Latest / The Chuck ToddCast / Full Episode - How America Can Produce Another “Leader Of The Free World” + Higher Ed In The Age Of AI

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Full Episode - How America Can Produce Another “Leader Of The Free World” + Higher Ed In The Age Of AI · The Chuck ToddCast

0:00
Speaker 1: This episode of the Chuck Todd cast is brought to
0:02
Speaker 1: you by Chapter. Now, almost everything you hear about Medicare
0:06
Speaker 1: is somebody quietly trying to steer you somewhere. And you're
0:11
Speaker 1: skeptical of that, as you should be. I get it.
0:14
Speaker 1: I mean, there's a federal lawsuit going on right now
0:17
Speaker 1: over exactly this. Companies that branded themselves as unbiased while
0:21
Speaker 1: allegedly pointing people toward whatever would pay them the most
0:25
Speaker 1: as some sort of broker. So if your default is
0:28
Speaker 1: to distrust everyone in this space, honestly, I get it.
0:31
Speaker 1: I'm a bit distrustful these days myself. That's the whole
0:34
Speaker 1: reason I want to tell you about Chapter. They're independent
0:37
Speaker 1: Medicare advisors whose entire model is that their advisors are
0:41
Speaker 1: not paid to push any one plan. They're just trying
0:45
Speaker 1: to help. Yes, there's compensation that goes with it. but
0:47
Speaker 1: it's across the board is what they're trying to do.
0:51
Speaker 1: At the end of the day, they're advocating for you.
0:52
Speaker 1: They're not the insurance companies themselves. They're an actual person
0:56
Speaker 1: who actually goes through your doctors, your prescriptions, your needs,
1:01
Speaker 1: and then compares them to every single plan available to
1:04
Speaker 1: find the best one that will work for you and
1:06
Speaker 1: hopefully save you a couple dollars too. And here's the
1:09
Speaker 1: part that sets chapter apart. They don't disappear once you've
1:14
Speaker 1: been in They will keep advocating for you. They're kind
1:17
Speaker 1: of like almost like a concierge service. You're just there.
1:19
Speaker 1: I need help. You're like customer service. You know, the plan,
1:22
Speaker 1: you know, help me navigate this again. So you ever
1:24
Speaker 1: get hit with a wrongful medical bill, they'll help you
1:28
Speaker 1: fight it. They want to stay an advocate for you
1:31
Speaker 1: even after you've done this. So look, I get it.
1:34
Speaker 1: I think there's all sorts of space. You see a
1:38
Speaker 1: lot of people are throwing themselves in this healthcare space.
1:41
Speaker 1: What I like about these chapter folks, I've spent time
1:44
Speaker 1: with them. This is a very transparent organization. It is
1:48
Speaker 1: Medicare and all of its affiliated stuff can be very confusing.
1:53
Speaker 1: The whole point of this is to make this easier
1:56
Speaker 1: and less confusing. OK, so look, take the skepticism you
2:00
Speaker 1: already have in all of this, point it at your
2:02
Speaker 1: own plan for 20 minutes. It's free. There's no pressure.
2:06
Speaker 1: And then call chapter today at 980-734-4200. Hello there. Greetings
2:18
Speaker 1: from Tempe, Arizona. I just spent my Wednesday at Arizona
2:24
Speaker 1: State University. They have a new IOP, Institute of Politics,
2:28
Speaker 1: started by former Arizona Senator Jeff Flake. He was, of course,
2:31
Speaker 1: Republican senator from Arizona. He was Joe Biden's ambassador to Turkey.
2:35
Speaker 1: And I just spent my Wednesday And we had a
2:37
Speaker 1: couple of great conversations. One of them you'll see on
2:40
Speaker 1: Newsphere over the weekend. And one of them you just
2:44
Speaker 1: missed an opportunity, perhaps, if you live in the Phoenix area.
2:48
Speaker 1: We had a terrific crowd and we talked a little midterms,
2:51
Speaker 1: a little future of the conservative movement, a little future
2:53
Speaker 1: of Republican politics, a little future of Democratic politics, some
2:58
Speaker 1: good stuff. And let me just tell you, I couldn't
3:03
Speaker 1: have picked a better week. I literally just missed the heat,
3:08
Speaker 1: just missed those 100-degree days. Came and landed. It wasn't
3:11
Speaker 1: quite 80. Getting that desert coolness. Me and the snowbirds
3:16
Speaker 1: have all made our way to Tempe here in October.
3:19
Speaker 1: I get it. It's the first time I've been here
3:21
Speaker 1: in October. I get it now. I've been here in July.
3:25
Speaker 1: What the heck? Is anybody thinking about settling anybody down?
3:28
Speaker 1: any human civilization in the valley here. But when you're
3:32
Speaker 1: here in October, you're like, oh, this is why half
3:35
Speaker 1: the Midwest has moved here. So I am on the road.
3:40
Speaker 1: I will be back in the creature comforts of the
3:44
Speaker 1: East Coast soon enough. But here we are. We're 19
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Speaker 1: days until Election Day. Millions of Americans have already voted.
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Speaker 1: We're learning a little something with the early vote, but
3:54
Speaker 1: not enough yet for me to share too many details,
3:58
Speaker 1: fascinating little micro trends that certainly a bunch of people
4:04
Speaker 1: are focused on, including what appears to be a bit
4:08
Speaker 1: of a surge of Hispanic voters in the early vote.
4:13
Speaker 1: The debate, though, is are we seeing just more Latinos
4:17
Speaker 1: voting early because they don't want to go to the
4:18
Speaker 1: polls in person for fear of whatever the government might do?
4:22
Speaker 1: And I have an update about a very disturbing incident
4:26
Speaker 1: that took place during hurricane recovery efforts down in Florida?
4:31
Speaker 1: Or is this simply enthusiasm about the election and you
4:35
Speaker 1: have a lot of Latino voters that are ready to
4:38
Speaker 1: get engaged? Either way, it is the early trend line
4:41
Speaker 1: that we're watching there. But there's something else I want
4:45
Speaker 1: to point out. And in fact, we're heading into what
4:47
Speaker 1: I think could be one of the more consequential weekends
4:49
Speaker 1: of the entire midterm campaign. because I want to start
4:53
Speaker 1: with something that's going to be happening on Saturday, that
4:56
Speaker 1: probably deserves a bit more attention than it's been getting,
4:58
Speaker 1: though I imagine, as you're listening to this on Thursday
5:02
Speaker 1: and on Friday, you'll start to realize coverage of this
5:05
Speaker 1: is going to ramp up. The fourth of these so-called
5:07
Speaker 1: No Kings rallies is taking place this weekend. They're calling
5:11
Speaker 1: it a day of action, and it's set for October 17th,
5:14
Speaker 1: this Saturday. And this one's going to look a lot
5:16
Speaker 1: different from the previous one, because the organizers themselves are
5:21
Speaker 1: very aware of what's taking place on November 3rd. In fact,
5:25
Speaker 1: they're calling this one No Kings Vote Early. And that
5:28
Speaker 1: tells you just about everything you need to know about
5:30
Speaker 1: what they're trying to accomplish. This isn't simply another day
5:33
Speaker 1: of mass demonstrations against Donald Trump and his administration. This
5:37
Speaker 1: is an attempt to turn what has become one of
5:39
Speaker 1: the largest protest movements in American history into an actual
5:43
Speaker 1: voter turnout operation. You got more than 2,000 events planned
5:48
Speaker 1: across all 50 states, plus the District of Columbia. But
5:52
Speaker 1: they're not focused on marches. The organizers are all encouraging
5:55
Speaker 1: block parties, cookouts, voter registration activities, and even organized walks
6:01
Speaker 1: to the polls. So it's quite the evolution for this movement, right?
6:05
Speaker 1: The first three No Kings demonstrations were largely about showing
6:08
Speaker 1: the country, showing the White House that there was a
6:12
Speaker 1: large group of Americans so upset they were willing to
6:16
Speaker 1: use their Saturday to demonstrate their anger at the administration.
6:22
Speaker 1: And those numbers were enormous. We kind of gloss over
6:24
Speaker 1: them by the time the second and third, well, look,
6:27
Speaker 1: another big protest, but they kept coming, right? Folks kept
6:31
Speaker 1: showing up. We don't have official numbers that aren't from
6:36
Speaker 1: the organizers, but the organizers have claimed millions of participants.
6:39
Speaker 1: And my own eyes don't deceive me. And I know
6:41
Speaker 1: I'm in the nation's capital and there's a tad more
6:45
Speaker 1: enthusiasm to protesting Trump at times, because he is literally,
6:49
Speaker 1: you know, come after residents of the district and of
6:56
Speaker 1: Northern Virginia and of Maryland. So there's, you know, I've
6:59
Speaker 1: always said, you know, the closer you are to Washington,
7:01
Speaker 1: the more acute your TDS is, and the anger at Trump,
7:06
Speaker 1: because he's been disruptive to your local life, to your
7:08
Speaker 1: local art centers, all these sorts of things. But the
7:13
Speaker 1: fact is we've seen these numbers have been enormous everywhere.
7:16
Speaker 1: And now if you're turning this mobilization into an early vote,
7:20
Speaker 1: this is something that the Democratic Party couldn't have put
7:23
Speaker 1: together had they tried. And it's going to be fascinating
7:27
Speaker 1: to see if they can convert protest energy into electoral participation.
7:32
Speaker 1: And it's some voters that don't normally participate. That's what
7:36
Speaker 1: we don't know in here. But look, the organizers all
7:39
Speaker 1: claim these are nonpartisan. And they aren't supposed to be
7:43
Speaker 1: campaign rallies for Democratic candidates. But look, politically, these are
7:46
Speaker 1: anti-Trump rallies now. And you look at some of the
7:50
Speaker 1: organizations involved and many of them have been associated more
7:55
Speaker 1: with the left. You know, you've got Indivisible, MoveOn, the ACLU, AFT.
8:01
Speaker 1: But there are other groups, Black Votes, Voters Matter, State Voices,
8:05
Speaker 1: Voto Latino, So this is sort of a protest movement
8:09
Speaker 1: that has become, it appears to have been turned into
8:13
Speaker 1: a get-out-the-vote operation. And it may have more credibility than
8:20
Speaker 1: a get-out-the-vote operation run by the actual Democratic Party. Being
8:29
Speaker 1: anti-Trump doesn't mean you're pro-Democratic Party. There are plenty of
8:33
Speaker 1: people who oppose Trump who don't consider themselves Democrats. who
8:36
Speaker 1: aren't particularly enthusiastic about the National Democratic Party. And they
8:40
Speaker 1: may have very different ideas on what should come after Trump.
8:44
Speaker 1: But this is a group of people united that are
8:46
Speaker 1: opposition to this administration. And perhaps conventional Democratic Party politics
8:53
Speaker 1: couldn't figure out how to talk to those people while
8:55
Speaker 1: this protest movement can. So look, we'll see what happens.
9:00
Speaker 1: But this could really, I'm very curious to see if
9:05
Speaker 1: we see a surge in new vote, or if essentially
9:10
Speaker 1: the protests earlies up voters that would have already participated
9:14
Speaker 1: down the road, something we really won't be able to
9:16
Speaker 1: measure until after election day, to be honest, to find
9:18
Speaker 1: out how effective this weekend is going to be. But
9:23
Speaker 1: I have a feeling this is gonna be a pretty
9:25
Speaker 1: big weekend for the blue team in organizing and getting
9:29
Speaker 1: people participating in the early vote. and it's going to
9:32
Speaker 1: be something. But first, I've got a few other things
9:35
Speaker 1: I want to get to. I've got a bit of
9:36
Speaker 1: an eclectic campaign notebook, including that confrontation with hurricane recovery workers.
9:44
Speaker 1: But we're going to close with something I wrote about
9:46
Speaker 1: on my substack and my Newsphere column on sort of
9:50
Speaker 1: the ingredients that I think already exist for the leader
9:53
Speaker 1: we need post-Trump. But let me start with a city
9:59
Speaker 1: that I spend a lot of time in. It's Pensacola,
10:03
Speaker 1: where I'm wondering if we've just lost the plot. If Trump,
10:07
Speaker 1: Stephen Miller, and ICE have completely lost the plot here.
10:10
Speaker 1: Let me start with what the story is. It's out
10:12
Speaker 1: of Pensacola Beach, Florida. This is where I've this podcast
10:15
Speaker 1: has for most of the summer was based in Pensacola Beach, Florida. OK,
10:21
Speaker 1: this is where I spend a lot of time. This
10:23
Speaker 1: is where my Florida headquarters are for the podcast. And
10:29
Speaker 1: according to Pensacola News Journal, federal immigration enforcement officials showed up.
10:35
Speaker 1: At a restaurant that when you come onto the beach,
10:37
Speaker 1: it's called the Grand Marlin. It's the first restaurant that
10:39
Speaker 1: you see. It's this big building. It's a well-known landmark
10:43
Speaker 1: to anybody that's spent time on Pensacola Beach. And they
10:46
Speaker 1: showed up at the restaurant where a crew of roofers
10:49
Speaker 1: were repairing damage from the hurricane from last week, Isaias.
10:53
Speaker 1: And I don't know if we've all come to an
10:56
Speaker 1: agreement on how we're pronouncing this hurricane's name. I've been
10:58
Speaker 1: going to Isaias. I know others say it differently, but
11:03
Speaker 1: I'm sticking to that pronunciation. Well, so it appeared to be,
11:09
Speaker 1: there wasn't confirmation if it was ICE or if it
11:11
Speaker 1: was HSI, which is Homeland Security Investigators, but they've been
11:15
Speaker 1: operating in tandem at many of these immigration raves. Well,
11:20
Speaker 1: the roofers refused to come down. They decided to stay
11:22
Speaker 1: on the roof when these folks showed up. And according
11:24
Speaker 1: to witnesses, these federal agents remained at the restaurant for
11:28
Speaker 1: about two hours before eventually they decided to leave without
11:30
Speaker 1: making any arrests. Now, again, we don't know for sure
11:35
Speaker 1: where these confirmed ICE agents. That wasn't clear. Witnesses said
11:39
Speaker 1: it was Homeland Security personnel. There was clearly some law
11:46
Speaker 1: enforcement agency claiming to act on the behest of the
11:50
Speaker 1: federal government, was essentially trying to find out what the
11:57
Speaker 1: citizenship status was for the people doing hurricane recovery. These
12:01
Speaker 1: guys were not committing a crime. they were repairing a
12:04
Speaker 1: roof damaged by a hurricane. This is a community trying
12:10
Speaker 1: to recover from a natural disaster, Mr. President. Businesses are
12:16
Speaker 1: trying to reopen. Homeowners are trying to make their properties
12:18
Speaker 1: livable again. It's a lot of work to be done.
12:21
Speaker 1: And anyone who's ever lived through a hurricane knows that
12:24
Speaker 1: one of the biggest challenges afterward is just simply finding
12:26
Speaker 1: enough people to help. Because everybody's working on their own house.
12:31
Speaker 1: And sometimes you need to find people that have traveled
12:34
Speaker 1: hundreds of miles and they will because they're looking for work.
12:37
Speaker 1: And I'll tell you this, anybody that's willing to travel
12:39
Speaker 1: hundreds of miles to work, I want them working with
12:41
Speaker 1: me because that's how badly they want to work. And
12:48
Speaker 1: in the middle of all this, the federal government decided
12:50
Speaker 1: they had time to spend two hours, not to lift
12:53
Speaker 1: a freaking finger and help the community, but to harass
12:58
Speaker 1: these roofers of Hispanic origins. What public policy priority does
13:06
Speaker 1: this serve? Do you live in the real world, Mr.
13:10
Speaker 2: Miller?
13:11
Speaker 1: Mr. Trump? This is your policy that you've concocted. And
13:16
Speaker 1: it is absolutely filled with just, you're just harassing decent
13:22
Speaker 1: Americans all over. Look, immigration enforcement is a legitimate function
13:30
Speaker 1: of the federal government. And I believe you campaigned on
13:34
Speaker 1: focusing on those that were here to do harm to
13:37
Speaker 1: our country, not to help, not people that came here
13:41
Speaker 1: to help us. I understand that a lot of us
13:47
Speaker 1: have very different opinions about how aggressively some of these
13:51
Speaker 1: laws should be enforced, but surely there's a difference between
13:55
Speaker 1: enforcing immigration laws and creating an environment in which people
13:59
Speaker 1: trying to help a community recover from a hurricane are
14:02
Speaker 1: afraid to come down from a roof. And ready for this?
14:09
Speaker 1: Pensacola News Journal also had this little item. They were
14:13
Speaker 1: talking to some immigration advocates in the community, and they
14:16
Speaker 1: said that before the hurricane, some families were afraid to
14:19
Speaker 1: go to emergency shelters because they worried about encountering immigration authorities.
14:24
Speaker 1: Think about that for a moment. This is America. I
14:28
Speaker 1: know we're so past anybody giving a shit about what
14:32
Speaker 1: the Statue of Liberty says. Give me your tired, give
14:34
Speaker 1: me your poor and all that. You know, we pride
14:38
Speaker 1: ourselves on being a nation of immigrants and we want
14:42
Speaker 1: people coming to this country in fear. Trust me, they've
14:46
Speaker 1: left fear. That's why they're here. And we're going to
14:50
Speaker 1: terrorize them. I thought we were better than this. So people,
14:57
Speaker 1: You had people in Pensacola who had to weigh the
15:00
Speaker 1: danger of staying, say, in a trailer that was probably
15:03
Speaker 1: not safe during a hurricane against the possibility of being
15:06
Speaker 1: detained if they decided to seek shelter. In the United
15:10
Speaker 1: States of America, if you were visiting another country, wouldn't
15:15
Speaker 1: you like to know that you could go to a
15:17
Speaker 1: shelter without getting deported in a time of an emergency?
15:23
Speaker 1: Is that what we're going to do to fellow human beings?
15:28
Speaker 1: Whatever your views are on immigration, surely we could all
15:30
Speaker 1: agree that people should not be afraid to seek shelter
15:33
Speaker 1: from a natural disaster. I mean, this administration, you know,
15:44
Speaker 1: they just don't know how to govern. They have no
15:47
Speaker 1: sense of proportion. They have no sense of priorities. Americans
15:52
Speaker 1: didn't want the chaos at the border, but they didn't
15:54
Speaker 1: want this. There's a difference. And everybody knows there's a difference.
16:02
Speaker 1: Donald Trump used to claim no one else had common
16:04
Speaker 1: sense and he had common sense. This is uncommon sense.
16:06
Speaker 1: And buddy, you're Mar-a-Lago. We already know that half the
16:12
Speaker 1: people you've hired over the years would probably be afraid
16:17
Speaker 1: of an ICE raid themselves. Sometimes the job of government
16:22
Speaker 1: is simply to help people get through a hurricane and
16:24
Speaker 1: put their lives back together. And if we're gonna talk
16:29
Speaker 1: about the labor shortage we have in this country, particularly
16:32
Speaker 1: in construction and other physically demanding jobs, maybe we ought
16:36
Speaker 1: to spend a little more time figuring out how we
16:37
Speaker 1: can make it easier for people to do the necessary
16:40
Speaker 1: work legally, rather than creating situations like this one. I
16:45
Speaker 1: don't know what prompted these officers to approach the workers,
16:48
Speaker 1: but literally the island is recovering from a hurricane. The
16:51
Speaker 1: power got turned on yesterday. But I'd like to get
16:56
Speaker 1: an explanation from these people chose to harass roofers. I
17:04
Speaker 1: tell you, I think it's really crummy politics for the Republicans.
17:08
Speaker 1: And if you're wondering why there's a dummy mander now
17:11
Speaker 1: in Texas and Florida where all of these congressional districts,
17:15
Speaker 1: they thought were going to go Republican because they suddenly
17:18
Speaker 1: had a bunch of Hispanic supporters. Well, keep harassing anybody
17:25
Speaker 1: of Latino descent and see how far that's going to
17:27
Speaker 1: get you politically. You know, the timing. I mean, I
17:34
Speaker 1: will say this. Democrats can't win in this environment. I
17:37
Speaker 1: don't know what environment they're going to have because this
17:38
Speaker 1: administration is going out of its way to push voters
17:45
Speaker 1: away from them. All right, let me move to Kansas
17:49
Speaker 1: here for a second. Roger Marshall, the Republican senator who's
17:53
Speaker 1: suddenly in the fight for his political life, has done
17:56
Speaker 1: something that for me is a tell that he knows
17:59
Speaker 1: this race is, He's on the verge of losing. With
18:06
Speaker 1: less than three weeks to go before election day, he's
18:10
Speaker 1: up with a positive ad. But it's not necessarily a
18:14
Speaker 1: positive ad. What it is, it's a fixes image ad.
18:19
Speaker 1: And it's an ad that tries to remind voters that
18:21
Speaker 1: he used to be a compassionate doctor. So the new
18:24
Speaker 1: television ad is called Deb, and it features a woman
18:26
Speaker 1: talking about how Marshall, when he was practicing medicine, helped
18:29
Speaker 1: her through an emergency procedure that and offered to cover
18:32
Speaker 1: some of the costs. I'm sure it's a true story,
18:37
Speaker 1: but the timing of the ad actually says a lot, right?
18:41
Speaker 1: We know that, you know, the billing, Marshall and his
18:45
Speaker 1: billings when he was a doctor and he was sending
18:47
Speaker 1: it to credit, you know, immediately, you know, sending people
18:50
Speaker 1: to small claims court, things like that. And it's been
18:53
Speaker 1: used and it's really hit him hard, right? It's hit
18:55
Speaker 1: his character hard and Marshall's favorable ratings are upside down.
19:01
Speaker 1: So what it tells you is they've decided their negatives
19:04
Speaker 1: are so bad, they can't just negative add Hamilton to
19:08
Speaker 1: death and hope they can like, we're going to make
19:11
Speaker 1: everybody so unpopular that now you'll vote for the incumbent.
19:17
Speaker 1: It's so bad they decided they had to try to
19:19
Speaker 1: go positive with less than three weeks to go. Ironically,
19:24
Speaker 1: one of the last places you want to be as
19:25
Speaker 1: an incumbent in October is running advertising designed to convince
19:30
Speaker 1: voters you're actually a decent human being. If that's what
19:33
Speaker 1: you feel like you have to do, you're spending all
19:35
Speaker 1: this money. Money's precious at this point in time. Airtime
19:38
Speaker 1: is expensive. And you've decided you've got to do this. Oh,
19:42
Speaker 1: my God. The numbers are even worse than we thought.
19:48
Speaker 1: This episode of the Chuck Todd. cast is brought to
19:51
Speaker 1: you by Kalshi. It's an exchange where you can trade
19:55
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20:12
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20:16
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20:18
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20:23
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20:26
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20:31
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20:34
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20:37
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20:45
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20:48
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Speaker 1: or 51 plus Senate seats. The blue tsunami scenario, a
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21:01
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21:15
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Speaker 1: at the same time, you hedge that trade with a
21:47
Speaker 1: no on the blue wave. But I could tell you
21:51
Speaker 1: right now, blue tsunami seems like a discount. And so
21:55
Speaker 1: does no on the blue wave. So here's what you
21:57
Speaker 1: need to know on CalSheet. You're going up against other
21:59
Speaker 1: traders directly. There's no house that's setting the odds. right?
22:04
Speaker 1: It's just people putting their opinions on the line and
22:07
Speaker 1: that's what determines this market. Trade $ 25 with the code
22:11
Speaker 1: Chuck Todd and they'll throw in another $ 25 instantly. Please
22:15
Speaker 1: remember to trade responsibly. This is a reminder, right? He
22:22
Speaker 1: didn't think he was going to be in a race.
22:24
Speaker 1: He never established this image of himself, right? A smart campaign,
22:30
Speaker 1: a good campaign, realizes that this could become a problem.
22:37
Speaker 1: This is not out of left field or right field
22:40
Speaker 1: that Kansas is competitive. It's been creeping into the competitive
22:44
Speaker 1: category every two years. This is just proof, you know, look,
22:49
Speaker 1: good gets better, bad gets worse. And just Marshall is
22:51
Speaker 1: just not very good at this, right? He may have
22:54
Speaker 1: been a decent doctor. He may know, he may understand
22:57
Speaker 1: what the job of a senator is, but this man
23:00
Speaker 1: is a terrible politician. And guess what? If you don't
23:03
Speaker 1: like people, don't get into politics. Get out of politics.
23:08
Speaker 1: But the fact that you're trying to say, no, no, no, no,
23:10
Speaker 1: I'm really a decent person, please. And it's October. Maybe
23:15
Speaker 1: time to stick a fork in that campaign. I'm not
23:17
Speaker 1: saying it's done, but now you know why. I think
23:20
Speaker 1: Kansas flips before Iowa flips. Both could end up flipping.
23:24
Speaker 1: But you can see here, Roger Marshall is in deep,
23:27
Speaker 1: deep trouble and his own campaign knows it. Speaking of
23:32
Speaker 1: more problems from this administration, we got a new inflation
23:36
Speaker 1: report on Wednesday. And here's something that shouldn't shock us.
23:42
Speaker 1: Prices have once again accelerated. And now they've accelerated to
23:46
Speaker 1: the point that now the Fed is probably going to
23:48
Speaker 1: have to raise interest rates again before Election Day. And
23:51
Speaker 1: imagine having to do it before elections. Now, none of
23:54
Speaker 1: this was particularly surprising. We spent months talking about the
23:57
Speaker 1: economic consequences of tariffs, the Iran war, higher energy costs,
24:01
Speaker 1: and the enormous uncertainty that all this has introduced in
24:04
Speaker 1: the economy. But you couldn't pick a worse time for
24:10
Speaker 1: this bad inflation report to come out. It's accelerating. And
24:14
Speaker 1: if you have to raise interest rates again, guess what
24:16
Speaker 1: you've just done? You've just put the house, you just
24:19
Speaker 1: put a starter home even further out of reach for
24:23
Speaker 1: somebody in their late 20s, early 30s. You've just made
24:26
Speaker 1: this economic ladder harder to climb. And these are all
24:32
Speaker 1: Trump policies. None of these, all of these were policies
24:36
Speaker 1: not put in by Joe Biden. All of these accelerants
24:41
Speaker 1: to this current situation that we're in are all choices
24:46
Speaker 1: Donald Trump himself made the tariffs the trade wars the
24:52
Speaker 1: war in iran the energy this is all on him
24:55
Speaker 1: and the voters know it and now it's this environment
25:03
Speaker 1: gets bleaker and i i think this is why you
25:06
Speaker 1: see that this is there is i don't we're already
25:09
Speaker 1: you see now i don't know what fuel deal he
25:12
Speaker 1: could cut at this point You know, the only shot
25:17
Speaker 1: they have at sort of changing the narrative of the
25:20
Speaker 1: belief in this economy is if somehow the Iran war
25:22
Speaker 1: ends in the next 72 hours. And when I say end,
25:25
Speaker 1: like end, signed, like statement, you know, some massive success
25:31
Speaker 1: that none of us can envision is possible. The cake
25:36
Speaker 1: is baked. This economy is the economy for this election.
25:45
Speaker 1: This is not a good economy. This is how you
25:48
Speaker 1: lose majorities. A couple other nuggets to share. I think
25:58
Speaker 1: some big news happened at a Georgia Senate debate on
26:02
Speaker 1: Tuesday night. John Ossoff said that he has no interest
26:07
Speaker 1: in running for president and pledged to serve a full
26:11
Speaker 1: six years and not run for president as senator. Wes
26:14
Speaker 1: Moore was asked a similar question, didn't pledge to serve
26:17
Speaker 1: for full years. But what was interesting is that local
26:22
Speaker 1: coverage of both debates, and with Moore, it wasn't a debate,
26:25
Speaker 1: it was a Q & A that he did. But
26:27
Speaker 1: the coverage of both of them indicated, hey, they both,
26:30
Speaker 1: you know, it was as if they both were, you know,
26:34
Speaker 1: talking down about their presidential ambitions. Now, look, I will
26:39
Speaker 1: say this, Ossoff's declaration did come across as more definitive.
26:45
Speaker 1: He was asked a direct question about serving the full term,
26:48
Speaker 1: and he said, absolutely, I have no interest in running
26:50
Speaker 1: for president. Moore left himself wiggle room. But this is
26:55
Speaker 1: the part of the story where the narrator will tell you, yeah,
26:58
Speaker 1: Bill Clinton pledged in a debate in 1990 that he
27:01
Speaker 1: was going to serve a full four-year term, and he
27:03
Speaker 1: ended up announcing his candidacy for president nine months into 1991.
27:11
Speaker 1: So if there's a reason reporters like me are very
27:15
Speaker 1: cynical about these pronouncements, all I'll say is Ossoff's was
27:19
Speaker 1: a little more definitive. Um, and it is why I've
27:22
Speaker 1: been a little more, why I haven't really talked up,
27:26
Speaker 1: you know, I know he's been sort of, uh, a,
27:30
Speaker 1: an exciting idea for some people in the anti-Trump, uh,
27:34
Speaker 1: in the Trump resistance movement, because he's pretty good with
27:36
Speaker 1: the zinger. Um, But I had not seen any other
27:40
Speaker 1: evidence that he was truly looking at this. And, you know,
27:44
Speaker 1: you don't just run for president on a whim. You know,
27:46
Speaker 1: you do start to have to put things together. It
27:49
Speaker 1: doesn't mean he doesn't have the building blocks to pull
27:51
Speaker 1: it off and he may change his mind. But he
27:53
Speaker 1: did put himself in a rhetorical box where he's going
27:55
Speaker 1: to have to explain why he said one thing to
27:57
Speaker 1: voters in October of 2026 if he suddenly decides to
28:01
Speaker 1: change his mind. But Ossoff off the board, you know,
28:04
Speaker 1: if you're Pete Buttigieg, You're secretly pretty happy about that.
28:11
Speaker 1: You know, I think Asaf and Pete in some ways
28:15
Speaker 1: are in the same lane, so to speak. One more
28:23
Speaker 1: fun little item that I've been having this in a
28:27
Speaker 1: while because it made me smile. Jamie Raskin, Democrat from Maryland,
28:34
Speaker 1: has introduced legislation that would direct the Smithsonian to collect
28:40
Speaker 1: and preserve some of the Trump administration's portraits and signs
28:45
Speaker 1: and posters and other displays in federal buildings that if
28:50
Speaker 1: you're around Washington, you see them all over. And it's
28:52
Speaker 1: kind of like, are we in North Korea? It's like
28:55
Speaker 1: something you'd expect out of Pyongyang, not out of the
28:57
Speaker 1: United States of America. But I found it interesting what
29:02
Speaker 1: Raskin is up to here, right? Because he wants to,
29:04
Speaker 1: you know, the Smithsonian needs to preserve all of these things,
29:09
Speaker 1: including some of the material accusing the Smithsonian of ideological bias. Now,
29:15
Speaker 1: the bill is not going to become law in this Congress,
29:18
Speaker 1: but it might in the next Congress. And I think
29:20
Speaker 1: it's a pretty clever idea because there's something wonderfully ironic
29:24
Speaker 1: about taking an administration's effort to control how history is
29:28
Speaker 1: presented and proposing to preserve those very efforts as historical artifacts.
29:36
Speaker 1: Imagine the exhibit 50 years from now. Here's how the
29:39
Speaker 1: trumpet tried to reshape the very institution you're visiting right
29:44
Speaker 1: now here in Washington, D.C., the Smithsonian. Here's what that
29:48
Speaker 1: administration wanted Americans to see. Here's what it wanted it removed.
29:52
Speaker 1: And here's how it described its political opponents. You know,
29:57
Speaker 1: and this is the beauty. One of the things that
29:58
Speaker 1: authoritarian-minded leaders frequently forget is that they don't get the
30:02
Speaker 1: final word. And now history remembers that. Oh, do they
30:05
Speaker 1: wish they did, right? They think they can control buildings
30:09
Speaker 1: and they can change a sign here or there. Maybe
30:11
Speaker 1: they can put up a portrait. But they never get
30:13
Speaker 1: to control what future generations think those actions meant. That's
30:18
Speaker 1: what I love about the Raskin proposal here, right? It's
30:20
Speaker 1: an attempt to turn the administration's own messaging into evidence
30:24
Speaker 1: for future historians. And frankly, I suspect historians are going
30:29
Speaker 1: to have an extraordinary amount of material to work with
30:32
Speaker 1: when they try to explain this era. As I've said
30:36
Speaker 1: to a bunch of people asking me these questions about
30:38
Speaker 1: this era, I've said, you know, I think 50 years
30:40
Speaker 1: from now, I think, you know, he's going to, Donald
30:43
Speaker 1: Trump might be as relevant to the history books as
30:48
Speaker 1: Grover Cleveland is. An anomaly. Two or three sentences. And
30:56
Speaker 1: you move on. That, if there's anything that would bother
31:02
Speaker 1: Trump the most, it's that he would be less relevant.
31:09
Speaker 1: And that's what I love about this Raskin proposal. One
31:15
Speaker 1: more thought before I get to this analysis of the
31:18
Speaker 1: third-party candidates that I've been promising you for the last
31:20
Speaker 1: couple of podcasts. My friend John Ellis, who writes the
31:23
Speaker 1: newsletter News Items, which also has, I think he's got
31:27
Speaker 1: various subsidiaries, political items. He had a terrific observation about
31:32
Speaker 1: political advertising. And it's not a new observation, but it's
31:35
Speaker 1: one that deserves repeating every now and then. And he
31:38
Speaker 1: talked about, you know, he lives in the New York
31:39
Speaker 1: City media market. And frankly, I see it here in D.C.
31:42
Speaker 1: and you see it, you know, wherever I travel, I
31:45
Speaker 1: see it. And he's like, he talks about being bombarded
31:49
Speaker 1: with ads for congressional and statewide races. And he notes
31:53
Speaker 1: that a substantial majority of them are negative. Now, as
31:57
Speaker 1: he notes, that's not a new development, negative advertising. frankly,
32:00
Speaker 1: has been the central feature of American campaigns for decades.
32:04
Speaker 1: But Ellis makes a point that I think is worth repeating,
32:08
Speaker 1: and frankly, worth repeating over and over again. So every
32:11
Speaker 1: two years, political campaigns spend billions of dollars telling Americans
32:15
Speaker 1: that the people running for office are dishonest, corrupt, incompetent, dangerous,
32:21
Speaker 1: or some combination of all four. And then we wonder
32:25
Speaker 1: why Americans don't trust politicians. What other industry spends this
32:32
Speaker 1: much money trying to convince its customers that the entire
32:35
Speaker 1: industry is rotten? It reminds me of a joke, an
32:43
Speaker 1: old journalism friend of mine, Matt Cooper, who I think's
32:45
Speaker 1: at Washington Monthly these days. I know he's at my,
32:48
Speaker 1: used to be at Newsweek, he's been a great journalist,
32:51
Speaker 1: very funny guy. Did amateur standup, but like really worked
32:55
Speaker 1: at it. And he had this whole longer riff about,
33:00
Speaker 1: you know, imagine if Miller and Budweiser used campaign tactics,
33:06
Speaker 1: you know, the tactics of the two parties in their advertising, right?
33:12
Speaker 1: And is basically the punchline is if Miller and Budweiser
33:15
Speaker 1: used the advertising tactics of political consultants, eventually nobody would
33:19
Speaker 1: drink beer, right? Miller Lite says it's less filling, but
33:25
Speaker 1: what they don't tell you is if you, you know, And,
33:29
Speaker 1: you know, might read the ingredients with a sinister voice.
33:33
Speaker 1: And that's the thing, right? If beer companies did this,
33:36
Speaker 1: nobody would drink beer. You'd think beer itself is the problem.
33:41
Speaker 1: And you got to ask yourself, are we doing the
33:43
Speaker 1: same thing to American politics? We've created a system in
33:47
Speaker 1: which winning an election increasingly involves persuading voters that the
33:51
Speaker 1: alternative is so awful they have no choice but to
33:53
Speaker 1: support you. I'm describing the entire 21st, every national election
33:58
Speaker 1: we've had this century. It's been the against election, the
34:02
Speaker 1: hold your nose. And then we are shocked when the
34:08
Speaker 1: people they do elect suddenly lose faith of the voters immediately.
34:16
Speaker 1: I don't know how we fix this, but it is
34:18
Speaker 1: an important reminder and an observation. One of the reasons
34:21
Speaker 1: I think so many Americans are looking for political alternatives
34:24
Speaker 1: is even if those alternatives don't have a realistic chance
34:28
Speaker 1: of winning is because of this. There's just an exhaustion
34:32
Speaker 1: from it all. And it brings me to this story
34:35
Speaker 1: about independent candidates. And there's an individual who's trying to
34:42
Speaker 1: exploit this dissatisfaction in a fascinating way. And it's not
34:47
Speaker 1: to win an election, but simply change which party wins.
34:50
Speaker 1: So let me tell you a little something, uh, about
34:56
Speaker 1: this person. There's a story in Semaphore about a gentleman
35:01
Speaker 1: named Aaron Day. Aaron Day ran as an independent in
35:05
Speaker 1: the 2016 New Hampshire Senate race when the Republican incumbent,
35:09
Speaker 1: Kelly Ayotte, lost to then the sitting governor, Maggie Hassan.
35:14
Speaker 1: And she lost by just over a thousand votes. It
35:16
Speaker 1: was a super close election. Day, Aaron Day, received more
35:21
Speaker 1: votes than the margin between Ayotte and Hassan. Now, it
35:26
Speaker 1: doesn't mean we could say definitively that Day cost Ayotte
35:29
Speaker 1: the election. We don't know how his voters would have
35:33
Speaker 1: behaved if he hadn't been on the ballot. But Day
35:37
Speaker 1: is so enamored with the role he may have played
35:40
Speaker 1: in 2016 that he actually is trying to replicate that
35:42
Speaker 1: experience across the country. Day has established something called the
35:47
Speaker 1: Stark Freedom Pack, and he's talking about spending as much
35:51
Speaker 1: as $ 2. 5 million to promote minor party candidates in competitive
35:54
Speaker 1: Senate races. And his objective is quite explicit. And he
35:58
Speaker 1: says it. He wants Republicans to lose control of the Senate.
36:01
Speaker 1: And he believes he's identified eight states where he thinks
36:04
Speaker 1: a relatively small investment in third-party candidates could change the result.
36:08
Speaker 1: And he's looking at Texas, Iowa, New Hampshire, Minnesota, South Carolina, Michigan, Ohio,
36:13
Speaker 1: and Kansas. And here's how he's proposing to do this.
36:18
Speaker 1: He wants to use artificial intelligence to produce inexpensive online
36:22
Speaker 1: advertising for these third-party candidates. with the theory that he
36:25
Speaker 1: doesn't need to persuade a huge number of voters. He
36:28
Speaker 1: just needs to make enough voters aware of an alternative
36:31
Speaker 1: candidate to move a few points. Moneyball, right? It's a
36:36
Speaker 1: moneyball approach to this. Find a relatively cheap way to
36:39
Speaker 1: influence the margin in a very expensive election. I have
36:43
Speaker 1: no idea if this is going to work. And I'm,
36:46
Speaker 1: you know, I think sometimes these efforts can be, you know,
36:53
Speaker 1: a little overrated, but there are plenty, you know, John Tester,
36:58
Speaker 1: two of his Senate races, he didn't get 50%. The
37:01
Speaker 1: libertarian made the, got just enough vote that made the
37:05
Speaker 1: winning number 49. And if you can lower the winning
37:11
Speaker 1: number in Iowa, Kansas, Texas, you know, Alaska's got the
37:19
Speaker 1: right choice. See, that's what right choice voting does. eliminates
37:22
Speaker 1: this possibility. But you can, if you lower the winning number,
37:27
Speaker 1: what's interesting is we've seen, actually, I told you a
37:29
Speaker 1: story a couple podcasts ago about what appears to be
37:33
Speaker 1: a Republican group trying to promote a socialist third-party candidate
37:36
Speaker 1: in the Ohio Senate race, right? So Ohio is competing
37:40
Speaker 1: spoiler strategies because there's also a libertarian on the ballot
37:43
Speaker 1: as well. So maybe they end up canceling each other out,
37:48
Speaker 1: but there's a libertarian sitting on the ballot in Kansas, right?
37:54
Speaker 1: It's in these redder states where the libertarian or in
37:58
Speaker 1: some states it's a constitutional party candidate where they're in
38:01
Speaker 1: some ways more, whatever they are, more conservative than the
38:04
Speaker 1: conventional Republican nominee. And it's been, like I said, Democrats
38:08
Speaker 1: use this strategy to big success in Montana over the years. Texas,
38:15
Speaker 1: I absolutely expect, I think Tallarico can't get more than 51,
38:19
Speaker 1: maybe 52. On his best day. But I don't expect
38:24
Speaker 1: Paxton to be at 48 or 49. I expect him
38:27
Speaker 1: to be at 44, 45, 46, because I expect a
38:30
Speaker 1: whole bunch of Republicans who can't bring themselves to vote
38:33
Speaker 1: for Tallarico who just can't stomach voting for Paxton. So
38:39
Speaker 1: I think he gets somewhere in that three or four
38:41
Speaker 1: percent range. Iowa has a libertarian candidate on the ballot.
38:49
Speaker 1: And in fact, he's not an ordinary candidate. Thomas Lane
38:52
Speaker 1: is an elected county attorney. He's got an interesting political background.
38:56
Speaker 1: He's pro-life, which could appeal to some conservative voters. But
39:00
Speaker 1: he's promised that if he wins, he would caucus with
39:02
Speaker 1: the Democrats. Again, if he just gets two or three
39:07
Speaker 1: points and he gets it from, you know, anti, you know,
39:12
Speaker 1: from the right side of the aisle. Josh Turek. As
39:18
Speaker 1: many of you know, look, this could be a close race.
39:21
Speaker 1: Turk would have a lot easier time to win if
39:23
Speaker 1: 48 or 49 were the winning number. South Carolina has
39:28
Speaker 1: two right-leaning teams. third-party candidates again we already know she's
39:35
Speaker 1: got problems consolidating the generic republican vote trump's got to
39:38
Speaker 1: go back down there and try to bail her out
39:41
Speaker 1: in the most republican part of the state in greenville
39:45
Speaker 1: um You get a constitutional party candidate, libertarian. They get
39:49
Speaker 1: three or four points. Annie Andrews can find a path
39:52
Speaker 1: to victory. And then you throw in that this guy
39:55
Speaker 1: wants to throw a little bit money on that. Now,
39:58
Speaker 1: it doesn't only work one way. There's a Green Party
40:00
Speaker 1: candidate in Michigan that could siphon votes away from Abdul El-Sayed.
40:04
Speaker 1: And some Republicans are helping there. In Mississippi, there's a
40:11
Speaker 1: third party candidate that wouldn't necessarily help the Democrats, a
40:14
Speaker 1: guy named Ty Pinkson. He was the Democratic Senate nominee
40:20
Speaker 1: in 2024, and he's running as an independent. You know,
40:25
Speaker 1: he absolutely could end up hurting the Democrats in that one.
40:30
Speaker 1: But you see the general trend here, and especially in
40:34
Speaker 1: states that lean largely, you know, if you're the challenger
40:38
Speaker 1: party and you're not the majority party in that state.
40:43
Speaker 1: So this is why this is likely to benefit more
40:46
Speaker 1: Democratic campaigns than it will this cycle Republican campaigns, because
40:50
Speaker 1: this is an election that's essentially being fought in Republican territory.
40:56
Speaker 1: And this doesn't even count the candidates where the independent
41:00
Speaker 1: is the main candidate, main challenger candidate to the incumbent.
41:04
Speaker 1: Osborne in Nebraska, Brian Banks in South Dakota, Todd Achilles
41:08
Speaker 1: in Idaho, and of course, Seth Bodnar in Montana. And again,
41:15
Speaker 1: I look at it as, I think they're already, we
41:20
Speaker 1: already know this. There's a whole bunch of voters who
41:22
Speaker 1: just feel more and more uncomfortable with the two major parties.
41:29
Speaker 1: And it's especially in the Republican coalition where they're not
41:36
Speaker 1: happy with Trump, but they can't bring themselves to vote
41:38
Speaker 1: for a Democrat. I think it's definitely, this to me
41:42
Speaker 1: is going to be one of the, Let me put
41:44
Speaker 1: it another way. If Democrats net six or seven Senate seats,
41:49
Speaker 1: I'm going to guess that they'll have at least three
41:52
Speaker 1: of their winners not get 50%. And that brings me
41:56
Speaker 1: to the subject that I want to spend the rest
41:58
Speaker 1: of today's podcast on. Because while we're spending an enormous
42:02
Speaker 1: amount of time trying to figure out which of these
42:03
Speaker 1: candidates are going to be able to pull this off
42:06
Speaker 1: and what the majorities are going to be and what
42:08
Speaker 1: your coalition look like, you know, and do you siphon
42:10
Speaker 1: votes away here or there? Um, We do have a
42:14
Speaker 1: bigger a bigger question we got to answer after these elections.
42:21
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Speaker 1: You get free shipping on your order, 365-day returns. Now
44:37
Speaker 1: available in Canada and the UK too. And when Quince
44:40
Speaker 1: asks where you heard about them, please let them know
44:43
Speaker 1: it was the Chuck Todd cast. It's the best way
44:47
Speaker 1: to support the show and the best way to make
44:49
Speaker 1: sure you're getting every discount. We got to find someone
44:55
Speaker 1: who can assemble a coalition that actually believes in their leadership, right?
44:59
Speaker 1: Right now, this is a coalition of no's, a coalition
45:01
Speaker 1: of against's that we have. It's a coalition united in opposition. Shoot,
45:07
Speaker 1: I think most of Trump's voters are not pro-Trump. They're anti-Democrat.
45:13
Speaker 1: And I think it's vice versa. I'm curious of when
45:17
Speaker 1: we're going to find a leader who can put a
45:20
Speaker 1: coalition together that's bigger than that. A coalition that believes
45:24
Speaker 1: a particular person is capable of leading the country through
45:28
Speaker 1: an extraordinarily difficult period. And it's interesting. It got me
45:33
Speaker 1: thinking about something Bill Kristol wrote. in one of his
45:36
Speaker 1: Bulwark newsletters earlier this week. And it made me think
45:43
Speaker 1: a little bit about what we need to look for
45:44
Speaker 1: in 2028. So Crystal made this point. He identified four
45:48
Speaker 1: rather unlikely figures who in their own ways have emerged
45:52
Speaker 1: as defenders of the Western liberal order, small l. At
45:56
Speaker 1: precisely the moment, the United States has been retreating from
46:00
Speaker 1: its traditional role as basically defender of the liberal world order.
46:06
Speaker 1: And the four people he singled out are Zelensky, Peter Magyar,
46:12
Speaker 1: the guy who beat Viktor Orban in Hungary, Mark Carney
46:15
Speaker 1: of Canada, and the Pope. Now, these are four very
46:21
Speaker 1: different men from four very different backgrounds confronting four very
46:26
Speaker 1: different challenges, but they all have one thing in common.
46:28
Speaker 1: They're defending principles that, until fairly recently, We Americans assumed
46:34
Speaker 1: our own political leadership would always defend pluralism, the rule
46:39
Speaker 1: of law, the consent of the governed, the belief that
46:42
Speaker 1: freedom is worth defending, that institutions matter, and that the
46:46
Speaker 1: strong shouldn't simply be allowed to impose their will on
46:50
Speaker 1: the weak. Small L liberalism, if you will. Not the
46:56
Speaker 1: ideological liberalism of the American left, but the larger liberal
47:00
Speaker 1: tradition that made the modern Western civilization dominance possible. Now,
47:09
Speaker 1: Crystal was writing, essentially asking, where's America's version of these leaders?
47:15
Speaker 1: I'm changing the question from what he asked. Why are
47:17
Speaker 1: we so convinced that America is incapable of producing one
47:21
Speaker 1: of these leaders? Because when I started to think about
47:25
Speaker 1: these four men and what struck me wasn't simply what
47:28
Speaker 1: they've accomplished so far, It was where they came from.
47:33
Speaker 1: Think about the institutions they all now lead. Think about
47:36
Speaker 1: what those institutions looked like before these four men arrived.
47:41
Speaker 1: And ask yourself how unlikely it would have seemed just
47:44
Speaker 1: a few years ago that any of these institutions or
47:46
Speaker 1: places would produce the kind of leadership that the Western
47:50
Speaker 1: world desperately needs. Ukraine. Start with Zelensky. The entire world
47:58
Speaker 1: thought Russia was just going to roll over Ukraine in
48:02
Speaker 1: a couple of days. Its government was still widely viewed
48:08
Speaker 1: as corrupt. Its military was thought to be overmatched. Its
48:12
Speaker 1: political institutions were considered too weak to withstand this assault
48:17
Speaker 1: from one of the world's great powers. And its president
48:20
Speaker 1: was a former television comedian, a guy whose qualifications for
48:24
Speaker 1: the job were frequently questioned, including by people inside his
48:27
Speaker 1: home countries. And yet when the moment came, Zelensky helped
48:30
Speaker 1: rally his country and much of the democratic world to
48:34
Speaker 1: resist Putin. And what has happened to Ukraine? It has
48:37
Speaker 1: become one of the most innovative military powers of the
48:40
Speaker 1: 21st century, largely because necessity demanded it. Now, I'm not
48:46
Speaker 1: saying Zelensky's perfect. Ukraine still has enormous challenges. The war
48:49
Speaker 1: is ongoing. The country's political future is very uncertain. He's
48:52
Speaker 1: going to have to hold elections at some point. But
48:56
Speaker 1: the point is that the leadership he demonstrated wasn't necessarily
48:59
Speaker 1: visible to the political establishment before this crisis arrived. The
49:05
Speaker 1: circumstances revealed something in him that a lot of people
49:09
Speaker 1: didn't know existed. And it's worth remembering when we're thinking
49:13
Speaker 1: about who our next great American president is going to
49:16
Speaker 1: end up being. How about Peter Maguire? in Hungary? For years,
49:21
Speaker 1: Orban was held up as proof that an illiberal democracy
49:25
Speaker 1: wasn't merely a theory, that it could be a governing
49:28
Speaker 1: model that could survive, consolidate power, and sort of become
49:33
Speaker 1: something that you could actually export. In fact, elements of
49:37
Speaker 1: the American right openly admired Orban's illiberal model and wanted
49:42
Speaker 1: to replicate parts of it here. There's a whole following
49:47
Speaker 1: on the right that doesn't believe in pluralistic democracy. And
49:54
Speaker 1: Hungary's opposition seemed hopelessly fragmented. And the political playing field
49:59
Speaker 1: had been tilted so dramatically in Orban's favor that defeating
50:02
Speaker 1: him appeared almost impossible. Till Magyar didn't. And what's always
50:09
Speaker 1: interested me about Magyar isn't simply that he did it,
50:12
Speaker 1: but how he did it. He had to persuade people
50:14
Speaker 1: who had become accustomed to Orban's political dominance that an
50:18
Speaker 1: alternative was possible. He had to reach voters who weren't
50:22
Speaker 1: necessarily ideological allies of the traditional opposition. He had to
50:26
Speaker 1: convince people who'd lost faith in the possibility of democracy
50:30
Speaker 1: working that participating in politics could actually produce a different result.
50:36
Speaker 1: That's an amazing political skill. It's what we're going to
50:40
Speaker 1: need in America in 2028. Our next president is going
50:44
Speaker 1: to have to persuade people who do not necessarily agree
50:47
Speaker 1: with one another that they can still trust the same
50:49
Speaker 1: person to lead them. How about Mark Carney in Canada?
50:53
Speaker 1: Before Carney's arrival, the country's political leadership, particularly on the left,
50:57
Speaker 1: looked exhausted. Its economy was vulnerable. Its relationship with the
51:01
Speaker 1: United States was increasingly precarious. Donald Trump seemed to regard
51:06
Speaker 1: Canada as little more than a punching bag for truth social.
51:09
Speaker 1: And along comes a former central banker, not the obvious
51:14
Speaker 1: profile of a political revolutionary. And yet Carney didn't just
51:18
Speaker 1: help to rally Canadians around their national sovereignty. He did
51:23
Speaker 1: so while trying to preserve the broader Western alliance that
51:27
Speaker 1: Trump seems so determined to get rid of. And the
51:31
Speaker 1: best part of Carney for me is his temperament. He's
51:33
Speaker 1: not somebody whose entire political identity depends on creating some
51:37
Speaker 1: daily controversy. He never makes himself the center of every conversation.
51:44
Speaker 1: He actually sees competence and stability as strengths, not weaknesses.
51:50
Speaker 1: And I suspect an awful lot of voters here in
51:52
Speaker 1: America would find basic stability and competence to be quite appealing.
51:58
Speaker 1: But competence alone isn't enough. You have to connect with voters.
52:01
Speaker 1: You have to understand their concerns. You have to build
52:02
Speaker 1: a coalition. But Carney is a reminder that voters sometimes
52:06
Speaker 1: respond to leadership that doesn't fit. the conventional political bowl.
52:10
Speaker 1: Then there's Pope Leo. Think about the Catholic Church and
52:16
Speaker 1: what it's been going through over the last couple of decades.
52:19
Speaker 1: This is an institution that has been confronting a crisis
52:22
Speaker 1: of credibility, much of itself inflicted. The Vatican was hardly
52:27
Speaker 1: the first institution most people would have identified as a
52:30
Speaker 1: potential source of renewed moral leadership for the West. And
52:34
Speaker 1: yet here is Pope Leo reminding the world of principles
52:38
Speaker 1: that have deep roots in both Catholic social teaching and
52:41
Speaker 1: American liberal tradition. Human dignity, compassion, the responsibilities of the powerful,
52:48
Speaker 1: the moral obligations we have to one another. And there's
52:52
Speaker 1: a wonderful irony here that I want to return to
52:54
Speaker 1: before we're done. One of Crystal's four unlikely defenders of
52:59
Speaker 1: the Western liberal order is already an American. Robert Prevost
53:04
Speaker 1: was born in Chicago, raised in the suburbs, educated at Villanova.
53:08
Speaker 1: The Catholic Church found its next moral leader in an American,
53:13
Speaker 1: even as America's own political institutions seem incapable of producing
53:18
Speaker 1: one themselves. Think about that. We produced Pope Leo. It
53:24
Speaker 1: took the Vatican to recognize it. Now, none of these
53:27
Speaker 1: men are perfect. Their circumstances are completely different, and their
53:31
Speaker 1: success so far shouldn't obscure the challenges that they all
53:36
Speaker 1: will be facing. But it's beside the point. If you'd
53:40
Speaker 1: been asked just a few years ago, which of these
53:41
Speaker 1: institutions or countries was most likely to produce the kind
53:45
Speaker 1: of leadership that the Western world desperately needed, would any
53:48
Speaker 1: of them been at the top of your list? That
53:51
Speaker 1: the new leader of Hungary, a new Pope? I'm sure, look,
53:58
Speaker 1: I'm like many people, I'd kind of given up on
53:59
Speaker 1: the Catholic Church as a source of these things. Just
54:03
Speaker 1: another institution that was sort of collapsing on itself. Ukraine, Canada,
54:13
Speaker 1: but here we are. So what about America? Well, we're
54:21
Speaker 1: less than three weeks away from a midterm election that
54:23
Speaker 1: could tell us an enormous amount about the future of
54:25
Speaker 1: both parties. And I've spent a lot of time over
54:29
Speaker 1: the last few weeks talking about the possibility of a
54:31
Speaker 1: significant repudiation of Donald Trump and the Republican Party. What
54:35
Speaker 1: we don't know is how significant. But the size and
54:39
Speaker 1: shape of this repudiation will tell us quite a bit
54:41
Speaker 1: about what comes next. And then for this, I'm watching
54:45
Speaker 1: the governorships closer than I'm watching the Senate races for
54:49
Speaker 1: this issue. And I talked a lot about governor's races
54:53
Speaker 1: in the last podcast, but I want to return for
54:55
Speaker 1: a different reason, because I think some of these races
54:57
Speaker 1: will tell us something about the kind of political leadership
55:00
Speaker 1: the country is capable of producing. A Democratic Senate victory
55:05
Speaker 1: in a red state can be explained away as a
55:07
Speaker 1: backlash against an unpopular president or an unpopular Republican nominee
55:11
Speaker 1: or some combination of the two. But if Democrats are
55:14
Speaker 1: winning governorships in places like Texas, Ohio, and Iowa, while
55:19
Speaker 1: also winning those states' Senate races, then there's something bigger happening.
55:24
Speaker 1: That's voters questioning the governing choices and political identity of
55:27
Speaker 1: the entire Republican Party itself. That's not just voting for
55:31
Speaker 1: a check on Trump's power. It's something else. Think about
55:37
Speaker 1: what a Democrat has to accomplish to win a governorship
55:39
Speaker 1: in Texas or Ohio or Iowa. That candidate has to
55:42
Speaker 1: persuade a substantial number of people who are instinctively suspicious
55:46
Speaker 1: of the Democratic Party right now to trust a Democrat
55:50
Speaker 1: with executive power. So they have to overcome the national
55:53
Speaker 1: party's negative brand. And remember, it's more unpopular than the
55:56
Speaker 1: GOP right now. They have to navigate a political environment
55:59
Speaker 1: that's already tilted against them in the red state that
56:02
Speaker 1: they live in. And then they have to build a
56:04
Speaker 1: coalition that extends well beyond the people who already agree
56:06
Speaker 1: with them. Sound familiar? That's what Bagyar had to do
56:11
Speaker 1: in Hungary. In some ways, that's what Carney's pulling off
56:14
Speaker 1: in Canada. And neither succeeded simply by rallying people who
56:19
Speaker 1: already were on their side. They had to persuade the skeptics.
56:23
Speaker 1: That's why I think these red state governor's races may
56:25
Speaker 1: be the most important test of political leadership in this election.
56:29
Speaker 1: The candidates who can win those races will have demonstrated
56:31
Speaker 1: precisely the skill our next president is going to need
56:37
Speaker 1: if they want to be successful. Because if we have
56:39
Speaker 1: another partisan president, we're doomed. We're doomed for another term
56:43
Speaker 1: of paralysis. We need somebody who has the ability to
56:47
Speaker 1: persuade ideological skeptics to trust them.
56:52
Speaker 2: Right?
56:53
Speaker 1: There's actually an interesting counterexample that succeeded quite a bit
56:57
Speaker 1: on the governor's level. It's in Vermont, Phil Scott. But
57:01
Speaker 1: the Republican brand is turning into a big problem for him.
57:03
Speaker 1: He spent years demonstrating that a Republican would win one
57:06
Speaker 1: of the most Democratic states in the country by rejecting
57:13
Speaker 1: Trumpism and building a coalition that extends well beyond his party.
57:17
Speaker 1: And Scott has won his last three re-election campaigns by
57:20
Speaker 1: 40 points. Now he's struggling this cycle. Now I don't
57:27
Speaker 1: know if Scott's actually going to lose, but he's a
57:29
Speaker 1: five-term incumbent. Remember, there are two-year terms in Vermont. He's
57:33
Speaker 1: been among the most popular governors, and he had to
57:35
Speaker 1: do it via building an extraordinary brand. But the fact
57:38
Speaker 1: we're even discussing the possibility tells us something about the
57:41
Speaker 1: Republican Party. If Phil Scott is now having trouble separating
57:44
Speaker 1: himself from the national Republican brand, think about what that
57:48
Speaker 1: means for Republicans who haven't spent years cultivating a reputation
57:51
Speaker 1: for independence. And it raises an interesting question about what
57:56
Speaker 1: happens after November. Will Republicans interpret a difficult election as
58:00
Speaker 1: merely a temporary setback caused by an unpopular president? Or
58:04
Speaker 1: will they begin reconsidering the larger direction Donald Trump has
58:07
Speaker 1: taken the party? That, to me, is one of the
58:11
Speaker 1: most important questions in American politics over the next two years.
58:14
Speaker 1: What happens to the Republican Party after Trump? I'm skeptical
58:18
Speaker 1: that the current Republican leadership has much interest in repairing
58:21
Speaker 1: the damage Trump has done to America's credibility. the rule
58:24
Speaker 1: of law, or the Western alliance. I think there's some
58:27
Speaker 1: elected Republicans who are alarmed. I think there are conservatives
58:31
Speaker 1: who have never been comfortable with Trumpism. And there are
58:33
Speaker 1: others who have gone along with it because they believed
58:35
Speaker 1: it was the only way to survive politically. But I
58:39
Speaker 1: don't know if they constitute a large enough coalition to
58:41
Speaker 1: reclaim their party. It's interesting in thinking about this, Marco
58:47
Speaker 1: Rubio becomes an interesting figure I've been thinking of Rubio.
58:51
Speaker 1: He could end up being something like the Joe Biden
58:52
Speaker 1: of the MAGA movement. And what do I mean by this?
58:56
Speaker 1: Biden emerged in 2020 as basically the compromise candidate in
59:00
Speaker 1: a party that was pretty divided. Progressive, though, were OK
59:06
Speaker 1: with it because they thought, eh, we can push him
59:08
Speaker 1: to the left. Moderates thought, he was fundamentally one of them.
59:12
Speaker 1: And the party establishment thought he was just simply somebody
59:14
Speaker 1: who could win. Everybody saw a little bit of what
59:17
Speaker 1: they wanted to see. I think that's what it's interesting
59:21
Speaker 1: to me. That's what Marco Rubio is, right? He's the
59:22
Speaker 1: Joe Biden. He's kind of a chameleon here. MAGA thinks
59:25
Speaker 1: he's becoming more MAGA. The establishment world still thinks Rubio's
59:30
Speaker 1: one of them. And he's been very careful. He's one
59:32
Speaker 1: of the few cabinet secretaries that hasn't gone out of
59:35
Speaker 1: his way to let his family enrich themselves. He's been
59:41
Speaker 1: better about this than most other of the cabinet members.
59:45
Speaker 1: But the problem he's got is he's been an active
59:47
Speaker 1: participant in this administration. He's had to defend its policies.
59:50
Speaker 1: He's adapted his positions. He had to carry out a
59:53
Speaker 1: foreign policy that has actually strained some of the very
59:56
Speaker 1: alliances he used to champion. So, yes, maybe Rubio could
1:00:03
Speaker 1: be a Band-Aid over the different factions of the Republican
1:00:06
Speaker 1: Party for one election. But I'm not sure he can
1:00:09
Speaker 1: pivot and be the person that takes them beyond Trumpism.
1:00:15
Speaker 1: And I'm not sure somebody so deeply involved in the
1:00:17
Speaker 1: Trump administration could credibly lead a restoration of American leadership post-Trump.
1:00:23
Speaker 1: because that's a much harder question. But I don't want
1:00:27
Speaker 1: to dismiss the idea that the Republican Party doesn't produce
1:00:30
Speaker 1: this change agent because nobody in 2015 thought Donald Trump
1:00:34
Speaker 1: was going to remake the Republican Party into what it
1:00:36
Speaker 1: had become today. Think about it. How many Republicans genuinely
1:00:41
Speaker 1: believed Donald Trump could hijack their party, bend it to
1:00:44
Speaker 1: his will, and remake its ideological identity all in under
1:00:48
Speaker 1: 10 years? Nobody was saying that in 2015 outside of
1:00:52
Speaker 1: Roger Stone and Donald Trump. but it's exactly what happened.
1:00:56
Speaker 1: So if one political movement could so thoroughly transform the
1:00:59
Speaker 1: Republican Party this quickly, I guess it's not inconceivable that
1:01:03
Speaker 1: another faction could do the same thing. I'm skeptical. We'll see.
1:01:10
Speaker 1: Now let's do the Democrats. Because I think this coming
1:01:13
Speaker 1: election presents an entirely different danger for them. Learning the
1:01:18
Speaker 1: wrong lesson from victory. One of the things I've learned
1:01:21
Speaker 1: from covering politics for more than three decades, is that
1:01:24
Speaker 1: success can teach political parties the wrong lessons. Sometimes winning
1:01:28
Speaker 1: an election convinces politicians that voters have endorsed an agenda
1:01:31
Speaker 1: they've never actually voted for. That's what happened to Scott Walker. Now,
1:01:39
Speaker 1: I think there's a real danger of that happening to
1:01:41
Speaker 1: Democrats if they have a big election victory this November. Now, look,
1:01:45
Speaker 1: I've got two competing theories about this and what a
1:01:48
Speaker 1: Democratic wave might produce for 2028. One is that the
1:01:51
Speaker 1: bigger the Democratic victory, the more emboldened the progressive wing becomes.
1:01:55
Speaker 1: The left concludes that the country is ready for a
1:01:57
Speaker 1: much more ideologically ambitious agenda. And Abdul El-Sayed, if he
1:02:02
Speaker 1: wins in Michigan, will be seen as an avatar or
1:02:06
Speaker 1: proof that, see, progressives can win even in swing states.
1:02:10
Speaker 1: And what it probably could mean is that the next
1:02:15
Speaker 1: Democratic presidential nominee is a progressive that is seen as
1:02:21
Speaker 1: the most acceptable to the center-left rather than a center-left
1:02:24
Speaker 1: candidate that is seen as acceptable enough to the progressive.
1:02:29
Speaker 1: But there's another way Democrats could go if they actually
1:02:33
Speaker 1: take a look at how they won. Maybe they look
1:02:36
Speaker 1: closely at how these candidates won in these red states,
1:02:41
Speaker 1: particularly the states that don't normally elect Democrats. Because if
1:02:44
Speaker 1: Democrats win Texas, Iowa, Ohio, and Kansas, And it won't
1:02:49
Speaker 1: necessarily be because their candidates successfully nationalized the party's progressive positions.
1:02:56
Speaker 1: It may be because they did the opposite. And they
1:02:59
Speaker 1: met voters where they were. They distanced themselves from the
1:03:03
Speaker 1: unpopular national positions when necessary. Focused on problems voters actually
1:03:09
Speaker 1: wanted solved. Political parties usually aren't this pragmatic. But that's
1:03:18
Speaker 1: the question I wonder. A candidate can win an extraordinarily
1:03:21
Speaker 1: favorable political environment without winning a mandate for every ideological
1:03:25
Speaker 1: position that candidate holds. And that's what Democrats have to
1:03:29
Speaker 1: be careful of. George W. Bush overreached. He won comfortably
1:03:33
Speaker 1: in 2004. It wasn't a blowout. It was close. But
1:03:37
Speaker 1: he interpreted it as a mandate to tackle Social Security privatization.
1:03:43
Speaker 1: Voters said, oh, no, we didn't give you permission to
1:03:45
Speaker 1: do that. You didn't campaign on that. It's the mistake
1:03:50
Speaker 1: Joe Biden made after 2020, particularly after January 5th and 6th,
1:03:54
Speaker 1: when they got control of the Senate on the 5th,
1:03:55
Speaker 1: and then what happened on January 6th? Joe Biden was
1:03:59
Speaker 1: elected in large part because voters believed he would restore
1:04:02
Speaker 1: some sense of normalcy, lower the temperature, govern as a pragmatist. Instead,
1:04:07
Speaker 1: there were times that his administration governed as though the
1:04:10
Speaker 1: progressive wing of the party had given him his decisive mandate.
1:04:15
Speaker 1: And that is what led to what we have today.
1:04:20
Speaker 1: I know some of my friends on the left are
1:04:21
Speaker 1: going to say, oh, Chuck Todd is just once again
1:04:26
Speaker 1: stiff-arming the left, trying to push both parties to the center.
1:04:31
Speaker 1: It's not my argument. I don't think it matters whether
1:04:35
Speaker 1: the next nominees from either party, which wing they come from,
1:04:39
Speaker 1: from the left, right, or center. I'm interested in whether
1:04:43
Speaker 1: that person has the skills to persuade voters who are
1:04:46
Speaker 1: ideologically suspicious of them to believe in their leadership. That's
1:04:52
Speaker 1: what I'm seeing with Gina Inouye. She comes out of
1:04:57
Speaker 1: the party's progressive wing in Austin, but she's refused to
1:05:01
Speaker 1: let opponents define her by the caricature of a progressive.
1:05:04
Speaker 1: And instead, she's meeting voters where they are. And that's
1:05:07
Speaker 1: the point. The next leader of the Democratic Party doesn't
1:05:09
Speaker 1: necessarily have to emerge from the moderate wing to behave
1:05:12
Speaker 1: this way. It can be from any wing. But it's
1:05:18
Speaker 1: the acknowledgement that you don't have, you need coalition partners.
1:05:24
Speaker 1: And are you good enough at convincing people you can
1:05:27
Speaker 1: be trusted? And I look at the next presidency, it's, look,
1:05:32
Speaker 1: I know every president, presidential election, most important of our lifetime, yada, yada, yada.
1:05:38
Speaker 1: But the next president is going to inherit an extraordinary mess,
1:05:41
Speaker 1: both domestically and internationally. I want to call it, we're
1:05:45
Speaker 1: going to be electing our first post-war president. What do
1:05:50
Speaker 1: I mean by that? Not because we've literally are emerging
1:05:52
Speaker 1: from a conventional war, although the Iran war and the
1:05:55
Speaker 1: continuing conflict in Ukraine are obviously still enormous challenges. I'm
1:05:59
Speaker 1: talking about this political, cultural cold war we've all been
1:06:03
Speaker 1: living through for much of the century. A cold war
1:06:07
Speaker 1: that has exhausted much of the electorate, weakened our institutions,
1:06:11
Speaker 1: made it increasingly difficult for Americans to believe that the
1:06:15
Speaker 1: government is even capable of solving any problems. So the
1:06:18
Speaker 1: next president is going to have to begin rebuilding. You
1:06:22
Speaker 1: got to repair alliances. The federal government's credibility is badly damaged.
1:06:28
Speaker 1: You got to have to restore that. The rule of
1:06:30
Speaker 1: law will need more than just rhetorical restoration. There's going
1:06:34
Speaker 1: to be enormous fiscal challenges. This debt problem is only
1:06:37
Speaker 1: getting worse. And the bond market is not going to
1:06:39
Speaker 1: be so kind to us anymore. There's going to be
1:06:43
Speaker 1: economic and social disruption caused by artificial intelligence. That's going
1:06:49
Speaker 1: to test the capacity of our governing institutions in ways
1:06:51
Speaker 1: we haven't even thought of yet. Think about the scale
1:06:56
Speaker 1: of the assignment for the next president. We're talking about
1:07:00
Speaker 1: somebody who may have to rebuild trust in government while
1:07:02
Speaker 1: simultaneously confronting technological disruption, enormous economic challenges, and a world
1:07:08
Speaker 1: in which American leadership can no longer be taken for granted.
1:07:14
Speaker 1: We can't afford an ordinary president. It's going to require
1:07:18
Speaker 1: more than an ordinary political skillset. And that brings me
1:07:21
Speaker 1: back to Carney, Zelensky, Magyar, and Leo. Because if I
1:07:25
Speaker 1: were advising somebody who genuinely wanted to become the next
1:07:28
Speaker 1: president of the United States, somebody who wanted to turn
1:07:30
Speaker 1: the page on the Trump era and begin rebuilding America's
1:07:33
Speaker 1: credibility at home and abroad, I'd be telling them, study
1:07:36
Speaker 1: all four of them, because they all have the qualities
1:07:39
Speaker 1: that the next American president desperately needs. I want Carney's
1:07:45
Speaker 1: temperament and competence. I want Pope Leo's moral grounding. I
1:07:49
Speaker 1: want Zelensky's courage. And I want Magyar's political savvy.
1:07:56
Speaker 2: Right?
1:07:56
Speaker 1: You give me all four of those things. Someone who
1:07:58
Speaker 1: isn't going to panic in a crisis. Somebody with an
1:08:00
Speaker 1: actual moral compass. Somebody willing to take political risks like Zelensky.
1:08:05
Speaker 1: And finally, a guy like Magyar who understands the mechanics
1:08:08
Speaker 1: of politics well enough to assemble a disparate coalition that
1:08:14
Speaker 1: doesn't begin and end with the committed. I think that
1:08:22
Speaker 1: the next successful nominee of the Democratic Party is gonna
1:08:25
Speaker 1: be somebody who can best persuade the most number of
1:08:35
Speaker 1: ideological skeptics in their own party. Now look, history doesn't
1:08:46
Speaker 1: always produce the leaders we expect. Harry Truman was an
1:08:50
Speaker 1: accidental president. Teddy Roosevelt, also an accident. Abe Lincoln emerged
1:08:57
Speaker 1: from a divided Republican Party. simply because he was acceptable
1:09:02
Speaker 1: to multiple factions. James Garfield emerged from a deadlock Republican convention.
1:09:11
Speaker 1: So we don't know. They're not easily... What I would
1:09:15
Speaker 1: say is this, that the obvious people that you think
1:09:19
Speaker 1: of in some ways, right? It's, we are looking for
1:09:25
Speaker 1: a needle in a haystack. So we'll see. But here's
1:09:35
Speaker 1: what I'll be looking for. I am curious of not
1:09:40
Speaker 1: the candidate who generates the most enthusiasm from an ideological wing.
1:09:45
Speaker 1: Not necessarily the one who's got the most money. I'm
1:09:49
Speaker 1: curious of the candidate who sparks the interest of people
1:09:53
Speaker 1: who normally wouldn't support them. That's the person who will
1:09:57
Speaker 1: demonstrate to me that they have the skill set to accomplish,
1:10:03
Speaker 1: to be the president we need in 2029, who can
1:10:09
Speaker 1: start to give America its credibility back. Political renewal doesn't
1:10:15
Speaker 1: always come from places we expect. Ukraine found courage from
1:10:19
Speaker 1: a former TV comedian. Canada found steadiness in a former
1:10:24
Speaker 1: central banker. And the Vatican came to America to find
1:10:28
Speaker 1: its moral voice. America is perfectly capable of producing the
1:10:35
Speaker 1: kind of leader this moment demands. We've already produced one
1:10:39
Speaker 1: who now leads an institution with more than a billion followers.
1:10:43
Speaker 1: It just took the Catholic Church to recognize him. So
1:10:48
Speaker 1: the question isn't whether America can produce the leader we need.
1:10:52
Speaker 1: The question is whether our politics will allow a person
1:10:56
Speaker 1: with the skillset to emerge. But a lot of it
1:11:03
Speaker 1: begins when we're gonna begin to get some clues of
1:11:10
Speaker 1: what's possible in about 19 days. All right, I'm gonna
1:11:16
Speaker 1: sneak in a break. My interview today is with Dr.
1:11:21
Speaker 1: Ayanna Howard. She is the president of Spelman College in Atlanta,
1:11:26
Speaker 1: but she's also a former robotics engineer, rocket scientist for NASA.
1:11:30
Speaker 1: She's written a fantastic book about AI, higher ed, where
1:11:35
Speaker 1: we're going next. And so, look, this is, I know
1:11:38
Speaker 1: I've probably over-indexed on some of these AI conversations, but
1:11:43
Speaker 1: I kind of want to get out of the political
1:11:44
Speaker 1: space and more in the And how's this going to work?
1:11:48
Speaker 1: How are we going to implement it? How are we
1:11:49
Speaker 1: going to teach it? And I do think you'll enjoy
1:11:53
Speaker 1: this conversation with Dr.
1:11:54
Speaker 2: Howard.
1:11:55
Speaker 1: So we'll sneak in the break. We'll get her, get that,
1:11:57
Speaker 1: do some questions. And it's Miami, Florida State Week. So,
1:12:00
Speaker 1: you know, I've got a lot to say about college football.
1:12:03
Speaker 1: We'll be right back.
1:12:08
Speaker 2: We'll be right back.
1:12:11
Speaker 1: Well, my guest today is Dr. Ayanna Howard. She's the
1:12:15
Speaker 1: president of Spelman College, which, of course, is one of
1:12:18
Speaker 1: America's most historic institutions of higher learning. She spent most
1:12:23
Speaker 1: of her professional life, though, thinking about artificial intelligence long
1:12:27
Speaker 1: before many of us were thinking about it every day.
1:12:30
Speaker 1: She spent a decade at the NASA Space Jet Propulsion Laboratory.
1:12:35
Speaker 1: So this conversation that we're going to have, and she's
1:12:37
Speaker 1: got a new book coming out. In fact, hopefully you
1:12:39
Speaker 1: can find it right now after this interview, Rebooting the Machines,
1:12:43
Speaker 1: because it's going to come out in November. And it
1:12:47
Speaker 1: gets at a topic that I've had with quite a
1:12:50
Speaker 1: few folks, whether it's in the AI space, which is
1:12:55
Speaker 1: who gets to write the rules, who gets to decide
1:12:57
Speaker 1: what history is. And as you know, I spend a
1:13:00
Speaker 1: lot of time bringing on authors here who are essentially
1:13:04
Speaker 1: providing us better details of what actually happened in the
1:13:07
Speaker 1: history of this country. And needless to say, if we
1:13:11
Speaker 1: let AI write our history, we are going to have
1:13:15
Speaker 1: literally a whitewashed set of historical findings in what we have.
1:13:22
Speaker 1: And I know it's something that Dr. Howard's been thinking
1:13:26
Speaker 1: a lot about, and she's got a unique perspective here,
1:13:28
Speaker 1: head of a higher education institution and intimate knowledge of
1:13:35
Speaker 1: how this technology works. Dr. Howard, welcome. Thank you.
1:13:40
Speaker 2: Thank you. I appreciate it. And I'm interested in how
1:13:44
Speaker 2: this is going to evolve. Well, good.
1:13:46
Speaker 1: I mean, I want to start with, look, the decision
1:13:52
Speaker 1: to sort of leave your area of expertise. You're at NASA, right?
1:13:56
Speaker 1: That's like, you know, for a scientist, no matter, you know,
1:13:59
Speaker 1: that's for an engineer, right? That's a peak place to be.
1:14:04
Speaker 1: And now you're at Spelman. which I'm glad for Spelman
1:14:07
Speaker 1: you're there. You want more presidents of higher ed to
1:14:13
Speaker 1: come from doing stuff, not always from other academia, right?
1:14:18
Speaker 1: There's sort of two types of university, well, three types
1:14:21
Speaker 1: of university presidents. Those that sort of grow up in
1:14:23
Speaker 1: a university, those that are sort of, politicians who get plucked, right?
1:14:28
Speaker 1: And then there's this third category of people who've had
1:14:32
Speaker 1: successful careers who come in. So first tell me about
1:14:36
Speaker 1: the decision to go into academia after being at NASA.
1:14:40
Speaker 2: Yeah, so I am a non-traditional academic and I always
1:14:43
Speaker 2: say that. I loved my experience at NASA. I loved
1:14:47
Speaker 2: having the shirts that said, you know, I am a
1:14:50
Speaker 2: rocket scientist or this is what a rocket scientist looks like.
1:14:52
Speaker 2: I was really geeked out around that. But when we
1:14:56
Speaker 2: had the second shuttle accident back in the day, There
1:15:00
Speaker 2: was a conversation around the value of NASA. What does
1:15:03
Speaker 2: it mean? What is the science exploration thing about? And
1:15:08
Speaker 2: people don't realize, but they froze funding for a lot
1:15:12
Speaker 2: of the projects. Now, back in the day, you didn't
1:15:14
Speaker 2: get furloughed, though. You would come to work and you
1:15:17
Speaker 2: literally could do nothing. For a scientist, that gives you
1:15:20
Speaker 2: a lot of time to explore about, OK, what's next?
1:15:23
Speaker 2: And everyone said, oh, this happens every decade or so.
1:15:26
Speaker 2: So I decided to see what's next at that time.
1:15:30
Speaker 2: I wanted to do robotics. I was a researcher. The
1:15:32
Speaker 2: only place you could really do robotics at the time
1:15:35
Speaker 2: was NASA. You can go to automotive or you could
1:15:38
Speaker 2: do academia. So I put my toe in.
1:15:43
Speaker 1: You know, it's interesting what you just said there. I
1:15:44
Speaker 1: have a friend of mine that I grew up with
1:15:46
Speaker 1: who's a nuclear engineer. He's been in this public-private sector
1:15:51
Speaker 1: for a long time, working for a private sector who's
1:15:54
Speaker 1: got big government contracts. He talks about that frustration of
1:15:58
Speaker 1: working for the government. There are times that you just
1:16:01
Speaker 1: have to sit there because maybe there's a government shutdown.
1:16:04
Speaker 1: Maybe there's or there's only a budget continuing resolution, and
1:16:09
Speaker 1: there's certain restrictions on what you can do with your research. Boy,
1:16:14
Speaker 1: just hearing you bring that up, I was just immediately
1:16:17
Speaker 1: triggered by him, and he would just talk about how
1:16:19
Speaker 1: frustrating that was. He goes, I'm just an engineer. I
1:16:21
Speaker 1: want to do work, and they won't let me.
1:16:24
Speaker 2: I want to do cool stuff. Yeah. And that was
1:16:27
Speaker 2: my first experience around that. So I was at that
1:16:31
Speaker 2: that era that, again, every decade or so. And I'm
1:16:35
Speaker 2: one that I can't be idle. I get in trouble
1:16:37
Speaker 2: when I'm idle. And so I have to make sure
1:16:41
Speaker 2: that I have work to do and have some creativity
1:16:44
Speaker 2: and exploration in what I do.
1:16:48
Speaker 1: I was been thinking about, as I was looking at
1:16:51
Speaker 1: your material and understanding your background and thinking about how
1:16:55
Speaker 1: are we going to regulate AI and what do we
1:16:58
Speaker 1: do with it? And there's a part of me that says, well,
1:17:02
Speaker 1: you know, how did we handle air travel? Right. And
1:17:06
Speaker 1: at first it was very, we, government wasn't involved, then
1:17:09
Speaker 1: it was involved, you know, and we decided we didn't
1:17:14
Speaker 1: have the regulatory institutions that we needed. We created FAA.
1:17:18
Speaker 1: In the military, we created an Air Force. I guess
1:17:21
Speaker 1: you could say NASA was in some ways an evolution
1:17:24
Speaker 1: to that a little bit. But I was thinking about
1:17:26
Speaker 1: NASA and wondering, do we need a new agency a
1:17:30
Speaker 1: la NASA that is focused on AI? We do.
1:17:33
Speaker 2: Actually, in my book, I talk about regulations and saying
1:17:36
Speaker 2: we need to create an FAA-like entity around AI. So
1:17:41
Speaker 2: one of the things that FAA does is that they
1:17:44
Speaker 2: have some rules of engagement that Everything from if you
1:17:48
Speaker 2: are harmed by an airline, i.e. you're sitting on the
1:17:51
Speaker 2: tarmac for four hours, there's some compensation to you. If
1:17:55
Speaker 2: AI does harm to you because it collected incorrect data
1:17:59
Speaker 2: or had a bad outcome, what is the payment or
1:18:02
Speaker 2: the compensation that's provided to us? People are trained, like
1:18:07
Speaker 2: pilots are trained. flight controllers are trained. Like everyone is
1:18:12
Speaker 2: trained at the airport. Here in AI is basically, if
1:18:15
Speaker 2: you can open up a webpage and read something, there's
1:18:19
Speaker 2: your training and now you can develop. And so thinking
1:18:22
Speaker 2: about that element of an FAA for AI, I think
1:18:26
Speaker 2: is required because AI can really cause harms, but it
1:18:30
Speaker 2: also would have some value. I mean, transportation is so
1:18:34
Speaker 2: much easier that we have flights, but we don't have
1:18:38
Speaker 2: as many crashes as there was when FAA didn't exist.
1:18:43
Speaker 1: Well, I mean, look, air travel is not 100%. We
1:18:47
Speaker 1: know this. There's risk with air travel. It's one of
1:18:50
Speaker 1: my favorite things to say whenever I hear, well, something
1:18:52
Speaker 1: is you're 95% certain about something. I'm like, hmm, would
1:18:56
Speaker 1: you go on a plane that had a 95% chance
1:18:59
Speaker 1: of landing, which means a one in 20 chance of crashing.
1:19:04
Speaker 1: You know, would you get on that plane? And when
1:19:05
Speaker 1: you put it in those terms, a lot of people,
1:19:07
Speaker 1: it's my way of reminding people, you know, probabilities look
1:19:11
Speaker 1: differently when you put yourself in the situation.
1:19:15
Speaker 2: It's true.
1:19:16
Speaker 1: On something like that. So what should be our risk
1:19:22
Speaker 1: tolerance for AI? And because it's, you know, risk tolerance
1:19:27
Speaker 1: is a funny thing. 95% for everybody else seems fine. 95%
1:19:30
Speaker 1: for me seems risky.
1:19:35
Speaker 2: So I think about correlating risk to the potential harm
1:19:39
Speaker 2: that it could cause. We're going to go back to
1:19:42
Speaker 2: FAA and airplanes. So, you know, airplanes could actually take off,
1:19:47
Speaker 2: fly and land by themselves. But when you think about
1:19:51
Speaker 2: it through that, the risk goes up. And so what
1:19:53
Speaker 2: do we have? We have human pilots that mitigate that
1:19:56
Speaker 2: risk so that it is at 99.9999%. It's the human
1:20:00
Speaker 2: in the loop. And so I truly believe, and I
1:20:02
Speaker 2: have a philosophy, that for high risk healthcare, as an example,
1:20:07
Speaker 2: We should have a human in the loop that is
1:20:08
Speaker 2: second guessing, that is putting their own judgment, that is
1:20:11
Speaker 2: overseeing because AI will never be 99.99999% because we as
1:20:18
Speaker 2: people are so adaptive and we change all the time.
1:20:21
Speaker 1: Well, that's easy to say and everybody seems to agree
1:20:25
Speaker 1: to it. And yet we can't even, I mean, look
1:20:28
Speaker 1: what we're doing now. And I'm torn and you must
1:20:31
Speaker 1: be torn as somebody who's an engineer that pushes the limits,
1:20:35
Speaker 1: meaning You want to keep finding, you want to keep experimenting,
1:20:40
Speaker 1: but do we want to use the human race as
1:20:42
Speaker 1: our guinea pigs?
1:20:44
Speaker 2: And I don't. So there has to be a balance.
1:20:47
Speaker 2: I don't want the, you know, nuclear, we have regulations.
1:20:51
Speaker 2: We didn't always have that. And we know the impact
1:20:53
Speaker 2: that that has had. I do have a fear that
1:20:57
Speaker 2: if we don't think about the regulations, we don't think
1:20:59
Speaker 2: about the guardrails, that we will have something happen. And
1:21:03
Speaker 2: then everyone will then come to the forefront and say, yeah,
1:21:06
Speaker 2: we need to have regulations. But who is going to
1:21:08
Speaker 2: be harmed when that happens? And so there's that element.
1:21:13
Speaker 2: But then The problem is, is that everyone, all of
1:21:16
Speaker 2: our countries, all of our neighboring areas are still iterating
1:21:20
Speaker 2: and trying to figure this out. So as a U.S.,
1:21:23
Speaker 2: if we stop, then it means that we will be
1:21:26
Speaker 2: left behind. And so we're in this really weird, precarious
1:21:29
Speaker 2: situation where other people are developing without guardrails. We have
1:21:34
Speaker 2: no guardrails because we want to keep developing. But something
1:21:36
Speaker 2: might happen that is detrimental to us as humanity.
1:21:40
Speaker 1: Right. Let me try pharmaceuticals. We don't let something get
1:21:47
Speaker 1: out to market until the FDA says it's okay. But
1:21:51
Speaker 1: we let some stuff into market sometimes before the FDA approves.
1:21:58
Speaker 1: Is that a model, right? Because with pharmaceutical companies, they're
1:22:02
Speaker 1: still allowed to innovate. They're trying to find something. Some stuff,
1:22:07
Speaker 1: they have trials. There's a process. If it doesn't work,
1:22:10
Speaker 1: they don't bring it to market. Should an AI model have,
1:22:14
Speaker 1: should that be the framework of an AI model?
1:22:18
Speaker 2: I think the models should be associated with the outcomes.
1:22:22
Speaker 2: So for example, we have AI for healthcare. Why don't
1:22:26
Speaker 2: we have something like the FDA that's already regulating pharma
1:22:30
Speaker 2: for healthcare?
1:22:31
Speaker 1: Okay, what does AI do? So you're saying you want
1:22:34
Speaker 1: to split it by specialty, that there shouldn't be an
1:22:39
Speaker 1: AI board generally that if it's a healthcare model, let
1:22:43
Speaker 1: people that are healthcare experts.
1:22:46
Speaker 2: Correct. So some of these things are highly regulated already.
1:22:49
Speaker 2: So we know healthcare is highly regulated field. We know
1:22:52
Speaker 2: nuclear is a highly regulated field. We know transportation is
1:22:55
Speaker 2: actually not highly regulated, but it's regulated. We have these bodies.
1:22:59
Speaker 2: And one of the nice things is not US-based, right?
1:23:01
Speaker 2: There are these national, international organizations that think about transportation
1:23:06
Speaker 2: and airfare and flights and all of these elements. So
1:23:09
Speaker 2: they have a system. Why is AI thought of this
1:23:12
Speaker 2: totally different entity that it needs to be separated? Because
1:23:16
Speaker 2: I think if I have AI for helping me make calls,
1:23:20
Speaker 2: I don't actually want that to be heavily regulated.
1:23:22
Speaker 1: Yeah, sure.
1:23:23
Speaker 2: There's some spam calls and all of that. I don't
1:23:26
Speaker 2: really think I care. But if it's impersonation, if it's
1:23:29
Speaker 2: doing mail fraud, for example, well, then we have regulations
1:23:32
Speaker 2: with respect to that.
1:23:34
Speaker 1: Well, don't we already have that? Isn't that what the
1:23:35
Speaker 1: FTC is? I mean, I look at the FTC and
1:23:38
Speaker 1: I'm like, do your job, FTC. You know, if we've
1:23:41
Speaker 1: got surveillance pricing and things like this, that feels like
1:23:45
Speaker 1: we already have the regulatory body for this.
1:23:49
Speaker 2: We do. But I think this is the problem. fundamentally
1:23:53
Speaker 2: is that people don't understand AI. So when I think
1:23:57
Speaker 2: about this, people don't understand it.
1:24:00
Speaker 1: When you say that, what does that mean? When you
1:24:01
Speaker 1: say they don't understand it? Let me give you an example.
1:24:05
Speaker 1: I view it all as a probability model. I think
1:24:09
Speaker 1: it is all predictive. I don't mean that in a,
1:24:12
Speaker 1: so I go about it that way. And that's why
1:24:16
Speaker 1: I know it's not 100% accurate, but why I assume
1:24:20
Speaker 1: it's finding the best guess. And it probably is better
1:24:24
Speaker 1: at initial search than me skimming a search page. But
1:24:30
Speaker 1: I also know it's just predictive and probability. But what
1:24:34
Speaker 1: is that? Me translating that to others, that hasn't worked
1:24:37
Speaker 1: for them. But it works in my brain. I'll admit that.
1:24:41
Speaker 2: Doesn't make it that element of prediction versus projection versus
1:24:49
Speaker 2: like all of that is a different way of looking
1:24:52
Speaker 2: at the world, which means you probably do this all
1:24:55
Speaker 2: the time. Weather is actually, you know, it's a guess
1:24:59
Speaker 2: in some cases, But yet we look at our weather
1:25:03
Speaker 2: app and we're like, is it going to rain today?
1:25:04
Speaker 2: And you're looking outside, you're like, well, it's clearly raining,
1:25:07
Speaker 2: but yet I'm still assuming that my weather app is correct.
1:25:11
Speaker 2: I just think it's the way we live our world.
1:25:13
Speaker 2: In fact, there's been some studies that have shown we
1:25:15
Speaker 2: are very bad as people. We are very bad at
1:25:19
Speaker 2: understanding what that means in terms of risk prediction, 99%
1:25:24
Speaker 2: versus 80%. Like, what does that actually mean if it
1:25:27
Speaker 2: comes to my day-to-day existence? We are really bad at that.
1:25:31
Speaker 1: So what is teaching people? I mean, the thing is,
1:25:35
Speaker 1: is that there's one thing to figure out how to
1:25:37
Speaker 1: teach this to school children. It's another thing to figure
1:25:41
Speaker 1: out what to do, what you have to do in
1:25:43
Speaker 1: higher ed and preparing for the next generation of jobs.
1:25:45
Speaker 1: But we've got an entire population that whether they like
1:25:49
Speaker 1: it or not, needs to understand how this works. So
1:25:52
Speaker 1: how do you have this sort of group learning exercise
1:25:55
Speaker 1: that we're in the middle of right now?
1:25:57
Speaker 2: So it's about the practical knowledge. It's about the practicality
1:26:00
Speaker 2: of what is it that I can do personally today
1:26:03
Speaker 2: that allows me to understand my nuances, my overtrust. I
1:26:07
Speaker 2: talk a little bit about actually a lot about overtrust
1:26:10
Speaker 2: of AI and understand how do I retrain myself based
1:26:14
Speaker 2: on my day to day. One example, we used to
1:26:17
Speaker 2: kind of laugh when we talked about, well, I'm going
1:26:19
Speaker 2: to have a media off day. So I'm not going
1:26:23
Speaker 2: to look at any of my social media. I'm not
1:26:25
Speaker 2: going to answer my cell phone or text. And we
1:26:28
Speaker 2: pride ourselves on that. But we can do the same
1:26:30
Speaker 2: thing with respect to artificial intelligence and retrain and understand
1:26:35
Speaker 2: what it is. If I'm doing search, now I have
1:26:37
Speaker 2: an AI summarizer for all of that. OK, let's try
1:26:41
Speaker 2: to do a little bit different. take three different search engines,
1:26:44
Speaker 2: which we used to do, take three different search engines,
1:26:48
Speaker 2: see how the information is different. You will be surprised.
1:26:52
Speaker 2: So now you're starting to think about, oh wait, AI,
1:26:54
Speaker 2: there is no general AI. Like each one is different,
1:26:57
Speaker 2: just like people. They give you bad advice all the time,
1:27:01
Speaker 2: three different ways.
1:27:02
Speaker 1: I do this a lot. I use three models and
1:27:06
Speaker 1: I always never let one model have the final say.
1:27:11
Speaker 1: I don't, you work the models against each other. Is
1:27:16
Speaker 1: this research complete? What's missing? Vice versa. And it's funny,
1:27:23
Speaker 1: what that tells me is that AI is not going
1:27:25
Speaker 1: to have the, you know, the fact that there are,
1:27:27
Speaker 1: I want to say slightly different outcomes. They're generally 85% overlap, right?
1:27:32
Speaker 1: But it is the 15% that makes it either really
1:27:37
Speaker 1: good or really sloppy, right? The difference between AI slop
1:27:41
Speaker 1: and really good AI tools is that 10 to 15%,
1:27:47
Speaker 1: which is if we already know that no one model
1:27:51
Speaker 1: has the answer, then, you know, are we like overselling
1:27:59
Speaker 1: this a little bit? Well, so.
1:28:02
Speaker 2: I would say we, we being the collective society. We are,
1:28:08
Speaker 2: I would say overselling based on the fact that we
1:28:13
Speaker 2: are selling it as if it is perfect. But the
1:28:17
Speaker 2: fact is, is that it is better than what we
1:28:20
Speaker 2: had three years ago. Again, I'll use search, right? I
1:28:24
Speaker 2: remember trying to do a search and I'd have to
1:28:27
Speaker 2: have four different, I'm going to call them problems, but
1:28:29
Speaker 2: four different search criteria to get to, the answer that
1:28:33
Speaker 2: I was actually looking for. Or I'd have to go
1:28:36
Speaker 2: through like 10 links and be like, you know what?
1:28:38
Speaker 2: This is ridiculous. Let me change my search, like my
1:28:41
Speaker 2: search terms. Now I have shortened my time by using
1:28:46
Speaker 2: the summarizer, even though I still use different types of
1:28:49
Speaker 2: search engines. So what does that mean? One, I'm more
1:28:53
Speaker 2: efficient with my time. I get to the answer faster.
1:28:57
Speaker 2: But I've already trained myself to basically one answer is
1:29:01
Speaker 2: not the truth. I still do a comparison function. Right.
1:29:04
Speaker 2: So it's better than going through all the links and
1:29:07
Speaker 2: clicking on them and navigating and then coming back and
1:29:09
Speaker 2: coming to trash like, oh, I hope my kid didn't
1:29:12
Speaker 2: see that page.
1:29:12
Speaker 1: Right.
1:29:13
Speaker 2: Like all of those things. Right. It's a lot easier. Right.
1:29:25
Speaker 1: This gets to, though, the issue of what of, you know,
1:29:29
Speaker 1: a large language model is only good as the is
1:29:32
Speaker 1: what it trains on.
1:29:33
Speaker 2: Right.
1:29:34
Speaker 1: The data that it trains on. And like I said,
1:29:36
Speaker 1: I've had a lot of authors, particularly African-American authors on
1:29:40
Speaker 1: this program about what a forgotten history, missing history, lost history.
1:29:45
Speaker 2: Right.
1:29:45
Speaker 1: We know we know what it is, the whitewashed history.
1:29:49
Speaker 1: If we have if we're just going to summarize history.
1:29:53
Speaker 1: You know, I say this, it doesn't, there's a lot
1:29:56
Speaker 1: of groups of what I would say were sort of
1:29:59
Speaker 1: minority groups pushed aside over the last 500 years, whether
1:30:02
Speaker 1: it's Jewish people, African-Americans, Islamic people, indigenous folks, whose histories
1:30:11
Speaker 1: really only in the last 30 years are being resurfaced, right?
1:30:17
Speaker 1: Are getting a little bit of attention. you know, that's,
1:30:24
Speaker 1: you know, do we embed in our stereotypes and, and
1:30:27
Speaker 1: how do we, you know, this for me feels like
1:30:31
Speaker 1: the real challenge of making these trusted and effective tools. Yeah.
1:30:36
Speaker 2: So, you know, I always ask the question of what
1:30:40
Speaker 2: is the purpose? What is the end goal of what
1:30:43
Speaker 2: we're doing? So large language models, um, if we are
1:30:46
Speaker 2: looking at, um, the history of communities. We know, for example,
1:30:52
Speaker 2: Central Park used to be the Seneca Village. It used
1:30:55
Speaker 2: to be a black neighborhood, middle class that got wiped
1:30:58
Speaker 2: out to create Central Park in New York. A lot
1:31:02
Speaker 2: of people don't know that. And so how do we
1:31:05
Speaker 2: put that in if we're thinking about issues with redlining
1:31:08
Speaker 2: or changing the voting map? That's the history that can
1:31:13
Speaker 2: allow us to see, oh, wait, there's something historically wrong
1:31:17
Speaker 2: of what we have now. How do we get to
1:31:19
Speaker 2: the next stage? But if it's around math, two plus
1:31:22
Speaker 2: two equals four. I'm not quite sure. There might be
1:31:26
Speaker 2: history that's lost in terms of math, of how we
1:31:29
Speaker 2: look at it, but we all accept that this is
1:31:31
Speaker 2: the math that we're using today, even though we know
1:31:35
Speaker 2: the abacus might be different in terms of math.
1:31:38
Speaker 1: You're speaking like an engineer. You're basically saying, hey, look,
1:31:41
Speaker 1: for essentially everything that's number-based, to loosely, this is going
1:31:47
Speaker 1: to be an incredibly exponentially incredible tool. Where we're going
1:31:53
Speaker 1: to consistently get into fights is what we've been fighting
1:31:55
Speaker 1: about since the dawn of us writing things down, right?
1:31:59
Speaker 1: Which is the subjectivity of human interpretation.
1:32:03
Speaker 2: Yeah, and this is one of the things that I
1:32:05
Speaker 2: keep talking about, which is the value of humanities, the
1:32:11
Speaker 2: social studies, linguistics, creative, the arts. Because that is the
1:32:17
Speaker 2: practice that is allows us to figure out how to
1:32:20
Speaker 2: become critical around things that we read or things that
1:32:23
Speaker 2: we hear. We look at it through that lens of
1:32:27
Speaker 2: I have two authors that write about the same event.
1:32:30
Speaker 2: And yet, because they have different lived experiences, their narration
1:32:34
Speaker 2: around it is different. We're good in the humanities and
1:32:39
Speaker 2: the social sciences. They're really good at getting students to
1:32:43
Speaker 2: learn and question that, which is why I think they
1:32:46
Speaker 2: have a lot of value in this age of AI
1:32:48
Speaker 2: because that's their discipline and they can teach us a
1:32:51
Speaker 2: lot about how to be critical if we're reading an
1:32:54
Speaker 2: AI summarization and saying, hey, how do I critique this
1:33:00
Speaker 2: commentary right here? What is the discipline to do that
1:33:04
Speaker 2: and the practice to get us into that mode?
1:33:08
Speaker 1: So let's talk about the challenge of teaching math now
1:33:11
Speaker 1: going forward, right? One of the things I remember seeing
1:33:14
Speaker 1: this in a focus group of some parents a few
1:33:17
Speaker 1: years back, and this was parents complaining a bit more
1:33:21
Speaker 1: about social media and tech. This was really just before
1:33:24
Speaker 1: the AI, now that AI has sort of become synonymous
1:33:28
Speaker 1: with our concerns about tech. But it was, you know,
1:33:32
Speaker 1: I don't know what the skill sets my kids are
1:33:35
Speaker 1: going to need. You know, it's like, You know, I
1:33:40
Speaker 1: think my parents' generation, I'm in my 50s, I feel
1:33:42
Speaker 1: like my parents' generation thought, well, they kind of had
1:33:45
Speaker 1: an idea of what skills I needed to have to
1:33:47
Speaker 1: survive in my adulthood. Towards the end of my kids' schooling,
1:33:55
Speaker 1: one is out of college, one's in the middle of college,
1:33:58
Speaker 1: I found myself, ooh, I don't know what skill sets
1:34:02
Speaker 1: they're learning now that'll be obsolete when they're 40, right?
1:34:06
Speaker 1: So math is a good one. If we're solving every
1:34:10
Speaker 1: math problem now, right, which apparently I think we're taping
1:34:15
Speaker 1: middle of October, I believe there was another, it feels
1:34:18
Speaker 1: like every week there's another barrier broken in the world
1:34:20
Speaker 1: of mathematics. Hey, we finally solved this problem. AI is
1:34:24
Speaker 1: going to, you know, we're going to solve every problem.
1:34:28
Speaker 1: So how do you teach math and what should be,
1:34:31
Speaker 1: and I think this is something I'm guessing we're all,
1:34:34
Speaker 1: particularly those of you in the engineering space, like, What
1:34:38
Speaker 1: is the skill set you need in order to get
1:34:40
Speaker 1: the most out of AI?
1:34:43
Speaker 2: So I think one fundamental skill set is the ability
1:34:46
Speaker 2: to have critical thinking. Because what we teach in terms
1:34:51
Speaker 2: of the tools today will be obsolete 20, 30, 40 years.
1:34:55
Speaker 2: I remember growing up when I was in college, the
1:34:58
Speaker 2: professors would ask about the, why don't we use the
1:35:01
Speaker 2: slide ruler anymore? Did you have one?
1:35:04
Speaker 1: My grandfather was a mechanical engineer. I was going to
1:35:06
Speaker 1: ask you about the slide rule. And I remember when
1:35:09
Speaker 1: I turned 12 or 13, he goes, let me, he
1:35:12
Speaker 1: gave me a nice slide rule. He spent a lot
1:35:15
Speaker 1: of money on this. It's like in the early 80s.
1:35:17
Speaker 1: just when computers were just, but we had those fancy calculators.
1:35:22
Speaker 1: And by then you were using to do trigonometry or
1:35:27
Speaker 1: any of that, you know, the cosine stuff. I'm really
1:35:30
Speaker 1: stretching back to my days there, right? A little bit
1:35:32
Speaker 1: on trig 101. But, and I remember going to my dad,
1:35:37
Speaker 1: I said, you know, I don't know if we're ever
1:35:39
Speaker 1: going to use a slide rule. They told us we
1:35:41
Speaker 1: had to buy a calculator. One of those fancy scientific,
1:35:44
Speaker 1: I think back then we used to call them scientific calculators.
1:35:47
Speaker 2: Yes.
1:35:48
Speaker 1: And it made the slide rule obsolete. Yet my grandfather thought, well,
1:35:51
Speaker 1: how do you not understand how a slide rule works?
1:35:54
Speaker 1: You're not going to understand engineering if you don't understand
1:35:56
Speaker 1: a slide rule.
1:35:58
Speaker 2: Exactly. And I was in that era where the professors
1:36:02
Speaker 2: were lamenting because we have moved to the calculators, the
1:36:05
Speaker 2: scientific calculators. And now in engineering, they're using computers, right?
1:36:10
Speaker 2: So they're using computes. They're still building bridges. They're still
1:36:14
Speaker 2: building rocket ships. They're still programming computers. And so it's shifted.
1:36:19
Speaker 2: But one of the things that we as educators do
1:36:22
Speaker 2: is how do we teach you how to think? I
1:36:26
Speaker 2: think that's really what it is. Like even with the calculator,
1:36:28
Speaker 2: scientific calculator, there was still some things you had to do,
1:36:30
Speaker 2: fundamental principles, before you could even figure out what to
1:36:33
Speaker 2: put in the calculator to get the answer. It's really
1:36:36
Speaker 2: that element because I think of it for computing, right?
1:36:42
Speaker 2: I know probably about 20 different languages in computing. We
1:36:48
Speaker 2: don't really do Fortran anymore. We don't really do Pascal anymore. COBOLs,
1:36:55
Speaker 2: every so often. I mean, these are people, like my
1:36:57
Speaker 2: students have no idea. What is Fortran?
1:36:59
Speaker 1: Are you even going to bother teaching different coding languages?
1:37:03
Speaker 2: That's the whole thing?
1:37:03
Speaker 1: No.
1:37:04
Speaker 2: Yeah. if you teach one and get them to think
1:37:07
Speaker 2: through the process of how do you learn, it means
1:37:10
Speaker 2: that in five years or 10 years, when is the next,
1:37:12
Speaker 2: you know, whatever it is, list 5.0, coupled with generative AI,
1:37:18
Speaker 2: I don't know. They'll be like, oh, I can learn
1:37:21
Speaker 2: how to use this tool to figure out how to
1:37:24
Speaker 2: program with my AI in conjunction with my AI.
1:37:28
Speaker 1: Well, I think about the last 20 years. I mean,
1:37:30
Speaker 1: I would say when I was raising my kids in
1:37:32
Speaker 1: the late aughts, early teens, everybody said, well, they've got
1:37:37
Speaker 1: to learn to code. And it was this idea in
1:37:40
Speaker 1: the same way that my mom in Miami said, you
1:37:44
Speaker 1: need to learn Spanish, right? It was the same mindset. Like, hey,
1:37:47
Speaker 1: this is the world you're going to grow up in.
1:37:50
Speaker 1: You need to speak the language of the world you're
1:37:52
Speaker 1: growing up in, whether it was the physical world of
1:37:55
Speaker 1: South Florida, Miami, where I grew up with Spanish versus
1:37:59
Speaker 1: the technical world of this. And then it turns out,
1:38:02
Speaker 1: Guess what? Between Google Translate, you know, I think we're
1:38:05
Speaker 1: about five years away from never having to learn a
1:38:09
Speaker 1: foreign language because it's all going to be instantly translated
1:38:12
Speaker 1: to code. So what have we done over the last
1:38:17
Speaker 1: 20 years? Did we waste 20 years of education on kids?
1:38:21
Speaker 2: I think we didn't waste education on all kids, but
1:38:26
Speaker 2: we have to frame how we think about education now.
1:38:30
Speaker 2: Coding as an example, it was a big thing. Coding, coding, coding, coding.
1:38:34
Speaker 2: And now if you look at the top jobs that
1:38:37
Speaker 2: are being eradicated by AI. We did magnet schools for.
1:38:39
Speaker 1: Coding, remember? Like we were doing charter schools for coding, right?
1:38:42
Speaker 2: I was there too. I did camps and summer camps
1:38:45
Speaker 2: for students to learn coding. But what I would say
1:38:50
Speaker 2: is how you think about what is it that I
1:38:53
Speaker 2: need to do today in terms of the basic skills?
1:38:56
Speaker 2: Because the fact is you still have to get a job.
1:38:59
Speaker 2: So what are the jobs of today? Because you still
1:39:02
Speaker 2: have to have the ability to have a paycheck, feed
1:39:05
Speaker 2: your family, feed yourself, buy housing. So you have to
1:39:08
Speaker 2: have the skills for today. But as the jobs navigate
1:39:11
Speaker 2: and the jobs grow and we get to the next stage,
1:39:16
Speaker 2: Can you learn those new jobs? Prompt engineering. Do you
1:39:20
Speaker 2: remember when prompt engineering came out as a job right
1:39:23
Speaker 2: after basically the chat GPT came out?
1:39:28
Speaker 1: Wow, that's what we're calling that? Prompt engineering?
1:39:31
Speaker 2: It was called prompt engineering. And you could go on,
1:39:33
Speaker 2: and they were hiring prompt engineers for over 100K.
1:39:36
Speaker 1: Just knowing how to use better words to get more
1:39:40
Speaker 1: out of the AI? Is that basically what you're describing?
1:39:43
Speaker 2: Yes. And now that's not a thing, but because it
1:39:46
Speaker 2: was so new. And I remember at that stage, the
1:39:50
Speaker 2: individuals who were being hired were the ones who understood language,
1:39:54
Speaker 2: understood language. conversation, understood all these little things to get
1:39:57
Speaker 2: the AI to get the answer correct. And they use
1:40:00
Speaker 2: the data to retrain the models. So now the AI
1:40:04
Speaker 2: was better at responding to us.
1:40:08
Speaker 1: So I was at a talk, my son attends SMU
1:40:12
Speaker 1: and their university president is a guy named Jay Hartzell.
1:40:16
Speaker 1: He used to be at UT Austin and he recently,
1:40:20
Speaker 1: I view him as somebody who was like, I can't
1:40:23
Speaker 1: do the public institution. Let me go private where there's
1:40:25
Speaker 1: fewer people minding my business type of mindset. But he
1:40:29
Speaker 1: said something interesting about what he thought the impact of
1:40:32
Speaker 1: AI would be on higher ed. And he said, and
1:40:35
Speaker 1: he's done this so far, is he wants to start
1:40:37
Speaker 1: to steer SMU away from STEM, not in a negative way,
1:40:42
Speaker 1: but that essentially everything goes back to basics, the quote
1:40:47
Speaker 1: unquote classical education.
1:40:49
Speaker 2: Right.
1:40:50
Speaker 1: What was considered a curriculum of the late 19th century,
1:40:53
Speaker 1: early 20th century is essentially the bill that we're back
1:40:58
Speaker 1: to the idea that we're doing building blocks so that
1:41:01
Speaker 1: it's almost tech proof. Is that realistic?
1:41:07
Speaker 2: I do not think so. There is some elements of
1:41:10
Speaker 2: classical education, but you have to realize classical education, it
1:41:14
Speaker 2: was really about being a finishing school. Like, let's really
1:41:16
Speaker 2: be real around how universities started. Universities were starting, it
1:41:21
Speaker 2: was pretty much the elite. And I need to send
1:41:24
Speaker 2: my sons and daughters to school so that they can
1:41:26
Speaker 2: take control. To be refined. It was a finishing school.
1:41:30
Speaker 2: And this was the intellectual discourse and all of these things.
1:41:34
Speaker 2: So there's some element of that. But we do not
1:41:37
Speaker 2: have that hierarchy quite, I mean, frankly, it's changed. During
1:41:43
Speaker 2: the World Wars, the universities then became much more around, oh,
1:41:47
Speaker 2: we need a workforce. We need individuals that actually work,
1:41:51
Speaker 2: not the aristocrats, not the finishing schools. We need people
1:41:54
Speaker 2: that can actually think and go out in the field
1:41:56
Speaker 2: and be engineers and seamstresses and dot, dot, dot. So
1:42:00
Speaker 2: it's shifted and GI Bill, we're going to pay for
1:42:03
Speaker 2: people to go to school because they're not in the
1:42:06
Speaker 2: elite class. I think we are trying to redefine and
1:42:10
Speaker 2: figure out what we are now. We have a lot
1:42:12
Speaker 2: of universities. A lot of universities will close because we
1:42:16
Speaker 2: frankly have too many, unfortunately. It'll be the ones that last.
1:42:21
Speaker 2: Spelman College, for example, we will continue. But some of
1:42:25
Speaker 2: the smaller ones will struggle until they close because we
1:42:28
Speaker 2: haven't figured out what is our identity at this point.
1:42:32
Speaker 1: That's interesting you say that. Look, I think there's the
1:42:33
Speaker 1: demographic challenge, number one, that seems to be the big.
1:42:37
Speaker 1: But you think we have too many universities. How did
1:42:40
Speaker 1: we end up with too many universities, you think?
1:42:43
Speaker 2: One, we did have a large population. population of individuals
1:42:47
Speaker 2: going to college. It became this thing of you have
1:42:50
Speaker 2: to go to college to get a job. And trade
1:42:53
Speaker 2: schools became less of an interest in a lot of cases.
1:42:57
Speaker 2: And I think trade schools have a great value in,
1:43:00
Speaker 2: especially in the U.S. and other places. But we sort
1:43:02
Speaker 2: of moved away from trades and went to, you have
1:43:06
Speaker 2: to go to college. And the problem is, is that
1:43:10
Speaker 2: it was a college without necessarily an output. You go
1:43:12
Speaker 2: to college, get a degree in And X didn't necessarily
1:43:18
Speaker 2: associate with a job. It was just, you go to college.
1:43:22
Speaker 2: So a lot of universities and colleges popped up just
1:43:25
Speaker 2: to address the X. You had this influx of students
1:43:29
Speaker 2: that just wanted a college degree. And now we are here,
1:43:33
Speaker 2: we have this demographic cliff where we have less 18-year-olds
1:43:37
Speaker 2: going to college. And you have colleges that haven't been
1:43:40
Speaker 2: able to describe what that X is. What is the
1:43:43
Speaker 2: value of X? And it costs. So what is the
1:43:47
Speaker 2: value of X associated with the cost it takes to
1:43:51
Speaker 2: achieve and receive whatever the X degree is?
1:43:55
Speaker 1: So give me that answer for Spellman. How are you
1:43:59
Speaker 1: addressing that question?
1:44:01
Speaker 2: Yeah, so Spelman is, I will say, is a boutique university.
1:44:06
Speaker 2: We take the creme de la creme, we focus on
1:44:09
Speaker 2: Black women excellence, but we really think about what is
1:44:13
Speaker 2: that hybrid of the, would you say, classical education, the
1:44:19
Speaker 2: social scientists, humanities, the creative, but couple it with What
1:44:23
Speaker 2: is it that you need to have skills moving forward?
1:44:27
Speaker 2: We're the number one producer, for example, of Black women
1:44:29
Speaker 2: who go into STEM PhDs. Hmm. the number of lawyers
1:44:33
Speaker 2: and judges that we have that are out, the number
1:44:36
Speaker 2: of C-suite executives that are in our, you know, 40, 50,
1:44:40
Speaker 2: 60 year olds. We have an amazing ability to train
1:44:44
Speaker 2: these leaders, these women leaders, Black women leaders for that world.
1:44:49
Speaker 2: But we are not, we have, you know, a class
1:44:52
Speaker 2: of 650-ish that come in. We are not a flagship
1:44:56
Speaker 2: where we bring in tens of thousands of students. But
1:45:00
Speaker 2: that is our focus and that's our emphasis. And so
1:45:03
Speaker 2: the way we think about it is we are not
1:45:05
Speaker 2: going to be everything to everyone. We have an identity.
1:45:09
Speaker 2: We have a legacy. Those are the schools, I believe,
1:45:11
Speaker 2: that are going to last. It's going to be the flagships.
1:45:13
Speaker 2: They have a unique identity.
1:45:15
Speaker 1: Now, that makes sense. I guess I'd love to. So
1:45:20
Speaker 1: what you just described and what you really described of
1:45:23
Speaker 1: what happened to universities post GI Bill is we took.
1:45:26
Speaker 1: we took the trade school and we took the finishing
1:45:29
Speaker 1: school and we merged them, right? Essentially. In that you
1:45:34
Speaker 1: go to college both to sort of learn how to be,
1:45:37
Speaker 1: you know, a better human, right? A little more empathetic,
1:45:40
Speaker 1: a little how to live with others, how to work
1:45:42
Speaker 1: with others. But you also then had to pick a major,
1:45:45
Speaker 1: pick a trade, essentially, right? What are you going to do?
1:45:48
Speaker 1: What are you going to do for a living? And
1:45:51
Speaker 1: then over the last, you know, and that led over
1:45:53
Speaker 1: the last 20 years of, you know, Take my there's
1:45:57
Speaker 1: a small little Catholic school in the neighborhood I live in. Hey,
1:46:01
Speaker 1: they no longer are going to offer English as a
1:46:03
Speaker 1: major anymore. Right. Because the idea was, what is English?
1:46:07
Speaker 1: What is what do you what job is directly associated
1:46:11
Speaker 1: with that besides English teacher or writer? Like, what is it?
1:46:16
Speaker 1: And we went to the trade. Do you think we
1:46:19
Speaker 1: should unwind that a little bit?
1:46:20
Speaker 2: Yeah.
1:46:22
Speaker 1: Or actually focus more on the trade side of things
1:46:25
Speaker 1: when it comes to higher education?
1:46:27
Speaker 2: So I think we need to do both. And I
1:46:32
Speaker 2: think that when students, I always call it the headwinds,
1:46:37
Speaker 2: students are still attuned. They've learned, parents have learned that
1:46:42
Speaker 2: you go to college with the ability to bring wealth
1:46:48
Speaker 2: back to your community. It's a source of finding your
1:46:52
Speaker 2: passion and getting paid for it. We can't change that messaging.
1:46:56
Speaker 2: That messaging is there. We can't suddenly say, oh, by
1:46:59
Speaker 2: the way, the messaging for the last 50 years is wrong.
1:47:03
Speaker 1: No, we've learned that if you're interested in what you're doing,
1:47:06
Speaker 1: you're going to be better at your job and there's
1:47:07
Speaker 1: probably going to be more advancement for you. And maybe
1:47:11
Speaker 1: the world, you may advance the cause of what you're
1:47:14
Speaker 1: working in because you enjoy it.
1:47:16
Speaker 2: Because you enjoy it. And so I think we need to,
1:47:19
Speaker 2: that messaging needs to be much clearer. saying it's one,
1:47:24
Speaker 2: aligning your passion to the job, but also showing that
1:47:31
Speaker 2: the classical education, that the reason why you're learning literature,
1:47:35
Speaker 2: the reason why you're learning history, the reason why you're
1:47:38
Speaker 2: learning even some fundamental chemistry and math is so that
1:47:42
Speaker 2: you are enabled to figure out your job later on, 20, 30,
1:47:47
Speaker 2: 40 years. And I will tell you, you interact with
1:47:52
Speaker 2: most alumni, at spellman i i interact with quite a
1:47:56
Speaker 2: bit the job they have when they're 50 was not
1:47:59
Speaker 2: the job or the type of job they had when
1:48:01
Speaker 2: they graduated at 21 22 right and they have the
1:48:05
Speaker 2: confidence to change and switch like how do we do
1:48:08
Speaker 2: that but then also there are trade schools so if
1:48:11
Speaker 2: a student says you know what i really want to
1:48:13
Speaker 2: be a railroad engineer that's really what i want to
1:48:16
Speaker 2: do well there's not a lot of railroad engineering programs
1:48:21
Speaker 2: in four-year colleges right and so let's let's not just
1:48:26
Speaker 2: say well you can be any engineer just go to
1:48:28
Speaker 2: college and you'll be an engineer and you can figure
1:48:30
Speaker 2: it out it's like okay let's let's have a real
1:48:32
Speaker 2: conversation around Do you want to be on the railroads?
1:48:36
Speaker 2: Is this a tech skill, a tech trade? Or do
1:48:39
Speaker 2: you want to be an engineer that happens to work
1:48:41
Speaker 2: for a railroad company?
1:48:45
Speaker 1: What do you want to see in K through 12 reform?
1:48:49
Speaker 1: Or frankly, I call it pre-K through 12 reform. And
1:48:52
Speaker 1: I personally think we need to start looking at it
1:48:54
Speaker 1: in smaller chunks. Like pre-K through third grade is one
1:48:58
Speaker 1: thing that we need to focus on. And then I
1:49:00
Speaker 1: think once you get there, it becomes easier to figure out, okay,
1:49:04
Speaker 1: what is... What is the path going forward? How much
1:49:07
Speaker 1: is it a trade path? How much is it an
1:49:09
Speaker 1: intellectual path? How much is it a skills training path
1:49:13
Speaker 1: and different things? But, you know, I feel like we
1:49:17
Speaker 1: need to do a dramatic sort of rethinking of our
1:49:19
Speaker 1: public education system. I hate what's happened with vouchers in
1:49:23
Speaker 1: charter schools. I'm not going to bring you into a
1:49:25
Speaker 1: political argument on that, but I think the voters are
1:49:28
Speaker 1: speaking pretty loudly about how they feel about vouchers because
1:49:31
Speaker 1: wherever it's been put in, it's not popular. what makes
1:49:38
Speaker 1: a better student at Spelman? What's missing right now in
1:49:41
Speaker 1: public education that would give you the ability to, you know,
1:49:47
Speaker 1: do something a little bit different at Spelman if you
1:49:48
Speaker 1: chose to?
1:49:50
Speaker 2: Yeah, so I think what's missing, honestly, is this focus
1:49:54
Speaker 2: on impacting your community, impacting society. I will tell you,
1:50:00
Speaker 2: when our students start here at Spelman, I talk to them.
1:50:03
Speaker 2: They volunteered at the local Red Cross or the hospitals
1:50:07
Speaker 2: or they built up a fresh garden in their neighborhood.
1:50:11
Speaker 2: Like they all have a story about something they did
1:50:14
Speaker 2: outside of themselves that shows that they care about others.
1:50:28
Speaker 1: That's the student you're looking for though, isn't it? Don't
1:50:31
Speaker 1: you sort of like, if they're already doing that, you
1:50:33
Speaker 1: want them at Spelman, correct?
1:50:34
Speaker 2: We want them. And so why in public school, and again,
1:50:37
Speaker 2: we can talk about funding and it's still hard. Teachers
1:50:40
Speaker 2: are stretched, especially in certain communities in terms of teaching.
1:50:44
Speaker 2: And then you want me to be the faculty volunteer
1:50:48
Speaker 2: for these student projects. It becomes very difficult. But I
1:50:52
Speaker 2: truly believe that when you root your education around a
1:50:56
Speaker 2: cause and It actually shows students the reason for whatever
1:51:02
Speaker 2: you're learning. As an example, we have a program here called,
1:51:07
Speaker 2: believe it or not, Cosmetic Science, which is in chemistry. Like, oh, wait,
1:51:13
Speaker 2: hold it. Yes. Like a lot of women wear makeup
1:51:17
Speaker 2: as an example. You know, there's a science to that.
1:51:20
Speaker 2: There's a science to how it spreads. There's a science
1:51:22
Speaker 2: to if you have an allergic reaction. There's a science
1:51:25
Speaker 2: to how do you take two colors and you blend
1:51:28
Speaker 2: them together based on the molecules. It's actually chemistry at
1:51:32
Speaker 2: its root cause.
1:51:33
Speaker 1: Right.
1:51:34
Speaker 2: And so can we do that more in public education
1:51:37
Speaker 2: where you have a student, they're interested in music? All right,
1:51:40
Speaker 2: guess what? Music is actually math. Like if you think
1:51:44
Speaker 2: about the beats and all of this, can we infuse
1:51:47
Speaker 2: then math in music? So you're learning your music and
1:51:50
Speaker 2: you're learning your beats and you're learning how to put
1:51:52
Speaker 2: together an X. but we're teaching you the math behind it.
1:51:55
Speaker 2: So you're like, oh, I have to learn, wait, I
1:51:57
Speaker 2: have to learn fractions? Yeah. Oh, but then I can
1:52:00
Speaker 2: become a better beat master? All right, I'm there.
1:52:03
Speaker 1: Now I understand what, no, I mean, this is why
1:52:06
Speaker 1: it seems to me we've got to do this in
1:52:08
Speaker 1: bite-sized chunks that, you know, it isn't a high school
1:52:12
Speaker 1: problem we have. I actually think it's a pre-K problem.
1:52:15
Speaker 1: And then once you get to universal pre-K through third, well,
1:52:18
Speaker 1: then you're probably going to raise the baseline. And then
1:52:21
Speaker 1: you have a, better chance of designing a more individualized
1:52:26
Speaker 1: public education experience going forward. But if you're spending all
1:52:31
Speaker 1: your time playing catch up all the time, you don't
1:52:33
Speaker 1: get to do that.
1:52:34
Speaker 2: And that's what we're doing now. We're playing catch up.
1:52:38
Speaker 2: And so, and I would just say- I hear.
1:52:41
Speaker 1: About this at a lot of universities, that a lot
1:52:43
Speaker 1: of universities, the freshman year is about bringing kids up
1:52:46
Speaker 1: to speed to get them prepared for college. Really, your
1:52:49
Speaker 1: sophomore year is really, you know, your first year of college.
1:52:52
Speaker 1: Do you feel that way these days?
1:52:55
Speaker 2: I would say a little bit, but it's more around
1:52:59
Speaker 2: the learning skills, the study skills, the, you know, this
1:53:05
Speaker 2: is what an A looks like.
1:53:07
Speaker 1: Is it maturity, you think, or is it poorly or
1:53:10
Speaker 1: just poor schooling?
1:53:13
Speaker 2: I will tell you there's a difference between the students
1:53:16
Speaker 2: that learn through COVID and the students that didn't.
1:53:20
Speaker 1: Tell me about it.
1:53:21
Speaker 2: Well, so, you know, if I pull it back, the
1:53:26
Speaker 2: students who had not learned how to learn, the students who,
1:53:31
Speaker 2: the study skills and working in a group and a
1:53:34
Speaker 2: group project, if they didn't have those skills, which we
1:53:37
Speaker 2: do in college all the time, this is their first
1:53:41
Speaker 2: exposure to it because a lot of schools did not
1:53:44
Speaker 2: go back to that tradition because in middle school, they
1:53:49
Speaker 2: went into lockdown. So socialization in middle school is so important.
1:53:54
Speaker 2: So they didn't learn that. They were in high school.
1:53:56
Speaker 2: And so now you have high school teachers coming back
1:53:59
Speaker 2: in person and their students do not have the skills
1:54:02
Speaker 2: of This is what group projects looks like. Okay, so
1:54:05
Speaker 2: then you have to, you teach to the middle. That's
1:54:09
Speaker 2: usually what teachers do. And now your middle has shifted
1:54:12
Speaker 2: and is different. And so what we've seen is then
1:54:15
Speaker 2: they come to college and the way that they interact
1:54:18
Speaker 2: with the world, the way that they learn is different
1:54:22
Speaker 2: because the students had to learn differently in high school
1:54:27
Speaker 2: and middle school. And I do not know what's going
1:54:29
Speaker 2: to happen when the students that were at the elementary
1:54:33
Speaker 2: school level actually get to college.
1:54:36
Speaker 1: Interesting. Yeah. What that looks like. It is interesting to
1:54:40
Speaker 1: me that we're finally starting to see improvements in third
1:54:42
Speaker 1: and fourth grade reading levels. And well, that makes sense
1:54:47
Speaker 1: because guess what? They started school after COVID.
1:54:50
Speaker 2: Yes.
1:54:51
Speaker 1: If you're in third or fourth grade, right?
1:54:53
Speaker 2: But look at many years that is before they get
1:54:55
Speaker 2: to college. So we have this whole generation of students
1:54:59
Speaker 2: that we as educators.
1:55:01
Speaker 1: It's another decade of this that you're going to be
1:55:02
Speaker 1: dealing with it, right?
1:55:03
Speaker 2: Correct. Correct. And then education is going to shift again.
1:55:07
Speaker 2: That's what I'm saying. There's a cycle. I mentioned NASA.
1:55:10
Speaker 2: Like every 10 years, it changes. It's the same as
1:55:13
Speaker 2: with education. All right.
1:55:15
Speaker 1: I want to hit two more topics. One goes back
1:55:18
Speaker 1: to your book because... I just feel as if none
1:55:22
Speaker 1: of these AI companies have enough people thinking about equity
1:55:25
Speaker 1: in the room. And I don't care whether it's gender equity,
1:55:28
Speaker 1: racial equity, religious equity, you name it. They're plowing forward,
1:55:36
Speaker 1: making advancements. And I go back to the movie Contact,
1:55:42
Speaker 1: which is Matthew McConaughey, Jodie Foster, where they spent half
1:55:45
Speaker 1: of the movie debating whether an atheist meeting the extraterrestrial
1:55:51
Speaker 1: is a good idea, which I thought was like, you
1:55:53
Speaker 1: know what? That's a fair, I thought that was a
1:55:55
Speaker 1: very realistic response. I know our politics. I know the
1:55:59
Speaker 1: way religion, you know, I'm, I'm probably more on the
1:56:02
Speaker 1: science side of things, but I understand the importance of it.
1:56:06
Speaker 1: And yeah, that's just our civilization at this moment. That's
1:56:11
Speaker 1: a big part of our civilization. I don't feel like
1:56:15
Speaker 1: AI has grabbed all of this. What, How do we
1:56:19
Speaker 1: force the equity upon the development of this?
1:56:22
Speaker 2: Yeah, so I think and I do mention in the book,
1:56:25
Speaker 2: which is a blueprint for both the developers, but also
1:56:29
Speaker 2: everyone else that's not a developer of the power that
1:56:32
Speaker 2: you have thinking about this. So it's not just developers, right?
1:56:36
Speaker 2: It's we have a say in how it's developed and
1:56:39
Speaker 2: we have a say in how it's used. And we
1:56:42
Speaker 2: sort of, I would say as humans, we need to
1:56:45
Speaker 2: not be so trusting of these technologies and using it,
1:56:50
Speaker 2: even though in some cases it makes our life convenient.
1:56:54
Speaker 2: And that's the problem. I think that the convenience allows
1:56:57
Speaker 2: us to be forgiving of its use because we're not
1:57:02
Speaker 2: willing to feel uncomfortable not using it. It just is.
1:57:08
Speaker 2: I always think about maps. You and I probably grew
1:57:11
Speaker 2: up where you had the triptych when you wanted to
1:57:14
Speaker 2: do cross country.
1:57:15
Speaker 1: Yeah. Oh, no. And you got this little, yeah, that
1:57:18
Speaker 1: little spiral notebook.
1:57:19
Speaker 2: You have a spiral notebook and you figure out how
1:57:21
Speaker 2: to maps. And now I will tell you, most people
1:57:25
Speaker 2: would not know how to get across their own city,
1:57:28
Speaker 2: even if they've driven it every day, because we're using
1:57:31
Speaker 2: these maps. whatever ways or Google maps or whatever is
1:57:35
Speaker 2: out there. Like one example would be, you know, take
1:57:40
Speaker 2: off a map day and like actually try to figure
1:57:44
Speaker 2: out how to navigate from one place to another on
1:57:46
Speaker 2: your own, looking at landmarks. And so there's these practices
1:57:50
Speaker 2: that we can invoke. The other is, is we can
1:57:53
Speaker 2: also provide feedback when a large language model, whatever your,
1:57:58
Speaker 2: your choices gives you a wrong answer. There's ways to
1:58:02
Speaker 2: provide your correction. And if we have a movement of
1:58:04
Speaker 2: all of us pushing back, guess what? The developers and
1:58:08
Speaker 2: the companies are like, oh, there's a large number of
1:58:10
Speaker 2: people that said this answer is wrong.
1:58:14
Speaker 1: Do you think it's inevitable that we'll have specialty large
1:58:17
Speaker 1: language models, not necessarily like specialty in that you'll have
1:58:21
Speaker 1: a health large language model, but specialty in that This
1:58:25
Speaker 1: one has a Christian identity and this one has a
1:58:28
Speaker 1: Muslim identity and this one has a Jewish identity or
1:58:32
Speaker 1: this large language model has a indigenous identity, an African-American identity.
1:58:36
Speaker 1: What's your sense? Are we going to have a bunch
1:58:39
Speaker 1: of those models? I think of it almost like the
1:58:42
Speaker 1: way we had a black press and a Latino press
1:58:46
Speaker 1: in this country. Do we see that or am I
1:58:50
Speaker 1: thinking almost two Americans? Um, I want to say, I
1:58:54
Speaker 1: hope so.
1:58:55
Speaker 2: And why I say that is we always talk about
1:58:58
Speaker 2: bias being negative, but it's not always negative. I want
1:59:02
Speaker 2: a healthcare robot that's actually trained on female based data.
1:59:07
Speaker 1: Yeah. Right.
1:59:09
Speaker 2: I like, I just do.
1:59:11
Speaker 1: That's my preference. A lot of people have a preference
1:59:13
Speaker 1: for my wife and I go to a, a healthcare
1:59:17
Speaker 1: practice where there is a woman doctor and a male doctor,
1:59:21
Speaker 1: and one of us is more comfortable. I mean, that
1:59:23
Speaker 1: is just normal. Most women are more comfortable, the woman doctor,
1:59:26
Speaker 1: most men, vice versa. So your large language model, having
1:59:30
Speaker 1: a bias towards your gender health makes a lot of sense.
1:59:34
Speaker 2: And it, and what allows us to do though, is
1:59:37
Speaker 2: to make a choice, right? So I can choose what
1:59:41
Speaker 2: I want, the identity of my counselor. I may want
1:59:44
Speaker 2: a mental health counselor. I want to make sure that
1:59:47
Speaker 2: it understands my neighborhood. Give me that choice versus just
1:59:51
Speaker 2: give me a, here's the general model, take it or
1:59:53
Speaker 2: leave it. in terms of I'm very US centric, but
1:59:57
Speaker 2: there's a whole world outside of the US. So if
2:00:00
Speaker 2: I'm in Africa, I don't necessarily want to interact with
2:00:05
Speaker 2: someone who's definitely US centric, because it's just different culturally,
2:00:09
Speaker 2: language wise, what's yes, no, what's approved, what's disapproved in
2:00:14
Speaker 2: terms of behaviors. Let's create models that have that.
2:00:20
Speaker 1: That are sort of, I mean, that's where I feel
2:00:25
Speaker 1: You know, the worst thing is, you know, in the
2:00:28
Speaker 1: world of politics and exit polling, right? I remember one
2:00:31
Speaker 1: time somebody saying the worst thing than no exit polls
2:00:35
Speaker 1: is one exit poll, meaning that everybody's relying on the
2:00:38
Speaker 1: same thing. And you actually either want none or you
2:00:40
Speaker 1: want five so that you have competing results. theories. And
2:00:45
Speaker 1: I think we should feel that way about large language models.
2:00:47
Speaker 1: We don't want three. We don't want to be talking
2:00:50
Speaker 1: about chat versus Claude versus Gemini. We want 300, 3000,
2:00:54
Speaker 1: 3 million, right?
2:00:56
Speaker 2: We do. I think so. And it's because humans are diverse. Like,
2:01:03
Speaker 2: we are so different. You take, I identify as a
2:01:06
Speaker 2: Black woman. You put another Black woman, we are actually
2:01:10
Speaker 2: quite different. Depends on our social economics, our training. Are
2:01:14
Speaker 2: they an engineer?
2:01:15
Speaker 1: When were you born? All those things. Yeah.
2:01:17
Speaker 2: So don't label us the same and say, oh, here
2:01:21
Speaker 2: you are. And I think that's the beauty of human
2:01:24
Speaker 2: diversity is that we are so different across all of
2:01:28
Speaker 2: our parameters. We should expect nothing less of our AI agents,
2:01:32
Speaker 2: our robots that we interact with.
2:01:34
Speaker 1: All right. Before I ask my final question, it's a
2:01:37
Speaker 1: little bit of a rabbit hole. Do you watch For
2:01:43
Speaker 1: All Mankind, that alternative history series on Apple about the
2:01:48
Speaker 1: Russians beat the Americans to the moon?
2:01:50
Speaker 2: No, I have not.
2:01:52
Speaker 1: OK, well, I won't get into I won't ask that.
2:01:55
Speaker 1: But it was about sort of. So the basic premise
2:01:57
Speaker 1: of the show is we end up making more advancements
2:02:00
Speaker 1: in space because we lose the initial race to the moon.
2:02:04
Speaker 1: And because we lose, we're Americans. We throw even more money,
2:02:08
Speaker 1: more everything. And eventually we're basing the moon. We're in
2:02:11
Speaker 1: Mars by the 90s. It's it's. It basically the premise
2:02:15
Speaker 1: of the show is instead of having a nuclear arms
2:02:19
Speaker 1: race with the Soviets, we have a space race. The
2:02:22
Speaker 1: space race continues because we don't we don't win it
2:02:26
Speaker 1: right away. We lose it.
2:02:27
Speaker 2: We're like, OK, we got it. We got it. We're
2:02:29
Speaker 2: still in the race.
2:02:30
Speaker 1: And I say this because let me ask you, put
2:02:34
Speaker 1: your NASA hat back on. Why haven't we based the moon?
2:02:39
Speaker 1: And why aren't we in Mars yet? Because it feels
2:02:42
Speaker 1: like we were making all these advancements. And I know
2:02:45
Speaker 1: we had a, look, I would argue the economic downturn
2:02:48
Speaker 1: of the 70s pulled a lot of that funding back
2:02:52
Speaker 1: and we had challenges and suddenly politically investing in space
2:02:56
Speaker 1: wasn't good politics. It was actually bad. Why don't, no, no, no, no,
2:03:00
Speaker 1: don't take, we gotta have social security and healthcare before
2:03:02
Speaker 1: we worry about going to Mars. I feel like we've
2:03:08
Speaker 1: had the ability to do these things sooner. We just
2:03:11
Speaker 1: haven't had the will. Is that your experience at NASA,
2:03:15
Speaker 1: that we just haven't had the financial will to do that?
2:03:18
Speaker 1: If we wanted to get to Mars 30 years ago,
2:03:21
Speaker 1: we probably could have.
2:03:23
Speaker 2: We probably could have, but every decision that we make
2:03:27
Speaker 2: has a cost benefit analysis. And the fact is, is
2:03:31
Speaker 2: the reason we got to the moon was it was
2:03:34
Speaker 2: a challenge and it was an existential threat, right? If
2:03:38
Speaker 2: we did not get to the moon first, then the
2:03:42
Speaker 2: other power would be stronger than us and might annihilate.
2:03:44
Speaker 1: Us, right? So this was- It sounds like the AI spin,
2:03:47
Speaker 1: by the way.
2:03:48
Speaker 2: But that's true. And so- When we talked about all
2:03:53
Speaker 2: of these nations are putting funding into AI, that is
2:03:57
Speaker 2: the reason why. And the difference, though, is that back
2:04:01
Speaker 2: then we did have guardrails. I mean, we weren't going
2:04:05
Speaker 2: to do certain things like, you know, let's put a
2:04:08
Speaker 2: nuclear reactor on the moon. We might have had them
2:04:12
Speaker 2: on our rovers, but we weren't going to just stick
2:04:16
Speaker 2: a nuclear plant on the moon, right? So there was
2:04:17
Speaker 2: still some guardrails understanding of how did we think about
2:04:20
Speaker 2: this in a little bit of a safety mechanism, even
2:04:23
Speaker 2: though we were going as pretty fast, I would say.
2:04:26
Speaker 2: We just don't have that oomph because the threat is
2:04:32
Speaker 2: not just the one. It's it's, it's an imaginary threat.
2:04:37
Speaker 2: It's a feeling it's a, we want to be first,
2:04:40
Speaker 2: but it's not a solid, like this is absolutely a
2:04:44
Speaker 2: threat to humanity. Although there's this conversation of a threat
2:04:48
Speaker 2: to humanity, which basically means is AI versus humans, which
2:04:54
Speaker 2: caters toward a different way of developing versus, you know,
2:04:58
Speaker 2: the U S against, I don't know the water. Yeah.
2:05:06
Speaker 1: Well, let me ask this. Now that there's a private
2:05:12
Speaker 1: industry in space, somewhat of a private industry, and it
2:05:16
Speaker 1: feels more hybrid-ish-y, right? Quasi. Yeah, that you still need,
2:05:21
Speaker 1: you know, it's sort of like, why is... Again, I'm
2:05:25
Speaker 1: not putting this in your words. These are my words.
2:05:28
Speaker 1: Why is Elon Musk enamored with whoever's president? Because at
2:05:31
Speaker 1: the end of the day, SpaceX needs... a good relationship
2:05:34
Speaker 1: with government if it actually wants to do what it
2:05:35
Speaker 1: wants to do, right? And why does Jeff Bezos need
2:05:39
Speaker 1: a relationship with the president? Same thing, if he wants
2:05:42
Speaker 1: Blue Origin to have some aspects of it. What's gonna
2:05:47
Speaker 1: happen in the next 50 years when it comes to Mars,
2:05:49
Speaker 1: when it comes to, you know, is that, do you
2:05:52
Speaker 1: expect us to colonize Mars in the next 50 years?
2:05:55
Speaker 1: And given your experience at NASA, how the technology is
2:05:58
Speaker 1: there and we can do it?
2:06:00
Speaker 2: I would say, if we discover natural resources, that has
2:06:07
Speaker 2: to be a reason, or suddenly the earth becomes uninhabitable
2:06:12
Speaker 2: and we need to find another home. But it's one
2:06:15
Speaker 2: of the things, and I'm a scientist, I love asking
2:06:18
Speaker 2: questions just because I'm curious. We have no longer have
2:06:23
Speaker 2: that curiosity for curious sake. We kind of have to
2:06:28
Speaker 2: have a reason. I mean, even the discovery, rediscovery, even
2:06:32
Speaker 2: though it was already inhabited by people of the U.S.,
2:06:35
Speaker 2: the motivation was around resources. Right.
2:06:40
Speaker 1: Yeah, we were there looking, you know, people came from
2:06:42
Speaker 1: Europe and Asia looking for stuff. They weren't just going, oh,
2:06:45
Speaker 1: look at this. You know, this is nice.
2:06:47
Speaker 2: This is nice. I mean, Australia, you know, they needed
2:06:49
Speaker 2: the land because they needed to send their, you know,
2:06:52
Speaker 2: we need to send the people we don't want near
2:06:54
Speaker 2: us to Australia. It's how we're wired. So Mars has
2:07:00
Speaker 2: to have that kind of Either we find aliens. So
2:07:05
Speaker 2: now it's like, oh, we need to get there because
2:07:06
Speaker 2: they may destroy us. Or there's natural resources. We need these.
2:07:11
Speaker 2: We no longer have whatever it is, water and minerals
2:07:14
Speaker 2: or things that we need to build stuff, our chips, maybe,
2:07:17
Speaker 2: for example. Yeah.
2:07:19
Speaker 1: So you expect both the moon and Mars. It depends
2:07:23
Speaker 1: on what resources we do find. Depends on how much
2:07:26
Speaker 1: energy we put into colonizing them or basing them or
2:07:29
Speaker 1: whatever it is we want to call it.
2:07:31
Speaker 2: It has to have a return on investment. And the
2:07:33
Speaker 2: question is, what is the return?
2:07:35
Speaker 1: Is that stuff better found in the private sector or
2:07:39
Speaker 1: the public space, given your experience?
2:07:41
Speaker 2: So I actually think that's why it needs to be
2:07:44
Speaker 2: a partnership, because public, i.e. traditionally government, is designed to
2:07:51
Speaker 2: deal with the things that don't have a quote unquote
2:07:54
Speaker 2: financial return on investment.
2:07:56
Speaker 1: Right.
2:07:57
Speaker 2: But the private allows you to do it more effectively
2:08:00
Speaker 2: and efficiently. So you're not going to, you know, wasteful spending.
2:08:04
Speaker 2: A lot of times government is known for wasteful spending.
2:08:06
Speaker 2: That partnership allows you to support. This is for the
2:08:10
Speaker 2: public good. And then the private is, but we have
2:08:13
Speaker 2: to do it as cheap as possible.
2:08:17
Speaker 1: I guess the thing that I'm disappointed in is, and
2:08:21
Speaker 1: you know, you probably know this better than most, which
2:08:23
Speaker 1: is we don't know the discoveries that we'll end up
2:08:27
Speaker 1: making in order to get to someplace that might actually
2:08:30
Speaker 1: benefit us. You know, so what it took to get
2:08:33
Speaker 1: to the moon led to all sorts of important discoveries
2:08:37
Speaker 1: that helped society here that had nothing to do with
2:08:39
Speaker 1: us being on the moon, right? It does.
2:08:42
Speaker 2: I'm going to circle back to this is also why
2:08:45
Speaker 2: universities are still important. So if you think about all
2:08:52
Speaker 2: of the things that came out, not just in terms
2:08:54
Speaker 2: of exploring the moon, but with all of our healthcare discoveries,
2:08:59
Speaker 2: it was professors or group of professors working on something
2:09:03
Speaker 2: where they worked on it their entire life. The Nobel
2:09:06
Speaker 2: Prize in X worked on it their entire life. I mean,
2:09:10
Speaker 2: that's a long time to work on something and there
2:09:13
Speaker 2: is no financial benefit because you're curious and you know
2:09:16
Speaker 2: you can solve it in just one more decade, just
2:09:19
Speaker 2: one more decade. And then you have this breakthrough that
2:09:24
Speaker 2: really changes the world.
2:09:27
Speaker 1: Look, that's why the world is so loves our university
2:09:30
Speaker 1: system compared to everybody else, right? We've been better at
2:09:33
Speaker 1: incubating this stuff than most. And I'd hate to see
2:09:37
Speaker 1: us lose that edge.
2:09:38
Speaker 2: And we still need to fund. That's the thesis of that. Yes.
2:09:43
Speaker 1: Well, the book's Rebooting the Machines. I mean, boy, you
2:09:48
Speaker 1: have a foot in two interesting camps, the engineering side,
2:09:52
Speaker 1: the academia side, this sort of nexus of the two. Boy,
2:09:59
Speaker 1: your observations, I think, are ones that a lot of
2:10:02
Speaker 1: people should be interested in. Appreciate having you on. Thank you.
2:10:06
Speaker 2: Thank you. Ask Chuck.
2:10:17
Speaker 1: All right, let's do a little Ask Chuck. We will
2:10:19
Speaker 1: start with Michael T. from Chicago. And he goes, thanks
2:10:21
Speaker 1: for your commentary these last few weeks, especially when it's
2:10:23
Speaker 1: harder than ever to separate reality from rhetoric. You recently
2:10:26
Speaker 1: discussed a survey showing that 50% of stockholders aren't changing
2:10:30
Speaker 1: their spending habits, which may explain why Trump seems so
2:10:33
Speaker 1: disconnected from the economic struggles on Main Street. Could he
2:10:36
Speaker 1: genuinely be unaware of what everyday Americans are experiencing and
2:10:39
Speaker 1: therefore see election fraud as the only explanation for Republican loss?
2:10:43
Speaker 1: Or does he know better and simply choose to perpetuate
2:10:45
Speaker 1: that narrative? And how far do you think he'll push
2:10:47
Speaker 1: those claims if or when Republicans lose in a few weeks?
2:10:51
Speaker 1: So I genuinely believe he does not know how the
2:10:55
Speaker 1: average person is handling this. I really don't. I think
2:10:58
Speaker 1: he's very out of touch. I think it's possible J.D.
2:11:02
Speaker 1: Vance has some idea. I would like to think maybe
2:11:05
Speaker 1: he's put himself in a bubble. I'm not sure. But
2:11:08
Speaker 1: at least he was once connected to working class Americans.
2:11:12
Speaker 1: But no, this is not an administration. I think you
2:11:17
Speaker 1: have people that know how to read polls. But I
2:11:22
Speaker 1: think he genuinely thinks this affordability issue is overrated because
2:11:27
Speaker 1: all of his friends are fine. And so I think
2:11:31
Speaker 1: he doesn't fully appreciate the sense of urgency on this.
2:11:35
Speaker 1: As for where he goes with election fraud. Look, I
2:11:42
Speaker 1: think it's pretty obvious that he's going– we know he's
2:11:46
Speaker 1: not going to accept the blame. I think the number
2:11:51
Speaker 1: one person he's going to blame is John Thune. He's
2:11:54
Speaker 1: going to say, you didn't pass the SAVE Act, and
2:11:58
Speaker 1: it did two things. It allowed the Democrats to rig
2:12:02
Speaker 1: the election to win the Senate, but that's on you.
2:12:04
Speaker 1: That's not me. It'll be his way of doing that,
2:12:07
Speaker 1: and he'll be like– And he's already kind of hinted
2:12:10
Speaker 1: at this. Well, we know the public doesn't like Republicans,
2:12:13
Speaker 1: but they like me. So he'll try that spin as well. Look,
2:12:21
Speaker 1: do I think he's I I don't think he's I
2:12:27
Speaker 1: he doesn't care about what happens to the Republican Party.
2:12:31
Speaker 1: So the reason why I'm not concerned he's going to
2:12:33
Speaker 1: try to do anything, because ultimately, as long as he's
2:12:36
Speaker 1: still president, what does he care? Um, so I don't
2:12:42
Speaker 1: think he's going to go to the lengths he went
2:12:45
Speaker 1: to in 2020 and 2021, because that was, that was,
2:12:50
Speaker 1: that he was, he was the one that was going to, that,
2:12:54
Speaker 1: that lost the election. So I, I think he's going
2:12:57
Speaker 1: to say these things, but I think he's going to,
2:12:59
Speaker 1: I think instead he's going to use it to try
2:13:04
Speaker 1: to blame others. And I do think that, Thune is
2:13:10
Speaker 1: the one that'll be in the, it'll be Thune in
2:13:13
Speaker 1: the SAVE Act. That's how, it's his way of manufacturing
2:13:17
Speaker 1: the voter fraud idea, concept that you brought up, but
2:13:22
Speaker 1: also attacking another wing of the party. Now I go
2:13:26
Speaker 1: back to what the reality is. The reality is the
2:13:29
Speaker 1: weakest Republican Senate candidates are the ones where he got
2:13:33
Speaker 1: involved in the primaries. The Senate candidates who have the
2:13:36
Speaker 1: best chance of surviving are the ones that John Thune
2:13:40
Speaker 1: basically forced upon Trump and told him to stay out
2:13:43
Speaker 1: of those primaries, Susan Collins, Mike Rogers in particular. So
2:13:48
Speaker 1: we'll see. But I just think that because it's not
2:13:52
Speaker 1: about him, he'll only care enough to use it as
2:13:58
Speaker 1: a way to try to use it as a wedge
2:14:03
Speaker 1: in his own party, maybe find a way to blame
2:14:05
Speaker 1: somebody else for all of this. But I don't think
2:14:09
Speaker 1: he's going to move now. He may ignore Congress. He
2:14:11
Speaker 1: may do all sorts of things. But he ignores Congress now,
2:14:13
Speaker 1: and it's been controlled by Republicans. So why should we
2:14:15
Speaker 1: expect him to change that behavior? All right. Next question
2:14:21
Speaker 1: comes from Major Matthew Kindig. And he goes, hey, I
2:14:25
Speaker 1: really enjoy your political insight. I'm active duty military stationed
2:14:28
Speaker 1: at Rock Island Arsenal. So I've been seeing plenty of
2:14:31
Speaker 1: Iowa political ads. During the Obama administration, Republicans flipped more
2:14:35
Speaker 1: than 900 state legislative seats in 29 chambers. Could a
2:14:38
Speaker 1: potential blue wave this November produce similar gains for Democrats
2:14:41
Speaker 1: at the state level? And which state legislatures do you
2:14:43
Speaker 1: think are most vulnerable to flipping? Thank you again for
2:14:46
Speaker 1: taking my question. Well, let me just run through what's
2:14:50
Speaker 1: sort of on edge. One thing the Democrats have done
2:14:54
Speaker 1: is that they've learned a hard lesson from the Obama years.
2:14:58
Speaker 1: And there's a lot more effort that's put into legislative races,
2:15:01
Speaker 1: a lot more money that's being spent. And you see
2:15:04
Speaker 1: that the margins are much tighter. So You know, for instance,
2:15:07
Speaker 1: Democrats need to pick up just four seats to control
2:15:12
Speaker 1: the Michigan Statehouse. Well, the governor, if the governor candidate
2:15:16
Speaker 1: can win by four or five points, that's possible. They
2:15:20
Speaker 1: had a trifecta at times when Gretchen Whitmer was there.
2:15:23
Speaker 1: So that's a big one. And most of the action
2:15:26
Speaker 1: is in, for what it's worth, is in the following states.
2:15:29
Speaker 1: It's all the battleground states. Michigan, Minnesota, Arizona, Wisconsin, and Pennsylvania.
2:15:35
Speaker 1: Those are the big ones. The Michigan Senate, it's decontrolled,
2:15:39
Speaker 1: but there's one vacancy, right? It can go either way.
2:15:42
Speaker 1: The Minnesota State House is tied. So that's why the
2:15:46
Speaker 1: Amy Klobuchar candidacy was so important to Democrats in Minnesota.
2:15:50
Speaker 1: The Minnesota State Senate is Democrats have a one seat majority. Arizona,
2:15:56
Speaker 1: Democrats have been making a lot of progress in Arizona.
2:15:59
Speaker 1: They only need three seats to control the Senate and
2:16:02
Speaker 1: they only need four in the House. Now, It's a
2:16:05
Speaker 1: very gerrymandered situation in Arizona, so we'll see. But that's
2:16:10
Speaker 1: another one that's up for grabs. Wisconsin Senate, our control.
2:16:15
Speaker 1: Democrats need two seats to pick that one. It's possible.
2:16:19
Speaker 1: The state assembly, it's a 100-seat legislature. They need five pickups. again, possible. Um,
2:16:28
Speaker 1: so we'll see. I mean, it's, it's, like I said,
2:16:31
Speaker 1: the big targets are the battle presidential battleground States plus
2:16:35
Speaker 1: Minnesota because Minnesota has been so tight. Um, but they've
2:16:39
Speaker 1: been tight for a while. The bottom line is, is that, um,
2:16:44
Speaker 1: you know, I'll be impressed if they do something like
2:16:48
Speaker 1: get a chamber in Georgia, right. You know, Democrats are
2:16:53
Speaker 1: more competitive in actual majorities in some of those Midwestern
2:16:57
Speaker 1: battleground states. Even as they've made progress in carrying, you know, Arizona,
2:17:03
Speaker 1: carrying Georgia, they've not been able to flip those legislatures
2:17:07
Speaker 1: just yet. So that for me, you know, I'll know
2:17:14
Speaker 1: something big happens if they are able to like flip
2:17:16
Speaker 1: control of a legislature in Georgia or suddenly make one
2:17:22
Speaker 1: of the two chambers more competitive than we've seen in
2:17:24
Speaker 1: a while in, say, Florida. But for the most part,
2:17:28
Speaker 1: most of the dollars are being spent by both parties
2:17:34
Speaker 1: in those presidential battleground-y states, right? Michigan, Minnesota, Arizona, Wisconsin,
2:17:41
Speaker 1: and Pennsylvania. They're getting the lion's share. New Hampshire's getting
2:17:44
Speaker 1: some attention, uh and you know plenty of other legislative
2:17:49
Speaker 1: chambers are getting some action but that for to answer
2:17:52
Speaker 1: the question you were asking directly really is there i
2:17:56
Speaker 1: mean i'm very curious to see if you know you're
2:17:59
Speaker 1: in iowa so you're seeing all the iowa ads i'm
2:18:01
Speaker 1: curious to see if if rob sands big victory for
2:18:04
Speaker 1: governor in iowa translates into him having any coattails And
2:18:08
Speaker 1: does he make the margins in the Iowa legislature tighter
2:18:11
Speaker 1: and more narrow? Dustin, Pennsylvania 11, writes, he goes, hey,
2:18:15
Speaker 1: your interview with Marcia Chatelain reminded me of a conversation
2:18:18
Speaker 1: with my T.O. in Baja, California, where I realized how
2:18:24
Speaker 1: much news coverage had shaped my own fears about Mexico,
2:18:27
Speaker 1: while he assumed everyone in the U.S. uses drugs based
2:18:30
Speaker 1: on what he sees on the news. It's amazing how
2:18:33
Speaker 1: easily media narratives can reinforce biases when we don't dig deeper.
2:18:37
Speaker 1: whether about Mexico, Somali immigrants, or other communities? How could
2:18:40
Speaker 1: journalists report the facts fairly while avoiding the stereotypes and
2:18:44
Speaker 1: distorted perceptions that so often come from news coverage? Go Canes,
2:18:48
Speaker 1: and which game will Mario screw up with his clock
2:18:50
Speaker 1: management this year? I think we can run the schedule
2:18:53
Speaker 1: and see where the chips fall in January. Oh, I'm just... Look,
2:18:59
Speaker 1: I think Mario already had that game. He let Wake
2:19:01
Speaker 1: Forest back into the game. I really believe that. Wake
2:19:05
Speaker 1: Forest just wouldn't Refused to come into the game. So
2:19:08
Speaker 1: I choose to believe the Mario mishap was avoided because
2:19:14
Speaker 1: Wake Forest missed their opportunity to take advantage of Mario's
2:19:18
Speaker 1: bad play calling. He doesn't call a play. Shannon Dawson does.
2:19:21
Speaker 1: But sort of one of those clock games. I'm going
2:19:29
Speaker 1: to repeat something that Mario said the other day, which
2:19:32
Speaker 1: is this team likes winning. They have an edge to them.
2:19:37
Speaker 1: at least they better have an edge to them. But
2:19:41
Speaker 1: I am hopeful that maybe we can avoid that this time.
2:19:44
Speaker 1: Do we have to do it this way? I think that,
2:19:48
Speaker 1: I really hope we don't. But your more important question.
2:19:54
Speaker 1: This is why you want diversity in a newsroom, right?
2:19:58
Speaker 1: Which is, and the diversity has to be all kinds
2:20:01
Speaker 1: of diversity, socioeconomic diversity, geographic diversity. Ethnic diversity. Religious diversity.
2:20:10
Speaker 1: And I teach this to my students in my class
2:20:12
Speaker 1: about media and political polarization. We all stereotype. All of
2:20:20
Speaker 1: us stereotype. It is human nature. It is how the
2:20:26
Speaker 1: human brain organizes itself. So stereotypes are not something you're
2:20:33
Speaker 1: ever going to get rid of. what you do with stereotypes,
2:20:37
Speaker 1: it's just like bias, right? We're all born with original bias.
2:20:40
Speaker 1: You can't, there's no such thing as neutrality. And there's
2:20:44
Speaker 1: no such thing as eradicating a stereotype. What there is,
2:20:49
Speaker 1: is context. What there is, is counterfactual information. And, you know,
2:20:57
Speaker 1: being a bit self-aware. I'd like to think the older
2:21:01
Speaker 1: I get, the more often I put my try to
2:21:03
Speaker 1: put myself in the shoes of somebody else, even when
2:21:06
Speaker 1: I think they're behaving crazy. Well, let me do my
2:21:11
Speaker 1: best to put my shoes over here, put myself in
2:21:14
Speaker 1: their shoes. Now, I think you do your best. So
2:21:19
Speaker 1: that's why a newsroom having, it's why you don't want
2:21:22
Speaker 1: one person always writing a story. You want a second
2:21:24
Speaker 1: set of eyes, a third set of eyes, a fourth
2:21:26
Speaker 1: set of eyes, but it can't be people that came
2:21:30
Speaker 1: from the same background, right? So I could tell you
2:21:36
Speaker 1: when I thought about diversity in the newsroom, the first
2:21:39
Speaker 1: thing I thought about was socioeconomic and geographic. Those things matter.
2:21:44
Speaker 1: Gender matters, ethnicity, religious beliefs, all of those, all those
2:21:47
Speaker 1: diversity things matter. And a great newsroom has everybody at
2:21:54
Speaker 1: the table, just like a great democracy and pluralism assumes
2:21:58
Speaker 1: everybody's at the table. So I know it sounds a
2:22:02
Speaker 1: little preachy, my answer to you on this, but you,
2:22:06
Speaker 1: I loved how you heard the interview and you immediately
2:22:10
Speaker 1: went to your own example. I have my, my own,
2:22:13
Speaker 1: I remember my grandfather's, you know, when I, it was,
2:22:18
Speaker 1: my grandfather's wife was like, why do you, I can't
2:22:21
Speaker 1: believe you're going to college in Washington, DC. This is
2:22:23
Speaker 1: a 1990. And if you remember the stereotype of Washington, DC,
2:22:27
Speaker 1: the eighties and nineties, you know, I'm in Miami, Florida,
2:22:31
Speaker 1: mind you in 1990. before I start school in the
2:22:35
Speaker 1: fall of 90 at GW. And my grandfather's wife goes,
2:22:39
Speaker 1: oh my God, it's so dangerous in Washington. And I
2:22:44
Speaker 1: remember saying to her, well, Aunt Ella, I lived in
2:22:51
Speaker 1: Miami when it was the nation's murder capital. I think
2:22:54
Speaker 1: at the time DC was considered the nation's murder capital.
2:22:58
Speaker 1: And I'm like, Miami had that title a couple of
2:23:01
Speaker 1: years ago and we were all fine. What you don't experience,
2:23:08
Speaker 1: what you don't physically see for yourself, you allow a
2:23:12
Speaker 1: stereotype to intervene. Our brains do it. They just do it.
2:23:16
Speaker 1: You have to fight it. You have to be aware
2:23:18
Speaker 1: about it. And the best journalists are self-aware about it.
2:23:21
Speaker 1: But the best way to deal with it is an
2:23:24
Speaker 1: incredibly diverse newsroom where diversity is socioeconomic, geographic, and ethnic.
2:23:34
Speaker 1: and gender. All right. What do we got here? Joe B.,
2:23:43
Speaker 1: North Carolina, 11th District, Asheville, North Carolina, go pack, go.
2:23:46
Speaker 1: All right. With Democratic Governor Josh Stein announcing a gas
2:23:50
Speaker 1: tax holiday in North Carolina shortly after the RNC pulled
2:23:53
Speaker 1: funding for Whatley, could the timing have unintended down-ballot consequences?
2:23:57
Speaker 1: Could lower gas prices lead less engaged voters in Republican
2:24:00
Speaker 1: strongholds like North Carolina's 11th district, to believe the economy
2:24:03
Speaker 1: is improving and potentially vote GOP? Thanks for helping us
2:24:06
Speaker 1: make sense of these interesting times. Regards, Joe B. Well,
2:24:10
Speaker 1: first of all, I just don't think, I mean, I
2:24:12
Speaker 1: think the lived experience where, you know, I'm answering your
2:24:15
Speaker 1: question on October 14th. You probably wrote it in maybe
2:24:19
Speaker 1: first week of October. You know, you're not, remember what
2:24:24
Speaker 1: these gas tech holidays, we're talking, the state level, what
2:24:28
Speaker 1: is it? 10 cents, right? So maybe you're saving a
2:24:32
Speaker 1: dollar 50 total for each fellow. Um, but you know,
2:24:38
Speaker 1: here's what tragically has happened because quite a few states
2:24:41
Speaker 1: have done this. Georgia did it. I think Pennsylvania has
2:24:44
Speaker 1: done it. I think New Hampshire has done it. I mean,
2:24:45
Speaker 1: quite a few states are, you know, you do what
2:24:47
Speaker 1: you can, right. Uh, on this, uh, and part of
2:24:51
Speaker 1: it is, you know, it's good politics by Stein, you know,
2:24:54
Speaker 1: to do this. Um, But the war ain't ending and
2:25:01
Speaker 1: the price still goes up anyway. I mean, in some places,
2:25:04
Speaker 1: imagine if you didn't do it. Now, I kind of
2:25:06
Speaker 1: think these gas tax holidays, they end up costing us
2:25:09
Speaker 1: more money. And they don't do, but there's a perception
2:25:15
Speaker 1: of at least, hey, I'm paying attention and I care.
2:25:18
Speaker 1: So there are good politics, even if they don't really
2:25:21
Speaker 1: have that impact. And I guess I'm not convinced people
2:25:25
Speaker 1: are really going to notice. All right, last question for
2:25:30
Speaker 1: the episode. Joanna Napa Valley writes in, hey, with all
2:25:36
Speaker 1: the controversy surrounding Pete Heggs' pledge to live stream and execution,
2:25:39
Speaker 1: one thing I haven't heard discussed is what platform would
2:25:42
Speaker 1: actually allow it? I can't imagine Facebook, Instagram, TikTok, or
2:25:45
Speaker 1: YouTube permitting something like that. So is this just a
2:25:48
Speaker 1: bunch of hot air if there's nowhere to stream it?
2:25:50
Speaker 1: Love the pod, even if my kiddos cringe every morning
2:25:53
Speaker 1: when I turn it on during our drive to school.
2:25:55
Speaker 1: I guess it's payback for all those years. My dad
2:25:57
Speaker 1: made me listen to talk radio on the way to school. Thanks, Chuck. Well, Joanna,
2:26:03
Speaker 1: and to your kids, I'm sorry. I'm happy to... We
2:26:09
Speaker 1: can include a topic your kids like if you want,
2:26:11
Speaker 1: so I can time it for you, Joanna. So let
2:26:14
Speaker 1: me know what their interests are on that. Well, it's
2:26:20
Speaker 1: funny you bring that up because you're right. None of these–
2:26:23
Speaker 1: I don't think it's legal for any of these folks
2:26:26
Speaker 1: to do this. But if the government is doing it,
2:26:31
Speaker 1: then it becomes coverage, I guess. If the government is
2:26:37
Speaker 1: permitting it, then I guess that supersedes it. But I
2:26:46
Speaker 1: can tell you this. I assume none of them would
2:26:48
Speaker 1: carry it. but truth social, I guess would. And for
2:26:53
Speaker 1: all we know, they'll turn it into some way to
2:26:57
Speaker 1: force more people to download the truth social app.
2:26:59
Speaker 2: Right.
2:27:01
Speaker 1: Uh, but actually for what it's worth, I think the
2:27:03
Speaker 1: backlash on this is pretty harsh. Uh, and it's coming
2:27:08
Speaker 1: from inside the house. Um, so I have a feeling
2:27:11
Speaker 1: Trump's going to, uh, go to put the kibosh on
2:27:14
Speaker 1: this and this doesn't happen. Um, but he does seem
2:27:18
Speaker 1: to have a hard time saying no to paid exit.
2:27:19
Speaker 1: But no, you're right. I mean, there's nobody, none of
2:27:23
Speaker 1: these platforms would feel legally comfortable doing this. But if
2:27:28
Speaker 1: the military is doing it and, you know, in fact,
2:27:34
Speaker 1: the president might have to sign an executive order as
2:27:36
Speaker 1: sort of in order to indemnify this. I don't, you know,
2:27:41
Speaker 1: I mean, what, so let's say it's live stream, not
2:27:47
Speaker 1: only on true social, and then people decide to film
2:27:50
Speaker 1: it from, you know, sort of film the platform itself
2:27:57
Speaker 1: airing it, and then it gets put on another platform. Um, I'm,
2:28:03
Speaker 1: you know, just Google and Facebook and all that. They
2:28:07
Speaker 1: just automatically take it down. I mean, I guess I
2:28:10
Speaker 1: personally hope so. But, you know, it's always tough to censor.
2:28:16
Speaker 1: I mean, you know, look at how they tried to
2:28:19
Speaker 1: get rid of the anarchist cookbook for decades. And it
2:28:22
Speaker 1: never seems to go away. so I'm always a little
2:28:26
Speaker 1: skeptical that these censorship things work as well as we
2:28:29
Speaker 1: think that they work. But I agree with you that
2:28:32
Speaker 1: none of these platforms would feel legally comfortable doing it.
2:28:37
Speaker 1: And they might, in order to air it, they might
2:28:40
Speaker 1: almost demand some sort of government shield, if you would.
2:28:48
Speaker 1: But I think the wind has shifted on this one.
2:28:52
Speaker 1: I think Hank Seth is on is on his own.
2:28:55
Speaker 1: I think he's on an island on this one. And
2:28:58
Speaker 1: assuming the midterms go as poorly for Trump as we think,
2:29:01
Speaker 1: he's not going to throw, you know, he's not going
2:29:04
Speaker 1: to light this fire. I just don't believe it.
2:29:16
Speaker 2: All right.
2:29:17
Speaker 1: Great questions. Now let's do my little preview, college football preview.
2:29:22
Speaker 1: You know, I'm sort of ashamed. It's Miami-Florida State week,
2:29:26
Speaker 1: and the national college football world is not covering the
2:29:29
Speaker 1: game at all, right? Both teams aren't ranked, right? Miami's ranked,
2:29:34
Speaker 1: but Florida State isn't, so that's a harm. Indiana-Ohio State
2:29:38
Speaker 1: is the big game of the weekend, and that's getting
2:29:41
Speaker 1: a lion's share of the attention. But you also have,
2:29:43
Speaker 1: I think, Florida and Texas, right? That's a pretty interesting
2:29:46
Speaker 1: matchup as well. It's a great weekend of college football,
2:29:50
Speaker 1: and I'm nervous as you know what. This is a
2:29:53
Speaker 1: rivalry game. You know, Florida State, they're not always good
2:30:00
Speaker 1: at the same time, but when they are, it's fantastic.
2:30:03
Speaker 1: But in years when one is really good and the
2:30:05
Speaker 1: other one isn't, the games are still always close and
2:30:07
Speaker 1: nail biters. They all went to high school with each other.
2:30:10
Speaker 1: They all know each other. There's this weird, and you know,
2:30:15
Speaker 1: last year, Miami was rolling and then all of a
2:30:17
Speaker 1: sudden in the fourth quarter, they just sort of took
2:30:19
Speaker 1: their foot off the gas and Florida State made a
2:30:21
Speaker 1: furious comeback and Suddenly they were an onside kick away
2:30:25
Speaker 1: from having the ball with a chance to win the game.
2:30:29
Speaker 1: So I'm very nervous. You know, it's funny. There's multiple
2:30:34
Speaker 1: ways this could go, right? Mike Norvell, poor Mike Norvell's
2:30:37
Speaker 1: been coaching for his job every week. I don't think
2:30:41
Speaker 1: a win saves his job. But if somehow Miami won
2:30:45
Speaker 1: by four or five scores, like every once in a while,
2:30:50
Speaker 1: both teams have put a, you know what, a whooping
2:30:52
Speaker 1: on the other. a big Miami win, and Norvell may
2:31:00
Speaker 1: not make it back to Tallahassee. But I just, I
2:31:05
Speaker 1: don't end, I'm assuming a typical Miami-Florida State game. I
2:31:11
Speaker 1: know there is some talent disparity, but it's mostly on
2:31:15
Speaker 1: the skill positions. I think where there's usually a lot
2:31:19
Speaker 1: where things level out, you know, when both Miami and
2:31:22
Speaker 1: When one of them is down, where they're less down
2:31:26
Speaker 1: is usually on the D-line and O-line. So I'm expecting
2:31:32
Speaker 1: that Florida State can't keep up with Miami score-wise and
2:31:35
Speaker 1: that Miami can build the lead quickly and do something
2:31:38
Speaker 1: with it. I think Florida State's a bit too one-dimensional
2:31:41
Speaker 1: to take advantage of things that you can take advantage
2:31:44
Speaker 1: of with Miami. I think you can pass the ball
2:31:47
Speaker 1: on Miami, as Wake Forest proved.
2:31:50
Speaker 2: But.
2:31:52
Speaker 1: you got to have the quarterback to do it. And
2:31:54
Speaker 1: I'm not sure he's the best passer in the world.
2:31:57
Speaker 1: He's proven to be a very good running quarterback, but
2:32:00
Speaker 1: I actually have some confidence that this defense can do
2:32:04
Speaker 1: a pretty good job containing him. So I, you know,
2:32:12
Speaker 1: I know I got that question about, you know, when is,
2:32:15
Speaker 1: I don't, the game you worry about, is the game
2:32:20
Speaker 1: is always one where there's a letdown possibility. Miami had
2:32:23
Speaker 1: a buy, they were preparing for it. So, you know,
2:32:27
Speaker 1: this is a coaching staff failure. Miami's not prepared and,
2:32:31
Speaker 1: and doesn't win this game substantially. I think the spread's
2:32:34
Speaker 1: a little high. It's over 21 points. This feels like
2:32:38
Speaker 1: in the 14 to 17 point range. Um, and yes,
2:32:42
Speaker 1: maybe I'm saying that defensively a little bit, but, um,
2:32:51
Speaker 1: I just can't imagine this being a total blowout. But
2:32:55
Speaker 1: if it is, then it very well might be Mike
2:32:57
Speaker 1: Norvell's last game. And I know we keep saying that
2:33:00
Speaker 1: pretty much every week. I know that Mrs. Todd, who
2:33:04
Speaker 1: many of you know, is a big Florida State alum,
2:33:06
Speaker 1: big fan, all of those things. I think she just
2:33:09
Speaker 1: wants this, the paralysis, you know, just, you know, Willie
2:33:14
Speaker 1: or won't he just, Pull the plug already, you know, right?
2:33:19
Speaker 1: Rip the bandaid off, whatever metaphor you want to use.
2:33:23
Speaker 1: But I think that there's an exhaustion from wondering, well,
2:33:27
Speaker 1: is this the week? Is it not the week? Et cetera,
2:33:29
Speaker 1: et cetera. But look, the big game, there's quite a few, right?
2:33:33
Speaker 1: Ohio State, Indiana. Indiana hosts this one. I don't know
2:33:38
Speaker 1: about you. I have a lot of questions about Indiana's offense.
2:33:41
Speaker 1: I have fewer about their defense. We'll see. I expect
2:33:45
Speaker 1: this to be a rock fight. Um, but I question
2:33:50
Speaker 1: whether Indiana can keep up offensively with Ohio state. So
2:33:54
Speaker 1: to me, Indiana wins this game is if they can
2:33:57
Speaker 1: basically shut saying down. Um, and I'm not sure that
2:34:02
Speaker 1: they can, I don't know if you can totally shut
2:34:05
Speaker 1: them down. Texas did until they didn't or didn't until
2:34:08
Speaker 1: they did. Um, but, um, it's, uh, Here's a question
2:34:20
Speaker 1: for you. If Ohio State loses, it's their second loss.
2:34:25
Speaker 1: And the Texas loss is not aging as well as
2:34:28
Speaker 1: it should. If Ohio State loses, what happens if they
2:34:35
Speaker 1: somehow stumble one more time? Does a 9-3 Ohio State
2:34:43
Speaker 1: team make the playoff? If the three losses are Indiana,
2:34:49
Speaker 1: Texas and say USC because it's at USC. But they
2:34:58
Speaker 1: beat Oregon, beat Michigan, beat Nebraska, and beat Northwestern. We
2:35:06
Speaker 1: know a 9-3 team in the SEC would probably make it.
2:35:10
Speaker 1: But I'm just going to put it this way. I
2:35:13
Speaker 1: don't know if a 9-3 Indiana team with that same
2:35:17
Speaker 1: set of three losses would make it. But I wonder
2:35:20
Speaker 1: if a 9-3 Ohio State team. Anyway, just something to
2:35:23
Speaker 1: think about as you watch that game. Florida, Texas. Boy,
2:35:28
Speaker 1: this feels like a– man, all the vibes in Texas
2:35:32
Speaker 1: are so negative for poor old Arch. I've expressed my views.
2:35:37
Speaker 1: I just think he's in a no-win situation. I still
2:35:42
Speaker 1: think this is a Sark problem more than it's an
2:35:44
Speaker 1: Arch problem. I don't think he's figured out how to
2:35:48
Speaker 1: get the best out of Arch. And that, you know, I,
2:35:51
Speaker 1: these are, these are still young kids. I think this
2:35:56
Speaker 1: is on, I always believe coaching matters a lot more
2:35:59
Speaker 1: in college than anywhere else. Like matters even more in
2:36:02
Speaker 1: high school, but you know, I, I put this on,
2:36:05
Speaker 1: on more on Sark than I do on Arch. But
2:36:09
Speaker 1: needless to say, pretty big game. And I don't, I
2:36:12
Speaker 1: don't think a three loss Texas team, the way they've
2:36:15
Speaker 1: been playing, I don't think a three loss Texas team
2:36:18
Speaker 1: gets to the, gets to the playoff. So I think
2:36:21
Speaker 1: this is kind of a big game for them. And obviously,
2:36:23
Speaker 1: if Florida wants to get back into the conversation, they
2:36:25
Speaker 1: need this after losing two in a row. But I
2:36:29
Speaker 1: have to say, I have no good vibe on this
2:36:32
Speaker 1: game at all. I think Texas will be up for
2:36:36
Speaker 1: this because Florida, frankly, ruined their, you know, it was
2:36:39
Speaker 1: the losing to a 4-8 team that, you know, made
2:36:43
Speaker 1: his argument that 9-3 Texas should have gotten over. He
2:36:46
Speaker 1: thought 9-3 Texas should get in over 10-2 Miami. last
2:36:49
Speaker 1: year Sark did. So, um, I think it's a, certainly a,
2:36:54
Speaker 1: it may be a playoff elimination game on that one,
2:36:57
Speaker 1: Mississippi state LSU. The every game is a elimination game
2:37:01
Speaker 1: for LSU. They have two losses. Now they're, I think
2:37:05
Speaker 1: they're decent losses. If you want to say they're good losses,
2:37:09
Speaker 1: I think they're explainable losses, but they can't lose anymore. And, uh,
2:37:16
Speaker 1: They got Mississippi State and they're hosting them. I have
2:37:18
Speaker 1: a feeling Mississippi State stays as a ranked team. Maybe,
2:37:23
Speaker 1: you know, the more film people have on Super Camario,
2:37:27
Speaker 1: perhaps the easier it'll be to transform. to stop them. Again, though,
2:37:33
Speaker 1: every game now for LSU is an elimination game now
2:37:36
Speaker 1: that they have two losses. I'll be paying a little
2:37:41
Speaker 1: attention to Kansas, Kansas State. I love interstate rivalries. It's
2:37:46
Speaker 1: one of my favorite parts of college football. We've got Miami,
2:37:48
Speaker 1: Florida State's a good one. I love You know, in Florida,
2:37:50
Speaker 1: Florida State, Kansas, Kansas State. I just I love those
2:37:53
Speaker 1: things because they never go the way they're supposed to go. Right.
2:37:55
Speaker 1: That's why you love them. You know, teams get fired
2:37:57
Speaker 1: up for various reasons. Fan bases love them. One game
2:38:02
Speaker 1: I'm curious about, though, for for for sort of for
2:38:06
Speaker 1: potential for upset potential. And that is Auburn, Georgia. Georgia
2:38:16
Speaker 1: just came off a huge win. And it took a
2:38:19
Speaker 1: lot out of them. It was a four-quarter game against
2:38:21
Speaker 1: Alabama in some crummy weather. Now they come home. They
2:38:26
Speaker 1: got an Auburn team. Nobody's paying a lot of attention.
2:38:29
Speaker 1: They're three touchdown favorites. Look, Auburn's got some athletes. They've
2:38:34
Speaker 1: got a quarterback that can, you know, I know this,
2:38:36
Speaker 1: you know, at some point, every team has a game
2:38:42
Speaker 1: where they, eh, they got off. They got out of
2:38:45
Speaker 1: the wrong side of the bed. They don't have Maybe
2:38:48
Speaker 1: they're not feeling so well. Anyway, this has a whiff
2:38:52
Speaker 1: of a trap game for Georgia here. So that's certainly
2:38:57
Speaker 1: one that will be in my four box. Because the
2:39:02
Speaker 1: Miami game's at night. So we're able to– I'm going
2:39:05
Speaker 1: to the Miami-Florida State game. I'll see you down there
2:39:07
Speaker 1: in Miami for those of you going. And Auburn-Georgia's at 3.30,
2:39:13
Speaker 1: so that'll be good. Alabama-Tennessee. Um, probably a game that
2:39:18
Speaker 1: matters more for Tennessee than Alabama, Tennessee hosts, uh, pretender
2:39:23
Speaker 1: or contender. Well, it's tough when you don't really have a,
2:39:26
Speaker 1: when you don't feel confident in your quarterback position. Um,
2:39:32
Speaker 1: and we all want to see how Alabama does, you know,
2:39:34
Speaker 1: that's a hangover effect, right? Do you let your, do
2:39:37
Speaker 1: you let Georgia beat you twice? Um, but I do
2:39:40
Speaker 1: think it's a bigger game for Tennessee and then Ole
2:39:43
Speaker 1: Miss hosts, Missouri. If, I'd like to see Missouri beat
2:39:48
Speaker 1: a good team on the road, and then I'll believe.
2:39:52
Speaker 1: Until they do that, it's hard for me to believe
2:39:54
Speaker 1: in Missouri. Before the season started, Penn State going to
2:40:05
Speaker 1: the big house this weekend, we would have circled that
2:40:07
Speaker 1: as a potential. It's like Miami, Florida State. How come
2:40:10
Speaker 1: that game's not a bigger deal game?
2:40:12
Speaker 2: Yeah.
2:40:14
Speaker 1: Because Michigan has two losses and Penn State has three.
2:40:16
Speaker 1: How about that? Penn State and Michigan combined, their record
2:40:21
Speaker 1: is six and five. Not good. Not good, Bob. Not
2:40:27
Speaker 1: good at all. Bill Belichick versus my friend Manny Diaz,
2:40:32
Speaker 1: North Carolina at Duke. Interstate rivalry. That's one that's fun.
2:40:37
Speaker 1: That's one that I think the fans love hating each other.
2:40:42
Speaker 1: So it's another one. Obviously, it's better on the hard
2:40:45
Speaker 1: court than it is on grass, but still there's something
2:40:48
Speaker 1: to it. And then there's one game I'm not going
2:40:53
Speaker 1: to be able to watch because I'm going to be
2:40:54
Speaker 1: at the Miami-Florida State game, which is going to be
2:40:56
Speaker 1: on at the same time as the Notre Dame-BYU game. Now,
2:41:00
Speaker 1: many people will note Notre Dame basically has a three-game
2:41:02
Speaker 1: schedule this year. They play at BYU, and they host Miami,
2:41:05
Speaker 1: and they host SMU. On paper, they don't have anybody
2:41:10
Speaker 1: else that should come within two touchdowns of them. You know,
2:41:15
Speaker 1: this is a game– look, Notre Dame can't afford to
2:41:21
Speaker 1: lose because if they lose to BYU, then it really
2:41:25
Speaker 1: makes the Miami game a must-win for them. I don't
2:41:28
Speaker 1: know if a 10-2 Notre Dame gets in with the
2:41:30
Speaker 1: schedule that they have. They had a slightly better schedule
2:41:34
Speaker 1: last year, but if they do the same thing where
2:41:37
Speaker 1: the two best teams on their schedule they lost to–
2:41:40
Speaker 1: last year it was Texas A & M and Miami,
2:41:41
Speaker 1: and this year if their two losses are BYU and Miami–
2:41:45
Speaker 1: That's tough for the committee. I know they have the
2:41:47
Speaker 1: automatic bid if they're ranked 12th or whatever it is.
2:41:50
Speaker 1: But I don't know if that keeps them ranked 12th.
2:41:54
Speaker 1: And BYU, it's arguably a bigger game for Notre Dame
2:41:58
Speaker 1: than BYU because BYU, it's actually a meaningless game. It's
2:42:02
Speaker 1: a good perception game. Are they really a top 10 team?
2:42:05
Speaker 1: How well do they do hosting? So I think it
2:42:07
Speaker 1: matters to them psychologically, but has no impact on the
2:42:13
Speaker 1: Big 12 standings. And they're still undefeated in the Big 12,
2:42:17
Speaker 1: regardless of what happens here. Upset alert at the Rose Bowl.
2:42:23
Speaker 1: Wisconsin going to UCLA. Wisconsin's won a few games in
2:42:27
Speaker 1: the Rose Bowl over the years when it was actually
2:42:29
Speaker 1: a Rose Bowl. UCLA, after their biggest win they've had
2:42:32
Speaker 1: probably in 20 years at Oregon, they lost their starting quarterback.
2:42:38
Speaker 1: This almost feels... Too sharp already. The line's only two
2:42:47
Speaker 1: and a half. There's a huge expectation here that that's
2:42:50
Speaker 1: a big letdown spot for UCLA. And it's hard not
2:42:53
Speaker 1: to assume that. And then Kentucky. Kentucky goes to Oklahoma.
2:42:59
Speaker 1: Is Oklahoma right at its ship? Or is that just
2:43:03
Speaker 1: an accidental victory for them? I know if you're Texas,
2:43:07
Speaker 1: you really want Oklahoma to win. You need to prove
2:43:09
Speaker 1: that that loss to Oklahoma was a good loss and
2:43:12
Speaker 1: not a bad loss. But it's a great weekend, folks. And,
2:43:16
Speaker 1: you know, as we're getting into the heart of conference, right,
2:43:19
Speaker 1: it's like all these important conference games taking place in
2:43:24
Speaker 1: all the various, you know, important ACC games, important SEC games,
2:43:29
Speaker 1: important Big Ten, important Big 12. So enjoy the weekend.
2:43:32
Speaker 1: I know I will. Let's go Canes. I'll see you
2:43:35
Speaker 1: in Miami.