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Speaker 1: Mr garbutschaf teared down this wall. Either you're with us

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Speaker 1: or you were with the terrorists. If you got healthcare already,

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Speaker 1: then you can keep your plan. If you are satisfied

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Speaker 1: with Trump is not president of the United States, take

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Speaker 1: it to a bank. Together. We will make America great again.

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Speaker 1: You'll never sharender. It's what you've been waiting for all day.

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Speaker 1: The Buck Sexton Show joined the conversation called Buck Toll

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Speaker 1: Free at eight four four nine hundred Buck. That's eight

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Speaker 1: four four nine hundred to eight to five the future

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Speaker 1: of talk radio buck Sexton. The Trump administration has been

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Speaker 1: accused I heard over the weekend of being vindictive and

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Speaker 1: mean spirited, and that seems horribly unfair. I think it

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Speaker 1: was horrible day for democracy. This attack on McCabe really

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Speaker 1: reminds me of something from a movie. It seems sort

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Speaker 1: of tragic and unfair on the surface. So it does

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Speaker 1: look vindictive. Should we not take it that way? It

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Speaker 1: feels vindictive just because it was the timing of it

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Speaker 1: which leads one to believe that this is authoritarian behavior

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Speaker 1: or the making of one. Welcome to the Buck section Show. Everybody.

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Speaker 1: Oh Man media was in a meltdown over the weekend

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Speaker 1: about that, weren't they? They're just also upset about McCabe

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Speaker 1: getting fired. There's so much to say here, folks. We're

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Speaker 1: gonna have some fun with this one. We're gonna really

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Speaker 1: air this one out, you know, so you can take

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Speaker 1: a moment, take a deep breath, stretch out, because we're

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Speaker 1: gonna lean into this. Oh my, here, let's let's start

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Speaker 1: with this. Trump didn't fire McCabe. Does that seem to

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Speaker 1: matter to anybody here? Did do any of these folks

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Speaker 1: who were saying that, you know, oh my gosh, our

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Speaker 1: institutions are all gonna just collapse? The President United States

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Speaker 1: did not fire McCabe. In fact, President United States had

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Speaker 1: no direct involvement whatsoever in the firing of McCabe. McCabe

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Speaker 1: got fired because of an inspector General report from within

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Speaker 1: the FBID. Now that's very significant, folks, That really matters,

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Speaker 1: because I can tell you this, a federal bureaucracy is

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Speaker 1: going to protect its own until it can't, you know,

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Speaker 1: until they decide you have to be voted off the island.

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Speaker 1: They're usually gonna treat you like one of their own,

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Speaker 1: and they're gonna protect you at the senior levels Oh no, no,

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Speaker 1: don't get me wrong. Let's not get this twisted. If

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Speaker 1: you're some average Joe Schmoe one of these places, they

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Speaker 1: may they may decide to feed your career into the

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Speaker 1: wood chipper, so to speak. They may decide that you're

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Speaker 1: you're done because it will send a message to the rest.

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Speaker 1: But at the McCabe level, been there for decades, close

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Speaker 1: with everybody, close with Comey. This was Comey's deputy, this

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Speaker 1: was Comey's right hand man, Mr. Six ft nine, sanctimony himself,

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Speaker 1: James Comey. He of tweeting out Placid Lake scenes while

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Speaker 1: writing anti Trump screeds fame. Uh, this is what we

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Speaker 1: see here that the Inspector General was the one that

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Speaker 1: decided that McCabe has be fired. Now, I don't want

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Speaker 1: to go too far down the road of what McCabe

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Speaker 1: did was so terrible. He leaked this inform, He leaked

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Speaker 1: information and lined about it. That's all we know right now.

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Speaker 1: I'm thinking that if we were to see, if we

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Speaker 1: were to see what was contained in the report in total,

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Speaker 1: we would we would then understand how does the FBI

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Speaker 1: would get rid of one of its own in this way?

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Speaker 1: But oh my gosh, the media were in a tizzy

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Speaker 1: over the weekend based on this. He got fired late

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Speaker 1: Friday night. You'll you'll call I told you here on

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Speaker 1: the show. I thought he was gonna fire. We were

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Speaker 1: on firing Watch. I even said on Outnumbered on Friday,

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Speaker 1: I thought he was gonna get fired, and he did. So,

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Speaker 1: you know, always bet on Buck. That's what I like

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Speaker 1: to say, Always bet on Buck. But you know, it

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Speaker 1: doesn't really change all that much here until we get

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Speaker 1: more information, you know, And do I think that this

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Speaker 1: was the right thing. Sure, it makes sense to me.

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Speaker 1: Oh oh, one more thing before we bust out the

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Speaker 1: world's smallest violin for Andy McCabe. Here, let's understand a

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Speaker 1: few things. He's somebody who no doubt jammed up, which

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Speaker 1: is the law enforcement term of art for blanking somebody

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Speaker 1: over jammed up. Uh, tons of people, for lying to

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Speaker 1: probably him as an FBI agent in his day, as

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Speaker 1: well as lots of other FBI folks, and for just that.

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Speaker 1: That's really one of the one of the favorite charges

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Speaker 1: of the federal government is lying to the federal government.

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Speaker 1: They love to get you on that one. I'm not

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Speaker 1: even saying lying under oath in a court proceeding. I'm

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Speaker 1: just saying, lying to a federal agent. Love that one,

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Speaker 1: and it's actually something I think should be revisited in

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Speaker 1: the context of if you didn't actually do anything wrong

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Speaker 1: but lied about something unimportant, should you really should you

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Speaker 1: get the Flynn treatment? Oh yeah, that's right. Flynn had

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Speaker 1: to sell his house to pay his legal bills. General Flynn,

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Speaker 1: he served decades in the military. Does anyone anyone crying

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Speaker 1: for him in the media. No, all, they think that's

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Speaker 1: totally fair. They are exposing themselves. We are seeing how

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Speaker 1: deep the deep state really goes. I would note that

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Speaker 1: some polls came out of the weekend. I think actually

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Speaker 1: CNN might even published one of them about how most

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Speaker 1: people believe there is a deep state. So so we

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Speaker 1: can have academics, right, Snyde pieces about how the deep

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Speaker 1: state in Turkey is a very specific Yet we got

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Speaker 1: an American deep state here, folks, And we already know

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Speaker 1: who some of the compos of this crime family are. Camy, Brannon. Ah,

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Speaker 1: we'll get to Brandon in a second. Don't think he's

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Speaker 1: gonna escape this one. McCabe call me Brennan McCabe, Sally Yates,

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Speaker 1: we're just getting started. There's a whole squad of folks

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Speaker 1: that are click clapper, Oh gosh, be here all day.

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Speaker 1: You know, struck you can get some of the lower

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Speaker 1: level ones to bruce or there was a clear anti

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Speaker 1: Trump effort at the top level of d J. It's

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Speaker 1: being more exposed with all these revelations. But I just

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Speaker 1: on the plane the smallest violent for McCabe ever. Understand,

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Speaker 1: he's sent people to prison. We're lying him many times.

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Speaker 1: He's not getting sent to prison. Other people lie and

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Speaker 1: lose their freedom. He's just getting his pension delayed, which

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Speaker 1: brings me to the oh, pull over the we ambulance

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Speaker 1: retiring at fifty full bench and benefits. That's a good deal.

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Speaker 1: That is a good deal. He's not losing his entire

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Speaker 1: pension everyone. That's not true. He might have to wait now,

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Speaker 1: he might not qualify under the current civil service rules

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Speaker 1: until he's I don't know, uh, sixty two or sixty

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Speaker 1: you know, like normal person retirement age. He might have

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Speaker 1: to do that. Oh no, but you're already seeing a

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Speaker 1: lot of Democrats come out and say that they are

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Speaker 1: willing to hire him. That's how clearly political this is.

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Speaker 1: Right from the beginning. That's how obvious it is that

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Speaker 1: this is just my team, their team. McCabe is anti Trump.

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Speaker 1: Therefore he is embraced by the left. So the Democrats,

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Speaker 1: what do I tell you? Time and again here on

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Speaker 1: the show. The left takes care of its own. The

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Speaker 1: Democrats make sure that anyone who does bad deeds for

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Speaker 1: them has good things come with it. That sends a

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Speaker 1: very important message, right you, some of you are a

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Speaker 1: Game of Thrones fans. I'm sure you know. Lanisters always

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Speaker 1: pay their debts. The left always takes care of its own.

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Speaker 1: You get book deals, you get media contracts, You get

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Speaker 1: you know, chancellorships at universities, board seats on companies. James Comey,

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Speaker 1: who is going to write the most sanctimonious giant pile

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Speaker 1: of Tyrannosaurus Pooh? I think imaginable is now the number

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Speaker 1: one selling author on Amazon in pre sales. Why because

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Speaker 1: everyone assumes that he's gonna, you know, slam Trump. There's

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Speaker 1: gonna be more of what we already know. But getting

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Speaker 1: getting really excited for you know, the the early comy

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Speaker 1: years reas a hall monitors like do you have a

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Speaker 1: pass attention for you? Sanctimonious people don't change. They if

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Speaker 1: they're if they're that annoying, now, trust me, they're annoying

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Speaker 1: in high school too. And I think Comy is he?

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Speaker 1: Is he a New Yorker? I forget is he? I

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Speaker 1: forget where he's Far's in New York or Philly? I

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Speaker 1: don't know. Yeah, yeah, I'm gonna I'm putting him on

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Speaker 1: your doorstep. Quinn, he's a Philly producer. Mike is looking

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Speaker 1: at me all a k A. Quinn. He's a Philly

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Speaker 1: guy if I ever saw one. I'm thinking there's some

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Speaker 1: filling with Comy. And I'm just trying to make him

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Speaker 1: not a New York ais. I'm gonna feel bad about

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Speaker 1: it anyway. So you get this, You get this, uh

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Speaker 1: sense that something terrible has happened because McCay has been fired.

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Speaker 1: Big deal. He's gonna get speaking, big deal, gonna get

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Speaker 1: a big book deal. And what oh he's call me.

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Speaker 1: He's a Catholic school boy from New York like me.

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Speaker 1: I thought, so, oh, dude, some of the worst, some

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Speaker 1: of the best, but some of the worst are from

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Speaker 1: my same my same general you know, pumpkin Patch, so

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Speaker 1: to speak. Right, we're the same me and Comey and

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Speaker 1: uh you know, you know who else Fitzgerald, the special

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Speaker 1: prosecutor in the Valerie Plame case. Whatever, he not only

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Speaker 1: went to my high school, went to my college. I

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Speaker 1: think he's he's also he's also a New York Catholic schoolboy,

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Speaker 1: and he's a super hall monitor and a and a

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Speaker 1: head hunter at the d o J. Who else falls

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Speaker 1: in that, But we got some of the best to

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Speaker 1: Scalia actually went to my rival high school here in

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Speaker 1: New York City, Xavier. We all like to say he

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Speaker 1: didn't get into regions, but then people blew us, so

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Speaker 1: we try not to say that too much publicly. Um,

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Speaker 1: but may he rest in peace. One of the great minds,

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Speaker 1: one of the great legal minds of of all time.

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Speaker 1: Uh So, comey McCabe. We've seen so much of it exposed,

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Speaker 1: but it gets worse, it gets worse. It's not just

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Speaker 1: at the d o J, in the FBI, where they

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Speaker 1: were clear senior officials appointees of the Obama administration, no

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Speaker 1: less President Obama in some cases very close to these

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Speaker 1: individuals who are obviously anti Trump and took actions against

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Speaker 1: the Trump campaign. There's some other folks too who have

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Speaker 1: exposed themselves on social media recently. We will get in

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Speaker 1: to that, including a former director of my own agency.

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Speaker 1: I'm throwing my my own, my pedigree, so to speak,

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Speaker 1: getting thrown to the bus. We got Catholic school guys

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Speaker 1: from New York City like comey being sanctimonious. Then we

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Speaker 1: got Brennan, former CIA director, who went on a do

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Speaker 1: we say tirade or tirade? Do we go both? People?

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Speaker 1: I feel like people go both the tirade? Right, I

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Speaker 1: say tirade, Some people say tarade, I think, or maybe

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Speaker 1: it's a sharade. I don't know, sharade, sharade, tomato tomato.

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Speaker 1: What did Brennan say? And what does it tell us

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Speaker 1: about this whole Russia collusion fiasco? And oh, by the way,

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Speaker 1: Vladimir Puttin on one reelection, we got that, We got

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Speaker 1: a lot more. We're gonna talk about China's theft of

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Speaker 1: intellectual property from the US. Here's what he's there. You go,

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Speaker 1: thank you perfectly. Time dropped. We got China talking about that.

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Speaker 1: We're also gonna get into some discussion of trade and

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Speaker 1: how all this trade war tours or you know, speaking

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Speaker 1: on home monitors some of my conservative buddies on this

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Speaker 1: or throwing a fit. Uh, it doesn't add up, folks,

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Speaker 1: you look at the numbers, it's not that big a deal,

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Speaker 1: no matter how you slice it. It's literally not that

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Speaker 1: big a deal aluminum steel. I'll give you the details

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Speaker 1: in the numbers. When somebody says it's just gonna start

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Speaker 1: a trade war and be like, yeah, this is a

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Speaker 1: tempest in a teapot, not what people are pretending it is.

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Speaker 1: We will also talk a bit about this Cambridge Analytica situation. Um,

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Speaker 1: I can't give you too much of a preview next

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Speaker 1: running the next break, but just all of a sudden,

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Speaker 1: now Facebook and Data are coming under all this scrutiny

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Speaker 1: when well, let's just say that this is this is

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Speaker 1: very very much a partisan narrative that is emerging about

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Speaker 1: all this. Keep in mind that it wasn't long ago

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Speaker 1: that the Obama administration was all about minding everything they

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Speaker 1: could online. Obama's digital team was the best in the business.

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Speaker 1: They're so amazing, the the digital whiz kids that he's

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Speaker 1: got and all that stuff. Now it's like, oh my gosh,

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Speaker 1: they're looking at social media profile and information and making

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Speaker 1: political determinations about it. Good heavens, yeah, of course they are.

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Speaker 1: This is this is a surprise there should be a

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Speaker 1: surprise to no one. But because Trump did it, you

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Speaker 1: know it must be bad. That's the idea. Because Trump's

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Speaker 1: team did it, Now it's evil. Now all of a sudden,

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Speaker 1: the incredible surveillance machine that is the Internet is scary.

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Speaker 1: Wasn't scary for eight years of Obama, who, by the way,

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Speaker 1: I actually did spy on journalists and do all kinds

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Speaker 1: of super shady bad stuff. But you know, it wasn't

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Speaker 1: a problem that now it's a problem. It's almost like

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Speaker 1: journalists were all at sleepaway camp for eight years and

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Speaker 1: now they've now they've come back and they actually want

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Speaker 1: to do their jobs. In fact, that's exactly what it's like. Um,

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Speaker 1: all right, we're gonna head a quick break eight four

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Speaker 1: eight to five eight four f buck, we have much

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Speaker 1: more show. Stay with You don't get to decide when

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Speaker 1: to tell the truth and when not to. I'm gonna

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Speaker 1: withhold judgment until Horowitz's report comes out because I don't

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Speaker 1: say what he found, just say, Harowitz is the inspector general.

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Speaker 1: Let's wait and see what he found. Let's wait and

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Speaker 1: see what that lack of candor was, and then we

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Speaker 1: could judge the fact pattern and the proportionality of the

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Speaker 1: penalty of his losing his pension. We can judge all

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Speaker 1: that once we understand exactly what he's alleged to a

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Speaker 1: vain but but make no mistake, the FBI is who

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Speaker 1: recommended that he be fired. It wasn't crazy House Republicans,

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Speaker 1: and it wasn't a Trump administration. It was his own

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Speaker 1: fellow bureau agents. The facts with regard to McCabe are

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Speaker 1: very important. They basically have said that McCabe leaked classified documents.

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Speaker 1: That's illegal, but then he also lied about leaking classified documents,

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Speaker 1: and so you know the fbire sticklers on this, and

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Speaker 1: they don't tolerate lying from their agents. And so if

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Speaker 1: all that's true, I see no way that he could

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Speaker 1: continue in his office, and that punishment is appropriate. Does

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Speaker 1: anyone have an argument against what was said there by

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Speaker 1: Trey Gaudy and then Rand Paul. You know, I think

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Speaker 1: those are two of them, two of the Republicans that

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Speaker 1: you can count on to to call bs when they

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Speaker 1: see it either way. You know, I think that Rampaul

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Speaker 1: is an honest and ethical guy. I don't think he's

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Speaker 1: always right, but I think he's honest and ethical. I

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Speaker 1: don't think that he is too clouded with partisanship to

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Speaker 1: see things for what they are. Um and I feel

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Speaker 1: the same way about Very Gaudy, although I don't know.

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Speaker 1: I think because Gouty's not run anymore, I start to

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Speaker 1: feel like he's he's lost his edge, or maybe I'm

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Speaker 1: just seeing it more. It seems to me like he's

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Speaker 1: a little too like, well, you know, i'd like the

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Speaker 1: New York Times right, nice things about me. Sometimes it's

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Speaker 1: very dangerous for Republicans. They write nice things about you

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Speaker 1: for a day and then they trash you, and your

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Speaker 1: own people think you're a sellout. You don't want to

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Speaker 1: go down that path. But I mentioned before we went

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Speaker 1: into the break that it's not just d Oh, It's

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Speaker 1: not just McCabe and Comy and all these other senior

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Speaker 1: FBI folks who are a problem. There's a lot more

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Speaker 1: when you look at this, including John Brennan, close confidante

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Speaker 1: of President Obama's and the former director of the Central

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Speaker 1: Intelligence Agents. And keep in mind, folks, that being the

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Speaker 1: director of the CIA, it's not like rising to be

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Speaker 1: the CEO of a company where like the best person

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Speaker 1: gets the job or somebody with a proven track record.

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Speaker 1: A lot of the time. These jobs, I'm just gonna

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Speaker 1: say it, go to somebody who the president likes and wants.

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Speaker 1: That person in the role was Leon Panetta, some intel genius.

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Speaker 1: No Obama liked him. He had some background. They put

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Speaker 1: him in these places, right, I mean any number And

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Speaker 1: there have been some really Panetta was actually okay as

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Speaker 1: directors go. I'm from what I'm told from people who

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Speaker 1: were there, and no, uh, there have been some really crap,

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Speaker 1: lousy CIA directors over the years. But Brennan was o

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Speaker 1: Amas Aids the director, and he was known to be

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Speaker 1: very chummy with the press and reputed to want to

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Speaker 1: get certain narratives out there into the media. And he

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Speaker 1: tweeted out in response to the McCabe firing the following.

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Speaker 1: This is a quote from the former CI director of

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Speaker 1: the obaministration. By the way, the same CI director who

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Speaker 1: was very much pushing the Russia collusion narrative with the

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Speaker 1: Trump campaign in full swing during the election. You know,

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Speaker 1: Brennan was one who was waiving the flags and screaming about,

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Speaker 1: oh look at all the Russia. You know, he was

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Speaker 1: the one, right, or one of a few. Now we

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Speaker 1: find out what he thinks of Trump and oh gosh,

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Speaker 1: you're not going to be surprised by this at all,

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Speaker 1: are you? Folks? Quote when the full this is in

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Speaker 1: response to President Trump directly on Twitter, this is blue

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Speaker 1: check warfare, blue check to blue check. When the full

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Speaker 1: extent of your venality, moral turpitude, and political corruption becomes

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Speaker 1: no own, you will take your rightful place as a

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Speaker 1: disgrace demagogue in the dustbin of history. You may scapegoat

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Speaker 1: Andy McCabe, but you will not destroy America. America will

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Speaker 1: triumph over you. I ask you, my friends, at all honesty.

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Speaker 1: Does that not seem like a slightly unhinged thing for

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Speaker 1: a former CI director to write about the current commander

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Speaker 1: in chief? You will not destroy America. America will triumph

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Speaker 1: over you. So we only have a few options here.

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Speaker 1: Are the former CI director in Obama's buddy is losing

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Speaker 1: it or he thinks that Trump is a clear in

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Speaker 1: present danger of the United States. And if that were

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Speaker 1: the case, what would the former CI director have been

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Speaker 1: willing to do against Trump? While still director? He's holding

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Speaker 1: the line for America. Buck Sexton is tex laugh. I

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Speaker 1: don't know. I mean, at this point, it does feel

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Speaker 1: as if you know it's one you talked to one

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Speaker 1: set of people and they think the wheels are coming

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Speaker 1: off this administration, and you talked to another set and

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Speaker 1: it's exactly the presidency that they wanted. So but the

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Speaker 1: fact of the matter is, I don't know if our

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Speaker 1: institutions can handle what Trump is doing. We can't seem

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Speaker 1: to see if our institutions are going to survive the

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Speaker 1: emotional spasms of Twitter. The great line, what does that

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Speaker 1: say about our institutions? By the way, if if Trump's

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Speaker 1: Twitter account can bring them tumbling down, they're not very durable,

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Speaker 1: are they. Now that's also crazy because Trump's Twitter is

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Speaker 1: not going to bring anything telling down, which is when

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Speaker 1: when you look at what's being said some of the

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Speaker 1: narratives that have gained traction on the left, you know

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Speaker 1: that these anti Trump stories, they're almost like bedtime stories

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Speaker 1: now the Democrats tell each other so they can sleep

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Speaker 1: at night. They're just nonsensical. They don't add up their

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Speaker 1: self contradictory. Did you get Chuck Todd there saying, you know,

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Speaker 1: I just don't know if our institutions can just I

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Speaker 1: don't know if they can survive. Well, if an institution

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Speaker 1: like the FBI is going to survive the Inspector General

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Speaker 1: has to be able to look for misconduct and when

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Speaker 1: it finds it has to be able to punish it. Right,

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Speaker 1: So this is this is not the least bit surprising

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Speaker 1: from that respect. So I just look at this and

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Speaker 1: I say to myself, what are they even talking about

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Speaker 1: with this? It was an institution operating exactly as it

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Speaker 1: should that fired Andrew McCabe from his job at the FBI.

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Speaker 1: I would notice that what rand Paul said. I'm not

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Speaker 1: sure if that has been verified or not yet. I

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Speaker 1: think that he was my impression from what I've read,

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Speaker 1: and I'm admitting that I haven't read the IG report.

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Speaker 1: Nobody is talking about this has read the IG report yet. Um,

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Speaker 1: but we don't know if it was classified information or not.

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Speaker 1: That he it was classified information, then he has to

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Speaker 1: be fired. And also then there's the issue of why

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Speaker 1: why doesn't he have criminal charges? But if we're just

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Speaker 1: talking about even uh internal information given to the press

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Speaker 1: that he then lied about that, why would he not

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Speaker 1: get fired for that? It just doesn't it again, it

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Speaker 1: doesn't add up, but it does not make sense. But

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Speaker 1: they are completely as you know, in the tank and

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Speaker 1: devoted to doing everything they can to make the president

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Speaker 1: look bad, up to including embarrassing themselves. They will be embarrassed.

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Speaker 1: They will be embarrassed if and when we ever find

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Speaker 1: out exactly what the allegations were in that Inspector General report.

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Speaker 1: That much I can tell you because they just see,

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Speaker 1: Oh someone was fired who was working against Trump. It

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Speaker 1: must be Trump's fault. That's not true. That's not the

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Speaker 1: way that this works. Are We got a bunch of calls,

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Speaker 1: so let's take some of them before we move on.

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Speaker 1: I want to get into some calls before we switch topics.

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Speaker 1: We'll start with Dean in Boston. What's up, Dean doing good?

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Speaker 1: Track by Elizabeth Warren and Ed Markey, So I'll be quick.

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Speaker 1: So this is funny. I'm listening to our own Seth

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Speaker 1: Moulton from Massachusetts who says that he would hire this

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Speaker 1: guy for three days so he can reach his pension.

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Speaker 1: And I stiled, thinking, who retires att with a full pension?

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Speaker 1: And why would someone who has that higher level job

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Speaker 1: decide all of a sudden, you know what I need

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Speaker 1: to put in from my retirement, and I need to

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Speaker 1: get out, and this is the earliest date that I

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Speaker 1: can get out. I don't know what the did he

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Speaker 1: just put that in and said I gotta get out

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Speaker 1: of gain. Well, it might have been his planning all along,

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Speaker 1: because let me think about if you can get your

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Speaker 1: full retirement at fifty, right, wuldn't you do? What did

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Speaker 1: you take it? I don't know if this was the

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Speaker 1: plan all along. He obviously went early because he was

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Speaker 1: gonna run out, you know, he was trying to run

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Speaker 1: out the clock and and had come under a lot

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Speaker 1: of scrutiny. The thing is, people ask me like, oh, Buck,

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Speaker 1: do you know what I mean? I was in the

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Speaker 1: c I A. I obviously wasn't a career officer who

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Speaker 1: spent twenty years there because then I would have had

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Speaker 1: to start when I was like five. So I don't.

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Speaker 1: I don't know how the vesting process works and all that.

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Speaker 1: What I can tell you, uh, is that one it

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Speaker 1: is very hard to get fired from these places. You

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Speaker 1: have to do something usually illegal. That's what I always

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Speaker 1: tell everybody. If you show up on time, if you

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Speaker 1: are where you are supposed to be for your job

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Speaker 1: in the federal government, when you're supposed to be there,

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Speaker 1: and you don't actively break the law, it's still and

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Speaker 1: but you refuse to do any work of any kind.

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Speaker 1: It still takes a long time to fire you. So

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Speaker 1: that's the way the civil service procedures work. And I

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Speaker 1: know that for some of these gigs. Look, some people

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Speaker 1: have great deals. I could sit here and talk to

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Speaker 1: you about, like UH fireman's pensions in UH California, for example,

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Speaker 1: and some of the major cities California. They are lucrative.

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Speaker 1: They ever, that's the deal, that's what they saw it

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Speaker 1: up for. But they've got great deals. The FBI think

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Speaker 1: has a pretty good deal. I would note that I've

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Speaker 1: read this today and we haven't checked on this, so

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Speaker 1: Mike got a fact check me on this one, Producer, Mike,

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Speaker 1: if I'm if I'm off. I read today that Anthony Weener,

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Speaker 1: who is currently serving I believe a federal prison sentence.

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Speaker 1: He's in prison now right. Anthony Weiner, who is a

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Speaker 1: convicted sex offender, will get a million what is the

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Speaker 1: equivalent of a million dollars worth of benefits for his

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Speaker 1: pension as a former member of Congress, despite being a

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Speaker 1: convicted felon sex offender. So there are some places where

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Speaker 1: you get great It's a great gig, Dean, if you

424
00:24:38,240 --> 00:24:43,040
Speaker 1: can get it in terms of the pension. Yeah, worth

425
00:24:43,119 --> 00:24:45,920
Speaker 1: one point two millions, worth one point to million. Do

426
00:24:46,000 --> 00:24:47,920
Speaker 1: we lose Dean or it is Dean just in awe

427
00:24:47,960 --> 00:24:52,000
Speaker 1: of all the knowledge bombs, I'm dropping you there, Oh,

428
00:24:52,000 --> 00:24:55,359
Speaker 1: there you go. Sorry, now I've done it. What do

429
00:24:55,440 --> 00:24:57,399
Speaker 1: I say to the American public that a House of

430
00:24:57,440 --> 00:25:02,159
Speaker 1: Representatives member who were thinking math has kind of hidden

431
00:25:02,200 --> 00:25:04,080
Speaker 1: agenda to try and get his name out for the

432
00:25:04,760 --> 00:25:07,800
Speaker 1: presidency sometime in the near future. But what does it

433
00:25:07,880 --> 00:25:10,719
Speaker 1: say that they step up after the Federal Bureau of

434
00:25:10,760 --> 00:25:15,040
Speaker 1: Investigation kind of internal affairs department and an inspector general,

435
00:25:15,040 --> 00:25:20,679
Speaker 1: a completely separate agency, decide that this person should be terminated,

436
00:25:20,880 --> 00:25:23,240
Speaker 1: and he then steps up and says, you know what,

437
00:25:23,359 --> 00:25:25,240
Speaker 1: I'll hire him from three days so he can get

438
00:25:25,240 --> 00:25:28,399
Speaker 1: his pension, right exactly? What what are we supposed to

439
00:25:28,400 --> 00:25:31,800
Speaker 1: think of our trusted institutions then? And this is this

440
00:25:31,840 --> 00:25:35,159
Speaker 1: is like the equivalent of saying, well, the FBI's processes

441
00:25:35,200 --> 00:25:38,320
Speaker 1: don't matter anymore. What matters is getting Trump and what

442
00:25:38,400 --> 00:25:40,600
Speaker 1: manages supporting people who tried to get Trump. That's what

443
00:25:40,640 --> 00:25:43,959
Speaker 1: they're saying. Yeah, yeah, alright, Dean shields him and thank

444
00:25:44,000 --> 00:25:46,119
Speaker 1: you very much for the call. Dean isn't a stute fellow.

445
00:25:47,119 --> 00:25:52,840
Speaker 1: Charlie in Ocean City, Maryland. Hey, Charlie, Hey Buck, I'm

446
00:25:52,880 --> 00:25:57,440
Speaker 1: glad you call and shields high brother. How do you sir? Hey?

447
00:25:57,560 --> 00:26:00,960
Speaker 1: I was just listening earlier to day on some talk

448
00:26:01,000 --> 00:26:04,520
Speaker 1: shows and they pointed out there's a report out that

449
00:26:04,680 --> 00:26:10,640
Speaker 1: McCabe is actually net worst about eleven mill And I'm

450
00:26:10,720 --> 00:26:14,480
Speaker 1: trying to think I was just a simple bricklayer. If

451
00:26:14,480 --> 00:26:17,960
Speaker 1: he made a hundred thousand a year in twenty years,

452
00:26:17,960 --> 00:26:21,919
Speaker 1: that's only two mills. How do you get eleven? Well,

453
00:26:21,960 --> 00:26:26,159
Speaker 1: his wife is a doctor, right, uh huh, So, I

454
00:26:26,160 --> 00:26:28,840
Speaker 1: mean she might be making I don't know, I don't

455
00:26:28,840 --> 00:26:30,919
Speaker 1: know what. I don't know what doctors in Virginia. She

456
00:26:31,000 --> 00:26:34,000
Speaker 1: was a primary care physician. I believe she could probably

457
00:26:34,000 --> 00:26:37,960
Speaker 1: make a half million dollars a year. Yeah, So I

458
00:26:38,000 --> 00:26:41,320
Speaker 1: mean the man, okay, his pench is what fifty six

459
00:26:41,400 --> 00:26:44,760
Speaker 1: thousand a year. If you're asking me, how are they

460
00:26:44,760 --> 00:26:47,520
Speaker 1: gonna have a networthy of eleven million, Charlie, the answer is,

461
00:26:47,640 --> 00:26:50,760
Speaker 1: I I don't know, um, but it's worth looking into.

462
00:26:51,040 --> 00:26:52,480
Speaker 1: But you know, they could have family, you know, she

463
00:26:52,520 --> 00:26:54,119
Speaker 1: could have family money. There's a lot of ways that

464
00:26:54,160 --> 00:26:56,760
Speaker 1: people can have money that don't necessarily you know. I

465
00:26:56,760 --> 00:27:00,000
Speaker 1: but I see this with who is the guy um

466
00:27:00,280 --> 00:27:05,680
Speaker 1: senator from Arizona who was the majority Harry Reid. How

467
00:27:05,800 --> 00:27:08,040
Speaker 1: is it that Harry Reid was what could afford living

468
00:27:08,040 --> 00:27:10,240
Speaker 1: in an in an apartment in the Ritz Carlton, which

469
00:27:10,280 --> 00:27:12,320
Speaker 1: is like the most expensive place in all of d C.

470
00:27:12,600 --> 00:27:14,320
Speaker 1: That was where he lived when he was in d C.

471
00:27:15,000 --> 00:27:17,480
Speaker 1: Where in Harry Reagan that kind of cash? I don't know.

472
00:27:18,640 --> 00:27:20,800
Speaker 1: Look at their friend Nancy, I mean she well she

473
00:27:20,880 --> 00:27:25,320
Speaker 1: married a rich guy. Yeah, that's the old fashioned way

474
00:27:26,200 --> 00:27:27,760
Speaker 1: marry somebody a lot of money. That's a good way

475
00:27:27,800 --> 00:27:30,119
Speaker 1: to do it. Charlie Shields simment, thank you for calling in.

476
00:27:30,280 --> 00:27:33,680
Speaker 1: I'll look a little more into whether or not McCabe.

477
00:27:34,680 --> 00:27:38,280
Speaker 1: You know, but that's there's always the option of your

478
00:27:38,359 --> 00:27:46,560
Speaker 1: family money. Uh maybe maybe Dr McCabe writes novels under

479
00:27:46,560 --> 00:27:48,080
Speaker 1: a pen name and it's done very well. You know.

480
00:27:48,080 --> 00:27:49,560
Speaker 1: There's all kinds of ways that people make money you

481
00:27:49,560 --> 00:27:51,920
Speaker 1: woun't know about, but it's it's worth looking, worth looking

482
00:27:51,920 --> 00:27:54,840
Speaker 1: to do. I would say this, I'm guessing FBI has

483
00:27:54,840 --> 00:27:58,440
Speaker 1: financial disclosures and so they probably know a whole lot

484
00:27:58,480 --> 00:28:02,719
Speaker 1: about how McCabe did or did not make money. Um,

485
00:28:02,760 --> 00:28:05,639
Speaker 1: so I'm not seeing that is a big issue, but

486
00:28:05,800 --> 00:28:07,560
Speaker 1: I'll keep an eye on it. I'll make that promise

487
00:28:07,560 --> 00:28:12,840
Speaker 1: to you. I want to switch gears because Cambridge Analytica

488
00:28:13,000 --> 00:28:16,879
Speaker 1: is getting a lot of attention. Facebook lost billions of

489
00:28:16,920 --> 00:28:20,440
Speaker 1: dollars in value today. It was down about five scent

490
00:28:20,560 --> 00:28:22,240
Speaker 1: something like that. In trading. I don't pay that close

491
00:28:22,280 --> 00:28:24,480
Speaker 1: attention to the markets, but Facebook had a very bad day.

492
00:28:24,480 --> 00:28:28,840
Speaker 1: Everyone's freaking out about this thing, and to me, well

493
00:28:28,880 --> 00:28:31,000
Speaker 1: a few things. One is that they're freaking out because

494
00:28:31,000 --> 00:28:34,480
Speaker 1: it involves Trump, so that always automatically, when Trump's arrangement

495
00:28:34,520 --> 00:28:38,720
Speaker 1: syndrome kicks in, everything is oh my gosh. Uh. But

496
00:28:38,800 --> 00:28:42,880
Speaker 1: they're acting like it's a huge surprise that people will

497
00:28:43,040 --> 00:28:48,000
Speaker 1: use the data they can glean from social media and

498
00:28:48,120 --> 00:28:51,720
Speaker 1: uh use that for the purposes of constructing political messaging

499
00:28:51,760 --> 00:28:56,680
Speaker 1: and memes and campaigns and everything else. Social media makes.

500
00:28:57,200 --> 00:29:00,160
Speaker 1: The reason these places are are so lucrative, and the

501
00:29:00,200 --> 00:29:02,880
Speaker 1: reason they offer you a service for free is to

502
00:29:02,960 --> 00:29:06,080
Speaker 1: aggregate your data to then capitalize off of that data.

503
00:29:06,160 --> 00:29:10,040
Speaker 1: That that is what social media does. That is how

504
00:29:10,160 --> 00:29:14,600
Speaker 1: Facebook is essentially a giant printing press. Of money, They

505
00:29:14,640 --> 00:29:18,040
Speaker 1: take the information about you, they take your activities, and

506
00:29:18,080 --> 00:29:23,040
Speaker 1: then they tailor advertising to you. And Facebook, by the way,

507
00:29:23,080 --> 00:29:25,840
Speaker 1: has clamped down hard on just you know, the way

508
00:29:25,880 --> 00:29:29,480
Speaker 1: that they are doing things these days. And it's their

509
00:29:29,480 --> 00:29:30,960
Speaker 1: way or the highway. As I've been saying for a

510
00:29:30,960 --> 00:29:36,960
Speaker 1: long time, we are in these progressive left wing mega

511
00:29:37,040 --> 00:29:40,400
Speaker 1: platforms and there's been no choice for a lot of folks.

512
00:29:40,400 --> 00:29:43,160
Speaker 1: You know. People now are well, I'm gonna I'm gonna

513
00:29:43,160 --> 00:29:45,200
Speaker 1: go in a whole rand here about something else. Cambridge

514
00:29:45,200 --> 00:29:50,360
Speaker 1: Analytica involved at the Trump campaign. People are freaking out why.

515
00:29:50,640 --> 00:30:05,560
Speaker 1: I'll answer the question after the break. Cambridge Analytic UH

516
00:30:05,840 --> 00:30:08,160
Speaker 1: was birthed out of a company called scl Group, which

517
00:30:08,160 --> 00:30:12,200
Speaker 1: is a military contractor based in London. It UH this

518
00:30:12,400 --> 00:30:17,960
Speaker 1: this data was used to create profiling algorithms that would

519
00:30:18,000 --> 00:30:22,520
Speaker 1: allow us to explore mental vulnerabilities of people UM and

520
00:30:22,560 --> 00:30:27,240
Speaker 1: then map out wigs to UH inject information into different

521
00:30:27,840 --> 00:30:31,360
Speaker 1: different streams or channels of content online so that people

522
00:30:31,680 --> 00:30:33,880
Speaker 1: started to see things all over the place that that

523
00:30:33,960 --> 00:30:35,719
Speaker 1: may or may not have been true. This is a

524
00:30:35,760 --> 00:30:39,800
Speaker 1: company that that really took fake news to to the

525
00:30:39,840 --> 00:30:44,160
Speaker 1: next level by powering it with algorithms So that's Christopher Wiley,

526
00:30:44,280 --> 00:30:48,600
Speaker 1: who helped found the data firm Cambridge Analytica. It's getting

527
00:30:48,640 --> 00:30:53,160
Speaker 1: so much news media attention right now and people are

528
00:30:53,160 --> 00:30:55,600
Speaker 1: talking about how it has well. He said that it

529
00:30:55,600 --> 00:30:59,360
Speaker 1: has an arsenal of weapons in a culture war as

530
00:30:59,400 --> 00:31:02,920
Speaker 1: I understand it. Here's what's happened. You have different companies

531
00:31:02,920 --> 00:31:06,120
Speaker 1: that are always trying to find ways to aggregate the

532
00:31:06,320 --> 00:31:08,760
Speaker 1: stuff that we're all doing online all the times. These

533
00:31:08,760 --> 00:31:13,880
Speaker 1: social media platforms, my friends, are like intel collectors on you.

534
00:31:14,960 --> 00:31:18,440
Speaker 1: Every click, every look, every like, all the stuff we're

535
00:31:18,440 --> 00:31:20,240
Speaker 1: doing all the time. We just think it goes into

536
00:31:20,320 --> 00:31:24,240
Speaker 1: some you know, vast cloud and who cares? And sure

537
00:31:24,400 --> 00:31:27,120
Speaker 1: that's somewhat true. Although I've been saying for a while,

538
00:31:27,240 --> 00:31:30,600
Speaker 1: just wait until one of these social media companies decides

539
00:31:30,680 --> 00:31:34,200
Speaker 1: to release the you know, private chat that some guy

540
00:31:34,200 --> 00:31:36,400
Speaker 1: had on Facebook with his mistress twenty years ago when

541
00:31:36,440 --> 00:31:40,800
Speaker 1: he's running for president, Because that's gonna happen. Guaranteed that's

542
00:31:40,800 --> 00:31:43,880
Speaker 1: gonna happen, just a question of when. And people say, oh, well,

543
00:31:43,920 --> 00:31:45,840
Speaker 1: you know, they're private company, they can do whatever they want.

544
00:31:46,080 --> 00:31:48,120
Speaker 1: What are you gonna do? They violated their terms of

545
00:31:48,160 --> 00:31:49,840
Speaker 1: service and they can say they changed their terms of

546
00:31:49,880 --> 00:31:54,360
Speaker 1: service the private company. Unless Congress passes laws to protect

547
00:31:54,400 --> 00:31:57,600
Speaker 1: people from the exploitation of their private information on these

548
00:31:57,600 --> 00:32:02,080
Speaker 1: social on these third party platforms, then that's the way.

549
00:32:02,120 --> 00:32:04,840
Speaker 1: That's the way it's gonna be. But so, here's what

550
00:32:04,880 --> 00:32:08,080
Speaker 1: happened with Camera gen Analytical. They are a group that's

551
00:32:08,760 --> 00:32:11,040
Speaker 1: looking at all this different social media data and they're

552
00:32:11,080 --> 00:32:14,880
Speaker 1: trying to find ways to create the most well to

553
00:32:15,000 --> 00:32:20,480
Speaker 1: understand the psyche of the masses really and then they

554
00:32:20,520 --> 00:32:25,200
Speaker 1: exploit that information. They exploit exploit that information advantage for

555
00:32:25,440 --> 00:32:28,680
Speaker 1: the purposes of politics. In this case, it seems that

556
00:32:28,720 --> 00:32:33,080
Speaker 1: they may have hired a company Cambridge Analytica, and their

557
00:32:33,120 --> 00:32:35,760
Speaker 1: ties to the Mercers and Benning and this is all,

558
00:32:35,760 --> 00:32:38,400
Speaker 1: oh my gosh, you know there you mind, you know,

559
00:32:38,440 --> 00:32:43,400
Speaker 1: the the Obama team back in twelve and uh two

560
00:32:43,400 --> 00:32:45,520
Speaker 1: thousand and eight, they were doing stuff that people thought,

561
00:32:45,560 --> 00:32:48,040
Speaker 1: oh my gosh, you know, they're look at how great

562
00:32:48,040 --> 00:32:51,720
Speaker 1: their digital team is looking at all this Facebook information

563
00:32:51,720 --> 00:32:54,400
Speaker 1: and data, and everyone's crunching all these numbers all the time.

564
00:32:55,200 --> 00:32:57,680
Speaker 1: The problem that, well, there's a few things going on

565
00:32:57,720 --> 00:32:59,760
Speaker 1: here with the Camera Generalytic. One of them is they

566
00:32:59,760 --> 00:33:03,080
Speaker 1: may have hired another company to be kind of a

567
00:33:03,200 --> 00:33:07,640
Speaker 1: front that would have you take a personality quiz and

568
00:33:07,680 --> 00:33:10,080
Speaker 1: then you answer all these questions about yourself. And I

569
00:33:10,120 --> 00:33:12,560
Speaker 1: think it might have also given you might have also

570
00:33:12,600 --> 00:33:17,920
Speaker 1: given that app uh access to your data, your friend lists,

571
00:33:17,920 --> 00:33:19,800
Speaker 1: your likes, all that stuff. And this is standard. A

572
00:33:19,840 --> 00:33:21,560
Speaker 1: lot of these apps say you know, can I have

573
00:33:21,600 --> 00:33:24,200
Speaker 1: access to? And it lists all the different things. This

574
00:33:24,280 --> 00:33:26,360
Speaker 1: is the brave new world we live in now. And

575
00:33:26,360 --> 00:33:30,040
Speaker 1: if you say yes, then guess what that means that

576
00:33:30,040 --> 00:33:33,320
Speaker 1: that service has access to sure enough all that stuff,

577
00:33:33,520 --> 00:33:34,800
Speaker 1: which is why a lot of these things that we

578
00:33:34,840 --> 00:33:38,960
Speaker 1: think are free are free for us. But they do

579
00:33:39,040 --> 00:33:41,920
Speaker 1: come at a cost. And the cost is your information

580
00:33:41,960 --> 00:33:45,960
Speaker 1: and your privacy. And that information is now out there.

581
00:33:46,680 --> 00:33:48,960
Speaker 1: And if you think it's protected, just start reading about

582
00:33:49,000 --> 00:33:52,719
Speaker 1: some of the major cyber breaches that have happened, and

583
00:33:52,720 --> 00:33:56,640
Speaker 1: including places like the government and and others that their

584
00:33:56,720 --> 00:34:00,000
Speaker 1: whole reason for existing is to prevent cyber breaches. Right there.

585
00:34:00,360 --> 00:34:02,560
Speaker 1: They're doing a lot of work, a lot of effort

586
00:34:02,600 --> 00:34:06,120
Speaker 1: to try and make sure that does not happen, and

587
00:34:06,160 --> 00:34:09,040
Speaker 1: they get breached. So don't think that all Facebook has

588
00:34:09,160 --> 00:34:13,200
Speaker 1: it. It It must be safe. But they you heard that

589
00:34:13,239 --> 00:34:16,360
Speaker 1: guy wildy when we started the segment here saying that

590
00:34:16,360 --> 00:34:21,120
Speaker 1: they're like weaponizing people's ideas, exploding psychological vulnerabilities. Another way

591
00:34:21,160 --> 00:34:22,719
Speaker 1: of saying it is, yeah, they're figuring out what's on

592
00:34:22,719 --> 00:34:27,920
Speaker 1: people's minds, what's popular, and then they're constructing narratives and stories,

593
00:34:27,960 --> 00:34:31,000
Speaker 1: and maybe that includes fake news, maybe it doesn't. Probably

594
00:34:31,040 --> 00:34:34,080
Speaker 1: does that will get the most clicks and shares and

595
00:34:34,080 --> 00:34:36,520
Speaker 1: everything else. By the way, every media entity I know

596
00:34:36,680 --> 00:34:40,040
Speaker 1: is doing this in one way or another. This is

597
00:34:40,080 --> 00:34:42,000
Speaker 1: the game now, folks. This is what is going on.

598
00:34:42,440 --> 00:34:46,920
Speaker 1: It's only being treated as so nefarious now because it

599
00:34:47,000 --> 00:34:49,879
Speaker 1: involves Trump and some of the Trump or Trump's associates,

600
00:34:49,880 --> 00:34:53,680
Speaker 1: people like Bannon and Mercer, who is bankrolling Trump. She's

601
00:34:53,719 --> 00:34:57,880
Speaker 1: the daughter of the billionaire Robert Mercer. And this is

602
00:34:57,880 --> 00:35:01,759
Speaker 1: going on in all kinds of ways. I have seen

603
00:35:01,800 --> 00:35:04,360
Speaker 1: this coming for a while. I've been trying to sound

604
00:35:04,400 --> 00:35:06,560
Speaker 1: the alarm as much as possible that the Internet in

605
00:35:06,600 --> 00:35:09,840
Speaker 1: particularly with the advent of the social media platforms and

606
00:35:09,880 --> 00:35:12,839
Speaker 1: their dominance in our discourse. I mean, I know people

607
00:35:12,880 --> 00:35:14,040
Speaker 1: now who are like, well, you know, I'm just gonna

608
00:35:14,080 --> 00:35:16,360
Speaker 1: build my business. I'm just gonna sell directly over Facebook

609
00:35:16,360 --> 00:35:18,920
Speaker 1: and I'm like, Okay, you can do that for a while.

610
00:35:19,000 --> 00:35:21,760
Speaker 1: But guess what happens when Facebook realizes that your company

611
00:35:21,800 --> 00:35:24,200
Speaker 1: is deriving a vast majority of its revenue from them?

612
00:35:24,239 --> 00:35:25,680
Speaker 1: Do you do you think that they can know that

613
00:35:25,760 --> 00:35:29,160
Speaker 1: and then decide that they're gonna use the leverage they

614
00:35:29,160 --> 00:35:32,359
Speaker 1: have over you to demand even higher rates and more.

615
00:35:32,400 --> 00:35:36,120
Speaker 1: You know, we're giving so much power to these things.

616
00:35:36,200 --> 00:35:41,719
Speaker 1: Facebook is the biggest example, but you know, Twitter, um, Instagram, Snapchat,

617
00:35:41,760 --> 00:35:44,480
Speaker 1: which I've always thought was kind of garbage, um, but

618
00:35:45,400 --> 00:35:48,880
Speaker 1: these are collecting information on millions and millions of people

619
00:35:49,880 --> 00:35:54,400
Speaker 1: and they're using that. Make no mistake about it. They

620
00:35:54,400 --> 00:35:56,680
Speaker 1: are using the information they get from your day to

621
00:35:56,719 --> 00:36:00,480
Speaker 1: day activities, every like, every click, every digital thought that

622
00:36:00,560 --> 00:36:06,200
Speaker 1: you leave online, and that may not be used against

623
00:36:06,320 --> 00:36:09,320
Speaker 1: you personally, but it will be used by these companies

624
00:36:09,360 --> 00:36:13,719
Speaker 1: to get an information advantage. And in the massive digital

625
00:36:13,840 --> 00:36:18,719
Speaker 1: propaganda wars that are going on right now, social media

626
00:36:18,760 --> 00:36:21,239
Speaker 1: platforms are the front line. Um more on camera. Ge

627
00:36:21,239 --> 00:36:35,280
Speaker 1: Atletic a for you tomorrow, promise he's holding the line

628
00:36:35,680 --> 00:36:40,319
Speaker 1: for America. Buck sex in his back. This neighborhood is

629
00:36:40,360 --> 00:36:44,239
Speaker 1: still being locked down right now for safety. Again, we're

630
00:36:44,239 --> 00:36:46,960
Speaker 1: doing this in over abundance of caution so that we

631
00:36:47,000 --> 00:36:49,640
Speaker 1: can keep this neighborhood safe. What we process the scene.

632
00:36:50,160 --> 00:36:52,600
Speaker 1: What I can tell you is based on the preliminary

633
00:36:52,680 --> 00:36:56,280
Speaker 1: review we have done at this time. We have seen

634
00:36:56,480 --> 00:37:00,880
Speaker 1: similarities in the device that exploded here last night and

635
00:37:00,920 --> 00:37:04,560
Speaker 1: the other three devices that have exploded in Austin starting

636
00:37:04,600 --> 00:37:08,440
Speaker 1: on March two. Again, this is preliminary information, but we

637
00:37:08,600 --> 00:37:12,600
Speaker 1: have seen similarities. The big difference in this device again

638
00:37:13,040 --> 00:37:15,480
Speaker 1: is we believe that a trip wire was used in

639
00:37:15,520 --> 00:37:19,000
Speaker 1: this device. Welcome to our to of the Buck Sexton Show,

640
00:37:19,560 --> 00:37:24,279
Speaker 1: Tough News out of Austin, Texas, where you have a

641
00:37:24,360 --> 00:37:27,759
Speaker 1: fourth a fourth bomb exploding this time, as you heard

642
00:37:27,840 --> 00:37:32,000
Speaker 1: from the Austin Police Chief, there as a result of

643
00:37:32,280 --> 00:37:36,280
Speaker 1: a trip wire, so a more sophisticated device. And now

644
00:37:37,400 --> 00:37:42,239
Speaker 1: the narrative from law enforcement down in Austin when we're

645
00:37:42,239 --> 00:37:46,520
Speaker 1: hearing it has shifted away from what was initially it

646
00:37:46,560 --> 00:37:53,440
Speaker 1: seemed like some perhaps even hate crime based attacks. So

647
00:37:53,560 --> 00:37:57,480
Speaker 1: now they just have a madman, a serial bomber on

648
00:37:57,520 --> 00:38:00,319
Speaker 1: the loose, and they have very little to work with.

649
00:38:00,400 --> 00:38:04,279
Speaker 1: From what we've been told so far, you've got four bombings.

650
00:38:04,560 --> 00:38:07,960
Speaker 1: There have been fatalities, there have also been some people

651
00:38:08,120 --> 00:38:12,279
Speaker 1: wounded as a result of it, and they're looking for

652
00:38:12,320 --> 00:38:15,520
Speaker 1: help right now down in Austin. They're looking for someone

653
00:38:15,600 --> 00:38:20,040
Speaker 1: to come forward from the public, because the analysis of

654
00:38:20,680 --> 00:38:26,360
Speaker 1: an actual bomb after it's gone off is a painstaking process.

655
00:38:26,440 --> 00:38:28,320
Speaker 1: It's not something that happens very quickly. You need to

656
00:38:28,360 --> 00:38:32,560
Speaker 1: find the pieces of it, that shrapnel has to be analyzed.

657
00:38:32,560 --> 00:38:36,080
Speaker 1: You're looking for any signature that you can find on

658
00:38:36,120 --> 00:38:38,560
Speaker 1: any of this, looking for d n A, looking for

659
00:38:39,160 --> 00:38:44,640
Speaker 1: the components. Using devices, can you reverse engineer the device

660
00:38:44,640 --> 00:38:46,520
Speaker 1: in such a way it might give you clues about

661
00:38:46,719 --> 00:38:49,680
Speaker 1: how someone put it together and where they got that information.

662
00:38:50,320 --> 00:38:54,800
Speaker 1: Maybe if you might get lucky and have some unique

663
00:38:54,800 --> 00:38:59,120
Speaker 1: component to it that is traceable, right, that's um, that

664
00:38:59,320 --> 00:39:02,640
Speaker 1: is what I believe. That's actually how the Oklahoma City

665
00:39:02,719 --> 00:39:06,600
Speaker 1: bombing of the of the Federal building there by Timothy McVeigh.

666
00:39:06,640 --> 00:39:10,239
Speaker 1: I think they found a VIN number among the UH

667
00:39:10,600 --> 00:39:12,960
Speaker 1: in the debris and that was the big break in

668
00:39:13,000 --> 00:39:16,400
Speaker 1: that case. You see, sometimes when you're looking for a bomber,

669
00:39:16,400 --> 00:39:20,320
Speaker 1: they make it much easier. I remember during the Fisal

670
00:39:20,360 --> 00:39:23,440
Speaker 1: Shazad case in two ten, the would be Times Square bomber.

671
00:39:24,040 --> 00:39:27,560
Speaker 1: He left the car that he tried to blow up,

672
00:39:27,760 --> 00:39:30,920
Speaker 1: make into a vehicle board and provides explosive device. He

673
00:39:31,000 --> 00:39:34,040
Speaker 1: left the car in times square, so you trace the

674
00:39:34,080 --> 00:39:36,000
Speaker 1: car and then you're able to trace the able to

675
00:39:36,040 --> 00:39:37,920
Speaker 1: find a whole bunch of information on they're able to

676
00:39:37,960 --> 00:39:40,719
Speaker 1: trace the phone that he had used. He had a

677
00:39:41,120 --> 00:39:42,600
Speaker 1: I believe he had a burner phone. He had a

678
00:39:42,719 --> 00:39:45,600
Speaker 1: pay as he goes cell phone. Um. And then he

679
00:39:45,640 --> 00:39:48,480
Speaker 1: got to the airport and almost got back to Pakistan.

680
00:39:49,480 --> 00:39:51,560
Speaker 1: They had to catch him on the plane at the airport.

681
00:39:51,600 --> 00:39:54,160
Speaker 1: He almost got out of the country, but he did

682
00:39:54,280 --> 00:39:57,719
Speaker 1: leave clues. He left information that law enforcem could work with,

683
00:39:57,800 --> 00:40:00,800
Speaker 1: including me. I remember being called in that weekend after

684
00:40:01,640 --> 00:40:05,520
Speaker 1: the bomb almost went off. Um, he did not. He

685
00:40:05,920 --> 00:40:07,880
Speaker 1: was not a skilled bomb maker. Otherwise you would have

686
00:40:07,880 --> 00:40:11,319
Speaker 1: had a high casualty count that day. But this time

687
00:40:11,360 --> 00:40:14,759
Speaker 1: around with Austin, it doesn't look like police have have

688
00:40:14,920 --> 00:40:17,720
Speaker 1: much to go on so far. UM. Here's the Austin

689
00:40:17,719 --> 00:40:21,359
Speaker 1: Police Chief on on where the investigation stands. There has

690
00:40:21,400 --> 00:40:24,680
Speaker 1: already been a significant presence from our federal partners since

691
00:40:24,719 --> 00:40:27,880
Speaker 1: these events began, and as we reported yesterday, we have

692
00:40:28,000 --> 00:40:32,320
Speaker 1: over five hundred agents and their teams working on Austin

693
00:40:32,400 --> 00:40:35,799
Speaker 1: cases alone, and we have additional resources being brought in

694
00:40:36,000 --> 00:40:39,240
Speaker 1: again by both of those agencies, And as has already

695
00:40:39,239 --> 00:40:42,959
Speaker 1: been broadcast, there is a hundred thousand dollar reward out

696
00:40:42,960 --> 00:40:45,160
Speaker 1: there for someone who can give us a tip leading

697
00:40:45,200 --> 00:40:48,480
Speaker 1: to the identification of the suspect or suspects in this incident.

698
00:40:50,120 --> 00:40:53,239
Speaker 1: So they're looking to law enforcems looking to get lucky.

699
00:40:53,320 --> 00:40:55,600
Speaker 1: Here someone will come forward and say, you know what

700
00:40:55,719 --> 00:40:57,879
Speaker 1: I've I've got something for you. Or maybe it's someone

701
00:40:57,920 --> 00:41:00,640
Speaker 1: who just wants the hundred k who was trying to

702
00:41:01,680 --> 00:41:04,239
Speaker 1: keep silent before mind their own business, so to speak,

703
00:41:04,280 --> 00:41:06,040
Speaker 1: and now they're gonna step forward, and who knows, we'll

704
00:41:06,080 --> 00:41:09,880
Speaker 1: have to see. You have five agents working on this case.

705
00:41:09,960 --> 00:41:14,200
Speaker 1: In the Austin area. Four bombings as I As I mentioned,

706
00:41:14,320 --> 00:41:16,960
Speaker 1: and the addition of a trigger device to this one

707
00:41:17,000 --> 00:41:19,719
Speaker 1: means that this is now something that could have I

708
00:41:19,760 --> 00:41:23,640
Speaker 1: could have gone off and killed anyone, children, anybody. I mean,

709
00:41:23,680 --> 00:41:26,560
Speaker 1: it doesn't seem like it is. Target of the first

710
00:41:26,600 --> 00:41:30,000
Speaker 1: three bombings were package bombs that were opened by individuals.

711
00:41:30,000 --> 00:41:32,240
Speaker 1: They were left on there I believe, left on their porches,

712
00:41:33,440 --> 00:41:38,640
Speaker 1: and they were left in what was a predominantly minority

713
00:41:38,719 --> 00:41:42,759
Speaker 1: area of Austin. So there was also initially put out

714
00:41:42,760 --> 00:41:44,720
Speaker 1: there by I don't know if it was the media

715
00:41:44,800 --> 00:41:46,719
Speaker 1: or and law enforcement or just the media, but the

716
00:41:46,760 --> 00:41:49,479
Speaker 1: notion this might have been a hate crime. Now it's

717
00:41:49,480 --> 00:41:52,880
Speaker 1: looking like there's a greater randomness to all of this.

718
00:41:53,800 --> 00:41:57,239
Speaker 1: The most recent bombing, I believe two people injured, neither

719
00:41:57,280 --> 00:42:00,160
Speaker 1: of them killed. But the most recent bombing was a

720
00:42:01,920 --> 00:42:06,960
Speaker 1: uh more well off part of the city and was

721
00:42:07,719 --> 00:42:11,040
Speaker 1: triggered by a trip wire. So that's just anybody in

722
00:42:11,080 --> 00:42:14,279
Speaker 1: the area. People are asking the question about is this

723
00:42:14,360 --> 00:42:16,800
Speaker 1: terrorism or not. That's a discussion that I've gotten involved

724
00:42:16,800 --> 00:42:19,439
Speaker 1: in at the national media level and a whole bunch

725
00:42:19,480 --> 00:42:22,840
Speaker 1: of cases in the past. There's just not enough to

726
00:42:22,880 --> 00:42:25,640
Speaker 1: go on right now. We just don't know um and

727
00:42:25,800 --> 00:42:29,760
Speaker 1: anything put out there right now about motive feels like speculation.

728
00:42:30,560 --> 00:42:33,400
Speaker 1: You know, this, this could be uh this could be

729
00:42:33,440 --> 00:42:36,880
Speaker 1: domestic terrorism. Absolutely. It also just could be a completely

730
00:42:37,040 --> 00:42:41,680
Speaker 1: sick and deranged individual who wants to send bombs or

731
00:42:41,800 --> 00:42:45,480
Speaker 1: or plant bombs and kill people just because you know,

732
00:42:45,520 --> 00:42:48,360
Speaker 1: we we don't know. So I don't have much on

733
00:42:48,400 --> 00:42:52,399
Speaker 1: the analytics side to give you on why I think

734
00:42:52,560 --> 00:42:56,000
Speaker 1: this person maybe this person is doing this. As to

735
00:42:56,040 --> 00:42:59,319
Speaker 1: how they find him, this is where you hope that

736
00:43:00,320 --> 00:43:03,160
Speaker 1: all these different ages. You've got a t F down there, FBI,

737
00:43:03,480 --> 00:43:07,000
Speaker 1: Austin City Police, I'm sure you get state police. I'm

738
00:43:07,000 --> 00:43:10,000
Speaker 1: sure Texas Marshals are all the men. Everyone's FBI. Ever,

739
00:43:10,080 --> 00:43:12,799
Speaker 1: everyone's in on this one as they should be, um

740
00:43:12,880 --> 00:43:15,759
Speaker 1: because this is now a city under siege in a sense.

741
00:43:15,760 --> 00:43:19,280
Speaker 1: You've got people that are concerned about and and rightfully

742
00:43:19,280 --> 00:43:21,879
Speaker 1: so concerned about just walking around the streets. Right these

743
00:43:21,880 --> 00:43:26,080
Speaker 1: are essentially I e. D. S going off in Austin,

744
00:43:27,200 --> 00:43:29,600
Speaker 1: and they have no real leads that we know of,

745
00:43:29,920 --> 00:43:32,239
Speaker 1: and there's no sense that they're gonna be able to

746
00:43:32,280 --> 00:43:36,600
Speaker 1: catch this person anytime imminently unless they get some sort

747
00:43:36,600 --> 00:43:39,960
Speaker 1: of a break. Now we're hoping that maybe, uh, they'll

748
00:43:40,000 --> 00:43:45,560
Speaker 1: be able to reverse kind of the surveillance footage from

749
00:43:45,680 --> 00:43:52,000
Speaker 1: different cameras, maybe street cameras or um in different buildings nearby.

750
00:43:52,440 --> 00:43:54,400
Speaker 1: You know, this is where they try to piece together

751
00:43:55,120 --> 00:43:58,400
Speaker 1: whatever they can to just get that one break in

752
00:43:58,440 --> 00:44:02,160
Speaker 1: the case, because right now it is bleak. It's terrible.

753
00:44:02,200 --> 00:44:04,320
Speaker 1: I've read the stories of a young man who was killed,

754
00:44:04,400 --> 00:44:06,279
Speaker 1: you know, opening this. He's with his mother, and mother

755
00:44:06,360 --> 00:44:08,799
Speaker 1: was severely injured. They brought this package into their into

756
00:44:08,840 --> 00:44:14,080
Speaker 1: their kitchen, and just this is it's so the whole

757
00:44:14,120 --> 00:44:18,760
Speaker 1: thing is so evil and so senseless. So I really

758
00:44:18,760 --> 00:44:22,200
Speaker 1: hope that they managed to track down whoever is responsible

759
00:44:22,239 --> 00:44:25,200
Speaker 1: and hold them to account and prosecute them the fullest

760
00:44:25,200 --> 00:44:29,000
Speaker 1: extent of the law. I'm assuming this was to me

761
00:44:29,200 --> 00:44:32,040
Speaker 1: on right on his face, this is a death penalty case. Um,

762
00:44:32,360 --> 00:44:35,520
Speaker 1: just based on what's going on already, and we'll have

763
00:44:35,560 --> 00:44:38,799
Speaker 1: to see if there's some kind of a manifesto, possible

764
00:44:39,600 --> 00:44:43,320
Speaker 1: political motivation behind this, you know, war against the government.

765
00:44:43,320 --> 00:44:47,440
Speaker 1: I mentioned Timothy with baby before. Someone who's you know,

766
00:44:47,480 --> 00:44:50,279
Speaker 1: who knows, could be any idea, you know, could be

767
00:44:50,320 --> 00:44:53,440
Speaker 1: any terrorist or extremist ideology. We just don't know right now.

768
00:44:53,840 --> 00:44:55,279
Speaker 1: We don't have much to go on. So if we

769
00:44:55,320 --> 00:44:58,080
Speaker 1: have anything that breaks during the show, I will bring

770
00:44:58,080 --> 00:45:00,239
Speaker 1: it to you. We're watching the case very close, Lee,

771
00:45:00,560 --> 00:45:03,520
Speaker 1: and our thoughts and prayers are with those in the

772
00:45:03,560 --> 00:45:07,520
Speaker 1: city of Austin tonight. We're we're thinking about you also, um,

773
00:45:07,560 --> 00:45:10,480
Speaker 1: you know, stay safe down there, and let's let law

774
00:45:10,520 --> 00:45:12,040
Speaker 1: enforce and do their work and hope they come up

775
00:45:12,040 --> 00:45:14,719
Speaker 1: with some solutions. Quickly, we'll hit a quick break. We'll

776
00:45:14,760 --> 00:45:37,000
Speaker 1: be right back. Trump and trade and of course China, China.

777
00:45:37,480 --> 00:45:41,839
Speaker 1: Trump talking about what he is going to do with tariffs.

778
00:45:41,840 --> 00:45:43,759
Speaker 1: But I've been trying to look at this from as

779
00:45:43,800 --> 00:45:47,480
Speaker 1: many perspectives as we possibly can here in the Freedom Hup.

780
00:45:47,480 --> 00:45:49,520
Speaker 1: We have somebody who is an actual expert on trade

781
00:45:49,560 --> 00:45:52,200
Speaker 1: will join us now here were the peace it's up

782
00:45:52,239 --> 00:45:56,080
Speaker 1: on the hill. How much does trade impact Americans? Not

783
00:45:56,160 --> 00:45:58,880
Speaker 1: all that much. We have Derek Scissors on the line.

784
00:45:58,920 --> 00:46:03,000
Speaker 1: He is an international coonymous at the American Enterprise Institute. Derek,

785
00:46:03,080 --> 00:46:05,759
Speaker 1: thank you so much. I'm glad to be here. So

786
00:46:06,600 --> 00:46:09,000
Speaker 1: I really like your piece because you're saying, look, the

787
00:46:09,080 --> 00:46:11,279
Speaker 1: people that are saying that this is a huge deal,

788
00:46:11,440 --> 00:46:13,759
Speaker 1: and if Trump does this thing he says you're gonna do,

789
00:46:14,160 --> 00:46:16,960
Speaker 1: the economy is gonna come tumbling down. It's a little

790
00:46:17,000 --> 00:46:21,080
Speaker 1: bit of chicken little going on. Yeah, It's the basic

791
00:46:21,120 --> 00:46:24,360
Speaker 1: story here on trade is if you have very strong,

792
00:46:24,400 --> 00:46:27,040
Speaker 1: paid trade policies for a long period of time, that

793
00:46:27,080 --> 00:46:29,320
Speaker 1: can matter even to a really big country like the

794
00:46:29,400 --> 00:46:34,320
Speaker 1: United States. But our economy, if you use gross domestic products,

795
00:46:34,320 --> 00:46:38,000
Speaker 1: is eighteen trillion dollars. Every steal on aluminum product. We

796
00:46:38,080 --> 00:46:43,719
Speaker 1: import everyone, no exceptions, all countries billion um. You do

797
00:46:43,760 --> 00:46:46,040
Speaker 1: the math. It's just not a big deal. It's hard

798
00:46:46,160 --> 00:46:48,200
Speaker 1: for trade to matter to the U. S can have

799
00:46:48,239 --> 00:46:51,399
Speaker 1: to matter the US over time. Sure can really big

800
00:46:51,440 --> 00:46:54,880
Speaker 1: sanctions against China matter. Sure the steel tariffs are not

801
00:46:54,920 --> 00:46:56,960
Speaker 1: gonna matter. What do you say to people who say, oh,

802
00:46:57,000 --> 00:47:00,120
Speaker 1: but Derek, if maybe it's only about fifty billions at

803
00:47:00,160 --> 00:47:02,440
Speaker 1: forty eight billions for stealing aluminium, but there will be

804
00:47:02,480 --> 00:47:07,359
Speaker 1: all of these reprisals and retaliation. Well, I mean the

805
00:47:07,400 --> 00:47:08,960
Speaker 1: rest of the world's We have the biggest coconomy in

806
00:47:09,000 --> 00:47:10,279
Speaker 1: the world, but the rest of the world's economy is

807
00:47:10,280 --> 00:47:13,040
Speaker 1: bigger than ours. If we're importing forty eight billion dollars

808
00:47:13,080 --> 00:47:16,839
Speaker 1: from everybody and everybody's economy put together as bigger than ours,

809
00:47:16,840 --> 00:47:18,520
Speaker 1: why do they care so much about the forty eight

810
00:47:18,520 --> 00:47:22,200
Speaker 1: billion dollars? There could be retaliation. I agree that the

811
00:47:22,239 --> 00:47:25,560
Speaker 1: retaliation will probably be worth about forty billion dollars um.

812
00:47:25,719 --> 00:47:29,200
Speaker 1: So this is not I think the way to attack

813
00:47:29,280 --> 00:47:32,600
Speaker 1: the stealing aluminum terraces. What are we trying to accomplish?

814
00:47:32,680 --> 00:47:34,400
Speaker 1: And and that's where I would push the President of

815
00:47:34,440 --> 00:47:36,440
Speaker 1: the administration, like what are we trying to accomplish here?

816
00:47:36,480 --> 00:47:38,759
Speaker 1: Tell me exactly where you're going with this. But the

817
00:47:38,800 --> 00:47:41,000
Speaker 1: idea that what we did is really going to hurt

818
00:47:41,120 --> 00:47:43,480
Speaker 1: us or them or both of us, and then they're

819
00:47:43,520 --> 00:47:46,040
Speaker 1: gonna do this, They're gonna have this huge retaliation. Why

820
00:47:46,080 --> 00:47:48,719
Speaker 1: would they have huge retaliation against what really is a

821
00:47:48,800 --> 00:47:51,279
Speaker 1: small trade step by the United States. They're gonna talk

822
00:47:51,280 --> 00:47:52,920
Speaker 1: a lot about it because they want to look like

823
00:47:53,000 --> 00:47:55,719
Speaker 1: they're they're being tough for their own people, just like

824
00:47:55,800 --> 00:47:58,800
Speaker 1: President Trump does. But again, their retaliation is going to

825
00:47:58,880 --> 00:48:01,759
Speaker 1: be small, just like our and was small. And in

826
00:48:01,880 --> 00:48:05,200
Speaker 1: terms of what China is doing, that is uh that

827
00:48:05,200 --> 00:48:07,759
Speaker 1: that would go in the category of unfair. Just for

828
00:48:07,800 --> 00:48:10,120
Speaker 1: everybody listening, Well, what does China do from a trade

829
00:48:10,160 --> 00:48:14,040
Speaker 1: perspective that gives them an advantage over rivals? That would

830
00:48:14,640 --> 00:48:19,719
Speaker 1: rufflesome feathers in the Trans Pacific partnership side of the aisle? Right,

831
00:48:19,760 --> 00:48:21,319
Speaker 1: the people that believe that if we all just got

832
00:48:21,320 --> 00:48:24,200
Speaker 1: together and did more trading, everything would be great, Well,

833
00:48:24,200 --> 00:48:26,680
Speaker 1: we do two things, one of which the administration is

834
00:48:26,719 --> 00:48:28,719
Speaker 1: looking into and we may hear what they're gonna do

835
00:48:28,760 --> 00:48:31,839
Speaker 1: about it as soon as this week, and the other one,

836
00:48:32,400 --> 00:48:33,920
Speaker 1: which I'll talk about a second, but the first one

837
00:48:33,960 --> 00:48:36,080
Speaker 1: that the aministrat is looking into is they they steal

838
00:48:36,760 --> 00:48:39,920
Speaker 1: or or try to push companies into transferring technology or

839
00:48:39,960 --> 00:48:44,280
Speaker 1: intellectual property. And basically the problem there is American firms

840
00:48:44,320 --> 00:48:46,480
Speaker 1: are the most innovative in the world. Not in every field,

841
00:48:46,719 --> 00:48:48,800
Speaker 1: but overall, we have the most innovative companies, We have

842
00:48:48,840 --> 00:48:51,560
Speaker 1: the most innovative workers, we have the most innovative people. Well,

843
00:48:51,600 --> 00:48:53,759
Speaker 1: if we innovate on the Chinese say hey, thanks for

844
00:48:53,800 --> 00:48:56,480
Speaker 1: the innovation, we're just gonna steal it, or we're gonna

845
00:48:56,640 --> 00:48:58,600
Speaker 1: push your companies saying you can't do any business in

846
00:48:58,680 --> 00:49:02,719
Speaker 1: China unless turn over this technology. Um. They we don't

847
00:49:02,760 --> 00:49:05,600
Speaker 1: get the benefits from that that we should are are

848
00:49:05,600 --> 00:49:07,799
Speaker 1: Our companies can't sell as many goods because the Chinese

849
00:49:07,800 --> 00:49:10,880
Speaker 1: are competing with them, which means fewer jobs for American workers.

850
00:49:10,880 --> 00:49:13,080
Speaker 1: So that's what the administration is looking at right now.

851
00:49:13,160 --> 00:49:15,520
Speaker 1: It's it's China taking the thing that we do best

852
00:49:15,920 --> 00:49:19,840
Speaker 1: and trying to steal the advantages of it. Um. The

853
00:49:19,880 --> 00:49:22,239
Speaker 1: other thing that they do is they heavily subsidize their

854
00:49:22,520 --> 00:49:25,240
Speaker 1: their Some of their firms stayed on enterprises in China

855
00:49:25,680 --> 00:49:28,319
Speaker 1: and those firms don't export because even heavily subsidized, they're

856
00:49:28,320 --> 00:49:31,239
Speaker 1: not competitive. But it basically means that Chinese market is

857
00:49:31,280 --> 00:49:33,760
Speaker 1: closed to a lot of American goods because Chinese standard

858
00:49:33,840 --> 00:49:37,000
Speaker 1: enterprises never lose. You can't outcompete them, you can't drive

859
00:49:37,040 --> 00:49:39,000
Speaker 1: them into bankruptcy because you have better products, you're a

860
00:49:39,000 --> 00:49:41,759
Speaker 1: better company, you're better workers, doesn't matter. They don't lose.

861
00:49:41,840 --> 00:49:44,719
Speaker 1: So that's the block on the Chinese market that they

862
00:49:44,719 --> 00:49:47,399
Speaker 1: don't let their stated on enterprises lose, and then if

863
00:49:47,440 --> 00:49:49,880
Speaker 1: that weren't enough, they go out and they take American

864
00:49:49,920 --> 00:49:52,960
Speaker 1: and other countries innovation. Now, the issue of technology is

865
00:49:52,960 --> 00:49:54,800
Speaker 1: actually something I'm going to address later from a national

866
00:49:54,840 --> 00:49:57,680
Speaker 1: security perspective. But when the president and everyone we're speaking

867
00:49:57,719 --> 00:50:00,239
Speaker 1: to Derek Scissors from the American Enterprise Institute, he's an

868
00:50:00,239 --> 00:50:03,839
Speaker 1: international economist. When the President says that we're getting killed

869
00:50:03,840 --> 00:50:07,640
Speaker 1: on trade, China is doing all this bad stuff on trade. Uh,

870
00:50:07,960 --> 00:50:10,480
Speaker 1: he's speaking in very general terms. But what is he

871
00:50:10,560 --> 00:50:14,960
Speaker 1: really trying to get at? Yeah, I mean that's that's

872
00:50:14,960 --> 00:50:18,680
Speaker 1: a good question. During the campaign and and sometimes as

873
00:50:18,719 --> 00:50:22,600
Speaker 1: president of President President Trump has really emphasized cutting into

874
00:50:22,600 --> 00:50:26,160
Speaker 1: the bilateral trade deficit. So if you can if you

875
00:50:26,200 --> 00:50:28,680
Speaker 1: include goods and services. The US has about a three

876
00:50:29,400 --> 00:50:32,520
Speaker 1: billion dollar bilateral trade deficit with China last year, and

877
00:50:32,600 --> 00:50:35,320
Speaker 1: President Trump just you know, that really bothers him, and

878
00:50:35,360 --> 00:50:37,080
Speaker 1: he'd like that to come down to, you know, a

879
00:50:37,200 --> 00:50:39,279
Speaker 1: hundred billion dollars. He knows he's not going to go away,

880
00:50:39,520 --> 00:50:41,520
Speaker 1: but he wants an improvement. He wants it to stop

881
00:50:41,680 --> 00:50:45,000
Speaker 1: rising and start dropping. But does he have a point?

882
00:50:46,239 --> 00:50:49,360
Speaker 1: Is that a problem because people tell us it's not

883
00:50:49,400 --> 00:50:52,600
Speaker 1: a problem. I don't think that's the problem. This is

884
00:50:52,640 --> 00:50:54,839
Speaker 1: the way I would put in. The US and China

885
00:50:54,880 --> 00:50:57,200
Speaker 1: have really big economies. You know, you put them together

886
00:50:57,239 --> 00:51:00,280
Speaker 1: in terms of gross domestic products GDP, it's thirty trillion dollars.

887
00:51:00,640 --> 00:51:02,799
Speaker 1: If the Chinese were good trade partners. If you had

888
00:51:02,800 --> 00:51:04,880
Speaker 1: asked me a question, you said, you know, what do

889
00:51:04,960 --> 00:51:07,239
Speaker 1: the Chinese do that that upsets people who you know,

890
00:51:07,320 --> 00:51:10,560
Speaker 1: have a very positive view of the world, um like

891
00:51:10,600 --> 00:51:13,399
Speaker 1: our tv P partners. And I said, I I don't know,

892
00:51:13,480 --> 00:51:15,319
Speaker 1: and none of my friends know. And we've been working

893
00:51:15,320 --> 00:51:17,320
Speaker 1: at this for years and they're great trade partners. I

894
00:51:17,320 --> 00:51:19,680
Speaker 1: wouldn't care about the trade deficits. What bothers me is

895
00:51:19,680 --> 00:51:22,920
Speaker 1: what they do the trade deficit is an outcome. So

896
00:51:23,200 --> 00:51:25,400
Speaker 1: you know, three forty million do sounds like a lot

897
00:51:25,400 --> 00:51:27,240
Speaker 1: of money. But if China was a great trade partner

898
00:51:27,239 --> 00:51:30,600
Speaker 1: that was open to American products, that didn't steal American technology,

899
00:51:30,640 --> 00:51:32,200
Speaker 1: I would say, I know that that's just the way

900
00:51:32,239 --> 00:51:34,880
Speaker 1: it is. The story I think the President is getting

901
00:51:34,920 --> 00:51:38,719
Speaker 1: at is they have that trade surplus because they're not

902
00:51:38,800 --> 00:51:42,400
Speaker 1: good trade partners, um and and you know what I

903
00:51:42,480 --> 00:51:44,720
Speaker 1: want is to change their practices. I think the President

904
00:51:44,719 --> 00:51:47,120
Speaker 1: would just be happy if the trade deficit fell for

905
00:51:47,640 --> 00:51:49,440
Speaker 1: you know, for whatever reason, the Chinese just buy a

906
00:51:49,480 --> 00:51:52,080
Speaker 1: bunch of US soybeans, um. So there's a little bit

907
00:51:52,120 --> 00:51:54,120
Speaker 1: of a split there. I don't think the trade deficit

908
00:51:54,200 --> 00:51:56,200
Speaker 1: is a problem. I think what China does is the problem.

909
00:51:56,440 --> 00:51:59,160
Speaker 1: I think the President really just wants the trade deficit

910
00:51:59,239 --> 00:52:04,080
Speaker 1: to shrink. And on the issue of UH steel specifically,

911
00:52:05,120 --> 00:52:07,360
Speaker 1: are we going to be able to see some improvement

912
00:52:07,480 --> 00:52:11,239
Speaker 1: in you know, US industry and steel output. But I

913
00:52:11,280 --> 00:52:13,680
Speaker 1: would assume then if it's only fifty billion dollars or importing,

914
00:52:13,960 --> 00:52:16,040
Speaker 1: there are limitations on how much of an impact this

915
00:52:16,080 --> 00:52:18,720
Speaker 1: will have in the economy apart from the national security

916
00:52:18,719 --> 00:52:22,239
Speaker 1: aspect of it. Right, and so yeah, I mean, if

917
00:52:22,400 --> 00:52:26,160
Speaker 1: if you apply tear after everyone, you didn't grant any exceptions,

918
00:52:26,760 --> 00:52:29,320
Speaker 1: you and you've got all steel allans, the limited paris

919
00:52:29,360 --> 00:52:32,520
Speaker 1: only ten percent. You're not gonna stop importing forty eight

920
00:52:32,520 --> 00:52:34,719
Speaker 1: billion dollars, which is the total last year. It's gonna drop.

921
00:52:34,719 --> 00:52:36,920
Speaker 1: It's gonna drop to like thirty five billion because those

922
00:52:36,920 --> 00:52:39,920
Speaker 1: products got more expensive. So we're talking about thirteen billion

923
00:52:39,920 --> 00:52:42,840
Speaker 1: dollars more production in the United States. That's not nothing.

924
00:52:43,640 --> 00:52:47,160
Speaker 1: But for people who are familiar with this industry, even

925
00:52:47,200 --> 00:52:50,000
Speaker 1: steel is heavily automated. It's a lot of capital spending

926
00:52:50,040 --> 00:52:52,160
Speaker 1: to set up a steel mill. They're not as many

927
00:52:52,200 --> 00:52:54,959
Speaker 1: workers as there used to be. Would it create some jobs? Yeah?

928
00:52:55,080 --> 00:52:57,600
Speaker 1: How many jobs will it create? I'm afraid not very many.

929
00:52:57,600 --> 00:53:00,160
Speaker 1: It's also not going to cause the cost of your

930
00:53:00,160 --> 00:53:02,640
Speaker 1: car or your plane fly to your house to go

931
00:53:02,719 --> 00:53:05,480
Speaker 1: staring through the roof. That's my point about. You know,

932
00:53:05,560 --> 00:53:08,640
Speaker 1: both sides are exaggerating how important this is. But cutting

933
00:53:08,640 --> 00:53:11,279
Speaker 1: steel imports by ten fifteen billion dollars, it's it's just

934
00:53:11,400 --> 00:53:13,959
Speaker 1: not going to create very many jobs. Let me ask

935
00:53:14,000 --> 00:53:15,279
Speaker 1: you what we got you on the phone here. One

936
00:53:15,320 --> 00:53:19,520
Speaker 1: more about about NAFTA, You've said before that you've had

937
00:53:19,520 --> 00:53:21,360
Speaker 1: it on my show that NAFTA it is time for

938
00:53:21,440 --> 00:53:24,000
Speaker 1: it to be renegotiated. So people that kind of roll

939
00:53:24,080 --> 00:53:26,120
Speaker 1: their eyes look skyward and all that when Trump says

940
00:53:26,120 --> 00:53:29,840
Speaker 1: we got to renegotiate NAFTA, it does need some some updating.

941
00:53:30,200 --> 00:53:32,520
Speaker 1: What would be the best way for Trump to go

942
00:53:32,560 --> 00:53:36,239
Speaker 1: about that? Right, So, it absolutely needs some updating. It's

943
00:53:36,239 --> 00:53:38,520
Speaker 1: a twenty three year old agreement. It was path breaking

944
00:53:38,520 --> 00:53:40,440
Speaker 1: at the time. You know, whether you think it's terrible

945
00:53:40,520 --> 00:53:43,879
Speaker 1: or great, people tend to agree that it was path breaking. Um,

946
00:53:43,880 --> 00:53:45,920
Speaker 1: it does need some updating. The world has changed a

947
00:53:45,960 --> 00:53:48,600
Speaker 1: lot since then. You know, we didn't have digital trade then,

948
00:53:48,640 --> 00:53:50,319
Speaker 1: we didn't have trade through the internet. We didn't have

949
00:53:50,360 --> 00:53:53,319
Speaker 1: people buying things online and anything like the quantities that

950
00:53:53,320 --> 00:53:58,000
Speaker 1: we have now. So, I mean there's another situation where

951
00:53:58,040 --> 00:54:00,000
Speaker 1: I think the President is right that it needs updated.

952
00:54:00,080 --> 00:54:02,120
Speaker 1: I think what the administration is negotiating with to try

953
00:54:02,160 --> 00:54:05,160
Speaker 1: to modernize the agreement and to say to Mexican Canada, look,

954
00:54:05,160 --> 00:54:08,080
Speaker 1: the US is very good at services. You need to

955
00:54:08,080 --> 00:54:10,320
Speaker 1: allow us to be able to sell our stuff digitally

956
00:54:10,400 --> 00:54:12,880
Speaker 1: and not have taxes or restrictions or planning games. So

957
00:54:12,960 --> 00:54:15,319
Speaker 1: that those are good things to try to do. The

958
00:54:15,400 --> 00:54:18,480
Speaker 1: President also really wants our bilateral trade deficit with Mexico

959
00:54:18,560 --> 00:54:20,319
Speaker 1: to fall, and that's going to be really hard because

960
00:54:20,320 --> 00:54:23,560
Speaker 1: the Mexican economy is basically not growing. So if you're

961
00:54:23,600 --> 00:54:26,200
Speaker 1: just trying to upgrade and improve nafter, you can do it.

962
00:54:26,280 --> 00:54:28,359
Speaker 1: And if you in the Mexicans and the Canadians don't

963
00:54:28,400 --> 00:54:29,960
Speaker 1: go along, it's their fault. But if you're trying to

964
00:54:29,960 --> 00:54:32,360
Speaker 1: get the trade deficit the fall, that's gonna be a

965
00:54:32,400 --> 00:54:35,600
Speaker 1: tough sell. Because we're growing faster than Mexico. It's gonna

966
00:54:35,600 --> 00:54:37,560
Speaker 1: be really hard for them to buy more products from

967
00:54:37,560 --> 00:54:39,239
Speaker 1: the United States when they're not buying more of their

968
00:54:39,280 --> 00:54:43,160
Speaker 1: own products. Derek Scissors of AI. Everybody go to a

969
00:54:43,320 --> 00:54:45,960
Speaker 1: EI dot org to read their latest research. Derek, thank

970
00:54:46,000 --> 00:54:48,440
Speaker 1: you so much for joining. Thanks to your peace. Thank you.

971
00:54:48,480 --> 00:54:50,920
Speaker 1: I enjoyed it. Say we're gonna roll into a quick break,

972
00:54:51,320 --> 00:54:53,560
Speaker 1: will be back in just a few minutes. We're gonna

973
00:54:53,560 --> 00:54:56,680
Speaker 1: have Jesse Kelly joining later this hour. Talk about raising

974
00:54:56,719 --> 00:54:59,040
Speaker 1: young men because he's got a couple of young men

975
00:54:59,040 --> 00:55:01,400
Speaker 1: that he's raising kids. I don't, so he's an expert

976
00:55:01,440 --> 00:55:03,640
Speaker 1: on that. I'm not. You'll be joining. We'll talk about that.

977
00:55:03,680 --> 00:55:17,120
Speaker 1: Stay with me. He's back with you now, because when

978
00:55:17,120 --> 00:55:20,520
Speaker 1: it comes to the fight for truth, the fuck never stops.

979
00:55:21,680 --> 00:55:24,920
Speaker 1: As a millennial, I've heard a lot of the stories

980
00:55:25,000 --> 00:55:29,840
Speaker 1: out there from those of you who are boomers gen xers.

981
00:55:30,640 --> 00:55:33,719
Speaker 1: Is Jen why a thing too about how you know, well,

982
00:55:33,880 --> 00:55:37,160
Speaker 1: when I was going to college, I I was a

983
00:55:37,239 --> 00:55:41,160
Speaker 1: bar back and I you know, worked as a golf

984
00:55:41,360 --> 00:55:43,520
Speaker 1: golf caddy over the summer, and you know, you have

985
00:55:43,560 --> 00:55:47,160
Speaker 1: you have all these stories about how you're saving money

986
00:55:47,239 --> 00:55:50,320
Speaker 1: for college or or raising money for your college tuition

987
00:55:50,360 --> 00:55:52,600
Speaker 1: when you're in it, and they make great stories to

988
00:55:52,640 --> 00:55:55,400
Speaker 1: tell your kids. And one of the get off my

989
00:55:55,520 --> 00:55:59,680
Speaker 1: lawn things you often hear from the boomer generation is,

990
00:56:00,160 --> 00:56:02,839
Speaker 1: you know, kids these days, they're just they expect someone

991
00:56:02,880 --> 00:56:05,200
Speaker 1: else to pay for it, or it's all it's all

992
00:56:05,239 --> 00:56:07,440
Speaker 1: taking out debt, and then they're hoping the debt will

993
00:56:07,480 --> 00:56:10,120
Speaker 1: just be wiped away. I would note that that is

994
00:56:10,160 --> 00:56:15,480
Speaker 1: a major major platform for the sander Nista left wing

995
00:56:15,520 --> 00:56:17,960
Speaker 1: of the Democrat Party going forward. You got a trillion

996
00:56:18,000 --> 00:56:20,600
Speaker 1: dollar student loan bubble out there, people are just gonna

997
00:56:20,600 --> 00:56:23,000
Speaker 1: say that, yeah, just we should just have debt forgiveness

998
00:56:23,000 --> 00:56:26,080
Speaker 1: of it, just forgive the debt. What do they think

999
00:56:26,080 --> 00:56:28,799
Speaker 1: about what that would mean? No, they don't. But it's

1000
00:56:28,800 --> 00:56:31,479
Speaker 1: gonna get bigger because there's no way people are gonna

1001
00:56:31,480 --> 00:56:34,200
Speaker 1: be able to pay off a lot of those loans um.

1002
00:56:34,280 --> 00:56:36,640
Speaker 1: But there's a great piece in the New York Time,

1003
00:56:36,880 --> 00:56:38,239
Speaker 1: you know, in the Wall Street Journal at the New

1004
00:56:38,320 --> 00:56:41,760
Speaker 1: York Times, you can't work your way through college anymore,

1005
00:56:42,880 --> 00:56:47,600
Speaker 1: and it just talks about how different the situation is

1006
00:56:47,640 --> 00:56:49,879
Speaker 1: now when you're talking about a particularly a four year

1007
00:56:49,880 --> 00:56:52,000
Speaker 1: private college, but even a lot of these states schools.

1008
00:56:52,680 --> 00:56:55,680
Speaker 1: The difference between what it used to be to go

1009
00:56:55,760 --> 00:56:59,160
Speaker 1: to a place like Yale, for example, very fancy, very

1010
00:56:59,160 --> 00:57:01,600
Speaker 1: elite school, versus what it would be to go to

1011
00:57:01,719 --> 00:57:04,160
Speaker 1: Yale today. And this is then filters down all the

1012
00:57:04,160 --> 00:57:08,520
Speaker 1: way across the spectrum. So the notion that you could

1013
00:57:09,040 --> 00:57:12,080
Speaker 1: wait tables, you know, you could have some job as

1014
00:57:12,120 --> 00:57:14,719
Speaker 1: a lifeguard at the beach, save money and pay off

1015
00:57:14,719 --> 00:57:18,000
Speaker 1: a semester at college that's gone, you would have to

1016
00:57:18,040 --> 00:57:20,200
Speaker 1: be making well. He gives you this, gives you the

1017
00:57:20,280 --> 00:57:23,080
Speaker 1: numbers here, and I'll walk you through someone numbers. Here's

1018
00:57:23,080 --> 00:57:24,960
Speaker 1: what he writes. This is by Richard West the Wall

1019
00:57:25,040 --> 00:57:27,400
Speaker 1: Street Journal. That's right for all you get off my

1020
00:57:27,480 --> 00:57:29,800
Speaker 1: law types. You guys, when it when it came to

1021
00:57:29,840 --> 00:57:32,840
Speaker 1: college tuition, I'm gonna say it, you had it easy.

1022
00:57:33,120 --> 00:57:35,760
Speaker 1: You had it easy compared to what's going on today.

1023
00:57:35,760 --> 00:57:38,720
Speaker 1: It is out of control now. And I would also

1024
00:57:38,760 --> 00:57:40,840
Speaker 1: know that you're supposed to get an advanced degree now,

1025
00:57:40,920 --> 00:57:42,960
Speaker 1: just to have one, even if you don't use it.

1026
00:57:43,200 --> 00:57:45,320
Speaker 1: And I know so many people that have j d s.

1027
00:57:45,360 --> 00:57:47,000
Speaker 1: You know, went to law school, and it's like, oh,

1028
00:57:47,040 --> 00:57:49,240
Speaker 1: what do you do? I work in marketing? What do

1029
00:57:49,240 --> 00:57:51,280
Speaker 1: you Why do you have a j d? Heh? You know?

1030
00:57:51,360 --> 00:57:54,760
Speaker 1: Is you know? I gotta gotta be competitive three years

1031
00:57:54,760 --> 00:57:58,520
Speaker 1: of law school anyway. Here's what Richard West writes in

1032
00:57:58,600 --> 00:58:01,959
Speaker 1: nineteen fifty six as a freshman at year Yil. Here's

1033
00:58:01,960 --> 00:58:05,640
Speaker 1: a Yale man, he's a yearly. I waited tables in

1034
00:58:05,680 --> 00:58:08,840
Speaker 1: a student dorm for about one dollar an hour, ten

1035
00:58:08,840 --> 00:58:12,320
Speaker 1: hours a week. I received a full scholarship. But even

1036
00:58:12,320 --> 00:58:15,000
Speaker 1: if it had ended, I recall that Yale's all in

1037
00:58:15,240 --> 00:58:19,320
Speaker 1: price is amazing. Yale is all in price, including tuition,

1038
00:58:19,640 --> 00:58:23,800
Speaker 1: room and board, was eighteen hundred dollars a year. And

1039
00:58:23,920 --> 00:58:27,720
Speaker 1: my work while in school during the term ten hours

1040
00:58:27,800 --> 00:58:31,520
Speaker 1: a week would have covered a sixth of that, So

1041
00:58:31,720 --> 00:58:33,919
Speaker 1: you would while you're in school. This is not even

1042
00:58:33,920 --> 00:58:36,880
Speaker 1: paying it off after you get out of school. While

1043
00:58:36,960 --> 00:58:40,040
Speaker 1: you were in school in six you could pay off

1044
00:58:40,080 --> 00:58:45,360
Speaker 1: a chunk of your Yale tuition, and then when you

1045
00:58:45,440 --> 00:58:47,880
Speaker 1: graduate you have even lesson. As everyone knows, you've gotta

1046
00:58:47,880 --> 00:58:50,080
Speaker 1: pay interest on the debt and everything else on the loan.

1047
00:58:51,160 --> 00:58:53,880
Speaker 1: He goes on. Today, tuition room and board of Yale

1048
00:58:53,960 --> 00:58:57,160
Speaker 1: run sixty six thousand, nine hundred dollars. Now for a

1049
00:58:57,160 --> 00:58:58,560
Speaker 1: lot of people, I know they're gonna say a book

1050
00:58:58,560 --> 00:59:01,080
Speaker 1: eighteen hundred dollars and nineteen fifty six was a lot

1051
00:59:01,120 --> 00:59:05,400
Speaker 1: more than than it is today. Uh, it wasn't sixty

1052
00:59:05,400 --> 00:59:09,920
Speaker 1: six thousand dollars. Might have been I don't know. We

1053
00:59:09,920 --> 00:59:12,480
Speaker 1: could actually look at what the uh what the inflation

1054
00:59:12,560 --> 00:59:15,440
Speaker 1: calculator would say for it. I don't know, maybe maybe

1055
00:59:16,080 --> 00:59:20,240
Speaker 1: five ten x, you know, maybe something like that. It was.

1056
00:59:20,360 --> 00:59:22,560
Speaker 1: It wasn't almost seventy grand now eighteen hundred bucks and

1057
00:59:22,600 --> 00:59:26,200
Speaker 1: nineteen fifty six wasn't seventy thousand dollars? Okay, so that

1058
00:59:26,320 --> 00:59:30,200
Speaker 1: much I know, no false, And we're not talking about

1059
00:59:30,240 --> 00:59:34,240
Speaker 1: eighteen fifty six. This is nineteen fifty six. So he

1060
00:59:34,280 --> 00:59:36,840
Speaker 1: goes into some of the number crunching here. This is

1061
00:59:36,880 --> 00:59:39,160
Speaker 1: just before we all, you know, hear all the stories.

1062
00:59:39,200 --> 00:59:43,880
Speaker 1: You know, order order trojure my university classes and four

1063
00:59:43,960 --> 00:59:46,800
Speaker 1: fut or snow. And I was carrying on my back

1064
00:59:46,960 --> 00:59:51,880
Speaker 1: the lumber for my job as a campus lumberjack. You know,

1065
00:59:51,920 --> 00:59:54,200
Speaker 1: I was carrying around paying her off the hard waree

1066
00:59:54,200 --> 00:59:57,280
Speaker 1: splinters in my hands when I was doing multi variable calculus.

1067
00:59:57,400 --> 01:00:00,400
Speaker 1: You know, we hear all these stories. You know, people,

1068
01:00:00,720 --> 01:00:03,680
Speaker 1: you know, are you finished with the sawmill at nine am?

1069
01:00:03,720 --> 01:00:06,200
Speaker 1: And I was on campus at ten am paying it off.

1070
01:00:06,640 --> 01:00:09,040
Speaker 1: Now that's all great, but it doesn't really work that

1071
01:00:09,040 --> 01:00:12,840
Speaker 1: way anymore. Here's what he writes. Quote today, tuition, room

1072
01:00:12,960 --> 01:00:16,240
Speaker 1: and board at Yale run sixty six dollars working the

1073
01:00:16,400 --> 01:00:20,120
Speaker 1: same amount as I did even at twelve dollars an hour.

1074
01:00:20,600 --> 01:00:25,760
Speaker 1: An increase of roughly one third after inflation, produces income

1075
01:00:25,800 --> 01:00:29,040
Speaker 1: of thirty six dollars, or slightly more than five of

1076
01:00:29,080 --> 01:00:32,880
Speaker 1: the total to earn enough to pay for one sixth

1077
01:00:33,080 --> 01:00:37,000
Speaker 1: of a Yale education, which require an hourly wage of

1078
01:00:37,040 --> 01:00:44,120
Speaker 1: more than thirty seven dollars. Yeah, not a lot of

1079
01:00:44,120 --> 01:00:46,760
Speaker 1: college kids are getting thirty seven dollars an hour for

1080
01:00:46,800 --> 01:00:50,640
Speaker 1: their job unless they're an s A T hooter maybe um.

1081
01:00:50,640 --> 01:00:52,680
Speaker 1: And I don't know what that markets like these days either,

1082
01:00:53,480 --> 01:00:55,600
Speaker 1: but this is where we start to look at how

1083
01:00:55,680 --> 01:00:58,959
Speaker 1: higher education is just completely out of control in terms

1084
01:00:58,960 --> 01:01:01,480
Speaker 1: of costs right now. I also think the quality has

1085
01:01:01,520 --> 01:01:06,080
Speaker 1: gone down dramatically. You look at what was required curriculum

1086
01:01:06,120 --> 01:01:07,720
Speaker 1: and a lot of these schools back in the fifties

1087
01:01:07,760 --> 01:01:09,439
Speaker 1: and sixty So for the get off my law types

1088
01:01:09,480 --> 01:01:11,560
Speaker 1: out there, you've got some you've got some stuff, you've

1089
01:01:11,560 --> 01:01:14,920
Speaker 1: got some likes to stand on. Uh. But now you know,

1090
01:01:14,960 --> 01:01:17,320
Speaker 1: you get everyone coming out of school with women in

1091
01:01:17,360 --> 01:01:21,640
Speaker 1: gender studies degree thirty forty fifty, sometimes a hundred thousand

1092
01:01:21,720 --> 01:01:26,440
Speaker 1: dollars in debt, and this has become the norm. This

1093
01:01:26,520 --> 01:01:30,240
Speaker 1: is now the expectation for a lot of well, this

1094
01:01:30,320 --> 01:01:33,960
Speaker 1: is the expectation, and society is is pushing people into this.

1095
01:01:34,720 --> 01:01:38,840
Speaker 1: It's just assumed that you shouldn't do trade school. You know,

1096
01:01:38,880 --> 01:01:40,320
Speaker 1: it's just and I want to say, assumed a lot

1097
01:01:40,360 --> 01:01:41,680
Speaker 1: of you are like Buck, I went to trade school.

1098
01:01:41,680 --> 01:01:44,200
Speaker 1: I didn't assume that. I'm talking about, you know, the

1099
01:01:44,200 --> 01:01:48,240
Speaker 1: the general cultural thrust right, the uh, the media, the

1100
01:01:48,240 --> 01:01:51,919
Speaker 1: institutions around us. How do here's a good example, how

1101
01:01:51,920 --> 01:01:57,920
Speaker 1: do high schools generally measure the success of their graduates?

1102
01:01:58,480 --> 01:02:02,360
Speaker 1: What percentage go to college? It's not what percentage get

1103
01:02:03,000 --> 01:02:06,000
Speaker 1: a good paying job right away and start saving for

1104
01:02:06,040 --> 01:02:08,200
Speaker 1: a down payment on a house and creating skills and

1105
01:02:08,240 --> 01:02:11,960
Speaker 1: financial security for themselves. That's not how they measure success.

1106
01:02:12,240 --> 01:02:14,160
Speaker 1: And maybe they should change that a little bit. You know,

1107
01:02:14,200 --> 01:02:17,520
Speaker 1: they should probably have a what yeah, okay, what level

1108
01:02:17,560 --> 01:02:21,120
Speaker 1: of people are uh coming out here? What percentage of

1109
01:02:21,120 --> 01:02:23,240
Speaker 1: people are coming out and going to college? But it

1110
01:02:23,240 --> 01:02:27,040
Speaker 1: would also be worthwhile to have what percentage of students

1111
01:02:27,240 --> 01:02:31,600
Speaker 1: leave this high school and have gainful employment within the first,

1112
01:02:31,760 --> 01:02:33,880
Speaker 1: you know, twelve months of graduating. If that's what they

1113
01:02:33,960 --> 01:02:37,200
Speaker 1: choose to do, we really need to change this. If

1114
01:02:37,240 --> 01:02:40,360
Speaker 1: if I knew now, or if I knew them what

1115
01:02:40,440 --> 01:02:43,160
Speaker 1: I know now about what it would mean to go

1116
01:02:43,200 --> 01:02:45,400
Speaker 1: away for four years and be told to just study

1117
01:02:45,400 --> 01:02:48,960
Speaker 1: and better myself and read. Oh my gosh. And I

1118
01:02:49,000 --> 01:02:52,560
Speaker 1: think even spending a year to working or serving your

1119
01:02:52,560 --> 01:02:55,720
Speaker 1: country the military is an obvious choice, but there are

1120
01:02:55,720 --> 01:02:58,240
Speaker 1: other capacities in which I think service would even be

1121
01:02:59,160 --> 01:03:02,360
Speaker 1: very illuminate eating. This needs to be a much bigger

1122
01:03:02,440 --> 01:03:06,400
Speaker 1: national conversation along with school choice. Uh. There are so

1123
01:03:06,480 --> 01:03:10,960
Speaker 1: many places here where conservatives are actually on you know,

1124
01:03:11,000 --> 01:03:13,600
Speaker 1: the conservatives are on the side of innovation and improvement.

1125
01:03:14,160 --> 01:03:17,240
Speaker 1: It is the liberals who are part of these sclerotic,

1126
01:03:18,120 --> 01:03:24,480
Speaker 1: stubborn bureaucracy that refuses to change, that excuses failure, in fact,

1127
01:03:24,480 --> 01:03:28,280
Speaker 1: always finds a way to transfer the responsibility to failure

1128
01:03:28,320 --> 01:03:32,080
Speaker 1: onto someone else's shoulders. And it's just unwilling to look

1129
01:03:32,120 --> 01:03:36,600
Speaker 1: at what's really happening in education in this country despite

1130
01:03:36,600 --> 01:03:38,560
Speaker 1: all the spending. You know, they're so quick to make

1131
01:03:38,600 --> 01:03:41,440
Speaker 1: fun of Betsy Devas, who's at least trying to do

1132
01:03:41,560 --> 01:03:45,040
Speaker 1: something to help kids in particularly inner city schools, in

1133
01:03:45,040 --> 01:03:50,800
Speaker 1: in minority uh minority areas with low average incomes. You know,

1134
01:03:50,840 --> 01:03:54,400
Speaker 1: she's trying to help those students, and people want to

1135
01:03:54,400 --> 01:03:56,600
Speaker 1: mock her. I know she's mocked on SNL over the weekend.

1136
01:03:57,360 --> 01:03:59,439
Speaker 1: When I look at this now and I see top

1137
01:03:59,480 --> 01:04:03,560
Speaker 1: to bottom education has become too expensive. It is not better.

1138
01:04:03,920 --> 01:04:08,320
Speaker 1: It is focusing on less applicable skills, and it's inexcusable

1139
01:04:08,320 --> 01:04:12,880
Speaker 1: because technology and the availability of information has never been

1140
01:04:12,960 --> 01:04:15,440
Speaker 1: better than it is right now. So we've just got

1141
01:04:15,440 --> 01:04:17,760
Speaker 1: to catch up with some of the ideas and policies

1142
01:04:17,840 --> 01:04:21,280
Speaker 1: and use the technologies we have so that everybody's finding

1143
01:04:21,480 --> 01:04:24,400
Speaker 1: their best path, whatever that may be. I gotta roll,

1144
01:04:24,480 --> 01:04:38,680
Speaker 1: no break team, I'll be back. Welcome back everyone. We

1145
01:04:38,760 --> 01:04:41,880
Speaker 1: are gonna switch gears here for a moment and uh

1146
01:04:42,000 --> 01:04:46,040
Speaker 1: get into some some man time. We've got Jesse Kelly

1147
01:04:46,120 --> 01:04:49,480
Speaker 1: with us. He is a former Marine. He is also

1148
01:04:49,600 --> 01:04:54,400
Speaker 1: former Congressional Kennedy. He writes, he does TV appearances. He's

1149
01:04:54,560 --> 01:04:58,240
Speaker 1: all around pundit and uh opinionated fellow. He's got a

1150
01:04:58,280 --> 01:05:01,720
Speaker 1: great piece up on the federal list. Why a good

1151
01:05:01,800 --> 01:05:05,520
Speaker 1: father prepares his sons for war, and we have Jesse

1152
01:05:05,640 --> 01:05:07,760
Speaker 1: now to tell us why that is. Jesse, thank you

1153
01:05:07,760 --> 01:05:11,000
Speaker 1: so much for joining Good talk to Are you down

1154
01:05:11,040 --> 01:05:12,800
Speaker 1: in Texas? Where are you right now? Coming to us Fry,

1155
01:05:12,800 --> 01:05:15,280
Speaker 1: I'm down in Texas. I'm down in Houston. So I

1156
01:05:15,320 --> 01:05:17,760
Speaker 1: hope you Northeast people are freezing at tests up there

1157
01:05:17,760 --> 01:05:20,240
Speaker 1: because it's eighty degrees down here and follow me. Oh

1158
01:05:20,280 --> 01:05:22,240
Speaker 1: my gosh, I am refusing to believe that we are

1159
01:05:22,240 --> 01:05:25,040
Speaker 1: about to get hit. Almost I think to the day

1160
01:05:25,120 --> 01:05:27,320
Speaker 1: the first day of spring with the North easter. That

1161
01:05:27,400 --> 01:05:30,880
Speaker 1: just seems like it's too cruel. But enjoy, enjoy your

1162
01:05:31,080 --> 01:05:34,280
Speaker 1: your warmth down in Texas while we freeze up here.

1163
01:05:34,720 --> 01:05:38,280
Speaker 1: So Jesse, tell me about why good good son prepared, sorry,

1164
01:05:38,280 --> 01:05:41,919
Speaker 1: a good father prepares his son for war, because that's

1165
01:05:41,960 --> 01:05:45,280
Speaker 1: why that's part of the reason why men were created

1166
01:05:45,320 --> 01:05:49,000
Speaker 1: on the men are the protectors of society, not of

1167
01:05:49,040 --> 01:05:53,960
Speaker 1: just this society, of any society, and power never disappears,

1168
01:05:54,120 --> 01:05:56,600
Speaker 1: it just changed his hands. So if we don't have

1169
01:05:56,760 --> 01:06:00,160
Speaker 1: strong men, then you get bullies and jerks who pick

1170
01:06:00,240 --> 01:06:02,120
Speaker 1: on the week. And that's why you're seeing a lot

1171
01:06:02,160 --> 01:06:05,120
Speaker 1: more of that in this society today because we're rating

1172
01:06:05,120 --> 01:06:09,040
Speaker 1: and raising a connald generation of boys, and we've told

1173
01:06:09,080 --> 01:06:12,080
Speaker 1: them they need to be sensitive and all these other

1174
01:06:12,160 --> 01:06:14,600
Speaker 1: things instead of telling them you need to be a man,

1175
01:06:14,880 --> 01:06:17,320
Speaker 1: you need to protect those weaker than you. And Jesse,

1176
01:06:17,560 --> 01:06:21,280
Speaker 1: you mentioned in your piece a journalist by the name

1177
01:06:21,320 --> 01:06:26,360
Speaker 1: of will likech I believe, who wrote about his experience

1178
01:06:26,360 --> 01:06:29,320
Speaker 1: shooting a twenty gauge, not even a twelve gauge, a

1179
01:06:29,440 --> 01:06:32,080
Speaker 1: twenty gage shotgun. Can you just give us a little

1180
01:06:32,120 --> 01:06:34,160
Speaker 1: bit of the backstory there, because this is quite this

1181
01:06:34,200 --> 01:06:38,280
Speaker 1: is quite a tale. Somebody sent me the tale. Apparently

1182
01:06:38,320 --> 01:06:41,600
Speaker 1: this Will has a series. I mean, he has an

1183
01:06:41,600 --> 01:06:44,360
Speaker 1: actual series about raising boys. He's got a couple of songs,

1184
01:06:44,720 --> 01:06:48,200
Speaker 1: and he tells the story about how horrible guns are

1185
01:06:48,240 --> 01:06:50,040
Speaker 1: and how scared he was. I guess when he was

1186
01:06:50,080 --> 01:06:53,400
Speaker 1: a boy, just a young boy. His dad just hand

1187
01:06:53,480 --> 01:06:56,760
Speaker 1: him at twenty gauge with no instructions, no help, no

1188
01:06:56,960 --> 01:07:00,920
Speaker 1: safety classes. The kid holds it up, a from his body,

1189
01:07:01,200 --> 01:07:04,280
Speaker 1: shoots off around into a field. The gun goes flying,

1190
01:07:04,400 --> 01:07:06,880
Speaker 1: the kids scared to death. That's good. It was the

1191
01:07:06,920 --> 01:07:09,800
Speaker 1: most embarrassing thing I have ever read in my life.

1192
01:07:09,840 --> 01:07:12,800
Speaker 1: As far as a fatherhood thing. That's not Will's problem.

1193
01:07:12,800 --> 01:07:16,280
Speaker 1: That's Will's father's problem. Every man should teach his son

1194
01:07:16,560 --> 01:07:18,760
Speaker 1: how to handle a weapon comfortably. You don't have to

1195
01:07:18,840 --> 01:07:21,439
Speaker 1: raise the Navy seal. Teach your son how to handle

1196
01:07:21,520 --> 01:07:24,680
Speaker 1: himself with a weapon, hand with safely, make sure he

1197
01:07:24,760 --> 01:07:27,520
Speaker 1: respects it, make sure he knows how deadly it is,

1198
01:07:27,560 --> 01:07:29,560
Speaker 1: and that teach him to be fast and deadly with it,

1199
01:07:29,600 --> 01:07:32,000
Speaker 1: because he may have to do one that. I also

1200
01:07:32,480 --> 01:07:34,600
Speaker 1: had to note that in in this piece. And by

1201
01:07:34,640 --> 01:07:37,000
Speaker 1: the way, so Jesse, you now realize that it is

1202
01:07:37,040 --> 01:07:39,400
Speaker 1: incumbent upon you to write how to How to Raise

1203
01:07:39,440 --> 01:07:42,480
Speaker 1: a Son properly series, right, because we've got the progressive

1204
01:07:42,560 --> 01:07:46,240
Speaker 1: left wing version from this fellow Mr Leitch, but now

1205
01:07:46,280 --> 01:07:48,919
Speaker 1: we need the Jesse Kelly version in in total, I can't.

1206
01:07:48,920 --> 01:07:51,000
Speaker 1: I mean, this piece is a great start, So I'm

1207
01:07:51,000 --> 01:07:53,400
Speaker 1: gonna I'm just gonna put some more work on your plate, Jesse,

1208
01:07:53,640 --> 01:07:56,080
Speaker 1: along with the podcast, and we're gonna keep hearing the

1209
01:07:56,120 --> 01:07:59,120
Speaker 1: freedom of demanding you launch in the next six months.

1210
01:07:59,160 --> 01:08:02,880
Speaker 1: But tell me, tell me more about will Light and

1211
01:08:03,160 --> 01:08:06,280
Speaker 1: this notion that he's upset that his children are sick

1212
01:08:06,360 --> 01:08:09,520
Speaker 1: or that his his boy specifically because they're white males,

1213
01:08:09,840 --> 01:08:13,560
Speaker 1: are succeeding, and how that's not good. He gets a

1214
01:08:13,640 --> 01:08:16,320
Speaker 1: call into his teacher, to his son's teacher. Uh, and

1215
01:08:16,360 --> 01:08:17,840
Speaker 1: his wife's go in and sit down in front of

1216
01:08:17,840 --> 01:08:21,960
Speaker 1: his son's teacher and finds out that his kid is

1217
01:08:22,200 --> 01:08:26,040
Speaker 1: doing great in school, that his kid is brilliant and

1218
01:08:26,160 --> 01:08:30,000
Speaker 1: personable and his grades are great, and the teacher specifically

1219
01:08:30,040 --> 01:08:34,120
Speaker 1: said his son was a golden child, and was Will happy. Yes,

1220
01:08:34,400 --> 01:08:37,080
Speaker 1: But also, and he writes us down in the piece,

1221
01:08:37,680 --> 01:08:40,439
Speaker 1: a part of him was really concerned, does his son

1222
01:08:40,520 --> 01:08:43,280
Speaker 1: only have that success at the expense of the others.

1223
01:08:43,720 --> 01:08:47,880
Speaker 1: Haven't and I quote this, haven't white men already succeeded enough?

1224
01:08:48,040 --> 01:08:51,680
Speaker 1: I mean, I cannot imagine how twisted up and tormented

1225
01:08:51,720 --> 01:08:53,720
Speaker 1: you have to be as a father to get a

1226
01:08:53,720 --> 01:08:57,040
Speaker 1: glowing report about your son and be uneasy about it.

1227
01:08:57,280 --> 01:08:59,680
Speaker 1: That is a mixed up person in science, and he's

1228
01:08:59,720 --> 01:09:02,000
Speaker 1: gonna mixed up as boys if you pass down to

1229
01:09:02,280 --> 01:09:05,360
Speaker 1: we're speaking of Jesse Kelly's former marine and uh you

1230
01:09:05,360 --> 01:09:09,719
Speaker 1: can follow him on Twitter at Jesse Kelly d C Jesse. I.

1231
01:09:09,720 --> 01:09:12,240
Speaker 1: I really liked the part of your article in The

1232
01:09:12,240 --> 01:09:15,719
Speaker 1: Federalist here where you went into it's not just about

1233
01:09:16,120 --> 01:09:18,960
Speaker 1: don't allow yourself to be bullied. It's also teaching your

1234
01:09:19,000 --> 01:09:22,920
Speaker 1: kids don't allow anyone to bully somebody else. That that bullying.

1235
01:09:22,960 --> 01:09:25,680
Speaker 1: You know, there's all these national anti bullying campaigns, and

1236
01:09:25,800 --> 01:09:28,840
Speaker 1: that's all fine and good. I think sometimes totally they're

1237
01:09:28,840 --> 01:09:31,240
Speaker 1: a little off as to how to prevent bullying. But

1238
01:09:31,360 --> 01:09:33,519
Speaker 1: bullying is very bad. But the real way to get

1239
01:09:33,560 --> 01:09:36,000
Speaker 1: it to stop is one, as you said, as a father,

1240
01:09:36,160 --> 01:09:39,080
Speaker 1: tell your kids, I better never hear about you bullying

1241
01:09:39,160 --> 01:09:41,679
Speaker 1: somebody else who's weaker than you, because I will ring

1242
01:09:41,800 --> 01:09:45,880
Speaker 1: down the fury. Uh and too if you see, if

1243
01:09:45,920 --> 01:09:48,840
Speaker 1: you see anyone else who is being bullied you, as

1244
01:09:48,880 --> 01:09:51,479
Speaker 1: an honorable young man, it is incumbent upon you to

1245
01:09:51,560 --> 01:09:55,519
Speaker 1: step in and stop that bullying. It is everything that

1246
01:09:55,920 --> 01:09:59,400
Speaker 1: the people praying on the week are the worst people

1247
01:09:59,439 --> 01:10:02,240
Speaker 1: in the world, and part of every man's duty is

1248
01:10:02,280 --> 01:10:05,000
Speaker 1: to stop that, put a stop to that. And you're right.

1249
01:10:05,040 --> 01:10:08,760
Speaker 1: My sons have been told several times you will never

1250
01:10:08,840 --> 01:10:12,040
Speaker 1: bully somebody, or you will not enjoy it, but you

1251
01:10:12,080 --> 01:10:14,320
Speaker 1: will stop a bully. And if you get in trouble

1252
01:10:14,400 --> 01:10:17,240
Speaker 1: in school or you get sent home, you get suspended

1253
01:10:17,280 --> 01:10:19,160
Speaker 1: for a couple of days. Guess what that's gonna be

1254
01:10:19,200 --> 01:10:21,680
Speaker 1: an enjoy a couple of enjoyable couple of days for you,

1255
01:10:21,760 --> 01:10:23,960
Speaker 1: because you're gonna be in no trouble in my household.

1256
01:10:24,240 --> 01:10:26,320
Speaker 1: A few months ago, my nine year old stop the

1257
01:10:26,360 --> 01:10:29,360
Speaker 1: bully in school was taken on another small kid. As

1258
01:10:29,360 --> 01:10:31,639
Speaker 1: you can imagine, I'm huge and my son is huge,

1259
01:10:32,120 --> 01:10:33,960
Speaker 1: and he put a stop to it. I've never been

1260
01:10:34,000 --> 01:10:36,320
Speaker 1: so proud of my dad on life, and that extends

1261
01:10:37,160 --> 01:10:40,439
Speaker 1: into adulthood too. That's not just the schoolyard camp campaign.

1262
01:10:40,720 --> 01:10:44,400
Speaker 1: The reason you see so much of this disgusting harassment

1263
01:10:44,400 --> 01:10:47,000
Speaker 1: in Hollywood is because there were Matt No meds to

1264
01:10:47,080 --> 01:10:49,519
Speaker 1: stand there, no man to step in and tell Harvey

1265
01:10:49,560 --> 01:10:52,080
Speaker 1: Weinstein to sit down or he's gonna get touched in

1266
01:10:52,120 --> 01:10:55,200
Speaker 1: his face. Because all the anti bullying programs in the

1267
01:10:55,240 --> 01:10:57,920
Speaker 1: world are fine, that's good, but there is still no

1268
01:10:58,080 --> 01:11:00,680
Speaker 1: substitute for balling up your fists and smashing it into

1269
01:11:00,760 --> 01:11:04,200
Speaker 1: somebody's nose. Jesse, what are the two or three most

1270
01:11:04,240 --> 01:11:07,880
Speaker 1: important things that you think that right now, every uh

1271
01:11:08,040 --> 01:11:14,040
Speaker 1: young man in America should hear from either father, older brother, guardian,

1272
01:11:14,080 --> 01:11:17,880
Speaker 1: whoever it is that is the the the prominent male

1273
01:11:18,000 --> 01:11:20,400
Speaker 1: figure in his life. What what are the two or

1274
01:11:20,439 --> 01:11:23,920
Speaker 1: three things you think everyone should be told now, given

1275
01:11:23,960 --> 01:11:26,759
Speaker 1: the direction of the culture, which is obviously not really

1276
01:11:26,800 --> 01:11:31,400
Speaker 1: handling this the way that it should. No whining life

1277
01:11:31,439 --> 01:11:34,439
Speaker 1: is unfair, and it is your duty to protect those

1278
01:11:34,439 --> 01:11:36,960
Speaker 1: who are weaker than you. All right, I like it.

1279
01:11:37,040 --> 01:11:38,600
Speaker 1: We can put that on a we just put that

1280
01:11:38,640 --> 01:11:41,439
Speaker 1: on a T shirt. Actually, Jesse Kelly was I'm with it,

1281
01:11:41,520 --> 01:11:44,080
Speaker 1: my friend, Jesse. Your piece and the Federalist is great.

1282
01:11:44,080 --> 01:11:48,400
Speaker 1: Everybody should check it out. It is all about how

1283
01:11:48,439 --> 01:11:52,519
Speaker 1: to raise a son who is quote prepared for war,

1284
01:11:52,680 --> 01:11:54,519
Speaker 1: not just in the military sense, but in the being

1285
01:11:54,560 --> 01:11:58,000
Speaker 1: a good person who defends other sense. Jesse, anywhere you

1286
01:11:58,000 --> 01:12:00,000
Speaker 1: want to direct the folks listening to find your stuff

1287
01:12:00,040 --> 01:12:03,400
Speaker 1: for more what you're up to. Come find everything I

1288
01:12:03,439 --> 01:12:06,479
Speaker 1: do on Twitter at Jesse Kelly d C. Every article

1289
01:12:06,560 --> 01:12:09,120
Speaker 1: I do, everything I talk about everybody'll hit. Everything I

1290
01:12:09,160 --> 01:12:11,760
Speaker 1: do is all on there at Jesse Kelly DC. And

1291
01:12:11,760 --> 01:12:14,000
Speaker 1: I also have a Facebook page Jesse Kelly. If you

1292
01:12:14,040 --> 01:12:16,559
Speaker 1: start it should pop right up. All right. Fantastic, Jesse.

1293
01:12:16,680 --> 01:12:19,160
Speaker 1: Thank you so much, sir for your service, for your time,

1294
01:12:19,640 --> 01:12:21,599
Speaker 1: and for the drinks you're gonna buy me the next

1295
01:12:21,600 --> 01:12:24,400
Speaker 1: time you're New York City. I appreciate it. I got

1296
01:12:24,400 --> 01:12:25,960
Speaker 1: your brother. I'll be there all right, talk to you

1297
01:12:26,000 --> 01:12:28,160
Speaker 1: to Jesse. Thanks man. Alright, team, we are going to

1298
01:12:28,320 --> 01:12:32,160
Speaker 1: roll into a break here for the third hour of

1299
01:12:32,400 --> 01:12:34,800
Speaker 1: the Box Sexton Show, which is going to talk a

1300
01:12:34,840 --> 01:12:37,479
Speaker 1: bit about China and how they're stealing our technology. You

1301
01:12:37,560 --> 01:12:50,679
Speaker 1: want to hear it. He's back with you now because

1302
01:12:50,760 --> 01:12:53,360
Speaker 1: when it comes to the fight for truth, the fuck

1303
01:12:53,520 --> 01:13:00,880
Speaker 1: never stops. You are now entering the Tle Operations Center.

1304
01:13:01,520 --> 01:13:06,280
Speaker 1: A programs must be kept strictly need to know Team

1305
01:13:06,360 --> 01:13:10,320
Speaker 1: Bucket is cleared and ready for the buck Brief. How

1306
01:13:10,520 --> 01:13:16,320
Speaker 1: China pushes the limits on military technology transfer is the

1307
01:13:16,360 --> 01:13:19,080
Speaker 1: title of the article in the Wall Street Journal. It

1308
01:13:19,160 --> 01:13:24,040
Speaker 1: should be how China is stealing us blind when it

1309
01:13:24,120 --> 01:13:30,200
Speaker 1: comes to our most critical national security technology are most

1310
01:13:30,200 --> 01:13:36,439
Speaker 1: critical commercial proprietary technology, and how this is not only

1311
01:13:36,479 --> 01:13:41,040
Speaker 1: being done on a scale that would infuriate most Americans

1312
01:13:41,040 --> 01:13:43,280
Speaker 1: if they actually knew what the heck was going on,

1313
01:13:44,160 --> 01:13:50,960
Speaker 1: but it's largely being done out in the open. Let

1314
01:13:51,000 --> 01:13:55,640
Speaker 1: me explain. This was a piece by a memory of

1315
01:13:55,680 --> 01:13:58,759
Speaker 1: Congress Bob Pittinger where he's talking about some of these

1316
01:13:58,880 --> 01:14:02,120
Speaker 1: joint projects that are out there. I mentioned this to

1317
01:14:02,160 --> 01:14:06,559
Speaker 1: you last week, how uh broad Colm was not allowed

1318
01:14:06,600 --> 01:14:10,000
Speaker 1: to take over quaal Calm. These are very high tech

1319
01:14:10,120 --> 01:14:15,519
Speaker 1: chip manufacturers and telecommunication companies because President Trump was just like, Nope,

1320
01:14:16,120 --> 01:14:20,400
Speaker 1: not gonna happen. There are important national security implications for

1321
01:14:20,479 --> 01:14:25,120
Speaker 1: this technology. We can't let China be in control of

1322
01:14:25,160 --> 01:14:28,719
Speaker 1: one of our most important, one of our most important

1323
01:14:28,760 --> 01:14:32,679
Speaker 1: companies in that area. Technically, the company would have been

1324
01:14:32,760 --> 01:14:36,679
Speaker 1: owned in Singapore, would have been acquired by a Singapore

1325
01:14:36,720 --> 01:14:40,880
Speaker 1: based company, but Singapore has deep ties to China. The

1326
01:14:41,000 --> 01:14:43,360
Speaker 1: Chinese have a lot of influence to bring to bear

1327
01:14:43,439 --> 01:14:46,600
Speaker 1: in Singapore, and if they had slowed things down or

1328
01:14:46,640 --> 01:14:51,559
Speaker 1: Garne in another direction, that Chinese could indirectly get a

1329
01:14:51,680 --> 01:14:56,640
Speaker 1: major advantage in the race for five G telecommunication technology.

1330
01:14:56,840 --> 01:14:59,519
Speaker 1: This is important stuff, folks, and we think about it

1331
01:14:59,520 --> 01:15:01,680
Speaker 1: in the data day as well. This would mean you

1332
01:15:01,720 --> 01:15:07,240
Speaker 1: could download an entire high definition movie in a second

1333
01:15:07,360 --> 01:15:10,880
Speaker 1: instead of twenty minutes on your WiFi. Think about what

1334
01:15:10,880 --> 01:15:14,480
Speaker 1: that also means though, for the transfer of military technology

1335
01:15:14,520 --> 01:15:19,479
Speaker 1: and for just communication across the board. This is critical stuff,

1336
01:15:20,520 --> 01:15:24,639
Speaker 1: and yet this somehow he's into major story. We also

1337
01:15:24,760 --> 01:15:28,200
Speaker 1: don't hear much about what the Chinese are really up

1338
01:15:28,200 --> 01:15:31,599
Speaker 1: to in the open. Recently, we've gotten a better sense

1339
01:15:31,640 --> 01:15:36,080
Speaker 1: of what they're hacking. UH efforts have led to. We're

1340
01:15:36,080 --> 01:15:38,759
Speaker 1: getting we're starting to learn more from our own government

1341
01:15:38,760 --> 01:15:42,479
Speaker 1: about just how intrusive Chinese hacking efforts have been into

1342
01:15:42,479 --> 01:15:45,759
Speaker 1: our systems. But what about the things that are happening

1343
01:15:46,400 --> 01:15:48,519
Speaker 1: out in the open. This is from this Wall Street

1344
01:15:48,600 --> 01:15:50,599
Speaker 1: journal piece. I wanted to share some of it with

1345
01:15:50,680 --> 01:15:54,360
Speaker 1: you and then tell you that it's even worse than

1346
01:15:54,479 --> 01:15:57,960
Speaker 1: Congressman Pittinger is saying here. But here's how he starts

1347
01:15:58,000 --> 01:16:02,080
Speaker 1: the piece. Quote, for years, the Chinese government has evaded

1348
01:16:02,120 --> 01:16:06,720
Speaker 1: America's technology transfer safeguards and been allowed to vacuum up

1349
01:16:06,760 --> 01:16:12,000
Speaker 1: military applicable technologies from US companies. The Chinese have perfected

1350
01:16:12,000 --> 01:16:16,160
Speaker 1: the weaponization of investment as a legal means to achieve

1351
01:16:16,240 --> 01:16:23,040
Speaker 1: this massive transfer of dual use technology, bolstering China's military modernization.

1352
01:16:23,760 --> 01:16:28,080
Speaker 1: If the US loses its military technology advantage over China

1353
01:16:28,160 --> 01:16:33,879
Speaker 1: and other adversaries, it will one day cost American lives.

1354
01:16:34,960 --> 01:16:39,759
Speaker 1: And he cites specifically the effort by Broadcom, Singapore based

1355
01:16:39,760 --> 01:16:44,640
Speaker 1: company to take over Qualcom, which Trump shot down. But

1356
01:16:44,920 --> 01:16:49,280
Speaker 1: when you look at what has already happened, what is

1357
01:16:49,320 --> 01:16:52,400
Speaker 1: already going on here, you see that there are US

1358
01:16:52,479 --> 01:16:58,840
Speaker 1: companies that are lobbying against any restrictions on their very

1359
01:16:59,120 --> 01:17:04,879
Speaker 1: cozy relationships with Chinese based companies because they want access

1360
01:17:04,920 --> 01:17:08,760
Speaker 1: to the markets. This is about the bottom line for

1361
01:17:08,800 --> 01:17:13,959
Speaker 1: those companies. But in order to get access to the markets,

1362
01:17:14,040 --> 01:17:19,480
Speaker 1: guess what, the Chinese Communist Party, which runs the economy

1363
01:17:19,560 --> 01:17:24,640
Speaker 1: as well as the government, will insist on US companies

1364
01:17:24,680 --> 01:17:30,320
Speaker 1: sharing some very sensitive dual use technology. This has happened

1365
01:17:30,360 --> 01:17:33,720
Speaker 1: in many cases as cited in this piece in the

1366
01:17:33,720 --> 01:17:35,680
Speaker 1: Wall Street Journal. Here are just a few of them.

1367
01:17:35,760 --> 01:17:41,200
Speaker 1: Quote in general, Electric formed a joint venture with Aviation

1368
01:17:41,280 --> 01:17:45,559
Speaker 1: Industry Corporation of China, one of China's premier state owned

1369
01:17:45,720 --> 01:17:50,040
Speaker 1: enterprises and the primary supplier of aircraft for China's military.

1370
01:17:50,120 --> 01:17:54,439
Speaker 1: Sharing cutting edge avionics technology, a v i C now

1371
01:17:54,520 --> 01:17:59,000
Speaker 1: has an enhanced capability to produce high performance aircraft cockpit

1372
01:17:59,080 --> 01:18:04,120
Speaker 1: controls and displays, as well as communications and navigation systems

1373
01:18:04,160 --> 01:18:08,640
Speaker 1: which it can adapt for Chinese warplanes. So thanks to

1374
01:18:08,760 --> 01:18:16,280
Speaker 1: JEEZ venture in China, Chinese war fighters, specifically in this case,

1375
01:18:16,680 --> 01:18:21,560
Speaker 1: aviators might have an advantage in the future. This is

1376
01:18:21,720 --> 01:18:24,240
Speaker 1: very serious stuff, and I think part of the problem

1377
01:18:24,280 --> 01:18:27,520
Speaker 1: here is that the left and academia in this country

1378
01:18:27,760 --> 01:18:31,240
Speaker 1: do not want us to know. They do not want

1379
01:18:31,280 --> 01:18:36,040
Speaker 1: you to be familiar with the full extent of the

1380
01:18:36,080 --> 01:18:41,720
Speaker 1: Soviet penetration of sensitive US government agencies. They're basically was

1381
01:18:41,760 --> 01:18:45,200
Speaker 1: a Soviet agent in every single major US government agency

1382
01:18:45,880 --> 01:18:48,320
Speaker 1: at the start of the Cold War and all the

1383
01:18:48,360 --> 01:18:52,000
Speaker 1: way up to those with direct access to the President.

1384
01:18:52,840 --> 01:18:56,760
Speaker 1: The Soviet theft of nuclear technology because of the Rosenbergs

1385
01:18:56,840 --> 01:18:59,880
Speaker 1: is somewhat well known, but how many Americans know that

1386
01:19:00,640 --> 01:19:06,120
Speaker 1: the penetrations of US avionics technology, for example, led to

1387
01:19:06,200 --> 01:19:09,400
Speaker 1: us to miscalculate what kind of advantage we would have

1388
01:19:09,520 --> 01:19:12,840
Speaker 1: in the air. During the Korean War. We figured that

1389
01:19:13,040 --> 01:19:16,640
Speaker 1: our first generation of jets, never mind even on some

1390
01:19:16,720 --> 01:19:20,639
Speaker 1: of our propeller planes, would dominate the skies in our

1391
01:19:20,680 --> 01:19:23,919
Speaker 1: fight with North Korea. But guess what. The MiG fighters

1392
01:19:23,920 --> 01:19:27,360
Speaker 1: they came up against were flying circles around the stuff

1393
01:19:27,400 --> 01:19:29,760
Speaker 1: we put up in the air. Because the Soviets had

1394
01:19:29,840 --> 01:19:33,760
Speaker 1: stolen our best stuff and used it for their own purposes,

1395
01:19:34,040 --> 01:19:37,800
Speaker 1: they actually had an advantage. And therefore Soviet planes that

1396
01:19:37,840 --> 01:19:42,479
Speaker 1: we went up against in the Korean War had an advantage.

1397
01:19:43,040 --> 01:19:46,040
Speaker 1: This is how the great game of nation states and

1398
01:19:46,080 --> 01:19:50,719
Speaker 1: civilizations has played out for millennia, and we in this country,

1399
01:19:50,760 --> 01:19:57,000
Speaker 1: I think, are blithely unbothered by what's going on here.

1400
01:19:57,520 --> 01:19:59,160
Speaker 1: Let's time for all of us to wake up on

1401
01:19:59,160 --> 01:20:02,000
Speaker 1: this one. This is where the important I've got more

1402
01:20:02,080 --> 01:20:04,200
Speaker 1: for you from this Wall Street Journal piece quote in

1403
01:20:04,280 --> 01:20:09,040
Speaker 1: ten Ge formed a joint venture with another Chinese company

1404
01:20:09,040 --> 01:20:13,439
Speaker 1: handing over advanced battery technology that could have battlefield applications

1405
01:20:13,479 --> 01:20:17,320
Speaker 1: such as powering heavy ground vehicles. The same year, General

1406
01:20:17,400 --> 01:20:21,680
Speaker 1: Electric formed a partnership with Chinese government affiliated Huawei to

1407
01:20:21,800 --> 01:20:26,200
Speaker 1: develop cloud based industrial applications for the Internet of Things.

1408
01:20:26,760 --> 01:20:30,360
Speaker 1: This arrangement could result in long term cyber vulnerabilities for

1409
01:20:30,360 --> 01:20:34,639
Speaker 1: the US, in part because, like so many so called

1410
01:20:34,640 --> 01:20:38,599
Speaker 1: private companies in China, Huawei is beholden to the Chinese

1411
01:20:38,600 --> 01:20:42,280
Speaker 1: Communist Party and is functionally an arm of the Chinese government.

1412
01:20:42,720 --> 01:20:47,880
Speaker 1: Just like I said. Likewise, IBM has systematically transferred high

1413
01:20:47,960 --> 01:20:52,320
Speaker 1: and computing technology to China. By according to a working

1414
01:20:52,320 --> 01:20:55,599
Speaker 1: group of experts in the National Security Agency and Energy Department,

1415
01:20:56,080 --> 01:20:59,799
Speaker 1: China had attained a near peer status with the US

1416
01:21:00,200 --> 01:21:05,759
Speaker 1: in high performance computing. Without a doubt, IBMS technology transfers

1417
01:21:05,760 --> 01:21:10,880
Speaker 1: have contributed to China's enhanced high performance computing capabilities. This

1418
01:21:10,960 --> 01:21:15,520
Speaker 1: will lead to a severe compromise of our national security

1419
01:21:15,600 --> 01:21:17,959
Speaker 1: as we have a loss of leadership and high performance

1420
01:21:17,960 --> 01:21:22,280
Speaker 1: computing end quote I mean, and there's even more in

1421
01:21:23,280 --> 01:21:26,400
Speaker 1: IBM formed a joint venture with a Chinese company in spur,

1422
01:21:26,920 --> 01:21:30,719
Speaker 1: handing over the capability to manufacture its own computer servers.

1423
01:21:31,360 --> 01:21:34,080
Speaker 1: That same year, IBM established a partnership with the state

1424
01:21:34,200 --> 01:21:40,080
Speaker 1: owned China Telecom, agreeing to hand over cloud computing technology. Folks,

1425
01:21:41,240 --> 01:21:44,519
Speaker 1: We have US based companies that are handing over the

1426
01:21:44,600 --> 01:21:47,800
Speaker 1: keys to the store, and yeah, they're doing it because

1427
01:21:47,800 --> 01:21:50,000
Speaker 1: they want access to the Chinese markets. They're just looking

1428
01:21:50,000 --> 01:21:55,360
Speaker 1: at their bottom line. But there are clear dual use

1429
01:21:55,400 --> 01:21:58,519
Speaker 1: applications here, and this is the kind of technology that

1430
01:21:58,600 --> 01:22:01,839
Speaker 1: if we actually go to war with China in the future,

1431
01:22:02,720 --> 01:22:08,240
Speaker 1: could be a major problem for us. Think about a

1432
01:22:08,280 --> 01:22:11,160
Speaker 1: world in which China actually has the technological advantage over

1433
01:22:11,240 --> 01:22:15,160
Speaker 1: us militarily. What if they have the best, the fastest,

1434
01:22:15,240 --> 01:22:21,160
Speaker 1: the smartest in planes, submarines, technology of all kinds that's

1435
01:22:21,160 --> 01:22:24,200
Speaker 1: applicable in the battlefield. That's what we are heading toward

1436
01:22:24,320 --> 01:22:25,960
Speaker 1: right now. If we don't get a handle on this,

1437
01:22:26,360 --> 01:22:29,040
Speaker 1: there's only so much our R and D can do

1438
01:22:29,160 --> 01:22:32,000
Speaker 1: to keep us ahead of China if China can keep

1439
01:22:32,120 --> 01:22:37,040
Speaker 1: stealing our research and development. And yet everyone's kind of

1440
01:22:37,040 --> 01:22:39,760
Speaker 1: asleep on this one for the most part. We all

1441
01:22:39,800 --> 01:22:44,559
Speaker 1: just want cheap flat screen televisions and all kinds of

1442
01:22:44,920 --> 01:22:48,439
Speaker 1: junks sent over in huge quantities for us to purchase

1443
01:22:48,479 --> 01:22:52,200
Speaker 1: at the cheapest possible price, and companies like General Electric

1444
01:22:52,280 --> 01:22:56,679
Speaker 1: and IBM are just happy to pad their bottom line.

1445
01:22:57,320 --> 01:22:59,679
Speaker 1: They don't see or don't care to see the national

1446
01:22:59,680 --> 01:23:03,960
Speaker 1: secure the implications of this. But when we faced off

1447
01:23:04,000 --> 01:23:09,559
Speaker 1: against our most recent near peer global competitor, the Soviet Union,

1448
01:23:10,240 --> 01:23:13,519
Speaker 1: it was our technological advantage that was among the most

1449
01:23:13,600 --> 01:23:18,240
Speaker 1: important things We had to keep them in check. Eventually,

1450
01:23:18,240 --> 01:23:21,439
Speaker 1: our economy ran them into the ground, but they were

1451
01:23:21,520 --> 01:23:24,240
Speaker 1: much closer to us militarily than they should have been

1452
01:23:24,240 --> 01:23:27,080
Speaker 1: at numerous points in the Cold War. Because of all

1453
01:23:27,160 --> 01:23:31,479
Speaker 1: this stuff. The Soviets stole Chinese how the second biggest

1454
01:23:31,520 --> 01:23:34,360
Speaker 1: economy in the world, and it's growing very rapidly. They

1455
01:23:34,360 --> 01:23:38,040
Speaker 1: have embraced a market mentality for the purposes of wealth

1456
01:23:38,080 --> 01:23:42,240
Speaker 1: creation and production. It's just state controlled, but their economy

1457
01:23:42,280 --> 01:23:44,920
Speaker 1: is not going to creater and collapse into nothing. They

1458
01:23:44,960 --> 01:23:48,599
Speaker 1: are looking to supplant us as the most powerful nation

1459
01:23:48,800 --> 01:23:53,360
Speaker 1: on earth, and they're stealing some of our most valuable

1460
01:23:53,400 --> 01:23:56,920
Speaker 1: intellectual property in that pursuit. And not only that, we

1461
01:23:57,000 --> 01:23:59,960
Speaker 1: have US companies that are handing it over to them.

1462
01:24:01,640 --> 01:24:04,000
Speaker 1: The Trump administration needs to take action here. I'll follow

1463
01:24:04,040 --> 01:24:06,000
Speaker 1: up more on there's a bill making its way through

1464
01:24:06,040 --> 01:24:08,760
Speaker 1: Congress that will discuss In fact, I'll try to see

1465
01:24:08,800 --> 01:24:10,320
Speaker 1: if you get one of the co authors, maybe even

1466
01:24:10,360 --> 01:24:12,559
Speaker 1: the author of this piece in the Wall Street Journalill

1467
01:24:12,560 --> 01:24:15,360
Speaker 1: come on and talk. I've got more team, stay with me.

1468
01:24:28,280 --> 01:24:31,360
Speaker 1: It was only a matter of time before it was

1469
01:24:31,360 --> 01:24:35,439
Speaker 1: gonna happen, and now it has. The first person on

1470
01:24:35,640 --> 01:24:41,799
Speaker 1: record has been killed by a self driving or autonomous vehicle.

1471
01:24:41,960 --> 01:24:46,679
Speaker 1: This happened in Arizona, and it is the first time.

1472
01:24:46,760 --> 01:24:50,320
Speaker 1: It will not be the last time. But it does

1473
01:24:50,439 --> 01:24:54,200
Speaker 1: have some implications I think for where all this is heading,

1474
01:24:54,240 --> 01:24:58,040
Speaker 1: where all this self driving phenomenon is gonna go. Uh.

1475
01:24:58,080 --> 01:25:00,320
Speaker 1: And first of all, it's just it's tragic, you imagine.

1476
01:25:00,360 --> 01:25:02,720
Speaker 1: I mean, there was somebody behind the wheel of this

1477
01:25:02,920 --> 01:25:07,120
Speaker 1: uber self driving car in Arizona, but they put it

1478
01:25:07,160 --> 01:25:12,280
Speaker 1: on autopilot essentially, and it struck a woman in a crosswalk.

1479
01:25:13,040 --> 01:25:18,840
Speaker 1: Now here's what I've known all along about this. People

1480
01:25:18,880 --> 01:25:22,920
Speaker 1: say that there are roughly what, gosh, I don't even know,

1481
01:25:23,040 --> 01:25:26,719
Speaker 1: thirty thousand. I think auto fatality is a year something

1482
01:25:26,840 --> 01:25:30,559
Speaker 1: like that, something in that neighborhood. Maybe it's less now

1483
01:25:30,600 --> 01:25:33,400
Speaker 1: I think that might have been the all time high. Um.

1484
01:25:33,600 --> 01:25:38,120
Speaker 1: But the thing about those fatalities is that they are

1485
01:25:38,200 --> 01:25:43,760
Speaker 1: spread out among Oh wow, forty forty thousand people died

1486
01:25:43,800 --> 01:25:47,160
Speaker 1: in motorbile vehicle accidents. I thought it was thirty thousands.

1487
01:25:47,200 --> 01:25:50,920
Speaker 1: It's even more than I thought. But a vast majority

1488
01:25:51,360 --> 01:25:55,400
Speaker 1: people don't often talk about this vast majority of vehicular

1489
01:25:55,439 --> 01:26:01,719
Speaker 1: fatalities involve driver error, which is not surprising. Um In

1490
01:26:01,720 --> 01:26:03,720
Speaker 1: in many cases I should actually check and see what

1491
01:26:03,800 --> 01:26:06,360
Speaker 1: the stats are. I think it's just people that make

1492
01:26:06,400 --> 01:26:08,519
Speaker 1: a mistake, much more so than it is people who

1493
01:26:08,520 --> 01:26:12,800
Speaker 1: are impaired or who are doing anything illegal necessarily during

1494
01:26:12,800 --> 01:26:14,800
Speaker 1: you know, people forget to look one way and you

1495
01:26:14,800 --> 01:26:17,479
Speaker 1: know they go through the light or things like that

1496
01:26:17,520 --> 01:26:19,720
Speaker 1: are are obviously a large portion I don't know what

1497
01:26:19,760 --> 01:26:21,800
Speaker 1: the what the percentages are, but a large portion of

1498
01:26:21,800 --> 01:26:26,960
Speaker 1: auti fatalities. But anytime a person dies in a car crash.

1499
01:26:27,080 --> 01:26:28,880
Speaker 1: And it's one thing that here in New York City

1500
01:26:29,520 --> 01:26:32,559
Speaker 1: growing up was was different than it was in other

1501
01:26:32,640 --> 01:26:35,479
Speaker 1: places around the country. I remember when I got to college,

1502
01:26:35,520 --> 01:26:39,479
Speaker 1: I noticed how friends of mine, all of my friends,

1503
01:26:40,280 --> 01:26:44,040
Speaker 1: pretty much to a person, had at least one of

1504
01:26:44,160 --> 01:26:46,599
Speaker 1: their friends died in a car accident in high school.

1505
01:26:46,600 --> 01:26:49,559
Speaker 1: I mean a high school aged person that they knew

1506
01:26:49,640 --> 01:26:52,120
Speaker 1: had died in a car accident. At worst. Because I'm

1507
01:26:52,120 --> 01:26:54,439
Speaker 1: from New York City, none of us even were driving.

1508
01:26:54,479 --> 01:26:57,320
Speaker 1: Really maybe some of us. I drove senior year of

1509
01:26:57,360 --> 01:27:00,479
Speaker 1: high school, but that just wasn't a problem for for

1510
01:27:00,600 --> 01:27:02,240
Speaker 1: us to be worried about. We had we had other

1511
01:27:02,240 --> 01:27:06,400
Speaker 1: things to worry about. But anyway, the overwhelming number of

1512
01:27:06,720 --> 01:27:10,920
Speaker 1: cases of a driver of fatalities a driver air but

1513
01:27:11,000 --> 01:27:14,920
Speaker 1: in all those forty thousand or so deaths, the liability

1514
01:27:14,960 --> 01:27:19,920
Speaker 1: for it is spread around to the individuals involved in

1515
01:27:19,920 --> 01:27:22,479
Speaker 1: the crash, not the car company. Al Right, So if

1516
01:27:22,520 --> 01:27:27,000
Speaker 1: you're in a a Ford Fiesta and you crash into

1517
01:27:27,040 --> 01:27:30,920
Speaker 1: somebody who's in a Prius and there's a fatality in

1518
01:27:30,960 --> 01:27:33,639
Speaker 1: that other car, that's something that you and your insurance

1519
01:27:33,640 --> 01:27:37,719
Speaker 1: companies are dealing with, but it's not something that falls

1520
01:27:37,880 --> 01:27:43,000
Speaker 1: squarely on the shoulders of the manufacturer. I don't know

1521
01:27:43,160 --> 01:27:45,760
Speaker 1: how they're going to handle this from an insurance standpoint.

1522
01:27:46,360 --> 01:27:48,639
Speaker 1: I'm sure there probably are ways, which is why they're

1523
01:27:48,680 --> 01:27:53,080
Speaker 1: pursuing this. But if any time there's a autonomous vehicular

1524
01:27:53,200 --> 01:27:57,479
Speaker 1: accident that ends in a fatality, it ends up being

1525
01:27:57,560 --> 01:28:00,360
Speaker 1: the company's fault, the company can be sued. I don't

1526
01:28:00,360 --> 01:28:02,519
Speaker 1: see how you have a situation that doesn't essentially turn

1527
01:28:02,600 --> 01:28:05,599
Speaker 1: into the equivalent of one long running class action lawsuit

1528
01:28:05,640 --> 01:28:10,400
Speaker 1: against Uber or against whichever company wins this race for

1529
01:28:10,520 --> 01:28:13,920
Speaker 1: autonomous driving dominance. And I also know that there are

1530
01:28:13,920 --> 01:28:15,559
Speaker 1: a lot of people that are gonna that are gonna

1531
01:28:15,560 --> 01:28:19,639
Speaker 1: push back against having all of the different vehicles out

1532
01:28:19,640 --> 01:28:25,000
Speaker 1: there that are machine driven, that are run by algorithms,

1533
01:28:25,000 --> 01:28:28,639
Speaker 1: that are run by artificial intelligence. People like to drive.

1534
01:28:29,320 --> 01:28:32,639
Speaker 1: Everyone in my family, all the males in my family,

1535
01:28:32,640 --> 01:28:39,600
Speaker 1: I should say, really like driving a lot. I do not.

1536
01:28:40,680 --> 01:28:42,840
Speaker 1: I'm fine with it, but I don't enjoy it. Like

1537
01:28:42,960 --> 01:28:46,120
Speaker 1: whenever someone says, hey, I'll drive you, I'm always like, yeah,

1538
01:28:46,360 --> 01:28:48,639
Speaker 1: that sounds good, go ahead. You know. I'm not somebody

1539
01:28:48,640 --> 01:28:50,559
Speaker 1: who fights for the steering row. I just don't really care.

1540
01:28:51,200 --> 01:28:53,799
Speaker 1: I'm also someone who now has avoided I haven't rented

1541
01:28:53,840 --> 01:28:58,000
Speaker 1: a car in in years because I would just prefer

1542
01:28:58,040 --> 01:29:00,559
Speaker 1: to Uber wherever I am, I have no entry. I've

1543
01:29:00,560 --> 01:29:03,880
Speaker 1: had some of the most negative consumer experiences of my

1544
01:29:03,920 --> 01:29:06,240
Speaker 1: life have involved car companies. I hate the whole thing.

1545
01:29:06,439 --> 01:29:09,040
Speaker 1: I hate the hard sell for the bogus additional insurance,

1546
01:29:09,600 --> 01:29:11,960
Speaker 1: all the little extras they try to throw on. You know,

1547
01:29:12,080 --> 01:29:14,720
Speaker 1: here's your little garment GPS, and if you lose it,

1548
01:29:14,720 --> 01:29:16,439
Speaker 1: it's like a thousand dollars or some I mean the

1549
01:29:16,439 --> 01:29:19,120
Speaker 1: whole thing, right, I hate all that stuff. So I'm

1550
01:29:19,160 --> 01:29:22,639
Speaker 1: a big Uber proponent. I just don't know how Google Uber.

1551
01:29:23,040 --> 01:29:26,280
Speaker 1: This is a massive technology race that's going on right now.

1552
01:29:26,720 --> 01:29:29,320
Speaker 1: I don't know how they deal with the issue of

1553
01:29:29,320 --> 01:29:32,960
Speaker 1: the liability of if you are relying on computers to

1554
01:29:33,040 --> 01:29:35,840
Speaker 1: do this, you know, if you're relying on computers to

1555
01:29:35,880 --> 01:29:41,639
Speaker 1: be driving vehicles, unless you can dramatically drop down the number,

1556
01:29:41,680 --> 01:29:43,519
Speaker 1: which is part of the argument. I mean, there's a

1557
01:29:43,520 --> 01:29:47,440
Speaker 1: lot of interesting philosophical components here, but unless you dramatically

1558
01:29:47,520 --> 01:29:52,880
Speaker 1: drive down the number of overall fatalities, it seems to

1559
01:29:52,920 --> 01:29:55,280
Speaker 1: me that you have a big problem of how do

1560
01:29:55,400 --> 01:29:59,360
Speaker 1: we pay for all of the liability that we have

1561
01:29:59,439 --> 01:30:01,800
Speaker 1: as a result of this? You know, computers are gonna fail,

1562
01:30:01,880 --> 01:30:03,840
Speaker 1: and then there's just another And this is not a

1563
01:30:03,880 --> 01:30:08,680
Speaker 1: technology based argument, um, And we're gonna be switching here

1564
01:30:08,760 --> 01:30:12,240
Speaker 1: into a discussion of a movie that I saw over

1565
01:30:12,280 --> 01:30:14,920
Speaker 1: the weekend in a few minutes, The Shape of Water.

1566
01:30:15,720 --> 01:30:18,840
Speaker 1: It was terrible, but I'll give you more than that.

1567
01:30:18,880 --> 01:30:24,439
Speaker 1: But uh, I get a little nervous even with things

1568
01:30:24,560 --> 01:30:28,960
Speaker 1: like elevators. Having been stuck in my fair share of elevators,

1569
01:30:29,640 --> 01:30:32,160
Speaker 1: and I just hate that sense of loss of control.

1570
01:30:33,120 --> 01:30:35,800
Speaker 1: Even if someone shows me the statistics about driving a

1571
01:30:35,840 --> 01:30:37,800
Speaker 1: car or someone else driving me in a car, that

1572
01:30:37,840 --> 01:30:40,519
Speaker 1: it's much less safe than what the autonomous vehicles will

1573
01:30:40,520 --> 01:30:43,920
Speaker 1: be able to to accomplish in in a few short years.

1574
01:30:44,439 --> 01:30:46,000
Speaker 1: I think there's a part of all of us, that

1575
01:30:46,000 --> 01:30:48,040
Speaker 1: there's a part of us as human beings that just

1576
01:30:48,160 --> 01:30:51,920
Speaker 1: want to be able to have some say, some control

1577
01:30:52,120 --> 01:30:56,280
Speaker 1: over are well, whether we live or die in this case.

1578
01:30:56,880 --> 01:30:58,800
Speaker 1: And even if the technology is better, it's gonna take

1579
01:30:58,800 --> 01:31:01,599
Speaker 1: a while for us to switch about anyways. Autonomous vehicle

1580
01:31:01,600 --> 01:31:03,479
Speaker 1: as a subject. We'll get into more going forward, but

1581
01:31:03,960 --> 01:31:07,080
Speaker 1: first fatality and uh, it's gonna slow this whole process

1582
01:31:07,120 --> 01:31:10,160
Speaker 1: down a bit, and very sad. We're gonna run to

1583
01:31:10,200 --> 01:31:23,000
Speaker 1: a quick break team. We'll be right back. He's back

1584
01:31:23,080 --> 01:31:25,439
Speaker 1: with you now, because when it comes to the fight

1585
01:31:25,520 --> 01:31:29,360
Speaker 1: for truth, the fuck never stops. This may very well

1586
01:31:29,439 --> 01:31:32,880
Speaker 1: be the most sensitive asset ever to be housed in

1587
01:31:32,920 --> 01:31:39,160
Speaker 1: this facility. You may think that thing looks human, stands

1588
01:31:39,200 --> 01:31:43,040
Speaker 1: on two legs, right, but we're created in the Lord.

1589
01:31:43,120 --> 01:31:45,360
Speaker 1: J You don't think that's what the Lord looks like.

1590
01:31:46,280 --> 01:31:52,560
Speaker 1: This creature is intelligent, capable of language, of understanding emotions.

1591
01:32:02,880 --> 01:32:06,479
Speaker 1: When he looks at me, he doesn't know how I

1592
01:32:06,520 --> 01:32:13,320
Speaker 1: am incomplete he sees me. I. That was from the

1593
01:32:13,360 --> 01:32:16,960
Speaker 1: trailer for the Shape of Water, which won the Oscar

1594
01:32:17,120 --> 01:32:22,240
Speaker 1: for Best Picture. I felt like I was obligated on

1595
01:32:22,320 --> 01:32:25,920
Speaker 1: Friday to watch this movie. Plus MS Molly wanted to

1596
01:32:25,960 --> 01:32:28,320
Speaker 1: check it out, and I said, okay, fine, And I

1597
01:32:28,320 --> 01:32:32,200
Speaker 1: remember thinking to myself, how bad could it really be?

1598
01:32:32,960 --> 01:32:38,000
Speaker 1: It won the best Picture for the entire year. Oh boy,

1599
01:32:39,160 --> 01:32:42,760
Speaker 1: I was wrong. It was even worse than I expected.

1600
01:32:43,520 --> 01:32:47,240
Speaker 1: The Shape of Water is about a woman who has

1601
01:32:47,280 --> 01:32:53,599
Speaker 1: a sexual relationship with an aquarium pet. I'm not even

1602
01:32:53,640 --> 01:32:56,559
Speaker 1: going to get too far into a criticism of the

1603
01:32:56,600 --> 01:33:01,280
Speaker 1: movie being kind of slow, the dialogue being lackluster, and

1604
01:33:01,320 --> 01:33:03,559
Speaker 1: all the rest of it, the whole thing being trite.

1605
01:33:04,080 --> 01:33:08,679
Speaker 1: I'm actually more annoyed about the messaging in this film

1606
01:33:09,200 --> 01:33:15,320
Speaker 1: and also the completely predictable lens that it looks at

1607
01:33:15,400 --> 01:33:21,200
Speaker 1: this situation that has created this this fantasy. But on

1608
01:33:21,320 --> 01:33:24,320
Speaker 1: the the biggest charge what I just said that this

1609
01:33:24,400 --> 01:33:29,320
Speaker 1: is about a woman who has a romantic relationship, has

1610
01:33:29,400 --> 01:33:34,640
Speaker 1: a love affair with an aquarium pet. For those who

1611
01:33:34,680 --> 01:33:37,680
Speaker 1: would say, oh, Buck, that's not fair. I say, at

1612
01:33:37,720 --> 01:33:40,840
Speaker 1: what point does it become clear? In this movie, which

1613
01:33:40,920 --> 01:33:45,719
Speaker 1: is about essentially the creature from the Blue Lagoon or whatever,

1614
01:33:45,800 --> 01:33:49,200
Speaker 1: or the Deep Lagoon, whatever, that monster creature is gets

1615
01:33:49,280 --> 01:33:53,880
Speaker 1: captured by some government scientists and then the experiment on it.

1616
01:33:53,960 --> 01:33:57,640
Speaker 1: And this woman is cleaning up the room where they

1617
01:33:57,680 --> 01:34:00,320
Speaker 1: keep the monster, not exactly the tightest secure early in

1618
01:34:00,320 --> 01:34:03,200
Speaker 1: the world, and then she decides that she really likes

1619
01:34:03,240 --> 01:34:07,400
Speaker 1: the sea monster, and they start getting kind of playful.

1620
01:34:07,760 --> 01:34:10,760
Speaker 1: Then she brings it home, plops it in her bathtub,

1621
01:34:11,160 --> 01:34:16,360
Speaker 1: and proceeds to get amorous. I will say, and by

1622
01:34:16,400 --> 01:34:19,599
Speaker 1: the way, you see a good bit of that in

1623
01:34:19,640 --> 01:34:23,120
Speaker 1: this movie that won the Academy Award for Best Picture. Now,

1624
01:34:23,160 --> 01:34:27,559
Speaker 1: I've seen a couple of different methods of trying to

1625
01:34:28,360 --> 01:34:33,040
Speaker 1: explain this away. I think it is bizarro on many levels,

1626
01:34:33,280 --> 01:34:37,679
Speaker 1: and and I think it is quite weird. Um, I'm

1627
01:34:37,720 --> 01:34:40,960
Speaker 1: not okay with the whole thing. But people say, Buck,

1628
01:34:41,000 --> 01:34:44,439
Speaker 1: look at other fairy tales, even the great fairy tales

1629
01:34:44,479 --> 01:34:47,320
Speaker 1: we were told as children, right, the princess who kisses

1630
01:34:47,360 --> 01:34:51,519
Speaker 1: the frog. Yeah, but the frog turns into a human being.

1631
01:34:51,680 --> 01:34:54,639
Speaker 1: That's the whole point. It's actually supposed to be a human.

1632
01:34:54,960 --> 01:34:57,439
Speaker 1: People say, oh buck, what about Beauty and the beast.

1633
01:34:57,479 --> 01:35:00,960
Speaker 1: You know, it's like she's with some kind of a

1634
01:35:01,080 --> 01:35:05,160
Speaker 1: large wolf like creature. It's actually human who has a

1635
01:35:05,200 --> 01:35:09,320
Speaker 1: spell on him. All right, that's different. This sea monster

1636
01:35:09,520 --> 01:35:13,120
Speaker 1: that the woman in the shape the shape of water

1637
01:35:13,960 --> 01:35:18,160
Speaker 1: falls in love with, at no point becomes a human being,

1638
01:35:18,680 --> 01:35:22,639
Speaker 1: is actually a human being, is even partially a human being.

1639
01:35:23,240 --> 01:35:26,559
Speaker 1: It's a fish from what we can tell. And then

1640
01:35:26,600 --> 01:35:29,320
Speaker 1: I know the response would be well backed. But it

1641
01:35:29,439 --> 01:35:35,400
Speaker 1: does sign language and it understands her, the protagonist, so well.

1642
01:35:35,800 --> 01:35:39,919
Speaker 1: And to that, I would say, chimpanzees can do sign language,

1643
01:35:40,040 --> 01:35:44,360
Speaker 1: in fact, can do it quite well. And yes, dogs

1644
01:35:44,520 --> 01:35:49,240
Speaker 1: can understand emotion quite well. And while you know, I'm

1645
01:35:49,400 --> 01:35:54,479
Speaker 1: quite fond of dogs, they are not human beings. And

1646
01:35:54,680 --> 01:35:58,639
Speaker 1: I think that the messaging in this movie is lame

1647
01:35:59,080 --> 01:36:02,559
Speaker 1: as well as a bit creepy. Never mind the fact

1648
01:36:02,640 --> 01:36:05,960
Speaker 1: that who who's the bad guy? Oh, of course a

1649
01:36:07,120 --> 01:36:09,719
Speaker 1: they might as well have had him. He's this white,

1650
01:36:09,760 --> 01:36:12,840
Speaker 1: square jawed government guy. He might as well have had

1651
01:36:12,840 --> 01:36:16,599
Speaker 1: a big maga hat on. For the entirety of the movie,

1652
01:36:16,640 --> 01:36:18,919
Speaker 1: even though it takes place, I guess in the late fifties.

1653
01:36:20,080 --> 01:36:23,759
Speaker 1: But he's all about you know, the government and God

1654
01:36:24,200 --> 01:36:30,440
Speaker 1: and America at and he's the worst. He is an unfeeling, sadistic,

1655
01:36:31,120 --> 01:36:34,479
Speaker 1: terrible piece of trash. And everyone else in the movie

1656
01:36:34,520 --> 01:36:37,400
Speaker 1: that you might identify as being somewhat of a liberal,

1657
01:36:37,600 --> 01:36:43,040
Speaker 1: even the communist traitor, the guy who's a double agent

1658
01:36:43,840 --> 01:36:48,720
Speaker 1: for the Soviets, right, he betrays his American colleagues. He's

1659
01:36:48,760 --> 01:36:53,360
Speaker 1: pretending to be someone he's not. Even he has some

1660
01:36:54,160 --> 01:36:56,639
Speaker 1: salvation the movie because well, I don't want to give

1661
01:36:56,680 --> 01:36:58,720
Speaker 1: it all away in case you want to watch it,

1662
01:36:58,760 --> 01:37:05,400
Speaker 1: but every one has redeeming characteristics and qualities except for

1663
01:37:05,600 --> 01:37:11,800
Speaker 1: the white male Christian government you know FBI guy. Basically,

1664
01:37:12,640 --> 01:37:14,120
Speaker 1: this is what I always have to laugh about. The

1665
01:37:14,160 --> 01:37:18,040
Speaker 1: media hates white males and the FBI by and large,

1666
01:37:18,040 --> 01:37:20,280
Speaker 1: you know, they really are against them for a whole

1667
01:37:20,320 --> 01:37:23,760
Speaker 1: bunch of reasons, except for any white males of the

1668
01:37:23,800 --> 01:37:27,519
Speaker 1: FBI that are useful in bashing Trump or or who

1669
01:37:27,600 --> 01:37:30,840
Speaker 1: are trying to take the Trump presidency down. But but

1670
01:37:31,040 --> 01:37:34,320
Speaker 1: the Shape of Water is just it was a really

1671
01:37:34,360 --> 01:37:36,599
Speaker 1: bad movie. I mean, they should rename it the Shape

1672
01:37:36,760 --> 01:37:40,360
Speaker 1: of Goose Turd, because that's what it was that at one.

1673
01:37:40,439 --> 01:37:43,720
Speaker 1: Best picture is just more evidence of what I've been

1674
01:37:43,760 --> 01:37:46,880
Speaker 1: saying for some time, which is that the movie industry

1675
01:37:47,280 --> 01:37:50,680
Speaker 1: is in a really weak spot these days. TV is

1676
01:37:50,720 --> 01:37:54,879
Speaker 1: doing well overall, and I think it's going to continue

1677
01:37:54,880 --> 01:38:00,960
Speaker 1: on this path. But the Shape of Water, it's just hollow.

1678
01:38:01,040 --> 01:38:07,840
Speaker 1: The whole thing. It is unredeeming in in every way. Uh.

1679
01:38:07,840 --> 01:38:09,800
Speaker 1: And I just couldn't believe it that that this is

1680
01:38:09,880 --> 01:38:12,240
Speaker 1: what This is not just a movie that I'm trashing, folks.

1681
01:38:12,280 --> 01:38:15,040
Speaker 1: This is supposed to be the collective wisdom of Hollywood

1682
01:38:15,120 --> 01:38:18,639
Speaker 1: is what is the best movie of Like I said,

1683
01:38:19,360 --> 01:38:38,439
Speaker 1: Big Goose, Turt, We'll be right back. I like to

1684
01:38:38,479 --> 01:38:42,679
Speaker 1: think of myself as an innovator. Team there are times

1685
01:38:42,680 --> 01:38:45,320
Speaker 1: when I have to stop and give myself a little

1686
01:38:45,320 --> 01:38:50,960
Speaker 1: bit of credit for being a trendsetter or perhaps a

1687
01:38:51,080 --> 01:38:56,040
Speaker 1: pioneer of style, at least when it comes to food

1688
01:38:56,880 --> 01:39:01,320
Speaker 1: and eating of meat. So I realized this because I

1689
01:39:01,720 --> 01:39:05,440
Speaker 1: made a ribby for Ms. Molly and I on Friday,

1690
01:39:05,479 --> 01:39:07,720
Speaker 1: and I will tell you that it was seared perfectly

1691
01:39:08,240 --> 01:39:13,160
Speaker 1: and it was amazing. The dollar cast iron pan that

1692
01:39:13,240 --> 01:39:15,920
Speaker 1: I got myself was one of the better investments I

1693
01:39:15,960 --> 01:39:21,240
Speaker 1: can remember making in recent years. But the next day,

1694
01:39:21,400 --> 01:39:24,400
Speaker 1: I thought to myself, you know, what is one to

1695
01:39:24,520 --> 01:39:29,960
Speaker 1: do with leftover ribby? Oh, that's right, I'm going to

1696
01:39:30,040 --> 01:39:34,400
Speaker 1: make steak and eggs. That was also amazing, by the way,

1697
01:39:34,479 --> 01:39:36,680
Speaker 1: But then I thought to myself, what am I going

1698
01:39:36,760 --> 01:39:40,479
Speaker 1: to do with some of that delicious thick cut bacon

1699
01:39:40,520 --> 01:39:43,080
Speaker 1: that I have in my fridge that I specifically got

1700
01:39:43,360 --> 01:39:46,080
Speaker 1: so that I could cook it to absolute perfection on

1701
01:39:46,120 --> 01:39:51,479
Speaker 1: Saturday and have a hashtag Buck brunch. Why is it

1702
01:39:51,600 --> 01:39:55,080
Speaker 1: just steaking eggs, my friends, when it could be steak

1703
01:39:55,840 --> 01:40:02,479
Speaker 1: and eggs and bacon. Ah. Indeed, so I went with

1704
01:40:02,520 --> 01:40:06,799
Speaker 1: all three the trifecta steak, eggs, and bacon for brunch

1705
01:40:06,880 --> 01:40:10,280
Speaker 1: on Saturday. And this is what everyone should do going forward.

1706
01:40:10,479 --> 01:40:12,479
Speaker 1: There's no need to cut out the bacon just because

1707
01:40:12,479 --> 01:40:15,920
Speaker 1: you're having the steak. Maybe just limit yourself to a

1708
01:40:15,960 --> 01:40:20,120
Speaker 1: pounder sew. And with that, I would like to get

1709
01:40:20,200 --> 01:40:33,479
Speaker 1: into some roll call. Team Buck. It's time for roll call,

1710
01:40:33,960 --> 01:40:40,320
Speaker 1: and remember, if you want to be a part of

1711
01:40:40,439 --> 01:40:43,840
Speaker 1: roll call, you can send us a message on Facebook

1712
01:40:43,880 --> 01:40:48,000
Speaker 1: at facebook dot com, slash Buck Sexton or official Team

1713
01:40:48,120 --> 01:40:50,759
Speaker 1: Buck at gmail dot com. If you'd like to send

1714
01:40:50,760 --> 01:40:54,559
Speaker 1: an email We are also thinking about setting up a

1715
01:40:54,680 --> 01:40:58,360
Speaker 1: special voicemail that we would be able to have recording

1716
01:40:58,400 --> 01:41:01,559
Speaker 1: when we're not on air, and then those of you

1717
01:41:01,600 --> 01:41:03,760
Speaker 1: who have a voice message you'd like to leave so

1718
01:41:03,800 --> 01:41:05,760
Speaker 1: that the rest of the team can hear it, we

1719
01:41:05,800 --> 01:41:08,559
Speaker 1: could do that. So if you couldn't listen live, for example,

1720
01:41:08,600 --> 01:41:12,960
Speaker 1: if you happen to be one of our wonderful podcast listeners,

1721
01:41:13,320 --> 01:41:17,360
Speaker 1: well then we very much could put your audio on

1722
01:41:17,520 --> 01:41:21,160
Speaker 1: air when we do our next live show. First up

1723
01:41:21,240 --> 01:41:26,920
Speaker 1: on roll Call is Roger. He writes, Buck just heard

1724
01:41:27,640 --> 01:41:32,080
Speaker 1: the podcast uh from the Friday show about Bob Dylan

1725
01:41:32,200 --> 01:41:35,360
Speaker 1: and gurgling with Gergen. It made me laugh out loud.

1726
01:41:35,720 --> 01:41:39,479
Speaker 1: No easy task, shields Hie. Thank you very much. Roger

1727
01:41:40,360 --> 01:41:45,160
Speaker 1: with Gergan and Bob Dylan also make me laugh. Monica

1728
01:41:45,320 --> 01:41:48,599
Speaker 1: next up here, she writes, Uh, this is the husband

1729
01:41:48,600 --> 01:41:53,360
Speaker 1: of Monica and I ate these in Belfast. You asked

1730
01:41:53,800 --> 01:42:00,880
Speaker 1: was their Irish ethnic food? Here it is Shepherd's pie. Okay,

1731
01:42:01,080 --> 01:42:04,400
Speaker 1: that's I'll take it. Not exactly something that's gonna get

1732
01:42:04,400 --> 01:42:07,559
Speaker 1: me too excited in the world of culinary excellence, but

1733
01:42:07,640 --> 01:42:12,040
Speaker 1: Shepherd's pie is indeed. Is it Irish thrower? Is it English? Oh?

1734
01:42:12,080 --> 01:42:13,439
Speaker 1: I don't want to get the middle of that one.

1735
01:42:14,080 --> 01:42:19,040
Speaker 1: Let's get to Erica, and she writes, I really listened

1736
01:42:19,040 --> 01:42:21,600
Speaker 1: to Thursday's program to get the name of the Progressive

1737
01:42:21,680 --> 01:42:25,400
Speaker 1: Hostility study. Since none of my Google searches found it,

1738
01:42:25,800 --> 01:42:28,880
Speaker 1: I tried again to conduct the exact title and nothing.

1739
01:42:29,520 --> 01:42:34,840
Speaker 1: Tried Duck duck go, and voila, there was the study. Well, Erica,

1740
01:42:34,880 --> 01:42:36,559
Speaker 1: I don't know about this duck duck go, but maybe

1741
01:42:36,640 --> 01:42:39,080
Speaker 1: it's better for some thing than Google. I'll have to

1742
01:42:39,120 --> 01:42:41,760
Speaker 1: check it out. But the piece that I mentioned was

1743
01:42:41,800 --> 01:42:45,320
Speaker 1: on quillette dot com and it was or I went

1744
01:42:45,360 --> 01:42:47,559
Speaker 1: into some depth about it and just mentioned it, and

1745
01:42:47,640 --> 01:42:54,439
Speaker 1: it was the Psychology of Progressive Hostility. Next up here,

1746
01:42:54,800 --> 01:43:00,479
Speaker 1: Joey Annette, wow Buck, you're right, Sessions did fire me, Cabe.

1747
01:43:01,600 --> 01:43:03,439
Speaker 1: Jeff is a little late to the party, but he

1748
01:43:03,479 --> 01:43:06,720
Speaker 1: finally showed up with a haymaker. Now he'll just un

1749
01:43:06,800 --> 01:43:10,519
Speaker 1: recuse himself and fire Muller and stop this stupid waste

1750
01:43:10,520 --> 01:43:14,479
Speaker 1: of taxpayer money masquerading as an investigation. Shields high and

1751
01:43:14,560 --> 01:43:17,360
Speaker 1: keep up the good work. Well, Joey in Annette, I

1752
01:43:17,439 --> 01:43:20,639
Speaker 1: will say that I not only called the firing on radio,

1753
01:43:21,040 --> 01:43:24,639
Speaker 1: I also went out there on Outnumbered on Fox News

1754
01:43:24,680 --> 01:43:28,000
Speaker 1: on Friday and said, Hey, guess what, there's gonna be

1755
01:43:28,040 --> 01:43:32,439
Speaker 1: a firing of McCabe And uh, I was correct, So

1756
01:43:32,600 --> 01:43:35,879
Speaker 1: thank you for noting that I was in fact correct.

1757
01:43:36,640 --> 01:43:43,920
Speaker 1: Next up here, hold on one second, is Philip, and

1758
01:43:44,000 --> 01:43:48,200
Speaker 1: he writes, Hey, man, I'm sure you've probably been told already,

1759
01:43:48,280 --> 01:43:54,519
Speaker 1: but producer Mike was incorrect about the population of Russia. Yes, Philip, Uh,

1760
01:43:54,600 --> 01:43:57,559
Speaker 1: I was in fact basically correct. I said a hundred

1761
01:43:57,560 --> 01:44:00,719
Speaker 1: and twenty million. The population of Russia's actually a hundred

1762
01:44:00,760 --> 01:44:03,640
Speaker 1: and forty million. Producer Mike on Friday told me it

1763
01:44:03,720 --> 01:44:07,000
Speaker 1: was seventy million based on a quick Google search. Do

1764
01:44:07,160 --> 01:44:12,240
Speaker 1: not worry. We will shortly assign him a code read Dick.

1765
01:44:14,240 --> 01:44:16,680
Speaker 1: Once again, this goes to my theory that even when

1766
01:44:16,720 --> 01:44:20,640
Speaker 1: I think I might be wrong, I'm usually right. Uh

1767
01:44:20,760 --> 01:44:25,280
Speaker 1: let's see, Dale, He writes, really enjoyed your sidebar the

1768
01:44:25,320 --> 01:44:28,599
Speaker 1: other evening about missed a game series near and dear

1769
01:44:28,680 --> 01:44:31,760
Speaker 1: to my heart, So Buck, which brother did you pick

1770
01:44:31,840 --> 01:44:35,439
Speaker 1: at the end of the original game, Dale, I cannot

1771
01:44:35,439 --> 01:44:37,639
Speaker 1: tell a lie. I didn't get that far and missed

1772
01:44:37,680 --> 01:44:39,360
Speaker 1: because I was really young when I was playing it,

1773
01:44:39,439 --> 01:44:43,200
Speaker 1: and some of those puzzles may have stumped me, but

1774
01:44:43,439 --> 01:44:46,320
Speaker 1: miss was. I remember going into computer stores in the

1775
01:44:46,360 --> 01:44:51,719
Speaker 1: early days of home PCs, or it is of PCs

1776
01:44:52,120 --> 01:44:55,760
Speaker 1: home PC would be repetitive, and there were missed. There

1777
01:44:55,800 --> 01:44:58,920
Speaker 1: were copies of missed everywhere. I also remember really not

1778
01:44:59,040 --> 01:45:01,680
Speaker 1: liking Mac computer uters for a while because all of

1779
01:45:01,720 --> 01:45:06,200
Speaker 1: the video games were for PC windows, and if you

1780
01:45:06,240 --> 01:45:10,360
Speaker 1: wanted good games, Mac was not the choice for you.

1781
01:45:10,880 --> 01:45:14,800
Speaker 1: And then later on people pretty much stopped using their

1782
01:45:14,840 --> 01:45:17,599
Speaker 1: computers for games. I feel like, in general at all

1783
01:45:17,640 --> 01:45:21,120
Speaker 1: went to PlayStations and these other consoles with the big

1784
01:45:21,120 --> 01:45:24,760
Speaker 1: flat screen TVs. But I did not get very far

1785
01:45:24,960 --> 01:45:28,360
Speaker 1: in missed. I must be honest with you. Now, we've

1786
01:45:28,360 --> 01:45:32,640
Speaker 1: got Pablo who writes listening to your show recently, and

1787
01:45:32,640 --> 01:45:36,040
Speaker 1: you were talking about visiting Vietnam. We're heading there a

1788
01:45:36,080 --> 01:45:39,639
Speaker 1: week from Monday and are super pumped. We're doing Hannoy

1789
01:45:39,800 --> 01:45:43,520
Speaker 1: for a few days in a Cinnamon Cathedral UH hotel

1790
01:45:43,760 --> 01:45:46,360
Speaker 1: and then onto how Long Bay for a few nights.

1791
01:45:46,800 --> 01:45:49,840
Speaker 1: We're disappointed to miss h some of the stuff, but

1792
01:45:49,880 --> 01:45:53,000
Speaker 1: pumping nonetheless. A Pablo, I think you're gonna have a

1793
01:45:53,000 --> 01:45:55,280
Speaker 1: great time. I love the food. I think it's I

1794
01:45:55,280 --> 01:45:57,760
Speaker 1: just think it's a really interesting place and very very

1795
01:45:57,800 --> 01:46:02,000
Speaker 1: different from other cultures and other countries around the world.

1796
01:46:02,560 --> 01:46:05,160
Speaker 1: But have a great time and let us know what

1797
01:46:05,280 --> 01:46:07,960
Speaker 1: you think. And for those of you who asked what

1798
01:46:08,080 --> 01:46:11,240
Speaker 1: cuisine I'd recommend to start with, I mentioned Foe, which

1799
01:46:11,280 --> 01:46:14,519
Speaker 1: is the most famous, which you usually spelled p h o,

1800
01:46:15,000 --> 01:46:18,040
Speaker 1: which is sliced beef in a kind of soup slash

1801
01:46:18,200 --> 01:46:21,519
Speaker 1: noodle stew. But the other thing that I really love

1802
01:46:21,680 --> 01:46:25,840
Speaker 1: is a rice pancake called a band saw, So if

1803
01:46:25,840 --> 01:46:27,760
Speaker 1: you can get that, I would say that's a very

1804
01:46:27,760 --> 01:46:31,000
Speaker 1: good place to start. And Boon Cha, which is a

1805
01:46:31,040 --> 01:46:34,160
Speaker 1: noodle dish, is also really excellent. By the way, one

1806
01:46:34,160 --> 01:46:36,080
Speaker 1: of the reasons I like this food so much, Vietnamese

1807
01:46:36,120 --> 01:46:38,880
Speaker 1: food is that it doesn't use that much soy sauce,

1808
01:46:38,960 --> 01:46:41,840
Speaker 1: so as a ciliac, I can eat most things on

1809
01:46:41,880 --> 01:46:45,560
Speaker 1: the menu. It uses mostly rice instead of flower noodles,

1810
01:46:45,640 --> 01:46:49,680
Speaker 1: so that's just for full disclosure. It's one of the

1811
01:46:49,720 --> 01:46:54,320
Speaker 1: only cuisines that is a an ethnic cuisine that is

1812
01:46:54,400 --> 01:46:58,080
Speaker 1: really easy for people who are gluten intolerant to enjoy.

1813
01:46:59,080 --> 01:47:02,040
Speaker 1: William is up next to here, He writes, quit crying

1814
01:47:02,080 --> 01:47:05,639
Speaker 1: about being old. I started Tae Kwondo at forty four,

1815
01:47:06,080 --> 01:47:08,759
Speaker 1: after twenty years of army service and over a thousand

1816
01:47:08,840 --> 01:47:12,599
Speaker 1: days in Iraq, and five kids. The five kids are

1817
01:47:12,640 --> 01:47:16,960
Speaker 1: much more challenging than convoy security. William, You're right, man,

1818
01:47:17,040 --> 01:47:19,880
Speaker 1: I uh, I shouldn't be given any I shouldn't be

1819
01:47:19,880 --> 01:47:22,439
Speaker 1: complained at all. I don't know how all you folks

1820
01:47:22,439 --> 01:47:24,680
Speaker 1: out there who are parents, I don't know how you

1821
01:47:24,760 --> 01:47:29,920
Speaker 1: do it. Uh. Kimberly is next up here, she writes, Buck,

1822
01:47:30,040 --> 01:47:35,280
Speaker 1: I love your show, O S S Team Buck, North Carolina. Well,

1823
01:47:35,320 --> 01:47:38,439
Speaker 1: thank you very much, Kimberly, I appreciate it. Next one

1824
01:47:38,479 --> 01:47:42,760
Speaker 1: here in roll Call is Christie. She writes, I think

1825
01:47:42,840 --> 01:47:45,880
Speaker 1: there's at least one movie in which Colin Farrell does

1826
01:47:46,000 --> 01:47:49,960
Speaker 1: not suck. He plays a hit man alongside a fellow

1827
01:47:50,000 --> 01:47:55,720
Speaker 1: brilliant actor in uh In in Bruges. Interesting film and

1828
01:47:55,760 --> 01:47:58,200
Speaker 1: beautiful scenery. I hope you all have a wonderful weekend.

1829
01:47:58,320 --> 01:48:01,320
Speaker 1: Happy St. Patrick's Day, and yeah us you're allowed to say,

1830
01:48:01,600 --> 01:48:05,320
Speaker 1: y'all we don't mind, Christie, O S S. Member, Well,

1831
01:48:05,360 --> 01:48:08,040
Speaker 1: thank you so much, Christie. Hope y'all have a great

1832
01:48:08,080 --> 01:48:14,200
Speaker 1: Saint Patrick's two down in Uh? Where were you? OSS member?

1833
01:48:14,360 --> 01:48:17,320
Speaker 1: From where? I'm not clear she was from the South,

1834
01:48:17,560 --> 01:48:21,040
Speaker 1: between which we know Christie. I haven't seen in Bruges,

1835
01:48:21,120 --> 01:48:23,479
Speaker 1: but I have heard good things, so maybe I'll add

1836
01:48:23,560 --> 01:48:26,799
Speaker 1: that to my now very rapidly expanding list of shows

1837
01:48:27,200 --> 01:48:30,679
Speaker 1: that I must check out. So um, with that team,

1838
01:48:30,800 --> 01:48:33,800
Speaker 1: I am going to close up shop here in the

1839
01:48:33,800 --> 01:48:36,479
Speaker 1: Freedom Hunt for the day. Thank you always for being

1840
01:48:36,640 --> 01:48:39,519
Speaker 1: with me. Please uh spread the word about what we

1841
01:48:39,600 --> 01:48:43,120
Speaker 1: do here and see you tomorrow shield Hie