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Speaker 1: Hello the Internet, and welcome to season two hundred, episode

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Speaker 1: five of Dire Day Introduction of I Heart Radio. It

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Speaker 1: is the season finale of season two hundred, and as promised,

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Speaker 1: we did absolutely nothing to recognize this incredible achievement by

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Speaker 1: the Daily Zigeys team. But shout out to DJ Dani'll

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Speaker 1: shout out to super producers on a hosnie a justin

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Speaker 1: uh dramas, everybody who carrying stump yeah back in that day.

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Speaker 1: So this is a podcast where we take a deep

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Speaker 1: dive into America's shared consciousness. Today is kind of a

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Speaker 1: special format, one where we take a deep dive into

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Speaker 1: America's share consciousness on a specific subject. We did a

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Speaker 1: couple of weeks back, and people seem to really enjoy it.

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Speaker 1: And I feel like this is a subject that you

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Speaker 1: can't even really do a deep dive because we don't

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Speaker 1: know ship about it for the most part. So we'll

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Speaker 1: talking about that. But it is Friday, September three. My

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Speaker 1: name is Jack O'Brien a K and he was blinded

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Speaker 1: by the Zi, chugging do like a choke with Miles,

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Speaker 1: smoking blunts all night. Blinded by the ZI. All right,

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Speaker 1: that's it. That is courtesy of Chauncey Yonders, A fun

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Speaker 1: name to say, Christian uh huh, A little sisty Chrish.

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Speaker 1: And I'm thrilled to be joined as always by my

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Speaker 1: co host, Mr Miles Gray. Miles Gray k Hideo NoHo

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Speaker 1: a k A. Smoke Gray, Old Tawny a k a.

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Speaker 1: The lothario of Lancer Sham lookout North Hollywood because he's here.

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Speaker 1: And just you know, I'm just adding new culturally relevant

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Speaker 1: a k of Lancas, Lancersham. You know, people, if you

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Speaker 1: don't know lakershim, you're not North Hollywood. That's true. And

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Speaker 1: is it good to smoke Gray? I feel like that

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Speaker 1: would be bad weed. Well, you know that's the problem

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Speaker 1: of trying to create puns out of you know, so

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Speaker 1: you could get a little narrow you smoked that ship

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Speaker 1: that makes your vision go black and white and great?

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Speaker 1: All right, well, Miles, we are thrilled to be joined

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Speaker 1: by a nationally recognized expert on cyber security, privacy, identity,

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Speaker 1: that fraud, and personal finance and the host of the

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Speaker 1: podcast With the Hack. He's the former director of the

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Speaker 1: New Jersey Division of Consumer Affairs. He's appeared on just

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Speaker 1: all the TV shows that today show, g m A,

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Speaker 1: all the shows on radio at MPR, ABC News, Bloomberg,

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Speaker 1: and now on our Second Rate podcast. Please welcome the brilliant,

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Speaker 1: the distinguished Adam Webbing. Welcome back. You'll flatter me. Miles.

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Speaker 1: Is great to be with you. Thank you for join.

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Speaker 1: We're thrilled to have you. Adam k Levin, I should

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Speaker 1: have said, is that do you put the middle initiation?

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Speaker 1: That that because there is an author, there is the

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Speaker 1: own of High Times, there are a series of lawyers,

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Speaker 1: and then there's that guy with the E at the

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Speaker 1: end of his name that fronts for some small band

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Speaker 1: called Maroon five people. And I get great restaurant reservations

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Speaker 1: because of that until I show up and it's like, oh,

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Speaker 1: they're like you're lying. You're like, no, I'm not. Just

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Speaker 1: I once I once was divided on the show in

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Speaker 1: San Francisco many years ago, and they said, and now

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Speaker 1: we have Adam Levine from Run five. Then I went, uh, no,

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Speaker 1: it's Adam Levin from Identities at nine on one and

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Speaker 1: they went, no, no, come on, you know you're Adam Levine.

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Speaker 1: I said, no, I'm not. They said, how does it

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Speaker 1: field have groupies? I said, well, there aren't really too

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Speaker 1: many cyberg ruvies. And uh then they said, okay, where

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Speaker 1: are you Where are you speaking to us from right now?

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Speaker 1: I said San Francisco and they said, see you approved

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Speaker 1: our point because Maroon five is appearing tonight in San Francisco.

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Speaker 1: So they oh, it was a radio show, and they like,

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Speaker 1: so was a radio show. So I like freaked out.

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Speaker 1: I hung up call because I wanted to make sure

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Speaker 1: I called the right show. And they went, he's back

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Speaker 1: You see that Levin boy, he just messes around with you,

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Speaker 1: called back in and saying moves like Jagger for them,

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Speaker 1: And I do have moods like Jagger, but yeah, my

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Speaker 1: son's name is Jaker. So hey, you know I'm trying

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Speaker 1: you go. I just like that these hosts so badly

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Speaker 1: needed you to be Atam Levine from my Room five.

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Speaker 1: That nothing, nothing that was presented to them that She's like,

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Speaker 1: oh man, that's great. Man. You sound a little bit different.

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Speaker 1: But what's it like having groupies? Even though you said

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Speaker 1: you're not out yet, are you? Are you sure you're

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Speaker 1: not at a Lavin? Maybe you are, Adam Levin. It

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Speaker 1: just somehow escaped your consciousness. Yeah, They're like, oh, this

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Speaker 1: guy he's such a joker this, Adam. Yeah. Wow, We've

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Speaker 1: got to do that sometime, just intentionally booked the wrong

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Speaker 1: guest and just interview them the entire time as though

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Speaker 1: they're the other person, strong and wrong. You gotta respect it,

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Speaker 1: all right. Well, Adam, we are going to talk to

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Speaker 1: you about cybersecurity, your area of expertise. We are also

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Speaker 1: in the third act going to bring on super producer

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Speaker 1: an A. Hosnier to do a streaming corner about White

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Speaker 1: Lotus now that everybody has had a chance to see it,

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Speaker 1: so we will let you go for that so as

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Speaker 1: not to waste your UM time. I think it's the

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Speaker 1: word I'm looking for. Um. All right, before we get

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Speaker 1: into our dumb questions, we have a set of dumb

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Speaker 1: questions we always ask our guests at the top, starting

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Speaker 1: off with what is something from your search history? Well,

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Speaker 1: of course, the first thing I'm obligated to tell you,

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Speaker 1: as being somebody in cybersecurity, I don't have a search

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Speaker 1: history because I use VPNs. But that being said, where

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Speaker 1: it's something from my search history, it would be things

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Speaker 1: about upcoming movies. Okay, And I was very sad to

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Speaker 1: learn that they have now moved Top Gun Maverick to

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Speaker 1: next year as opposed to this year. But they put

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Speaker 1: Fishing Impossible up to November, so there's some hope. Oh

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Speaker 1: I thought they moved it Mission Impossible till later in

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Speaker 1: the year, so well they they did. They I was

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Speaker 1: thinking about they moved Tom Cruise from oblivion back up

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Speaker 1: to something. So he's coming in November Mission Impossible seven.

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Speaker 1: Not that I'm the pr guy for Mission Impossible seven,

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Speaker 1: but hey, you're really looking forward to Top Gun though.

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Speaker 1: I really was that that show. It's just it's one

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Speaker 1: where if you if you watch the cinematography and listen

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Speaker 1: to music, it's like the planes are actually dancing to

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Speaker 1: the music. Pretty insane. Yeah, I need to actually I

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Speaker 1: need to watch it like that now, Like, hey, you

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Speaker 1: like this fighter jet music video? Top Good? What if

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Speaker 1: something you think is overrated? Home cooking? After being locked

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Speaker 1: in a house during the pandemic for eighteen months? Yeah,

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Speaker 1: you're ready to get out, ready to get out, although

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Speaker 1: we're in Arizona so we're out right. What's the home

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Speaker 1: cooking situation for you? What is it sort of the

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Speaker 1: thing that you kind of made the same like six

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Speaker 1: things or three things, and like it's like that or

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Speaker 1: what you know, give me a glimpse into the into

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Speaker 1: Adam's kitchen. Oh well, Adam's kitchen is basically burnt chicken. Uh.

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Speaker 1: My son loves chicken nuggets. He likes anything chicken related. Not.

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Speaker 1: He's one of the few kids in the world that

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Speaker 1: hates cheese, hates chips, doesn't eat bread. So we we

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Speaker 1: have to do things in a healthy side. My wife

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Speaker 1: is a is a fitness competitor, so clearly you can

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Speaker 1: tell I'm not. But wait, what's so? What kind of

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Speaker 1: fitness competitions? What's the fitness competitors? Bikini five fitness competition

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Speaker 1: And as a matter of fact, coming up this weekend,

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Speaker 1: she's actually competing in Pittsburgh because she is trying to

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Speaker 1: get her probok. Is that a like modeling thing? Is

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Speaker 1: that a fitness as in like they have to do

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Speaker 1: feats of fitness or it's just they have to actually

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Speaker 1: live through a really difficult fitness training regimen as well

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Speaker 1: as a very strict kind of diet where they're everything

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Speaker 1: is weighed and it can only be a certain amount

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Speaker 1: of grams of this and that, and it has to

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Speaker 1: be starch and protein, and it's really tough and she

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Speaker 1: like we go out to restaurants. She she takes her

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Speaker 1: own meal with her and it's a it's a real commitment.

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Speaker 1: That is tough. I still weigh everything, but it's mostly

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Speaker 1: like pounds of cheese. How many pounds of cheese do

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Speaker 1: I want to put on my na I generally tend

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Speaker 1: to weigh myself often have learned that it's like the

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Speaker 1: old thing. Insanity is doing the same things every the

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Speaker 1: same way, except expecting a different result. So I'm insane

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Speaker 1: when it comes to that because there is no effort result.

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Speaker 1: What restaurant are you a fan of chain restaurant? Well,

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Speaker 1: I can tell you that my son is obsessed with

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Speaker 1: Panda Express, who isn't and the other The other night

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Speaker 1: we went to Panda Express and his favorite rapper is

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Speaker 1: post Malone and so he post Alone comes on the

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Speaker 1: radio sings new a song and Jagger is eating his

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Speaker 1: Panda Express in my car. He he pushes the car

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Speaker 1: seat back and he goes, Daddy, life doesn't get any

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Speaker 1: better than Thisanda Express. Yeah, simple, simple, it's the simple things. Yeah,

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Speaker 1: oh man, yeah, Panda Express. Uh. I I had a

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Speaker 1: run where I think my blood type was orange chicken

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Speaker 1: because it I there was like a you know, like

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Speaker 1: when you're a kid, like you'll just you'll get stuck

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Speaker 1: on eating one thing because you think it's like cool,

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Speaker 1: and like that's the thing you gotta do, like that's

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Speaker 1: your identity. And my god, orange chicken was that for me?

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Speaker 1: For sure? Same thing for him. So you guys are

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Speaker 1: kindred spirits. I'm just right there with the youth of America.

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Speaker 1: What if something you think is underrated? Now I have

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Speaker 1: to sort of escape back into my cyber background. But

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Speaker 1: underrated is the whole concept of cyber hygiene, or let's say,

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Speaker 1: password managers are underrated. And the other thing, because I know,

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Speaker 1: you know, you get into very current affairs. Disinformation and

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Speaker 1: misinformation is extremely underrated. That it is entirely dangerous. And

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Speaker 1: I mean the amount of time and effort in Vitrey

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Speaker 1: all that's the cause of misinformation and disinformation, whether it

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Speaker 1: be the election or the pandemic or a whole host

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Speaker 1: of other things, or Democrats eating babies, these kinds of things.

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Speaker 1: I mean, that's kind of disinformation. That that is, it's underrated,

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Speaker 1: it's dangerous. People are not paying enough attention to it,

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Speaker 1: and it could it can cause a great deal of harm.

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Speaker 1: Do you think that we sort of look at it

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Speaker 1: in this way where like when I hear that, I go, yeah,

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Speaker 1: I mean, I know it's bad because I know, like

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Speaker 1: you know, a lot of the lines were drawing to

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Speaker 1: a lot of societal friction is because of misinformation. But

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Speaker 1: what are sort of the ways you think that we're

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Speaker 1: not actually considering aside from the overt examples of how

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Speaker 1: disinformation misinformation is manifesting into Well, the problem is it's

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Speaker 1: like you have to think of it like a blob

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Speaker 1: and it just kind of sucks everything in and you

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Speaker 1: have a significant percentage of the population that will buy

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Speaker 1: into it for whatever reason, and it's almost like it's

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Speaker 1: it's cult culture, right, and uh, it feeds on itself.

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Speaker 1: I mean, if you go back to I won't name

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Speaker 1: the particular media outlet, but you know their definition of

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Speaker 1: a fact is one host says some thing, and then

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Speaker 1: three other people echo it, and then people continue to

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Speaker 1: echo it, and all of a sudden, it bleeds out,

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Speaker 1: It trickles down, as it were, into the community of

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Speaker 1: people who are relatively like minded, and all of a sudden,

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Speaker 1: that's a fact, right, And I mean, yeah, with Fox,

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Speaker 1: like a lot of the talking points that they get

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Speaker 1: actually come from like they're basically field tested in the

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Speaker 1: world of talk radio, and they see like what is

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Speaker 1: resonating with people, and then those like bubble up to yes, yeah,

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Speaker 1: that's it's and and these are the people that say,

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Speaker 1: you know, I can't believe that people follow polls. You

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Speaker 1: have to be a leader, which means you follow, you know,

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Speaker 1: the north star, whatever it is that you believe in,

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Speaker 1: and that's how you lead. And the problem is a

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Speaker 1: lot of these guys are feeding on what they're listening

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Speaker 1: audience wants to hear as a part. And I've noticed

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Speaker 1: some posts that have gone from radio to podcasting, and

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Speaker 1: you'll notice that their political alignment starts to slide over

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Speaker 1: in order to be appealing to the people that they

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Speaker 1: think will most support whatever they say or do. It's

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Speaker 1: like almost this way where before punditry or people who

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Speaker 1: had opinions and and and people that were interested in

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Speaker 1: those people, it was like they were actually just speaking

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Speaker 1: their perspective that they felt was their truth. But now

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Speaker 1: you're right, there's so much triangulating where it's like, well,

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Speaker 1: what is what's an audience gonna want? You know, like,

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Speaker 1: let's I'm not going to consider what I think is

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Speaker 1: ethical or true. It's more about how can I experience

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Speaker 1: success by saying whatever I need to? And then I'm

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Speaker 1: that just accelerates things even further. And I mean, what

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Speaker 1: what an audience want wants is essentially like the now

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Speaker 1: now the number one concern for all media, whether it

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Speaker 1: be social media or not, because like, you have algorithms

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Speaker 1: that are encouraging engagement over like any sort of evaluation

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Speaker 1: of you know, inherent value or truth, and so it's

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Speaker 1: all just a society that is like kind of engineered

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Speaker 1: down to the most cellular level to just create engagement

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Speaker 1: and excitement without any kind of recognition or you know,

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Speaker 1: relationship to to the truth, right mhm. And and the

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Speaker 1: truth changes unfortunately weakly, so therefore it's not a truth,

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Speaker 1: you know. And I try to teach my little guy,

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Speaker 1: is that a fact is a fact, right it? And

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Speaker 1: now there can be interpretations of a fact, there can

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Speaker 1: be opinions of that particular fact, but a fact is

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Speaker 1: a fact. There's no such thing as an alternative fact,

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Speaker 1: you know, Just like when you have people saying, well,

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Speaker 1: the only reason why the government wants us to wear

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Speaker 1: masks is because it wants to control us, and that's

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Speaker 1: how they control us. They mandate that we marry, we

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Speaker 1: wear these things, and it's kind of like no, right, Well,

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Speaker 1: and then they go, well it changed, because the answer

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Speaker 1: is because science has found that things change. Studies have

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Speaker 1: determined that what may have worked at one point isn't

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Speaker 1: working now, or it may not have worked, but because

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Speaker 1: of a combination vaccine and other things, it may be

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Speaker 1: working now. So and it's so frustrating to be in

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Speaker 1: a place where there, you know, again, spirited debate is

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Speaker 1: a wonderful and healthy thing, but when it it disintegrates

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Speaker 1: into name calling and hostility and beating people down for

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Speaker 1: an opinion, that's that's outrageous, and that's that's not kind

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Speaker 1: of the world we want our kids to grow up in,

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Speaker 1: especially when you can't even debate things where both, you know,

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Speaker 1: both are the parties involved in a debate can't agree

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Speaker 1: on what like firm like actual solid ground is for

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Speaker 1: them to even debate upon. Well. I was in Washington

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Speaker 1: a few i guess about three years ago, and we

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Speaker 1: were talking about different pieces of legislation that we're coming up,

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Speaker 1: and I was speaking to the majority staff of one

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Speaker 1: particular House Committee and they said, well, we hope to

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Speaker 1: have something coming up on security in the next year

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Speaker 1: or so. I said, yeah, don't don't rush, guys. And

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Speaker 1: then uh and they said and I said, what about privacy?

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Speaker 1: And they said, now, we can't a bigreue or what

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Speaker 1: privacy is, so there won't be anything on privacy. What

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Speaker 1: do you think the divide is like that you see

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Speaker 1: on what people think privacy is, you know, in terms

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Speaker 1: of how one party might observe it and how another

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Speaker 1: might well, you know, and again I am finding a

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Speaker 1: little bit more a unanimity of opinion about privacy. But

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Speaker 1: you know, we're living in and I know this sounds

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Speaker 1: are welly and almost but we're living in a surveillance economy.

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Speaker 1: Forgetting even the whole issue that Edward Snowdon brought up

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Speaker 1: about a surveillance society is we're living in a surveillance

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Speaker 1: economy where we are surrounded by almost thirty billion Internet

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Speaker 1: of Things devices that are tracking sending information back to

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Speaker 1: manufacturers or sometimes that information is diverted to the bad

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Speaker 1: guys and everything. We just to the point where you

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Speaker 1: feel like you're having a conversation with someone about a

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Speaker 1: subject you've never talked about before. You haven't even searched

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Speaker 1: it on the internet, you think, and all of a sudden,

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Speaker 1: it starts popping up on Facebook ads, so people do,

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Speaker 1: my phone is listening to me? And and the issue

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Speaker 1: is nobody really knows for sure, although I have found

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Speaker 1: several times when all of a sudden, series goes hello

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Speaker 1: and it's like, wait a minute, I didn't call your

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Speaker 1: name right, and so it's it's it's it's very concerning

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Speaker 1: because you really don't know who he is listening or not.

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Speaker 1: I don't know if you remember. I guess it was

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Speaker 1: a couple of years ago where Samsung issued an advisory

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Speaker 1: that you needed to disable the microphone feature of your

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Speaker 1: big screen TV if you didn't want it listening to you,

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Speaker 1: because it's like, oops, it's listening. So you know, in

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Speaker 1: that kind of environment, we have a lot of things

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Speaker 1: that are taking note at a granular level of anything

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Speaker 1: and everything we're looking for. Like remember the story about

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Speaker 1: the father who found out that his child was pregnant

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Speaker 1: because Walmart or either Target or Walmart sent to their

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Speaker 1: house flyers on diapers, and he was going, why would

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Speaker 1: they send stuff about diapers to our house? And it

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Speaker 1: was like he found out that she had been searching, right,

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Speaker 1: and she didn't ask for it to show up, but

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Speaker 1: it did. Like based on your based on your activity,

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Speaker 1: we are presuming you are pregnant. Now, if you really

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Speaker 1: want to mess someone up, use their computer and do

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Speaker 1: something like well, there is there a case that I

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Speaker 1: was involved in a few years ago where two neighbors

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Speaker 1: hated each other and when one neighbor was out of town,

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Speaker 1: the other neighbors snuck overs, sat on his front porch,

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Speaker 1: hacked into his computer and then had that go to

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Speaker 1: child pornography sites and then called the police. And the

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Speaker 1: police came and arrested this poor guy, and it took

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Speaker 1: him six months to convince the police that he didn't

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Speaker 1: do it. One't him, He wasn't searching for that. So,

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Speaker 1: you know, I've I've heard it said that there's like

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Speaker 1: growing pains at the start of every sort of media era,

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Speaker 1: Like newspapers had all sorts of you know, yellow journalism,

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Speaker 1: and then like eventually like they sort of we're able

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Speaker 1: to regulate things. Do you see any version of this

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Speaker 1: where they like we're able to put the genie back

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Speaker 1: in the bottle with regards to like misinformation and like

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Speaker 1: this new kind of social media like online media landscape. Well,

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Speaker 1: the danger you have with that is that people will

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Speaker 1: of course, you will live through the whole cancer culture argument.

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Speaker 1: And you know, you saw the fewer that happened when

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Speaker 1: Trump was taken off all of the social media platforms

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Speaker 1: and claiming that its censorship and uh. And the problem

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Speaker 1: is that when you have these platforms saying you know,

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Speaker 1: this information needs to be fact checked or there's something

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Speaker 1: wrong with this, don't believe it, and then you get

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Speaker 1: people screaming about how the big platforms have made a

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Speaker 1: decision as to the particular kinds of political philosophies they

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Speaker 1: will accept or not accept, and they get caught up

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Speaker 1: in the middle of this. And now you have Congress

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Speaker 1: talking about regulating big tech, and it should be regulated

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Speaker 1: for a variety of reasons. But the problem with misinformation

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Speaker 1: and labeling it as misinformation is you still have a

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Speaker 1: significant percentage of the population that refuses to believe that

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Speaker 1: it is misinformation and disinformation, even when you can show

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Speaker 1: them concrete proof that it's not true. Right, Yeah, that

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Speaker 1: doesn't matter. And you know the perfect example is the election.

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Speaker 1: I mean, you've had sixty courts, you've had every major

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Speaker 1: political figure who has any sense of reason, even people

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Speaker 1: on you know, both sides of the aisle of come

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Speaker 1: down and say it's over. And you still have the

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Speaker 1: cyber ninas in Arizona. And and now there was an

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Speaker 1: issue brought up with the if you know, the conference

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Speaker 1: that was held by the Pillow Man in Wisconsin where

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Speaker 1: it was all about election disinformation relative to they stole

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Speaker 1: the election or not. And they were passing around examples

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Speaker 1: of software that was being used by the voting machine company,

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Speaker 1: and it's voting machine software companies, election system companies, and

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Speaker 1: all of a sudden, now this information about algorithms and

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Speaker 1: other things that were legitimate is now out there, and

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Speaker 1: now they're talking about the fact that they're going to

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Speaker 1: have to replace a lot of the software is simply

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Speaker 1: because it's been exposed by people who were simply trying

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Speaker 1: to discredit the election results with absolutely no knowledge of

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Speaker 1: how no knowledge. Right, All right, let's take a quick

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Speaker 1: break and we'll come right back and continue this conversation,

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Speaker 1: and we're back. Uh, And Adam, you mentioned that the

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Speaker 1: idea of a surveillance economy, that we live in a

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Speaker 1: surveillance economy, which is something we've touched on briefly, but

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Speaker 1: could you speak a little bit more about that, and

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Speaker 1: like how that kind of I mean that the thing

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Speaker 1: that really kind of got me to get my mind

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Speaker 1: around it is that it really robs you of your

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Speaker 1: free will essentially, like you're no longer an autonomous person

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Speaker 1: if you live in a surveillance economy that it knows

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Speaker 1: this much about you, and it's like programming your day basically,

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Speaker 1: and you're you're you're a thousand percent right about that.

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Speaker 1: And the other problem is that you know, people unfortunately

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Speaker 1: are all too willing to fling as much information about

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Speaker 1: themselves as possible out there, whether it's on social media

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Speaker 1: or if they say, you know, you can get great

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Speaker 1: deals if you give us all of your contact information,

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Speaker 1: like the loyalty programs, and they they like feed it

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Speaker 1: by saying, look at how much money you save by

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Speaker 1: having become a member of our loyalty pro you say so.

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Speaker 1: And there have been surveys of people where they will say,

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Speaker 1: I am really really concerned about privacy. But then when

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Speaker 1: they go, but would you be willing to give up

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Speaker 1: your privacy for a really great deal, and a greater

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Speaker 1: percentage of people say, sure, I'd like to do that.

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Speaker 1: You know, you know, in one sense people love customized ads,

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Speaker 1: but in another sense, they don't understand what you're contributing

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Speaker 1: of you in order to put yourself in a position

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Speaker 1: where they will send you customize ads. Right, can you

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Speaker 1: speak about, like what what do they specifically give up?

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Speaker 1: Because I think privacy like has certain connotations, and I

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Speaker 1: think a lot in a lot of ways, we lack

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Speaker 1: the imagination to like see the negative consequences. Can you

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Speaker 1: like speak about that a little bit, like any any

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Speaker 1: instances where it really like was extreme? Oh? Sure. There

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Speaker 1: is a terrific educator in Canada who used to be

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Speaker 1: the Information and Privacy Commissioner for Ontario. Her name is

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Speaker 1: and Cavukian, and she came up with the whole concept

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Speaker 1: of privacy by design, which is that products and services

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Speaker 1: are designed at the core where privacy and security are

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Speaker 1: the core of them, as opposed to all we want

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Speaker 1: to do is make something work and then we'll figure

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Speaker 1: out privacy and security. For instance, originally electronic health records,

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Speaker 1: it was all about let's make it work, as opposed

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Speaker 1: to let's make sure that it's actually private and secure.

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Speaker 1: And the Internet of Things devices for instant. All those devices,

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Speaker 1: whether it's your printer or your computer, your television set,

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Speaker 1: your toaster, your refrigerator, all these things that are connected

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Speaker 1: now to the internet. The issue is, well, let's make

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Speaker 1: it work so it can feedback information, and manufacturers they

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Speaker 1: can make it better, they can update where they need to,

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Speaker 1: and they don't realize that each one of these things

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Speaker 1: is gathering information. There was something a couple of years

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Speaker 1: ago known as the smart mattress cover, where if you

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Speaker 1: put it on your bed, you can tell when you

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Speaker 1: went to sleep, when you woke up. It would be

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Speaker 1: able to turn on the heating or the air conditioning,

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Speaker 1: depending upon where you were in your sleep cycle. It

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Speaker 1: would even be able to ultimately turn on your coffee pot.

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Speaker 1: Now you might say, well that's great, that's convenient, but

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Speaker 1: all of that data in the hands of the wrong

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Speaker 1: person will tell them are you home, are you not?

427
00:26:23,760 --> 00:26:27,239
Speaker 1: Are you sleeping? Are you awake? You know. These are

428
00:26:27,240 --> 00:26:30,400
Speaker 1: the kinds of things and each of these pieces. In

429
00:26:30,520 --> 00:26:34,800
Speaker 1: order to create a successful theft of someone's identity, you

430
00:26:34,880 --> 00:26:39,159
Speaker 1: have to essentially have a mosaic of their lives, and

431
00:26:39,359 --> 00:26:44,719
Speaker 1: each piece of factual data is a a tile in

432
00:26:44,800 --> 00:26:48,159
Speaker 1: that mosaic. So you may not think you're giving up

433
00:26:48,240 --> 00:26:51,240
Speaker 1: much information when you give them your name, your address,

434
00:26:51,280 --> 00:26:56,320
Speaker 1: your cell phone number, your email address. But if you

435
00:26:56,400 --> 00:27:00,000
Speaker 1: think about it, now, your cell phone number is more

436
00:27:00,080 --> 00:27:04,240
Speaker 1: of a personal identifier than even your social Security number.

437
00:27:04,680 --> 00:27:07,200
Speaker 1: I think we have learned that we can trust sleepwear

438
00:27:07,280 --> 00:27:13,400
Speaker 1: providers after Mike Lindell's got nailed it. Miles, you're gonna

439
00:27:13,400 --> 00:27:15,200
Speaker 1: ask a question, I cut you. Oh no, I was

440
00:27:15,240 --> 00:27:18,040
Speaker 1: just in general, right, I mean, you know, I think,

441
00:27:18,160 --> 00:27:21,320
Speaker 1: like most people, I feel that the biggest threat to

442
00:27:21,359 --> 00:27:24,480
Speaker 1: me isn't just a person on the internet, is identity theft.

443
00:27:24,600 --> 00:27:27,040
Speaker 1: So that's like I have a very narrow, sort of

444
00:27:27,080 --> 00:27:30,000
Speaker 1: myopic view of what I think the threats are to me.

445
00:27:30,080 --> 00:27:32,439
Speaker 1: And over the years, I've learned to try and use

446
00:27:32,560 --> 00:27:35,600
Speaker 1: VPNs more because I realized, like, oh, right, like this

447
00:27:35,880 --> 00:27:38,719
Speaker 1: I'm giving up these are that this is the information

448
00:27:38,800 --> 00:27:41,719
Speaker 1: company just want to package and sell and you know,

449
00:27:41,840 --> 00:27:44,679
Speaker 1: make a buck off of me passively. But what are

450
00:27:44,680 --> 00:27:47,520
Speaker 1: the sort of other things that I most people aren't

451
00:27:47,520 --> 00:27:50,760
Speaker 1: really you know, aware of or need to be aware of,

452
00:27:50,800 --> 00:27:53,280
Speaker 1: because I think most people would just say, oh, yeah,

453
00:27:53,440 --> 00:27:56,840
Speaker 1: I I have you know, I have my passwords, different

454
00:27:56,960 --> 00:27:58,840
Speaker 1: and things like that, And only now I feel like,

455
00:27:59,000 --> 00:28:00,920
Speaker 1: maybe in the last six months have I really gotten

456
00:28:00,920 --> 00:28:04,680
Speaker 1: into two factor authentication for certain things. But can you

457
00:28:04,760 --> 00:28:06,959
Speaker 1: kind of just give us, you know, for most of us,

458
00:28:06,960 --> 00:28:09,040
Speaker 1: and I think a lot of our listeners are kind

459
00:28:09,040 --> 00:28:12,680
Speaker 1: of like looking at our own privacy in this very

460
00:28:12,760 --> 00:28:14,760
Speaker 1: narrow way, and I think, you know, I'd love to

461
00:28:14,760 --> 00:28:17,560
Speaker 1: hear sort of what we aren't aware of. Well, I

462
00:28:17,560 --> 00:28:20,080
Speaker 1: think one of the big things people aren't aware of

463
00:28:20,200 --> 00:28:23,480
Speaker 1: is if you ask people, are you worried that you're

464
00:28:23,480 --> 00:28:25,480
Speaker 1: going to get hacked, that you're going to become a

465
00:28:25,560 --> 00:28:27,640
Speaker 1: victim of identity? The majority of the people will tell

466
00:28:27,680 --> 00:28:31,199
Speaker 1: you no, I'm not why because I'm just me. I

467
00:28:31,240 --> 00:28:34,159
Speaker 1: look in the mirror and I see me. Well, you

468
00:28:34,240 --> 00:28:36,080
Speaker 1: may see you when you look in the mirror, but

469
00:28:36,119 --> 00:28:38,440
Speaker 1: when a hacker is looking at you, they see Beyonce

470
00:28:38,600 --> 00:28:42,320
Speaker 1: and jay Z, they or Adam Levine. I mean, you

471
00:28:42,480 --> 00:28:45,320
Speaker 1: got what they want. You've got data, You've got personal

472
00:28:45,360 --> 00:28:48,840
Speaker 1: identifiable information. Or the big thing that a lot of

473
00:28:48,840 --> 00:28:51,680
Speaker 1: people don't really think about is you could be the

474
00:28:51,720 --> 00:28:55,080
Speaker 1: tributary to a larger river, which means it may not

475
00:28:55,280 --> 00:28:58,480
Speaker 1: be about you, but it could be about your spouse,

476
00:28:58,640 --> 00:29:03,719
Speaker 1: your child, Where you work or where you work not

477
00:29:03,920 --> 00:29:08,320
Speaker 1: because of the company, but where you work because that

478
00:29:08,400 --> 00:29:12,600
Speaker 1: company is a service provider or a third party vendor

479
00:29:13,120 --> 00:29:16,400
Speaker 1: to where they really want to get to. So, for example,

480
00:29:16,440 --> 00:29:21,400
Speaker 1: the most iconic breach was Target, and with Target, they

481
00:29:21,440 --> 00:29:23,640
Speaker 1: didn't go in the front door, but hackers did as

482
00:29:23,640 --> 00:29:26,360
Speaker 1: they compromise somebody that worked for the h v A

483
00:29:26,440 --> 00:29:31,280
Speaker 1: C subcontractor of Target and use the access of that

484
00:29:31,520 --> 00:29:35,960
Speaker 1: h v a C subcontractor into the Target systems where

485
00:29:35,960 --> 00:29:38,080
Speaker 1: they then first got port of sale, then they got

486
00:29:38,080 --> 00:29:41,920
Speaker 1: their databases, and then they moved the data out. So

487
00:29:42,080 --> 00:29:44,840
Speaker 1: people have to remember that you are part of an

488
00:29:44,880 --> 00:29:48,400
Speaker 1: ecosystem as it were, and it as You may not

489
00:29:48,560 --> 00:29:51,120
Speaker 1: be the principal thing they're looking for, but you could

490
00:29:51,120 --> 00:29:53,239
Speaker 1: be their gateway to where they really want to go.

491
00:29:54,000 --> 00:29:56,440
Speaker 1: And think about how many people tend, even though they

492
00:29:56,440 --> 00:30:00,120
Speaker 1: may have different passwords, sometimes they tend to use the

493
00:30:00,160 --> 00:30:03,520
Speaker 1: same password in their private life and their work life,

494
00:30:04,400 --> 00:30:07,200
Speaker 1: and which means if you get compromised outside of work,

495
00:30:07,880 --> 00:30:10,160
Speaker 1: that could be the way in. Because what they're looking

496
00:30:10,200 --> 00:30:12,800
Speaker 1: for is credentials. They want to know your user I,

497
00:30:12,880 --> 00:30:15,960
Speaker 1: D and password. And if you think most people's uh,

498
00:30:16,240 --> 00:30:20,280
Speaker 1: use your ideas their email address, and most people's passwords

499
00:30:20,280 --> 00:30:25,080
Speaker 1: are dumb. Password is not a password, And and then

500
00:30:25,080 --> 00:30:27,200
Speaker 1: there were people that no, no no, I have a really

501
00:30:27,360 --> 00:30:30,960
Speaker 1: complex password. Well, what they don't realize is that there's

502
00:30:30,960 --> 00:30:36,000
Speaker 1: a difference between an easily decipherable password like password and

503
00:30:36,040 --> 00:30:40,240
Speaker 1: then a discovered password. And if you think about all

504
00:30:40,280 --> 00:30:43,600
Speaker 1: of the breaches that have occurred for the past few decades,

505
00:30:44,160 --> 00:30:49,000
Speaker 1: then the billions of files containing personal identifiable information in it,

506
00:30:50,120 --> 00:30:52,840
Speaker 1: and the fact that how many sites have you seen?

507
00:30:52,880 --> 00:30:54,880
Speaker 1: If you're just going to have I been pawned, you'll

508
00:30:54,880 --> 00:30:59,800
Speaker 1: see where your email address and passwords have shown up

509
00:31:00,200 --> 00:31:03,960
Speaker 1: based on breaches. You realize that you could have a

510
00:31:04,040 --> 00:31:06,600
Speaker 1: difficult password. But if they put it together with your

511
00:31:06,880 --> 00:31:10,480
Speaker 1: your user I D and then they just start route

512
00:31:10,480 --> 00:31:12,760
Speaker 1: forcing their way into anything they can think of. And

513
00:31:12,960 --> 00:31:16,080
Speaker 1: you'll say, well, why would that affect my work? Everybody

514
00:31:16,120 --> 00:31:19,960
Speaker 1: talks about what they do on LinkedIn. In fact, not

515
00:31:20,040 --> 00:31:22,960
Speaker 1: only that, but not only will they know where you work,

516
00:31:23,440 --> 00:31:26,120
Speaker 1: but LinkedIn makes it so that they can figure out

517
00:31:26,160 --> 00:31:29,800
Speaker 1: everybody else who works with you at work. And that's

518
00:31:29,800 --> 00:31:32,479
Speaker 1: where you get all of these emails coming to people

519
00:31:32,800 --> 00:31:36,040
Speaker 1: that have attachments or links they click on and then

520
00:31:36,080 --> 00:31:39,400
Speaker 1: all of a sudden, malware is into the company, and

521
00:31:39,400 --> 00:31:42,800
Speaker 1: then the company is now at risk or ransomware gets

522
00:31:42,840 --> 00:31:46,600
Speaker 1: in there, which is kind of the new cool, hip,

523
00:31:47,280 --> 00:31:51,880
Speaker 1: extremely profitable thing that hackers are used, right. I I

524
00:31:51,960 --> 00:31:55,520
Speaker 1: do feel like there's something somewhat unprecedented about like what

525
00:31:55,560 --> 00:32:01,920
Speaker 1: we're facing, right because traditionally power dynamic mix are more

526
00:32:01,960 --> 00:32:06,600
Speaker 1: controllable by the large like established powerful entities, like you

527
00:32:06,640 --> 00:32:08,640
Speaker 1: have the most guns, you have the most bombs, you

528
00:32:08,680 --> 00:32:11,920
Speaker 1: control the bomb and gun making equipment, you have the

529
00:32:11,960 --> 00:32:16,280
Speaker 1: most and richest companies, and that's like unfakeable. But now

530
00:32:16,520 --> 00:32:19,760
Speaker 1: a skilled hacker in a basement can like bring a

531
00:32:19,800 --> 00:32:24,360
Speaker 1: massive corporation to their knees because they've you know, grown

532
00:32:24,440 --> 00:32:26,640
Speaker 1: up there. They're like fourteen, and they've grown up with

533
00:32:26,680 --> 00:32:30,600
Speaker 1: a more advanced vocabulary and understanding of you know, coding

534
00:32:30,760 --> 00:32:34,160
Speaker 1: than older people who built their way up two positions.

535
00:32:34,200 --> 00:32:37,240
Speaker 1: The power in the company is there like an alternate

536
00:32:37,280 --> 00:32:40,640
Speaker 1: model that we're headed for where government and corporations are

537
00:32:40,680 --> 00:32:44,080
Speaker 1: better better able to like kind of use their size

538
00:32:44,440 --> 00:32:51,200
Speaker 1: and power to exert control over the field of cybersecurity. Well,

539
00:32:51,240 --> 00:32:55,000
Speaker 1: it is hoped that they can certainly with the recent

540
00:32:55,080 --> 00:32:57,840
Speaker 1: meetings with the President and the and the big tech

541
00:32:57,880 --> 00:33:02,440
Speaker 1: companies and their commitment to really make billions of dollars

542
00:33:02,440 --> 00:33:06,800
Speaker 1: available in the fight. You know, we're making progress, but

543
00:33:06,880 --> 00:33:10,400
Speaker 1: the problems Government hasn't done enough, business hasn't done enough.

544
00:33:10,680 --> 00:33:13,840
Speaker 1: And frankly, we have to admit as consumers, maybe we

545
00:33:13,880 --> 00:33:17,520
Speaker 1: didn't do enough. And for consumers, we didn't ask for it.

546
00:33:17,560 --> 00:33:20,120
Speaker 1: We're not trained for it. We didn't we don't. Half

547
00:33:20,120 --> 00:33:22,280
Speaker 1: the time, we don't even know what the heck to do.

548
00:33:23,080 --> 00:33:26,000
Speaker 1: But as the CEO of Microsoft said a couple of

549
00:33:26,040 --> 00:33:29,480
Speaker 1: years ago, we now have a shared responsibility where we're

550
00:33:29,520 --> 00:33:32,680
Speaker 1: kind of all in this together. And the problem is

551
00:33:32,680 --> 00:33:34,960
Speaker 1: that you can't just limit it even to one country,

552
00:33:35,080 --> 00:33:37,880
Speaker 1: because you know, it's not like you can put a

553
00:33:38,040 --> 00:33:40,760
Speaker 1: dome over something and say, okay, well, the US is

554
00:33:40,800 --> 00:33:43,240
Speaker 1: secure even though the rest of the world is going crazy.

555
00:33:44,080 --> 00:33:47,600
Speaker 1: You have countries out there that there, without question, their

556
00:33:47,680 --> 00:33:51,520
Speaker 1: goal is to put themselves in a position where other

557
00:33:51,640 --> 00:33:55,280
Speaker 1: countries are either beholden to them or they have access

558
00:33:55,320 --> 00:33:58,440
Speaker 1: into power grids and critical infrastructure and things like that.

559
00:33:59,120 --> 00:34:01,080
Speaker 1: So even if you have an agree, for instance, the

560
00:34:01,160 --> 00:34:04,120
Speaker 1: US had an agreement with China that they were only

561
00:34:04,120 --> 00:34:07,840
Speaker 1: going to be specific areas that hacking would be allowed

562
00:34:08,239 --> 00:34:13,400
Speaker 1: to occur. And you know, after Solar wins and the

563
00:34:13,480 --> 00:34:16,800
Speaker 1: Microsoft hacks and things like that, we we realized that

564
00:34:16,800 --> 00:34:19,759
Speaker 1: that one didn't work in anymore. And you can't even

565
00:34:19,840 --> 00:34:23,120
Speaker 1: talk about mutual assured destruction like you could with nuclear

566
00:34:23,160 --> 00:34:27,200
Speaker 1: war because it's never gonna work that way. And the

567
00:34:27,239 --> 00:34:30,919
Speaker 1: reason is because, again, as you said, as Trump used

568
00:34:30,920 --> 00:34:33,120
Speaker 1: to say, the fourteen year old sitting in his mother's

569
00:34:33,160 --> 00:34:36,319
Speaker 1: basement who weighed four hundred pounds on a mattress could

570
00:34:36,320 --> 00:34:39,160
Speaker 1: bring down a company. Recently, you saw a T mobile

571
00:34:39,239 --> 00:34:41,719
Speaker 1: was hacked by someone who just wanted to see if

572
00:34:41,760 --> 00:34:44,680
Speaker 1: they could do it and didn't realize their security was

573
00:34:44,719 --> 00:34:48,320
Speaker 1: so miserable. And the only way we're gonna get better

574
00:34:48,400 --> 00:34:52,320
Speaker 1: is there has to be a national commitment, first here

575
00:34:52,360 --> 00:34:55,600
Speaker 1: and then international that we are really going to beef

576
00:34:55,680 --> 00:34:59,880
Speaker 1: up our cybersecurity and it's going to be a serious priority,

577
00:35:00,400 --> 00:35:03,400
Speaker 1: and it's not just throwing money at it. If you

578
00:35:03,440 --> 00:35:06,719
Speaker 1: don't create a culture of privacy and security from the

579
00:35:06,760 --> 00:35:09,960
Speaker 1: boardroom down to the mail room and back and forth,

580
00:35:10,160 --> 00:35:13,480
Speaker 1: or if home you're working from home from your living

581
00:35:13,560 --> 00:35:15,799
Speaker 1: room to your home office, if you don't have that

582
00:35:15,920 --> 00:35:20,440
Speaker 1: kind of mindset. It's never gonna it's never gonna work, right,

583
00:35:20,800 --> 00:35:24,440
Speaker 1: This is my dumb question. Can Mr Robot happen? But

584
00:35:24,760 --> 00:35:27,320
Speaker 1: is there a version of this where like a really

585
00:35:27,400 --> 00:35:30,120
Speaker 1: wide scale I guess I think for people to get

586
00:35:30,160 --> 00:35:34,759
Speaker 1: their mind around this like something that I think we've

587
00:35:34,760 --> 00:35:36,960
Speaker 1: seen a lot of. Like even even though they are

588
00:35:37,040 --> 00:35:40,280
Speaker 1: large scale attacks that lose lots of people lots of money,

589
00:35:40,600 --> 00:35:47,960
Speaker 1: they're not like these blanket socially kind of destabilizing, debilitating attacks,

590
00:35:48,000 --> 00:35:51,000
Speaker 1: at least not in the United States. Is that still

591
00:35:51,040 --> 00:35:54,400
Speaker 1: something that's kind of looming out there and it's like,

592
00:35:54,520 --> 00:35:59,080
Speaker 1: is that something that's happened to developed countries? Well? Yeah,

593
00:35:59,120 --> 00:36:02,319
Speaker 1: As a matter of fact, the most people would argue

594
00:36:02,360 --> 00:36:06,319
Speaker 1: the most cyber advanced company in the world is Estonia

595
00:36:06,800 --> 00:36:10,160
Speaker 1: because they can take they got taken offline, and in fact,

596
00:36:10,200 --> 00:36:12,080
Speaker 1: we had a conference a few years ago and the

597
00:36:12,120 --> 00:36:16,160
Speaker 1: former president of Estonia came and spoke and they have

598
00:36:16,560 --> 00:36:22,800
Speaker 1: they became a really cyber conscious nation and a cyber

599
00:36:22,920 --> 00:36:27,640
Speaker 1: dedicated nation after that incident, and you know, arguably everything

600
00:36:27,680 --> 00:36:31,839
Speaker 1: they do is really top flight cyber security related within

601
00:36:31,880 --> 00:36:35,960
Speaker 1: the country. So it almost is going to take that

602
00:36:36,040 --> 00:36:39,000
Speaker 1: kind of effort because it is it is scary. Now

603
00:36:39,400 --> 00:36:41,879
Speaker 1: if you want to talk about things that consumers can

604
00:36:41,880 --> 00:36:44,560
Speaker 1: do to better protect themselves or businesses can do, you know,

605
00:36:44,719 --> 00:36:46,560
Speaker 1: happy to do that. I don't know how much time

606
00:36:46,800 --> 00:36:49,919
Speaker 1: that we have for that, but it really also has

607
00:36:50,680 --> 00:36:54,520
Speaker 1: adopting a philosophy and it really works for everybody of

608
00:36:54,680 --> 00:37:00,160
Speaker 1: what I call the three ms because breaches app I'm

609
00:37:00,200 --> 00:37:03,520
Speaker 1: the third certainty and life behind death and taxes. That's

610
00:37:03,560 --> 00:37:06,200
Speaker 1: never going to change. So the issue isn't if but

611
00:37:06,400 --> 00:37:09,759
Speaker 1: when a company is going to get attacked, or a

612
00:37:09,840 --> 00:37:12,880
Speaker 1: consumer is going to suffer a problem, or government agencies

613
00:37:12,920 --> 00:37:16,600
Speaker 1: are going to hit But it's all about minimizing your

614
00:37:16,680 --> 00:37:21,680
Speaker 1: risk of exposure, reducing your attackable surface, monitoring so you

615
00:37:21,719 --> 00:37:24,719
Speaker 1: know as quickly as possible that you have a problem,

616
00:37:24,800 --> 00:37:28,520
Speaker 1: and then managing the damage, having a plan to manage

617
00:37:28,520 --> 00:37:31,560
Speaker 1: the damage. And there are there are things that people

618
00:37:31,600 --> 00:37:35,920
Speaker 1: can absolutely do at the government level, the corporate level,

619
00:37:36,160 --> 00:37:39,120
Speaker 1: and the consumer level, but they have to be kind

620
00:37:39,120 --> 00:37:42,400
Speaker 1: of willing to do it. Is this sort of in

621
00:37:42,440 --> 00:37:47,399
Speaker 1: action around modernizing our ability to defend against cybersecurity kind

622
00:37:47,400 --> 00:37:49,520
Speaker 1: of like just this very American thing that we see

623
00:37:49,560 --> 00:37:51,640
Speaker 1: where it's like, well, we'll do something when it gets

624
00:37:51,680 --> 00:37:54,920
Speaker 1: absolutely horrific enough for us to do something. But we

625
00:37:54,960 --> 00:37:57,920
Speaker 1: can weather these smaller things, even though it's a problem

626
00:37:57,960 --> 00:38:00,080
Speaker 1: that many people are saying we need to be aware of.

627
00:38:00,520 --> 00:38:02,839
Speaker 1: Is that kind of just we're on that similar path

628
00:38:02,920 --> 00:38:05,799
Speaker 1: as it relates to cybersecurity, because I know, yeah, like

629
00:38:05,920 --> 00:38:10,200
Speaker 1: their potential for these kinds of wide scale cyber attacks

630
00:38:10,200 --> 00:38:13,160
Speaker 1: and things seem like they're just over the horizon. But

631
00:38:13,440 --> 00:38:15,879
Speaker 1: at the same time, like you're saying, like you'll talk

632
00:38:15,920 --> 00:38:18,560
Speaker 1: to people in d C and they're like, yeah, yeah, yeah,

633
00:38:18,600 --> 00:38:21,319
Speaker 1: we're gonna we'll get to that. Yeah, that's that's that's

634
00:38:21,320 --> 00:38:23,319
Speaker 1: on the list. Is it just sort of they're just

635
00:38:23,360 --> 00:38:26,279
Speaker 1: not connected to the real, true sense of urgency. I

636
00:38:26,320 --> 00:38:28,879
Speaker 1: think they are becoming more connected to the truth sense

637
00:38:28,920 --> 00:38:34,640
Speaker 1: of urgency, certainly as insurance rates for cyb reliability insurance skyrocket,

638
00:38:34,920 --> 00:38:38,160
Speaker 1: as insurance companies in some cases are now pulling away

639
00:38:38,200 --> 00:38:43,040
Speaker 1: from reimbursing companies that have been hit with ransomware that

640
00:38:43,080 --> 00:38:46,000
Speaker 1: even to get cyber reliability insurance, you you have to

641
00:38:46,040 --> 00:38:49,000
Speaker 1: go through a living hell in terms of disclosures, and

642
00:38:49,239 --> 00:38:52,000
Speaker 1: you have to mean it. And then of course, in

643
00:38:52,040 --> 00:38:55,400
Speaker 1: addition to whole regulatory issue. You have to face the

644
00:38:55,480 --> 00:39:01,200
Speaker 1: ultimate regulators, the American economy, class action lawsuit attorneys. So, uh,

645
00:39:01,239 --> 00:39:04,640
Speaker 1: you know, I think the attitudes are changing. Cybersecurity is

646
00:39:04,680 --> 00:39:08,719
Speaker 1: becoming more a front burner issue. I mean with the

647
00:39:08,760 --> 00:39:12,960
Speaker 1: conferences they had in Washington member the last administration, they

648
00:39:13,000 --> 00:39:16,640
Speaker 1: talked a good game about protecting but at the same

649
00:39:16,680 --> 00:39:19,080
Speaker 1: point they got rid of the cyber coordinator in the

650
00:39:19,080 --> 00:39:22,120
Speaker 1: White House. That there's a lot of things that they

651
00:39:22,440 --> 00:39:25,080
Speaker 1: said that they were going to do that they didn't do.

652
00:39:25,760 --> 00:39:27,719
Speaker 1: And then you had people within the government that took

653
00:39:27,760 --> 00:39:30,200
Speaker 1: their own initiative, like Chris Krebs, who ended up then

654
00:39:30,200 --> 00:39:33,759
Speaker 1: getting fired after the election because he said it was

655
00:39:33,800 --> 00:39:37,440
Speaker 1: a fair election. And they worked really hard, working with

656
00:39:37,520 --> 00:39:39,799
Speaker 1: the States to do everything they could to make sure

657
00:39:39,840 --> 00:39:42,480
Speaker 1: that it was going to be a good and fair election.

658
00:39:42,560 --> 00:39:47,480
Speaker 1: But meanwhile, while everybody was focused on let's protect American

659
00:39:47,520 --> 00:39:50,440
Speaker 1: democracy by making sure we don't have cyber issues with

660
00:39:50,480 --> 00:39:54,440
Speaker 1: the election, the Russian hackers and the Chinese hackers were

661
00:39:54,480 --> 00:39:57,680
Speaker 1: focusing on getting into solar winds, and so it's like,

662
00:39:58,320 --> 00:40:01,799
Speaker 1: look there, so we can go over year and we

663
00:40:01,840 --> 00:40:07,080
Speaker 1: have to understand these are very creative, very sophisticated extremely

664
00:40:07,160 --> 00:40:12,160
Speaker 1: persistent people who are fighting us. And you know, we

665
00:40:12,239 --> 00:40:14,719
Speaker 1: used to we used to do election security the kind

666
00:40:14,800 --> 00:40:18,080
Speaker 1: to company as the sole part of it. And one

667
00:40:18,080 --> 00:40:21,240
Speaker 1: of the areas we would go into smaller states, rural

668
00:40:21,280 --> 00:40:27,160
Speaker 1: counties and say, you are facing off against Russia, and

669
00:40:27,200 --> 00:40:29,799
Speaker 1: you have a county that may have one tech guy

670
00:40:30,960 --> 00:40:34,600
Speaker 1: and and a few people are a little bit about technology,

671
00:40:34,640 --> 00:40:40,640
Speaker 1: but and they're facing off against a incredibly well resourced

672
00:40:41,360 --> 00:40:44,800
Speaker 1: state sponsored hacker whose entire goal is I'm going to

673
00:40:44,880 --> 00:40:48,000
Speaker 1: get into their election system. And so you know that

674
00:40:48,000 --> 00:40:51,239
Speaker 1: that is where you get the lack of balance in

675
00:40:51,320 --> 00:40:54,120
Speaker 1: all of this. And that's why people always have to

676
00:40:54,200 --> 00:40:58,480
Speaker 1: keep in mind we have day jobs. We raise a family,

677
00:40:58,719 --> 00:41:02,520
Speaker 1: were involved in government, we're going to school, were involved

678
00:41:02,560 --> 00:41:06,919
Speaker 1: in philothropic activities. But to these other guys, we are

679
00:41:07,040 --> 00:41:12,839
Speaker 1: their day job, right mm hmmm. We being like the

680
00:41:12,880 --> 00:41:16,600
Speaker 1: cybersecurity community like well, the cyber comunity, you know, and

681
00:41:16,680 --> 00:41:18,760
Speaker 1: we have people who are very focused in the cyber

682
00:41:18,800 --> 00:41:23,200
Speaker 1: security community. And and remember we are very open as

683
00:41:23,200 --> 00:41:25,960
Speaker 1: to what we talk about in this country because we

684
00:41:26,000 --> 00:41:29,560
Speaker 1: have we don't have a national breach notification law, but

685
00:41:29,640 --> 00:41:33,680
Speaker 1: we have fifty four separate jurisdictions that have their own

686
00:41:33,840 --> 00:41:40,800
Speaker 1: laws that impact cybersecurity and cybercurity. Reporting what we're doing

687
00:41:41,320 --> 00:41:46,440
Speaker 1: to China, Russia, Iran other countries like that, you know,

688
00:41:46,680 --> 00:41:48,600
Speaker 1: we're not going to hear because they're not going to

689
00:41:48,719 --> 00:41:51,880
Speaker 1: talk about it for sure, and we're not going to

690
00:41:51,960 --> 00:41:55,200
Speaker 1: talk about what we're doing to them. But I believe

691
00:41:55,280 --> 00:41:57,400
Speaker 1: that a lot of what's going on here is going

692
00:41:57,480 --> 00:42:03,560
Speaker 1: on there. And the US is a great offensive cybersecurity

693
00:42:03,600 --> 00:42:07,839
Speaker 1: country when it comes to any cybersecurity weaponry, as it were,

694
00:42:08,520 --> 00:42:13,480
Speaker 1: whereas on cybersecurity defense, we're not that good yet m hm.

695
00:42:14,000 --> 00:42:16,520
Speaker 1: And the same can be said of Russia and China.

696
00:42:17,160 --> 00:42:19,920
Speaker 1: One of the few countries that is really top flight

697
00:42:20,040 --> 00:42:24,160
Speaker 1: both offensive defensive is Israel because it has to also

698
00:42:24,239 --> 00:42:26,400
Speaker 1: do with the concept of the Iron Dome, which they

699
00:42:26,440 --> 00:42:29,560
Speaker 1: needed because they can't patrol they don't have enough people

700
00:42:29,600 --> 00:42:33,040
Speaker 1: to patrol their borders, and they're surrounded by nations that

701
00:42:33,080 --> 00:42:36,960
Speaker 1: are not necessarily their best friends. So interesting. Well, Adam,

702
00:42:37,040 --> 00:42:40,359
Speaker 1: I feel like we could talk to you about this

703
00:42:40,560 --> 00:42:44,080
Speaker 1: all day, but we definitely should have you back to

704
00:42:44,160 --> 00:42:48,520
Speaker 1: kind of continue this conversation. It's been very, very fascinating

705
00:42:48,880 --> 00:42:51,560
Speaker 1: talking to you about it. Where can people find you

706
00:42:51,640 --> 00:42:56,839
Speaker 1: and follow you. Okay, Well, Adam Levin dot com is

707
00:42:56,880 --> 00:42:59,919
Speaker 1: our our website, which is a sort of destination fight

708
00:43:00,280 --> 00:43:04,200
Speaker 1: site for cybersecurity issues. And also on the podcast What

709
00:43:04,280 --> 00:43:07,040
Speaker 1: the Heck with Adam Levin, which is available anywhere that

710
00:43:07,160 --> 00:43:10,560
Speaker 1: people get podcasts, and we'd like to have you guys

711
00:43:10,640 --> 00:43:12,520
Speaker 1: come on too and we can have some fun with

712
00:43:12,520 --> 00:43:14,839
Speaker 1: you on that. We actually try to take a little

713
00:43:14,840 --> 00:43:19,960
Speaker 1: bit of a lighthearted look. Yeah. Yeah, I mean, as

714
00:43:20,000 --> 00:43:24,279
Speaker 1: someone who was pounded in the Equifax leaks and uh

715
00:43:24,560 --> 00:43:27,560
Speaker 1: and and as a Team Mobile customer, I'm constantly what

716
00:43:28,280 --> 00:43:32,040
Speaker 1: in the world am I like nowhere? I'm like, everything

717
00:43:32,080 --> 00:43:35,280
Speaker 1: I'm I'm been attached to seems to be so vulnerable.

718
00:43:35,360 --> 00:43:38,040
Speaker 1: One thing I meant to ask the earlier. We just

719
00:43:38,080 --> 00:43:39,800
Speaker 1: don't have a lot of time. But like I feel

720
00:43:39,840 --> 00:43:43,040
Speaker 1: like the as we've learned more about like all the

721
00:43:43,880 --> 00:43:48,440
Speaker 1: you know, cookies and tracking software and the like surveillance economy.

722
00:43:48,480 --> 00:43:50,719
Speaker 1: Like the only change I've seen is that now when

723
00:43:50,719 --> 00:43:52,600
Speaker 1: I go to a website, they like make me a

724
00:43:52,680 --> 00:43:57,359
Speaker 1: great like take their cookies. They're like, you, this site

725
00:43:57,400 --> 00:44:00,560
Speaker 1: uses cookies. But if I want to use the internet,

726
00:44:00,600 --> 00:44:02,880
Speaker 1: like I have to agree to it. And it's just

727
00:44:02,960 --> 00:44:07,759
Speaker 1: like basically we got like end user agreements in exchange

728
00:44:07,840 --> 00:44:11,120
Speaker 1: for you know, our knowledge that we're being fucked. Is

729
00:44:11,160 --> 00:44:14,560
Speaker 1: there a solution there? Well, First of all, the reason

730
00:44:14,600 --> 00:44:18,120
Speaker 1: why you see all of these do you accept or

731
00:44:18,200 --> 00:44:22,440
Speaker 1: reject cookies? It's because of the g d p R,

732
00:44:22,880 --> 00:44:25,680
Speaker 1: which is the privacy law that was passed in the

733
00:44:25,719 --> 00:44:30,160
Speaker 1: EU that was for its time actually instilled the most

734
00:44:30,160 --> 00:44:34,520
Speaker 1: advanced law. And now you have the California Consumer Protection Law,

735
00:44:34,680 --> 00:44:39,640
Speaker 1: which is their privacy law. You have a law in Colorado, Virginia,

736
00:44:39,640 --> 00:44:42,960
Speaker 1: and New York that are very you know, forward thinking,

737
00:44:43,040 --> 00:44:46,680
Speaker 1: tough laws, and as a result of that, they're requiring

738
00:44:47,360 --> 00:44:51,839
Speaker 1: anyone who's gathering data in any form to actually make

739
00:44:51,960 --> 00:44:56,279
Speaker 1: disclosures so that people are aware that they're their information

740
00:44:56,640 --> 00:45:00,920
Speaker 1: is let's say, more exposed than they originally thought. And uh,

741
00:45:01,080 --> 00:45:04,480
Speaker 1: it's part of you know, you should know what information

742
00:45:04,600 --> 00:45:08,800
Speaker 1: they're asking for. You should also have the right, which

743
00:45:08,840 --> 00:45:10,680
Speaker 1: is you know, the goal of some of the more

744
00:45:10,719 --> 00:45:15,239
Speaker 1: advanced privacy laws to the right to be forgotten, where

745
00:45:15,239 --> 00:45:20,319
Speaker 1: you can actually delete information from websites. That's what I

746
00:45:20,440 --> 00:45:23,120
Speaker 1: want is like an ability to like toggle like yes

747
00:45:23,239 --> 00:45:26,439
Speaker 1: or no to cookies, but like the version I seem

748
00:45:26,520 --> 00:45:28,719
Speaker 1: to see a lot is just well, you can come

749
00:45:28,760 --> 00:45:31,120
Speaker 1: to this website if you accept that we use cookies.

750
00:45:31,320 --> 00:45:34,279
Speaker 1: Otherwise like get out of here and well, or they'll

751
00:45:34,320 --> 00:45:36,760
Speaker 1: say you can come here, but you know, don't expect

752
00:45:36,800 --> 00:45:38,399
Speaker 1: when you come back that we're going to know who

753
00:45:38,440 --> 00:45:40,440
Speaker 1: you are. And so it's gonna be you're gonna be

754
00:45:40,520 --> 00:45:43,279
Speaker 1: like a guest every time you come. And some of

755
00:45:43,320 --> 00:45:46,440
Speaker 1: them absolutely prefer you not come unless they can suck

756
00:45:46,480 --> 00:45:50,080
Speaker 1: every piece of information out of you they can. Yeah,

757
00:45:50,200 --> 00:45:53,080
Speaker 1: so you know that that is at least a change

758
00:45:53,200 --> 00:45:55,920
Speaker 1: that is trying to at least make people more aware

759
00:45:56,040 --> 00:45:59,120
Speaker 1: because for so long again, yeah, I'll do whatever you

760
00:45:59,120 --> 00:46:02,520
Speaker 1: want as long as you give me what I want. Anyways,

761
00:46:02,520 --> 00:46:04,160
Speaker 1: like I said, we can we can talk about this

762
00:46:04,239 --> 00:46:07,520
Speaker 1: all day and we will definitely have to have you back,

763
00:46:07,719 --> 00:46:11,400
Speaker 1: but thank you so much for joining us, and we

764
00:46:11,520 --> 00:46:14,200
Speaker 1: will be back in a moment with super Producer on

765
00:46:14,320 --> 00:46:31,320
Speaker 1: a Hosnie streaming corner. And we're back, and Adam Levin

766
00:46:31,560 --> 00:46:40,040
Speaker 1: has been replaced by super Producer on a Hosni streaming corner. Assholes,

767
00:46:40,640 --> 00:46:44,319
Speaker 1: open your ears. Sorry, Yeah, hard to pivot from that

768
00:46:44,520 --> 00:46:48,000
Speaker 1: very serious conversation about security and privacy and now, the

769
00:46:48,239 --> 00:46:51,080
Speaker 1: pressing issues of our time, the way we distract ourselves

770
00:46:51,080 --> 00:46:56,560
Speaker 1: healthily from that television TV. Although this I feel like

771
00:46:56,600 --> 00:47:00,200
Speaker 1: this show really nailed something about the zeitgeist or just

772
00:47:00,239 --> 00:47:04,160
Speaker 1: I guess America. Oh White Lotus. Yeah, White Lotus show

773
00:47:04,320 --> 00:47:08,560
Speaker 1: definitely always is always nailing as I guess. Hello, Anna Hosnie,

774
00:47:09,400 --> 00:47:12,400
Speaker 1: thank you for joining us. What why why do we

775
00:47:12,440 --> 00:47:15,320
Speaker 1: watch White Lotus? What struck you when you first said

776
00:47:15,400 --> 00:47:18,040
Speaker 1: why are you watching it? What was partning? Well? Okay,

777
00:47:18,080 --> 00:47:20,880
Speaker 1: first I have to do my streaming corner theme song. Okay,

778
00:47:21,000 --> 00:47:28,680
Speaker 1: go go three six seven ten bati d d dude,

779
00:47:31,040 --> 00:47:37,759
Speaker 1: it's a stream in corner. Do do, dude, it's a

780
00:47:37,800 --> 00:47:45,400
Speaker 1: stream in corner. You didn't watch White Lotus, did you?

781
00:47:45,400 --> 00:48:00,280
Speaker 1: You didn't watch it happens last time when you like ill?

782
00:48:00,400 --> 00:48:02,399
Speaker 1: So I missed all that. I was doing my theme song.

783
00:48:04,000 --> 00:48:07,040
Speaker 1: We were just saying that you have delaying because you

784
00:48:07,040 --> 00:48:09,879
Speaker 1: didn't actually watch What Lotus when we asked you about

785
00:48:09,920 --> 00:48:16,960
Speaker 1: Godfather too. Anyway, have ever been more offended than people

786
00:48:16,960 --> 00:48:19,680
Speaker 1: just speaking through my forty five minutes stream of corner

787
00:48:19,719 --> 00:48:22,400
Speaker 1: And we were just so confused. We didn't want to

788
00:48:22,440 --> 00:48:25,360
Speaker 1: get scammed again. No, I was just Um, I was

789
00:48:25,600 --> 00:48:28,719
Speaker 1: what is it when you're like pulling from someone? I

790
00:48:28,719 --> 00:48:35,640
Speaker 1: was pulling my inner Kim Cantrell, Um, I guess before

791
00:48:35,680 --> 00:48:38,440
Speaker 1: we get into the just the talk, I'll just I

792
00:48:38,480 --> 00:48:41,160
Speaker 1: will read what the description of White Lotus is, so

793
00:48:41,200 --> 00:48:43,200
Speaker 1: if you haven't seen it, you understand what we're gonna

794
00:48:43,200 --> 00:48:45,640
Speaker 1: be ranting and raving about. They say from Mike White,

795
00:48:46,120 --> 00:48:48,920
Speaker 1: the creator of HBOS in Lighten The White Lotus is

796
00:48:48,960 --> 00:48:51,960
Speaker 1: a sharp social satire following the exploits of verious employees

797
00:48:51,960 --> 00:48:54,319
Speaker 1: and guests at an exclusive Hawaiian resort over the span

798
00:48:54,360 --> 00:48:57,840
Speaker 1: of one highly transformative week. As darker dynamics emerge with

799
00:48:57,880 --> 00:49:01,720
Speaker 1: each pressing day, this biting, sick episode series gradually reveals

800
00:49:01,719 --> 00:49:05,600
Speaker 1: the complex truths of the seemingly picture perfect travelers, cheerful

801
00:49:05,640 --> 00:49:10,759
Speaker 1: hotel employees, and idyllic locale itself. There it is, and

802
00:49:10,920 --> 00:49:14,400
Speaker 1: another interesting fact, Mike White did in fact go to

803
00:49:14,600 --> 00:49:18,800
Speaker 1: high school or college. I forget with my friend Laurie's wife.

804
00:49:19,800 --> 00:49:23,120
Speaker 1: Really okay to me? That the other thing? We guess

805
00:49:23,280 --> 00:49:26,960
Speaker 1: now we're cooking. He also did he write? He wrote

806
00:49:27,000 --> 00:49:32,360
Speaker 1: School of Rock. He's enlightened with Laura Dern. Yeah, yeah,

807
00:49:32,400 --> 00:49:34,960
Speaker 1: but also School of Rock he's okay, stop bringing up

808
00:49:34,960 --> 00:49:40,320
Speaker 1: School of Rock every time. But interesting kind of varied career.

809
00:49:40,480 --> 00:49:44,520
Speaker 1: But this is I don't know, very kind of keenly

810
00:49:45,120 --> 00:49:50,959
Speaker 1: just sharply observed about the one percent, I guess, and

811
00:49:51,160 --> 00:49:56,160
Speaker 1: uh and their relationship to themselves and their world and

812
00:49:56,200 --> 00:50:01,080
Speaker 1: there their leisure, their leisure. I don't know. It was

813
00:50:01,760 --> 00:50:03,239
Speaker 1: how do we get into this? What do we? What

814
00:50:03,280 --> 00:50:06,160
Speaker 1: do we? I mean what I just say so, like,

815
00:50:06,200 --> 00:50:08,000
Speaker 1: I know there's been a lot of think pieces on

816
00:50:08,040 --> 00:50:10,000
Speaker 1: it and all that, but you know, I'm not really

817
00:50:10,040 --> 00:50:12,600
Speaker 1: one that thinks too hard. So I just thought it

818
00:50:12,640 --> 00:50:16,279
Speaker 1: was just like a fun dark comedy that just like

819
00:50:16,520 --> 00:50:20,399
Speaker 1: kind of you know, show that rich white people are

820
00:50:20,480 --> 00:50:24,200
Speaker 1: just like vapid idiot losers. And that's just kind of

821
00:50:24,280 --> 00:50:28,920
Speaker 1: like funny to me. Yea some woman like I'm really simple,

822
00:50:29,000 --> 00:50:31,879
Speaker 1: Like if you're like, look at this rich white woman,

823
00:50:32,080 --> 00:50:34,839
Speaker 1: like she doesn't get that like white men are over,

824
00:50:34,920 --> 00:50:39,759
Speaker 1: I'm like, it's um so like that's all it really

825
00:50:39,800 --> 00:50:41,880
Speaker 1: takes for me. Yeah. Well, I think because a lot

826
00:50:41,920 --> 00:50:44,399
Speaker 1: of people I felt like we're mad because they were

827
00:50:44,440 --> 00:50:46,880
Speaker 1: expecting this show to have some kind of really biting

828
00:50:47,880 --> 00:50:51,960
Speaker 1: sort of commentary on what it was. And I get that,

829
00:50:52,040 --> 00:50:54,640
Speaker 1: maybe you thought because it was like adjacent to something

830
00:50:54,719 --> 00:50:58,080
Speaker 1: really interesting, because throughout this show, like there is this

831
00:50:58,200 --> 00:51:01,640
Speaker 1: juxtaposition of like under standing like what life is like

832
00:51:01,760 --> 00:51:05,560
Speaker 1: for the people of Hawaii, like the relationship that it

833
00:51:05,560 --> 00:51:08,839
Speaker 1: has to the mainland, and like just how like sort

834
00:51:08,840 --> 00:51:11,920
Speaker 1: of the cast system that even annexation has created in

835
00:51:11,920 --> 00:51:15,799
Speaker 1: that sense. But there's also like there's just yeah, this

836
00:51:15,920 --> 00:51:18,520
Speaker 1: dark comedy aspect about it, which just sort of makes

837
00:51:18,560 --> 00:51:20,880
Speaker 1: it palatable. And I in the beginning, I thought maybe

838
00:51:20,880 --> 00:51:23,480
Speaker 1: this was going to be a broader commentary on something

839
00:51:23,560 --> 00:51:25,560
Speaker 1: like that, and in the end it just was really

840
00:51:25,600 --> 00:51:28,920
Speaker 1: just sort of this very more narrowly focused dark comedy.

841
00:51:29,080 --> 00:51:30,959
Speaker 1: So I didn't mind that it didn't have that, because

842
00:51:30,960 --> 00:51:33,759
Speaker 1: I also it was kind of one a very American

843
00:51:33,800 --> 00:51:36,920
Speaker 1: thing where like the show almost was able to like

844
00:51:37,080 --> 00:51:40,880
Speaker 1: observe an issue or like a controversy, but not quite

845
00:51:40,920 --> 00:51:43,400
Speaker 1: have a reckoning with it. So it's just sort of like, damn,

846
00:51:43,440 --> 00:51:46,520
Speaker 1: that's sucking a while. This sort of the vible was

847
00:51:46,560 --> 00:51:48,640
Speaker 1: that the show rather than like, this is why we

848
00:51:48,680 --> 00:51:51,240
Speaker 1: need to really seriously talk about like what it means

849
00:51:51,280 --> 00:51:54,880
Speaker 1: to have annexed the Kingdom of Hawaii. What you know,

850
00:51:54,960 --> 00:51:56,799
Speaker 1: like all these other things like what it means for

851
00:51:56,880 --> 00:51:59,040
Speaker 1: that these power dynamics among all these other people, but

852
00:51:59,120 --> 00:52:04,040
Speaker 1: really it was just a mess Occupy Hawaii, Yeah, I know.

853
00:52:04,200 --> 00:52:06,400
Speaker 1: And and the kind of the great part about it

854
00:52:06,520 --> 00:52:09,640
Speaker 1: is that, like it just I kind of liked It's

855
00:52:09,680 --> 00:52:12,480
Speaker 1: like you didn't really try, and I'd rather you just

856
00:52:12,520 --> 00:52:15,920
Speaker 1: didn't try, Like you created humor and the fact that

857
00:52:16,000 --> 00:52:18,399
Speaker 1: like these people were really shitty and you're pointing it out,

858
00:52:18,440 --> 00:52:21,120
Speaker 1: but like they didn't really make that much of an effort,

859
00:52:21,200 --> 00:52:23,520
Speaker 1: and it's like I'd rather than not make an effort

860
00:52:23,520 --> 00:52:25,920
Speaker 1: than make like a half assed effort something, you know

861
00:52:25,920 --> 00:52:28,759
Speaker 1: what I mean. Trying to be like deep with it,

862
00:52:29,040 --> 00:52:32,800
Speaker 1: but I feel like the commentary was all there like that.

863
00:52:33,040 --> 00:52:36,680
Speaker 1: It definitely didn't end in a satisfying way. But the

864
00:52:36,719 --> 00:52:40,879
Speaker 1: way it ended was that the people who you've kind

865
00:52:40,880 --> 00:52:43,680
Speaker 1: of just been disgusted by the whole time because they

866
00:52:43,719 --> 00:52:47,680
Speaker 1: are just myopically just obsessed with their own privilege and

867
00:52:47,719 --> 00:52:51,359
Speaker 1: like preserving the illusion that they deserve like everything, and

868
00:52:52,000 --> 00:52:56,080
Speaker 1: like fighting anybody who's in the service and service positions,

869
00:52:56,120 --> 00:52:58,080
Speaker 1: like they just get away with it and don't learn

870
00:52:58,120 --> 00:53:02,799
Speaker 1: their lesson. And that's just like that that is how

871
00:53:02,840 --> 00:53:05,440
Speaker 1: it works. Yeah, but didn't that all feel like just

872
00:53:05,560 --> 00:53:08,319
Speaker 1: in the writing like very surface level, Like there were

873
00:53:08,320 --> 00:53:10,000
Speaker 1: a lot of things that they just touched on that

874
00:53:10,040 --> 00:53:12,759
Speaker 1: they very quickly, very like it was just like and

875
00:53:12,760 --> 00:53:16,000
Speaker 1: then they like you know, moved on. Like I feel like, yeah,

876
00:53:16,040 --> 00:53:19,960
Speaker 1: you know, they'd be like this guy hates the manager

877
00:53:20,080 --> 00:53:23,960
Speaker 1: or whatever. Jake Lacey's character Shane hates Armand. Yeah, Shane

878
00:53:23,960 --> 00:53:26,480
Speaker 1: hates Armand And it's like okay, but we're not really

879
00:53:26,480 --> 00:53:30,200
Speaker 1: going to explain, like explore further like what the funk

880
00:53:30,320 --> 00:53:32,600
Speaker 1: is wrong with Shane and like why, you know, like

881
00:53:32,719 --> 00:53:34,840
Speaker 1: other than him being like, look, I was just born

882
00:53:34,920 --> 00:53:38,160
Speaker 1: into this, okay, like what am I supposed to do?

883
00:53:38,520 --> 00:53:40,719
Speaker 1: And it's like, yeah, surface level, that's who he is.

884
00:53:40,800 --> 00:53:45,000
Speaker 1: And that's all these people are. They're all surface level people, right, Yeah,

885
00:53:45,200 --> 00:53:47,600
Speaker 1: maybe that is Maybe that is the observation. So like

886
00:53:47,680 --> 00:53:49,960
Speaker 1: just to give people an idea, like there's like this tension.

887
00:53:50,000 --> 00:53:53,040
Speaker 1: There's this character Armand, who's like the hotel manager. Then

888
00:53:53,080 --> 00:53:55,279
Speaker 1: there's a couple of Nicole and Mark, which is played

889
00:53:55,280 --> 00:53:58,240
Speaker 1: by Connie Britten and Steve's on, who's like this wealthy

890
00:53:58,320 --> 00:54:01,560
Speaker 1: couple who have brought their kids and one of their

891
00:54:01,640 --> 00:54:04,040
Speaker 1: kids friends with them to just kind of like have

892
00:54:04,239 --> 00:54:08,080
Speaker 1: one of those rich people vacations. And then the other story.

893
00:54:08,120 --> 00:54:11,640
Speaker 1: The other storyline involves Tanya, which is Jennifer Coolidge's character,

894
00:54:11,680 --> 00:54:14,080
Speaker 1: who's like mourning the loss of her mother and is

895
00:54:14,080 --> 00:54:18,240
Speaker 1: there to spread ashes alongside this newlywed couple of Shane

896
00:54:18,280 --> 00:54:22,319
Speaker 1: and Rachel, where this journalist has like married rich and

897
00:54:22,480 --> 00:54:24,799
Speaker 1: is kind of having this existential dilemma of like what

898
00:54:24,840 --> 00:54:29,120
Speaker 1: that means for her. Yeah, but I think that there's

899
00:54:29,120 --> 00:54:34,279
Speaker 1: something where when they're on vacation, they are left with

900
00:54:34,360 --> 00:54:38,920
Speaker 1: too much time to think about like just themselves and

901
00:54:39,000 --> 00:54:41,480
Speaker 1: how awful they are, so they like do things like

902
00:54:41,760 --> 00:54:45,919
Speaker 1: create the issue with urmand that that Jake has, or

903
00:54:46,200 --> 00:54:49,000
Speaker 1: Connie Britten, who's like supposed to be a Cheryl Sandburg

904
00:54:49,080 --> 00:54:52,359
Speaker 1: type character, is like at one point like moving furniture

905
00:54:52,400 --> 00:54:55,920
Speaker 1: around the hotel room, like just like doing these things,

906
00:54:55,960 --> 00:55:00,440
Speaker 1: like creating these tasks and these problems too, just like

907
00:55:00,600 --> 00:55:04,600
Speaker 1: focus on to like continue this like sort of endless

908
00:55:04,680 --> 00:55:09,440
Speaker 1: like competition and like urge to prove something that like

909
00:55:09,520 --> 00:55:12,120
Speaker 1: I feel like deep down they know they can't prove,

910
00:55:12,160 --> 00:55:14,759
Speaker 1: which is that they deserve any of this ship. Mm

911
00:55:14,880 --> 00:55:18,120
Speaker 1: hmm what's um. I I want to say that this

912
00:55:18,520 --> 00:55:21,400
Speaker 1: one of the best things about this show, where like

913
00:55:21,440 --> 00:55:25,880
Speaker 1: some of just the individual performances and I don't know,

914
00:55:25,920 --> 00:55:27,520
Speaker 1: I just want to maybe go around and we can

915
00:55:27,520 --> 00:55:29,800
Speaker 1: talk about some of our favorite people from the show.

916
00:55:30,200 --> 00:55:33,360
Speaker 1: I remember when I wasn't watching yet and Anna was

917
00:55:33,400 --> 00:55:38,080
Speaker 1: and You're like, dude to Jennifer Coolidge, it's fucking crushing

918
00:55:38,160 --> 00:55:40,279
Speaker 1: this whole fucking show. And that's when I was like,

919
00:55:40,360 --> 00:55:43,719
Speaker 1: I'm watching because I'm such a Jennifer Coolidge fan. And yeah,

920
00:55:43,800 --> 00:55:49,719
Speaker 1: Tanya's character was called cool dogs. Hey where the cool

921
00:55:49,760 --> 00:55:53,399
Speaker 1: Dogs at? But yeah, like honestly, her performances like fantastic,

922
00:55:53,920 --> 00:55:56,800
Speaker 1: and like her sort of storyline with Belinda and Natasha.

923
00:55:56,880 --> 00:56:01,800
Speaker 1: Rothwell's character was just like this fucking stre range journey

924
00:56:01,840 --> 00:56:06,640
Speaker 1: of like white savior, doom and guilt and like also

925
00:56:06,960 --> 00:56:10,120
Speaker 1: people trying to act like they were being authentic by

926
00:56:10,120 --> 00:56:12,719
Speaker 1: offering or not offering money. It was a it was

927
00:56:12,760 --> 00:56:16,320
Speaker 1: a lot. It was a lot. Yeah, you know, Jennifer Coolidge,

928
00:56:16,360 --> 00:56:20,440
Speaker 1: I mean truly like a legendary actor who like comedic

929
00:56:20,480 --> 00:56:23,160
Speaker 1: actor who never really I think like I feel like

930
00:56:23,200 --> 00:56:27,319
Speaker 1: she gets you know, pigeonholed a lot in what she

931
00:56:27,440 --> 00:56:29,440
Speaker 1: has been offered in the past, and it was like

932
00:56:29,560 --> 00:56:33,200
Speaker 1: really nice to see her like playing this, like just

933
00:56:33,239 --> 00:56:36,319
Speaker 1: showing that she has like this wild range where she

934
00:56:36,360 --> 00:56:39,279
Speaker 1: can play like this, Like what is she? She calls

935
00:56:39,320 --> 00:56:44,560
Speaker 1: herself an alcoholic she comes to like an alcoholic psychopath

936
00:56:44,719 --> 00:56:49,880
Speaker 1: or something like. She's like, under, you're just gonna find

937
00:56:49,920 --> 00:56:57,440
Speaker 1: an alcoholic psychopath And you're like wow, wow, like that

938
00:56:57,600 --> 00:57:00,440
Speaker 1: level of just like madness. You're like, wow, she's kind

939
00:57:00,440 --> 00:57:03,000
Speaker 1: of And the thing is she's nailing it. Like her character,

940
00:57:03,120 --> 00:57:06,120
Speaker 1: every person she interacts with, I immediately feel bad for

941
00:57:06,200 --> 00:57:11,520
Speaker 1: them and that she's nailing it. Yeah, it just walks

942
00:57:11,600 --> 00:57:22,520
Speaker 1: up like you having a good she's trapping it. She

943
00:57:22,640 --> 00:57:27,880
Speaker 1: reminded me of the character and shadows the energy vampire. Yeah,

944
00:57:28,400 --> 00:57:32,840
Speaker 1: she just came in and would destroy the life force

945
00:57:32,920 --> 00:57:38,320
Speaker 1: of everyone except the dying guy who she ultimately ends

946
00:57:38,360 --> 00:57:41,000
Speaker 1: up with. Right. I do want to add this one thing.

947
00:57:41,080 --> 00:57:43,840
Speaker 1: Those characters of Paula and Olivia, like the gen Z

948
00:57:44,120 --> 00:57:48,400
Speaker 1: college girls. My dad said he like they made him

949
00:57:48,400 --> 00:57:51,040
Speaker 1: feel so uncomfortable that he couldn't get past the first

950
00:57:51,080 --> 00:57:54,600
Speaker 1: episode because he was getting like zoomer anxiety. He's like,

951
00:57:54,640 --> 00:57:56,880
Speaker 1: oh man, they're like they're just gonna fucking read your

952
00:57:56,920 --> 00:57:59,160
Speaker 1: ass and like you don't know what to do, and

953
00:57:59,280 --> 00:58:01,160
Speaker 1: he was like he was feeling that off the screen.

954
00:58:01,160 --> 00:58:03,400
Speaker 1: He's like, yeah, I couldn't really get past it. First year.

955
00:58:03,840 --> 00:58:08,800
Speaker 1: They nail the cruelness that gen Z can bring in

956
00:58:08,800 --> 00:58:12,680
Speaker 1: their critiques and you're like, oh my, just like them

957
00:58:12,800 --> 00:58:15,280
Speaker 1: reading at the look that they both give you at

958
00:58:15,320 --> 00:58:17,480
Speaker 1: the same time, and you're like no, no, no, no,

959
00:58:17,600 --> 00:58:20,720
Speaker 1: don't look at me, right, because these characters are like

960
00:58:20,760 --> 00:58:24,640
Speaker 1: almost like you know, they have like the cutting commentary

961
00:58:24,720 --> 00:58:26,800
Speaker 1: that like a five year old would where they'll be like,

962
00:58:26,920 --> 00:58:30,320
Speaker 1: oh you're bald, and you're like, okay, thank you chi,

963
00:58:30,920 --> 00:58:34,480
Speaker 1: but they're just like you're like an empty, like lame

964
00:58:34,680 --> 00:58:36,920
Speaker 1: want of your wife. Like they have like this expanded

965
00:58:37,000 --> 00:58:40,760
Speaker 1: vocabulary and know a lot more like psychological terminology, so

966
00:58:40,840 --> 00:58:43,600
Speaker 1: like it's like the same kind of observation, but it

967
00:58:43,720 --> 00:58:46,480
Speaker 1: just cuts you in half. But also they're just like

968
00:58:46,560 --> 00:58:48,640
Speaker 1: disdained for things too. I think was really that line

969
00:58:48,640 --> 00:58:54,680
Speaker 1: where they're like, do you guys meet on Riya Like wow, okay,

970
00:58:55,680 --> 00:59:00,520
Speaker 1: she's just like oh no, You're just like damn, they

971
00:59:00,560 --> 00:59:03,880
Speaker 1: just come for you immediately. The reading is like the

972
00:59:04,240 --> 00:59:07,440
Speaker 1: books they're reading are like these like h like Nietzsche

973
00:59:07,520 --> 00:59:11,640
Speaker 1: and like Freudan. It's like, okay, uh, nobody wants nobody

974
00:59:11,640 --> 00:59:16,440
Speaker 1: actually reads that. But um. And then Jake Lacy, the

975
00:59:16,840 --> 00:59:20,160
Speaker 1: like bro character who's like inherited a bunch of money

976
00:59:20,240 --> 00:59:23,160
Speaker 1: and like it seems to have like the most violent

977
00:59:23,560 --> 00:59:29,200
Speaker 1: conflict with like just well just with every everything about himself,

978
00:59:29,200 --> 00:59:34,439
Speaker 1: and like he's always reading Malcolm Gladwell blank and he's

979
00:59:34,600 --> 00:59:38,120
Speaker 1: never yeah yeah, and never making any progress in it.

980
00:59:38,120 --> 00:59:41,240
Speaker 1: It's always like at the same place I thought was

981
00:59:41,760 --> 00:59:44,640
Speaker 1: he captures like a guy who says he's gonna read

982
00:59:44,680 --> 00:59:47,560
Speaker 1: on a trip energy and it's like, yeah, almost, dude,

983
00:59:47,560 --> 00:59:49,919
Speaker 1: I'm bringing the book here. I'm bringing the book there.

984
00:59:50,040 --> 00:59:51,840
Speaker 1: I'm bringing I brought it to bed. No, I didn't

985
00:59:51,840 --> 00:59:54,960
Speaker 1: read it, but I was about to. But you know,

986
00:59:55,560 --> 00:59:59,440
Speaker 1: vacation and I gotta say, Molly Shannon comes in. I

987
00:59:59,440 --> 01:00:04,720
Speaker 1: mean Shannon is honestly like every every role she plays

988
01:00:04,760 --> 01:00:07,440
Speaker 1: immediately is like she just progresses in a way where

989
01:00:07,440 --> 01:00:09,600
Speaker 1: I'm like, she's so fucking funny. She just comes in

990
01:00:09,640 --> 01:00:12,440
Speaker 1: as a mom who's just like, you know, like you're

991
01:00:12,440 --> 01:00:15,000
Speaker 1: a pretty you know, like that wedding I blacked out.

992
01:00:15,160 --> 01:00:19,720
Speaker 1: You're like, don't you know saying that? It's like, what

993
01:00:19,760 --> 01:00:22,720
Speaker 1: are you saying? People say it's lovely? I don't remember

994
01:00:22,720 --> 01:00:26,920
Speaker 1: that at all, but it was great. Nothing. Yeah, I

995
01:00:26,920 --> 01:00:31,400
Speaker 1: feel like her, and I feel like the character Jake,

996
01:00:31,880 --> 01:00:35,560
Speaker 1: the mom, Molly Shannon, and the two gen Z girls

997
01:00:35,560 --> 01:00:37,760
Speaker 1: were like the ones that like stuck out to me

998
01:00:37,800 --> 01:00:40,280
Speaker 1: as like the most I don't know, like I hadn't

999
01:00:40,400 --> 01:00:44,560
Speaker 1: seen them on camera like in a thing before, like

1000
01:00:44,680 --> 01:00:49,400
Speaker 1: nailing to that degree, like that archetype because they're Yeah,

1001
01:00:49,560 --> 01:00:51,800
Speaker 1: there's like a lot of pain in them, like the

1002
01:00:52,520 --> 01:00:56,080
Speaker 1: like that is and the way they deal with it

1003
01:00:56,120 --> 01:00:59,920
Speaker 1: is like very pathetic and like just completely like transfer

1004
01:01:00,080 --> 01:01:03,600
Speaker 1: ring like their anger about one thing to another thing,

1005
01:01:03,720 --> 01:01:06,960
Speaker 1: and they just really like nailed it in a way

1006
01:01:06,960 --> 01:01:11,360
Speaker 1: that felt realistic and yet like so just obvious. And

1007
01:01:11,400 --> 01:01:14,480
Speaker 1: also Steve's On. I forgot about Steveson until I saw

1008
01:01:14,560 --> 01:01:17,439
Speaker 1: Meg and I was like, oh wait, Steveson is actually hilarious.

1009
01:01:17,600 --> 01:01:21,680
Speaker 1: His whole like meltdown through the series of like he

1010
01:01:21,760 --> 01:01:25,440
Speaker 1: finds out his dad died of AIDS and and he's like,

1011
01:01:26,120 --> 01:01:30,640
Speaker 1: I just we First he thinks he has testicular cancer.

1012
01:01:30,800 --> 01:01:32,840
Speaker 1: Then he finds out his dad died of eates because

1013
01:01:32,880 --> 01:01:36,400
Speaker 1: he was you know, bisexual or gay. Well, I don't

1014
01:01:36,440 --> 01:01:38,960
Speaker 1: even know. It's not really explained. And then if I

1015
01:01:39,200 --> 01:01:42,480
Speaker 1: let these like starts to be like he starts to

1016
01:01:42,480 --> 01:01:44,600
Speaker 1: melt it down because he at one point he had

1017
01:01:44,600 --> 01:01:46,920
Speaker 1: an affair and decides he wants to be open with

1018
01:01:47,000 --> 01:01:49,520
Speaker 1: his son, and his son is really not accepted. He's

1019
01:01:49,560 --> 01:01:53,480
Speaker 1: just like, okay, cool, dad, Like stop telling me about this.

1020
01:01:54,960 --> 01:02:00,960
Speaker 1: I got your mom. They're so like his character. And

1021
01:02:01,000 --> 01:02:04,280
Speaker 1: then just like that scene at the dinner where they're like,

1022
01:02:04,560 --> 01:02:06,960
Speaker 1: be nicer to your brother. You know, it's tough for

1023
01:02:07,080 --> 01:02:11,040
Speaker 1: young white guys. And then like Paula, they're like, well,

1024
01:02:11,160 --> 01:02:13,160
Speaker 1: you know. The daughter is like, you've never even asked

1025
01:02:13,160 --> 01:02:16,040
Speaker 1: paula question. And he's like, well, Paula doesn't know anything

1026
01:02:16,080 --> 01:02:18,400
Speaker 1: about me, and she's like, well I know about your balls, bro,

1027
01:02:19,480 --> 01:02:22,760
Speaker 1: what do you mean walking around lamenting that? Yeah? And

1028
01:02:22,760 --> 01:02:25,520
Speaker 1: then he's like, okay, ask me a question, Paula and

1029
01:02:25,640 --> 01:02:28,680
Speaker 1: she says, what do you stand for? Oh my god.

1030
01:02:29,360 --> 01:02:34,320
Speaker 1: His character just like like what do I stand for?

1031
01:02:34,480 --> 01:02:38,880
Speaker 1: Because they're all that like emotional turmoil. He still lacks

1032
01:02:39,000 --> 01:02:42,400
Speaker 1: the depth needed to analyze any of it, but he

1033
01:02:42,600 --> 01:02:46,200
Speaker 1: can't do it. It's just I thought his character was

1034
01:02:46,240 --> 01:02:49,640
Speaker 1: like perfect, just like Dad, it's just like kind of

1035
01:02:49,760 --> 01:02:53,080
Speaker 1: checked out, is so self involved with his own crap.

1036
01:02:53,720 --> 01:02:56,080
Speaker 1: It's kind of nice to see like Zon he like

1037
01:02:56,160 --> 01:02:59,160
Speaker 1: you can see that he can there's a like whatever.

1038
01:02:59,200 --> 01:03:01,920
Speaker 1: This next phase is him playing this kind of weird

1039
01:03:02,080 --> 01:03:05,280
Speaker 1: middle aged guy, like because that angst when he was younger,

1040
01:03:05,400 --> 01:03:07,240
Speaker 1: Like sure it was funny, but I feel like it

1041
01:03:07,280 --> 01:03:09,560
Speaker 1: really suits him now, like as he's gotten older and

1042
01:03:09,640 --> 01:03:12,080
Speaker 1: like you know that he now looks like he I

1043
01:03:12,080 --> 01:03:13,960
Speaker 1: don't know, it just feels like more spot on. And

1044
01:03:13,960 --> 01:03:16,919
Speaker 1: then also like Molly Shannon too, is just really helped

1045
01:03:16,960 --> 01:03:19,400
Speaker 1: to see, like you're like fun dude. Mony Shannon has

1046
01:03:19,440 --> 01:03:22,080
Speaker 1: like always been super talented, Like now she's getting like

1047
01:03:22,360 --> 01:03:26,200
Speaker 1: great roles to really you know Fred or wings in. Yeah,

1048
01:03:26,240 --> 01:03:27,760
Speaker 1: I thought this was a great role. There's one more

1049
01:03:27,800 --> 01:03:30,600
Speaker 1: moment with steveson the moment he gets the call from

1050
01:03:30,600 --> 01:03:33,000
Speaker 1: his uncle and he's like, well, how did my dad die?

1051
01:03:33,040 --> 01:03:36,280
Speaker 1: Of AIDS? And he's like he was sleeping around with men.

1052
01:03:36,520 --> 01:03:40,040
Speaker 1: That face he makes I cried just his I think

1053
01:03:40,120 --> 01:03:43,160
Speaker 1: his facial expressions alone throughout the series of just like

1054
01:03:43,280 --> 01:03:49,000
Speaker 1: complete confusion, like what he Yeah, he embodied the like

1055
01:03:49,240 --> 01:03:53,160
Speaker 1: circuits frying in a computer, but somehow made that a

1056
01:03:53,240 --> 01:03:55,919
Speaker 1: facial expression. And then the face he's making when he's

1057
01:03:55,920 --> 01:03:57,840
Speaker 1: just sitting like this the next day, where it's with

1058
01:03:57,920 --> 01:03:59,680
Speaker 1: his hand, with his face in his hand, and his

1059
01:03:59,760 --> 01:04:01,640
Speaker 1: daughter has been like, that's really homophobic for you to

1060
01:04:01,640 --> 01:04:04,760
Speaker 1: be this upset about it. Like what if Grandpa was

1061
01:04:04,840 --> 01:04:08,280
Speaker 1: like a power bottom just like is a camp process

1062
01:04:08,440 --> 01:04:12,160
Speaker 1: any of the information. I mean, I was dying, Mike what.

1063
01:04:12,400 --> 01:04:16,720
Speaker 1: The creator and writer of the show's dad was Reverend

1064
01:04:16,840 --> 01:04:20,760
Speaker 1: Dr James Melville White, a former speechwriter and ghostwriter for

1065
01:04:20,800 --> 01:04:24,600
Speaker 1: the religious right figures such as Jerry Falwell and Pat Robertson.

1066
01:04:25,360 --> 01:04:31,200
Speaker 1: His father came out as gay, so kind of lived

1067
01:04:31,200 --> 01:04:36,160
Speaker 1: in experience, right, cool and interesting Mark, Yeah. And then

1068
01:04:36,200 --> 01:04:39,480
Speaker 1: the other character, I just want to like Murray Bartlett

1069
01:04:39,520 --> 01:04:44,040
Speaker 1: as armand is like one of the most realistic depiction

1070
01:04:44,120 --> 01:04:48,000
Speaker 1: of like a relapse just of being high and like

1071
01:04:48,120 --> 01:04:52,600
Speaker 1: uninhabited and or uninhabited, and just like that performance is

1072
01:04:52,680 --> 01:04:56,640
Speaker 1: fucking incredible. Yeah, that, especially that last episode when like

1073
01:04:56,760 --> 01:05:02,000
Speaker 1: he's like fuck it maybe it's yeah, it's yeah that,

1074
01:05:02,160 --> 01:05:04,840
Speaker 1: I mean, his whole it's also like you really felt

1075
01:05:04,840 --> 01:05:08,000
Speaker 1: for his character too, because like, you know, like he's

1076
01:05:08,200 --> 01:05:10,040
Speaker 1: he's trying to keep a ship together, he's trying to

1077
01:05:10,040 --> 01:05:12,800
Speaker 1: stay clean, and he's also like in the midst of

1078
01:05:12,840 --> 01:05:16,680
Speaker 1: like the most chaotic week of his career is like

1079
01:05:16,720 --> 01:05:21,320
Speaker 1: managing a hotel with like unruly guests, finding bags of

1080
01:05:21,400 --> 01:05:23,680
Speaker 1: drugs and not knowing what to do and like his

1081
01:05:23,720 --> 01:05:27,200
Speaker 1: own demons. It's like, yeah, it's funny because he provided

1082
01:05:27,240 --> 01:05:31,480
Speaker 1: a lot of comedic relief, but also like super like

1083
01:05:31,520 --> 01:05:34,800
Speaker 1: you said, like this very realistic portrayal of of someone

1084
01:05:34,880 --> 01:05:38,480
Speaker 1: just like struggling with their own addiction to Yeah, I

1085
01:05:38,520 --> 01:05:40,880
Speaker 1: also like that the people around and we're kind of like, okay,

1086
01:05:40,960 --> 01:05:44,560
Speaker 1: armand no one was really that concerned that this guy

1087
01:05:44,680 --> 01:05:47,640
Speaker 1: was so off the deep end, Like you open your

1088
01:05:47,640 --> 01:05:50,440
Speaker 1: door and your boss is eating ass, like that's the problem.

1089
01:05:50,880 --> 01:05:53,320
Speaker 1: There was just like, you know what, not my business,

1090
01:05:53,440 --> 01:05:57,120
Speaker 1: and you haven't seen the show. It's yeah, you'll you'll

1091
01:05:57,160 --> 01:05:59,760
Speaker 1: be surprised, but I think it's worth checking out for sure.

1092
01:06:00,000 --> 01:06:02,600
Speaker 1: Oh yeah, we should probably put a spoiler alert at

1093
01:06:02,600 --> 01:06:05,960
Speaker 1: the beginning of this, because I think this is spoiler

1094
01:06:05,960 --> 01:06:11,840
Speaker 1: alert twenty minutes ago, spoiler alert all you can eat,

1095
01:06:11,880 --> 01:06:18,120
Speaker 1: but fet I actually really like Dylan. He doesn't get Yeah,

1096
01:06:18,280 --> 01:06:21,680
Speaker 1: I can have any shift I want you I have

1097
01:06:21,880 --> 01:06:24,360
Speaker 1: more like right, And then I was just kind of like, yo,

1098
01:06:24,480 --> 01:06:26,840
Speaker 1: this is so gross. And then I'm like, well this

1099
01:06:26,920 --> 01:06:31,200
Speaker 1: is this is this dark comation. It's like finally, let's party.

1100
01:06:31,560 --> 01:06:35,120
Speaker 1: There is a scene last episode that's the grossest thing

1101
01:06:35,120 --> 01:06:38,720
Speaker 1: I've ever seen with armand that has to be real.

1102
01:06:38,880 --> 01:06:43,760
Speaker 1: They have to have like shown actual like that. Right,

1103
01:06:43,800 --> 01:06:45,840
Speaker 1: you can't take that, or you it would cost a

1104
01:06:45,880 --> 01:06:48,000
Speaker 1: lot of money to fake that, or you just don't

1105
01:06:48,000 --> 01:06:50,640
Speaker 1: put it in a post. Yeah that's true. You think

1106
01:06:50,640 --> 01:06:55,440
Speaker 1: that was digitized. I don't think it worse. I ran

1107
01:06:55,520 --> 01:06:58,000
Speaker 1: that back a number of times and just like watch

1108
01:06:58,080 --> 01:07:00,360
Speaker 1: it and frame by frame and I'm pretty sure really

1109
01:07:00,360 --> 01:07:05,080
Speaker 1: did your own yourself and to replicate the shot. Yeah yeah, yeah,

1110
01:07:05,120 --> 01:07:06,480
Speaker 1: there's like what are you doing in the bathroom? Like

1111
01:07:07,600 --> 01:07:14,680
Speaker 1: everything a suitcase? I got a new one coming in

1112
01:07:14,720 --> 01:07:17,400
Speaker 1: the mail. I don't worry about it. Anna as always

1113
01:07:17,440 --> 01:07:20,320
Speaker 1: such a pleasure having you and your streaming corner on

1114
01:07:20,800 --> 01:07:24,640
Speaker 1: where can people find you and follow you? Well? Hold on,

1115
01:07:24,680 --> 01:07:27,920
Speaker 1: I have to do my outro song for sure, boy,

1116
01:07:28,480 --> 01:07:34,240
Speaker 1: just because you as like another four that's the end.

1117
01:07:37,160 --> 01:07:39,800
Speaker 1: Thank you. Yeah, I can get the horn section from

1118
01:07:39,880 --> 01:07:45,160
Speaker 1: Spodi Policias, thank you. I also sampled that. H yeah, okay,

1119
01:07:45,200 --> 01:07:51,040
Speaker 1: So I think for the next I would love to

1120
01:07:52,320 --> 01:07:56,160
Speaker 1: recommend which we've also kind of already recommended, but like

1121
01:07:56,360 --> 01:07:59,000
Speaker 1: maybe hopefully by the time we do it again, the

1122
01:07:59,040 --> 01:08:02,920
Speaker 1: show will be fully out. But Reservation Dogs, yeah, we

1123
01:08:02,960 --> 01:08:05,760
Speaker 1: got to talk about that. We gotta talk about reservation Dogs.

1124
01:08:06,560 --> 01:08:10,400
Speaker 1: And I don't want you guys to watch this, but

1125
01:08:10,520 --> 01:08:15,160
Speaker 1: I did watch that show click Bait on Netflix, and

1126
01:08:15,400 --> 01:08:18,400
Speaker 1: uh not good. And that's my thoughts. I don't want

1127
01:08:18,439 --> 01:08:19,680
Speaker 1: you guys to watch it, but I did watch it,

1128
01:08:19,760 --> 01:08:23,720
Speaker 1: so got it cool? Where can people uh find you

1129
01:08:23,760 --> 01:08:26,160
Speaker 1: and follow you? I'm at in a hosting on Twitter?

1130
01:08:27,000 --> 01:08:28,519
Speaker 1: And is there a tweeter or some of the work

1131
01:08:28,600 --> 01:08:31,960
Speaker 1: of social media you've been enjoying. Did you see that

1132
01:08:32,520 --> 01:08:35,719
Speaker 1: Paul Strader what's his name? Strader? I think I said

1133
01:08:35,920 --> 01:08:39,639
Speaker 1: Schaefer got kicked out of a No, it's Paul Straighter,

1134
01:08:39,720 --> 01:08:43,400
Speaker 1: not Shaeffer, Shroder. Strader the filmmaker got kicked out of

1135
01:08:43,400 --> 01:08:46,400
Speaker 1: a bunch of poker zooms because he just keeps saying

1136
01:08:46,400 --> 01:08:50,240
Speaker 1: like really wild shipped to the women, like just so inappropriate.

1137
01:08:50,280 --> 01:08:51,720
Speaker 1: And then he did a news article or he like,

1138
01:08:51,760 --> 01:08:53,720
Speaker 1: did an interview about it that was like, I mean,

1139
01:08:53,880 --> 01:08:56,320
Speaker 1: cancel culture. Am I right? You can't tell a woman

1140
01:08:56,360 --> 01:08:59,080
Speaker 1: to fuck another woman in a zoom poker call? And

1141
01:08:59,120 --> 01:09:01,559
Speaker 1: I said I would. It was a great friend of mine,

1142
01:09:01,720 --> 01:09:05,720
Speaker 1: s G. Goodman, I mean. And then Paul Dano, who

1143
01:09:05,760 --> 01:09:07,680
Speaker 1: was running one of them, kicked his ass out, and

1144
01:09:07,680 --> 01:09:10,600
Speaker 1: I'm like, well, okay, Paul Dana, Yeah, there you go.

1145
01:09:10,760 --> 01:09:16,440
Speaker 1: Hold the line married to Zoe Kazan star of click Bait. Okay, um,

1146
01:09:16,479 --> 01:09:19,599
Speaker 1: all right. I like both of them very much. Miles,

1147
01:09:19,600 --> 01:09:22,800
Speaker 1: Where can people find you? What the tweet you've been enjoying? Twitter? Instagram?

1148
01:09:22,840 --> 01:09:25,760
Speaker 1: At Miles of Gray. Also for the ninety Days Ship

1149
01:09:25,920 --> 01:09:29,439
Speaker 1: go to four twenty day Fiance with Sophia Alexandra and I.

1150
01:09:29,960 --> 01:09:35,600
Speaker 1: A tweet that I am liking is from at Tawanda

1151
01:09:35,640 --> 01:09:38,280
Speaker 1: Ghana t A w A n d A g O

1152
01:09:38,520 --> 01:09:41,559
Speaker 1: n A tweeted I'm gonna say candy Man five times

1153
01:09:41,560 --> 01:09:43,840
Speaker 1: while my homie says beatles to three times and we're

1154
01:09:43,840 --> 01:09:48,320
Speaker 1: gonna make him fight. I felt really great. And then

1155
01:09:48,439 --> 01:09:51,680
Speaker 1: the last one is from at zero suit camu c

1156
01:09:51,920 --> 01:09:54,639
Speaker 1: A m us It says my son asked me if

1157
01:09:54,720 --> 01:09:58,040
Speaker 1: he was gonna die someday. I told him no because honestly,

1158
01:09:58,080 --> 01:09:59,680
Speaker 1: I'm not really in the mood. I hope I did

1159
01:09:59,680 --> 01:10:07,080
Speaker 1: the right uh parenting. Dave King tweeted, is it true

1160
01:10:07,120 --> 01:10:09,479
Speaker 1: that the Alicia Key song No One is about? Who

1161
01:10:09,720 --> 01:10:14,320
Speaker 1: out pizzas the Hut? And Brendan O'Connor tweeted, if anyone

1162
01:10:14,360 --> 01:10:17,160
Speaker 1: else is worried about the rats, don't worry. I looked

1163
01:10:17,160 --> 01:10:19,840
Speaker 1: it up and they can swim for three days without rest,

1164
01:10:20,439 --> 01:10:24,360
Speaker 1: so like, wow, reassured. Uh. You can find me on

1165
01:10:24,360 --> 01:10:26,680
Speaker 1: Twitter at Jack Underscore O'Brien. You can find us on

1166
01:10:26,680 --> 01:10:28,920
Speaker 1: Twitter at Daily zi Guist for at d Daily zut

1167
01:10:28,920 --> 01:10:32,400
Speaker 1: Geist on Instagram. We have Facebook fan page and a website,

1168
01:10:32,479 --> 01:10:34,679
Speaker 1: Daily za guist dot com, where we post our episodes

1169
01:10:34,720 --> 01:10:36,880
Speaker 1: down our foot notes where we link off to the

1170
01:10:36,960 --> 01:10:39,960
Speaker 1: information that we talked about in today's episode, as well

1171
01:10:40,000 --> 01:10:42,559
Speaker 1: as a song we think you'll enjoy. Myles. What's this song?

1172
01:10:43,280 --> 01:10:45,360
Speaker 1: It's uh, We're gonna do another one from one of

1173
01:10:45,400 --> 01:10:48,880
Speaker 1: my favorite new rappers, the Korean rapper park Hey Jon,

1174
01:10:49,479 --> 01:10:52,360
Speaker 1: and this track is called what You're Doing Later? And

1175
01:10:52,439 --> 01:10:54,640
Speaker 1: so I love her flow. She's like I heard like

1176
01:10:54,720 --> 01:10:58,120
Speaker 1: low energy delivery is fantastic and the beats fucking knocks.

1177
01:10:58,120 --> 01:11:01,160
Speaker 1: So take what you're doing later into this weekend and

1178
01:11:01,200 --> 01:11:03,720
Speaker 1: ask your friends what're you doing later? There you go.

1179
01:11:03,920 --> 01:11:06,360
Speaker 1: The Daily Zeke is to the production of I Heart Radio.

1180
01:11:06,400 --> 01:11:08,519
Speaker 1: From more podcasts from my heart Radio, visit the I

1181
01:11:08,560 --> 01:11:10,760
Speaker 1: heart Radio app, Apple podcast, or where I've be listening

1182
01:11:10,760 --> 01:11:12,599
Speaker 1: to your favorite shows. That's gonna do it for us

1183
01:11:12,640 --> 01:11:14,920
Speaker 1: this morning. We're back this afternoon to tell you what's

1184
01:11:14,920 --> 01:11:17,440
Speaker 1: trending and we'll talk to you all then. Bye bye

1185
01:11:17,439 --> 01:11:17,719
Speaker 1: bye