v Speaker 1>anti venom and they don't have any, you're dead. Yeah,

0:41:54.236 --> 0:41:56.516
<v Speaker 1>because you mispronounced. Sorry, we're not giving you any. All

0:41:56.556 --> 0:41:59.316
<v Speaker 1>we have is anti vinin. We don't have any anti venom.

0:42:00.156 --> 0:42:02.476
<v Speaker 1>And by the way, I don't normally correct people, but

0:42:02.596 --> 0:42:05.876
<v Speaker 1>forgive me for that that bitten thing, Thank you very much. Sure,