Episode 33: "America This Week," with Matt Taibbi and Walter Kirn

2023-04-07 00:30:14

Welcome to America This Week, with Matt Taibbi and Walter Kirn, the national news wrap-up so true, we recommend you stow all sharp objects before reading. <br/><br/><a href="https://www.racket.news/s/america-this-week?utm_medium=podcast">www.racket.news</a>

2Speaker 2
00:04.70 – 00:08.52

Welcome to America this week, I'm Matt Taib. How's it going, Walter?

1Speaker 1
00:09.64 – 00:38.26

So, Matt, I have a Megatan, a hypertan, which I ask all of those who watch, yeah, watch this, to admire here. Um, it's completely natural. I have to defend myself out of the box. Um, in terms of taking my, you know, usual three-hour walks in Las Vegas and then in Los Angeles, where I was last week. But, uh, a guy this brown can't be feeling down.

00:38.72 – 00:50.02

So, um, I'm glad, I'm glad to hear it. Well, how about you? where are you? uh, back in Las Vegas, land of the land of the low odds proposition.

00:50.86 – 01:06.56

Um, but uh, yeah, yeah, I had a friend here. It's nice when I have visitors who've never been to Las Vegas, they're usually just enchanted and delighted. They're like, Where was this place?

01:06.60 – 01:38.98

I'd heard about it, but um, it's sort of what I used to imagine New York would be when I was a little boy, before I'd been to New York. And that's one of the reasons I like it, you know, I, I like it. 24 hours. Um, and uh, it's starting to pick up for the summer. The they're having the auditions for the people who serve drinks at the pools, the beautiful body, people. Um, you know, Las Vegas comes into its own from about now until July or so.

01:38.98 – 01:43.84

Excellent when it just becomes so ungodly great. Um, I'm going to, I'm going.

2Speaker 2
01:43.84 – 01:59.68

Off on vacation right after the show? So, um, looking forward to a warm place or just a far away? I'm actually, I'm going eventually going to Hawaii. Uh, this is complicated. Um, I have a complicated family story.

01:59.76 – 02:29.16

My my father was born in Hawaii, he was adopted. Um, and so we have. We have relatives in Hawaii, uh, my Filipino relatives whom I've never met. So, um, we're. We're going to meet them, uh, this this next week, taking the kids to Hawaii. Uh, we'll stop in Disney World or Disneyland on the way, and, uh, then we'll go.

1Speaker 1
02:29.98 – 02:34.18

So looking forward to it. Uh, is there such a thing as a little stop?

2Speaker 2
02:35.30 – 02:43.12

I, I, I guess not a little stop at Disney with three kids, it's a huge proposition.

1Speaker 1
02:43.94 – 03:00.92

Yeah, yeah, exactly. You'll have to get in line a day and a half before. Um, we need to come to Las Vegas, because it is the capital, the capital of Filipino, uh, immigration in the United States, it really is. Um, is that true?

03:01.02 – 03:14.44

I didn't know people all through the city. Absolutely, absolutely yes. Las Vegas, in terms of its its population, its composition is a lot like Queens.

03:15.20 – 03:51.62

Um, it, it's. It's a true panoply of immigrant groups, um, drawn by the fact that you can come here, um, and make money. Uh, sort of from the ground up, doing all kinds of things that don't necessarily require an American higher education. It's it's a working class town or immigrants, and because of that, it's a beautiful place for food. Um, conversation and sort of cultural, uh, discovery. Uh, that, that's why, that's really why I like it.

2Speaker 2
03:51.84 – 03:56.52

Interesting, I should check it out for sure. I mean, I've been to Vegas, but, uh, you know.

03:58.50 – 04:04.76

Um, I have thought that it would be a cool place to live, but, uh, never, never took the step.

1Speaker 1
04:07.22 – 04:18.44

Yeah, I'm not sure about that, but uh, if you like the golf, you know I, I'm. I'm only here part of the year. Um, right, because my wife. We should hook up before we go to Davos, maybe.

04:19.84 – 04:27.66

Yeah, yeah, oh yeah. Exactly why don't they hold Davos in Las Vegas? Who are these joyless technocrats?

04:27.80 – 04:29.38

Why? why don't they go somewhere fun?

2Speaker 2
04:29.46 – 04:38.98

Maybe their core body temperature is is like 50 degrees lower than that of regular people. Uh, it's like a V the final battle.

1Speaker 1
04:39.00 – 05:05.08

Actually, you know, silicon, silicon chips and computer processing require cold temperatures, or they thrive in cold temperatures. And because most people in Davos, it's it's not known to general public, are run by remote AI connections to silicon brains. They they like to be in ski area. Um, that, that's my theory.

05:07.88 – 05:37.18

So yesterday, Matt, let's address the elephant in the living room. You had a contentious prosecutorial on their part uh, interview on MSNBC, um, with a very high speed interrogator. Uh, I noticed, uh, uh. He was putting as many words into one minute as I managed to get in in half an hour on this show. Um, yeah.

2Speaker 2
05:37.26 – 05:41.14

It wasn't a good look with my own Jeff Spicoli delivery, which is, yeah.

1Speaker 1
05:47.72 – 06:04.34

Yeah, yeah, yeah, you, you, you had a. you had a real, uh, high processing, uh, high verbiage count, uh. Interviewer as it were. uh, it didn't seem so much as an of an interview to me as a.

2Speaker 2
06:04.34 – 06:24.58

Cross examination, right? but I still have an obligation to hold up under cross examination. And what happened, what happened was that he, he got. He got me to lose my temper in the first seconds of the show. And, uh, because he, he read off the great Vampire Squid line at the beginning.

06:24.80 – 06:42.06

So I knew right away that was leading to the What happened to you man? critique. Then there was sort of a passage that implied that the story about the IRS visiting my house might not have been true. There was this passage about. Can I fact check that?

1Speaker 1
06:42.54 – 07:04.78

Can I fact check that story? I was sitting, I was sitting here, uh, you know, we. We talked for a few minutes, maybe five, before the show. As you, uh, as you uh, examined that note, I saw it with my own eyes. You held it up to the screen. And we're still processing what to do about it.

2Speaker 2
07:05.20 – 07:43.42

Yeah, I mean, the Washington Examiner published all, all of those documents are are, um, well, the the committee has all the documents the Washington Examiner published, the the note on my door, um, but more than that. I mean, does anybody really think that I would go to the committee that the, you know, uh, a congressional committee and tell them that the IRS visited my house with? And that not be true? Uh, considering all the things that, um, might blow from such an, you know, a false accusation, look, you still have to check, I get it.

07:43.46 – 08:15.78

But considering that there was information out there to check that, so that so that kind of had me triggered and and but more mostly, um, you know, I I it. It was this, um, very hostile interview, which I expected and, uh it. It was going kind of as I expected. Until he presented me with, um, some mistakes that I had made, and they were, they were errors, like, so let's go through them.

08:15.78 – 09:08.18

The the first one was a situation where, um, I had, I was looking at a Slack chat and it said EIP, uh, or like from EIP, escalated by CIS. And when I was reading that, um, in the time since I I published, um, that tweet, and now, um, uh, you know, I. I kind of learn more about the Center for Internet Security. And I hadn't yet put two and two together. But in that moment, I realized, Oh God, um, cause I cause. I thought it was a it was a misprint by the Twitter person and that it was actually CISa, it was actually CIS.

09:09.24 – 09:30.04

And so I I put a missing a there. Now, CIS is still a government contractor. It's it's a mistake, there's no question about it, but it was an honest mistake. I, you know, wouldn't have done it if I, you know, had known, uh, or had had been cognizant of it.

09:30.04 – 10:14.94

So I, you know, I immediately put a correction up about that. Um, the next one was just the thing where I. I mixed up two elections in my head as I was, um, writing a tweet about the timeline of when the election Integrity Project was formed versus when the Disinformation Governance Board was formed. And got it wrong that the Uh, DGB was before the EIP. So I mixed up a date, so one was one was in 2000 when, and one was in 2020, and one was in 2022. And what happened?

10:14.94 – 10:36.68

Was I in my? In my head? I thought it was the DGB was before the 2020 election. Um, or I, you know, I had remembered it that way. And when we were going over it, um, we must've just missed it, you know? Um, and that happens, so you transposed.

10:37.16 – 10:42.44

Yeah, no, I, I. I said that X happened before Y, and it was really Y happened before X.

1Speaker 1
10:42.96 – 10:49.18

So it was a it was a date. And what is the substantial criticism that came along with?

2Speaker 2
10:49.18 – 10:51.68

Noting that, uh, reversal.

10:53.32 – 12:02.42

Well, the I guess they would say that. What I was trying to say, and what I thought at the time was that the EIP had been created after, uh, the collapse of the DGB. Um, and I was, I was saying that. In in in the context of a video from EIP's director, Alex Stamos, who was talking on on camera about how the EIP had been formed. To quote, fill the gaps of what government couldn't do itself. So, um, you know, I, I, that's still true, that that that's the reason that they formed it. They they, you know, uh, deny that. But um, he said what he said, uh, and you can see that from from the list of partners of EIP that that includes CISA. Um, that, you know they. They imagined themselves as a body that was going to be stepping in the shoes of of what the government wasn't able to do.

12:04.38 – 12:15.38

So, um, but yeah, no, I screwed up a date, you know, there's no question about it that happens. Um, I, you know, in journalism, you make mistakes. So so far, so far.

1Speaker 1
12:16.82 – 12:36.78

So far on the list, we have acronymal I'm going to make up a word there, acronym confusion cis c-i-s versus c-i-s-a. Number two, you have a transposition of two elections, 2020 and 2022..

2Speaker 2
12:37.44 – 13:25.02

Uh, what, what? What's left now? So the third thing is is, uh, more complicated it. It's a. It was a re-report of something I'd read in a report from the Foundation for Freedom Online. Um, but I had also read the source material, which was the final report of the election Integrity Partnership. Where they discuss, um, how, they how? Essentially, just under 22 million, uh, tweets came to be flagged. Um, now they claim that the actual number was 2,962, or something like that, or 2,900, something.

13:26.74 – 14:17.52

First of all, I knew that wasn't true because I had personally seen something like thousands of EIP Uh flags just in the Slack chats that I was looking at. Which is a fraction of what overall, um, you know, the the traffic overall to to Twitter. But secondly, if you read the report and you talk to people like Mike Benz, who's the former state cybersecurity guy. Um, under Trump, who has been, you know, very angry about this going back to 2016, wrote a long thing about it. Um, they in their report, they talk about how each incident is. A is a sort of a unique URL incident, so you might have one URL that can be collapsed into thousands of incidents.

14:18.36 – 15:13.36

Um, so even if they say they're talking, they're only identifying 2,900 individual incidents. We could be talking. The. The number of raw tweets that could be flagged as part of an overall narrative, um, is enormous. Now, um, we're still working out whether there there might've been an error in terms of whether or not that flagging, you know, was external or internal. Um, Benz, you know, I have different people saying different things to me about that. I, I wrote it one way, um, but uh, the 22 million number is real. And they're playing, they're playing semantic games with words like individual incident, um, you know, cascading, right? So narrative.

15:13.36 – 15:42.98

And, uh, um, what's what's the other one? So so, like individual tweets, um, might be part of cascading narratives that can be collapsed, that's the word they use, collapsed, um, into one incident, so it's complicated, it's. It's exacerbated by the fact that they didn't talk to me, um, before the piece, even though I, I, I reached out to them.

15:43.72 – 15:54.60

Um, and didn't talk to you before the interview? You mean, no, no, Stanford before the Twitter files? Oh, okay.

15:54.68 – 16:24.54

Oh, okay, yeah, um, but you know, I. We're still trying to work it out. But they're essentially claiming that that Stanford only flagged 3000 things, which is not true. The algorithmically, they flagged an enormous number of stuff. And you can read read it in their own language in the report. Um, you know, this is one of those things where it might take a while to sort out exactly.

16:25.28 – 16:48.98

Um, I was trying to refer directly to their language and to the report, uh, so that people could work it out for themselves. Um, but, you know, in the moment, um, you know, I just didn't give a very good answer to that. So those are the three things that they that they keyed on. Now, two of them I've, I've corrected, the third one about the 22 million.

16:49.62 – 17:10.90

Um, I'm restoring, uh, pending more investigation. I I think it's probably right. Um, at most, it may need some language tweaking. Um, but you know, this, this, this is the result of, like the entire critique of of the Twitter files. This is, this is what happens in journalism.

17:10.90 – 17:46.44

I mean, as as I'm about to publish today, I think, you know, even going back to my first pieces about Rolling Stone periodical writing, you know, um, any kind of journalism. You're going to get a few things wrong, even if you check. Even with an army of fact checkers and multiple editors at Rolling Stone, we miss some things over the years. Um, even even the famous Golden Sacks piece had some things that, uh, you know, some regrettable language in it. Um, but that's part of the process of journalism is you face your critics.

17:46.58 – 18:28.14

They if you make mistakes, you own up to them. Uh, and that's how we kind of arrive collectively at, um, you know, at what the truth is now. The thing that irritates me about this is that this is going to be used, as you know, a gotcha to undermine the entire thing. To say that, um, I'm, I'm a hack and I lie. Uh, and all this stuff should be dismissed. When. My whole beef with MSNBC over the years is that I'm one of those reporters who, like lies, awake at night, worrying about stuff like this.

18:28.14 – 19:05.44

And I'm going to continue to, and I'm going to lose sleep over this vacation, over these little mistakes. Um, while you know huge, enormous things like the Hamilton, 68, uh, go uncorrected on that network, uh, the gall of it is. It has got me in a state of of, um, anger. That's, it's kinda hard to explain, but anyway, I've gone too long. But, uh, it's, it's. It's a gotcha thing. Where they're not engaging in the material, they're being disingenuous about their, the network's own behavior.

19:06.20 – 19:48.38

Um, and you know, they're trying to just attack me personally rather than go after the stuff, uh, or to talk about the stuff, uh. And that that. That's really upsetting because there was a brief moment where the was interesting, where we were talking about. Um, there was a number that 40 of government requests for moderation had been honored. And he seemed to be arguing that that wasn't a big deal. And I was arguing that it was like, that's the kind of conversation that we should have been having, uh. But instead, it was just, you know, one kind of personal thing after another. And and he's nitpicking little things.

19:48.74 – 19:50.78

And um, so, anyway.

1Speaker 1
19:53.84 – 20:24.74

Well, you know, to personalize the story is is is a, um, great rhetorical and narrative technique. To make it sound as though the Twitter files are the work somehow of Matt, rather than a, you know, vast record, which Matt is attempting to sort through and make make meaningful. Um, but uh, what was, what was the business about India? and so on, I mean?

2Speaker 2
20:24.82 – 21:01.66

It took a strange turn. So this all began with with him shooting an email at me saying, like, How come you haven't commented on Elon Musk's, you know, behavior in India? Where, I I guess the particulars of it were, you know, the silencing of some critics of Modi, or or something along those lines. Yeah, my position about all of this all along, um, has been my relationship with Elon Musk, um, I'm not his keeper.

21:01.78 – 21:17.82

He's not mine, uh, I don't have to agree with him about everything, I like him personally. I think what he's done with the Twitter files is enormous public service. I think he's done some cool things about, um, opening the source code to the readers.

21:17.94 – 22:02.66

I think he has a genuine desire to, um, try to engage in some transparency that will, you know, bring back some credibility. Or at least punk pierce the veil of this idea of, um, a single, you know, digitally controlled information network, um. But that doesn't mean I have to agree with him about everything, about his labor practices, about, you know, what else, what he's doing at modern Twitter. And I didn't write anything in the Twitter files that precludes me from turning around and doing a story on Elon. If, if it, if I had to, but at the moment, I don't really feel like it.

22:02.80 – 22:30.36

Um, I'm sort of positively disposed toward the guy. Moreover, you know, I'm working on a story, uh, where the the point of it is to focus on getting this right. Um, and this question, I think he's asked in bad faith because he's asking me to participate in changing the subject away from my own work. And I refuse to do it, I won't do it.

22:31.56 – 22:43.70

Um, and he's like, why won't you criticize Elon Musk? I'm like, I don't know, cause I don't want to like, because you know, it's not a it's not a priority. I don't know the particulars. I mean, like, all of those things are.

1Speaker 1
22:43.70 – 22:44.16

A reason?

22:46.86 – 23:43.98

Elon Musk could be an AX murderer. And it would not change the content of Twitter's archives or the record of their interactions with various organizations. Um, you know, I wasn't the reason that they wanted to break into Daniel Ellsberg's psychiatrist's office. So that the person who had leaked the Pentagon papers could be personally attacked. As though that would somehow change the content, uh, or or, or our view of the content. I mean, um, you know, to step back from the minutia of these Um conflicts you had yesterday? Um, uh. The attempt to personalize all news is not getting us anywhere. Um, most of us don't know Elon Musk, but a lot of us are on Twitter.

23:44.26 – 24:36.24

Most of us don't have maybe even opinions on Elon Musk's opinions on India, let alone opinions of our own. But we do exist in the United States as voters attempting to sort out issues. We do exist as citizens of a state that had various public health policies. In the in the in the Covid moment. That affected us personally and we had to make decisions about whether to get vaccinated, et cetera. Whether this has any bearing whatsoever on Elon Musk's opinions on other countries and their leaderships? Uh, I really doubt, um, but, uh. It's a great way to derail a conversation, it's a great way to, uh uh, attack you by association.

24:37.22 – 24:42.04

Um, suddenly, you are responsible for the opinions of a man you met very recently.

2Speaker 2
24:42.94 – 25:03.48

Right, and and and look, it would be one thing if the Twitter files reports were advertisements for current Twitter or lionized Elon Musk, or said anything about Elon Musk. Frankly, um, they, they didn't. Um, we very conspicuously kind of honed in.

1Speaker 1
25:03.92 – 25:19.02

Almost entirely to a time before he came along. I mean, there was no Elon Musk around or in Twitter at the time. That is that issue, right? And some people would would argue.

2Speaker 2
25:19.12 – 26:26.52

Okay, that's a flaw of of the reports, and what I would say to that is, maybe, I mean, I guess, globally, if you, if you pull back years from now, and all we've got are these stories. But opening up this, these documents, for people to look at. UM, was a unique chance to take a look at the, uh, under the hood of something that had been completely unavailable to the American public beforehand. Um, it's not everything in the world, it's not a comprehensive report about everything that there, you know, people imagine that there's going to be, um, a kind of list of stuff that you can see, um, about every conceivable topic. And then I should have sort of democratically, uh, gamed it out so that you would have, um, you know, a balance that would properly represent everybody in, uh, in the country. But we didn't do it that way.

26:26.56 – 27:00.72

We all kind of, um, at the beginning, we put searches in about stuff we personally were interested in, and we got documents back based on those searches. Um, that were, they were big, but they were still fairly limited. And because I focused in from the start on Twitter's relationship with, uh, the DHS and the FBI, and what that might mean, and how that information flow worked. Um, which is a was a very hard thing to sort out, um, you know, in a couple of three weeks.

27:02.54 – 27:50.92

Uh, you know, we incidentally saw some things along the way, um, but we weren't, we didn't have, we weren't looking at a global picture of everything. That's not how the searches worked again. People will will say, well, um, isn't that a a criticism of these reports? Generally? Because maybe you were only looking at things they wanted you to see? But that's true of every, again, that's true of every single news story that that you deal with, that involves sources giving you that stuff. And um, and the things that we were reporting on, we only did reports on stuff that we could demonstrate were self-contained, true news stories in themselves. Uh, in the file.

27:51.66 – 28:13.20

Right? So, no matter what other context came in, these things were newsworthy. Um, and all of the stuff on the outside. Like, years from now, if you look back, the thing that's going to matter about these stories is where they true or not. Um, and and all this other stuff, why didn't you look at this? why? why aren't you speaking out about that?

28:13.28 – 28:29.16

Why? why aren't you telling us your personal opinions about this? Like, I'm affirmatively not worried about that stuff where I haven't been. I. I, you know, I may have a bit of an attitude problem about saying that out loud, but I, I just don't think that's part.

1Speaker 1
28:29.16 – 28:31.32

Of the equation that I have to worry about right now.

28:33.82 – 29:12.66

Do you have any reason to believe that major news stories, and, um, other topics of concern were suppressed on Twitter? That you don't know about that? Do you have any reason to believe that? Uh, pseudo governmental, governmental and private organizations acting in a concerted fashion, uh, changed the behavior of Twitter that you don't know about. That could absolutely be true. Yeah, how would you go about finding them?

29:12.80 – 29:36.88

For example, if the Republican National Committee, or the Hoover Institute, or Heritage, or one of these conservative organizations had somehow had held sway over Twitter's operations. Um, do you have any reason to believe that such things happened? uh, and do you think that it might be discovered if they did?

2Speaker 2
29:37.08 – 30:01.12

So we tried to find out stuff like that, like, give you an example. We early on identified who was the chief, who were the chief government liaisons at Twitter. So we took those email addresses and we ran them kind of generally, then we ran them against terms like RNC and DNC.

30:01.40 – 30:11.48

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