Latest / The Chuck ToddCast / Full Episode - Trump Can’t Defend His Bad Economy + Can Government Effectively Regulate The AI Arms Race?

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Full Episode - Trump Can’t Defend His Bad Economy + Can Government Effectively Regulate The AI Arms Race? · The Chuck ToddCast

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  Speaker 1: so use that code. Hello, They're happy Wednesday, and welcome
• 1:41
  Speaker 1: to another episode of the Chuck Podcast. Look, we've got
• 1:45
  Speaker 1: the President headed to China and I'm gonna have a
• 1:48
  Speaker 1: lot more to say about where it is, where the
• 1:51
  Speaker 1: status of him when it comes to aron world economy.
• 1:57
  Speaker 1: What I fear is going to not be a great
• 2:00
  Speaker 1: trip to China, But we'll talk about that again a
• 2:03
  Speaker 1: little bit tomorrow. I've got a terrific guest lineup for
• 2:05
  Speaker 1: tomorrow's episode. I have a very interesting episode today, very
• 2:09
  Speaker 1: special edition that's a deep dive on AI some good
• 2:15
  Speaker 1: stuff that we did at Newsphere and I wanted to
• 2:17
  Speaker 1: share it with you guys. So that's coming up today.
• 2:19
  Speaker 1: But I did want to say, Like I said, I'm
• 2:21
  Speaker 1: going to spend a lot more time on Iran, a
• 2:23
  Speaker 1: lot more time on this China trip in general, but
• 2:28
  Speaker 1: sort of the incredibly weak position that the President has
• 2:32
  Speaker 1: put himself in, right, this is one of those cases
• 2:35
  Speaker 1: where he put himself into this position with the illegal tariffs,
• 2:40
  Speaker 1: which have been struck down now twice by courts, and
• 2:43
  Speaker 1: he's got very little leverage going into this meeting. He
• 2:46
  Speaker 1: needs more from China than China needs from the United States.
• 2:49
  Speaker 1: Never a good way to go into a incredibly important
• 2:51
  Speaker 1: bilateral meeting. But I'm going to have Mark Zandy for
• 2:55
  Speaker 1: the Thursday podcast from Moody's chief economist, who I just
• 3:00
  Speaker 1: think is the straightest shooter out there on what's happening
• 3:03
  Speaker 1: because this massive inflation report that came out today really
• 3:11
  Speaker 1: sort of and you could hear the defensiveness with the President.
• 3:14
  Speaker 1: He met with reporters just before he got on to
• 3:17
  Speaker 1: marid One to start the trek halfway around the world
• 3:21
  Speaker 1: for his China for his China trip, and he was
• 3:26
  Speaker 1: asked a question that really, look, there's a few clips
• 3:29
  Speaker 1: and there's been one I think that has made more rounds,
• 3:32
  Speaker 1: that is, you know, one of those things where he
• 3:35
  Speaker 1: was answering a longer question about concern about Iran nuclear
• 3:38
  Speaker 1: weapons and then what he said about I don't think
• 3:41
  Speaker 1: about people's financial situations. It's one of those where you
• 3:45
  Speaker 1: can clip it out of context and really make it
• 3:47
  Speaker 1: an effective attack on him in a campaign. And I
• 3:50
  Speaker 1: have a feeling most of you have seen that clip,
• 3:53
  Speaker 1: but there was another clip after it that was not
• 3:55
  Speaker 1: out of context, So it is it was the answer.
• 3:59
  Speaker 1: It's the question, frankly, that you could argue every single
• 4:06
  Speaker 1: campaign ad ought to be asking, every voter ought to
• 4:10
  Speaker 1: be asking every elected officials, is Trump's policy is not working?
• 4:17
  Speaker 1: So the reporter did a shouted question about the new
• 4:21
  Speaker 1: inflation report that showed we've hit the highest inflation rate
• 4:25
  Speaker 1: month over a month of month increase year over year,
• 4:28
  Speaker 1: highest level in three years, And the question was pretty simple,
• 4:35
  Speaker 1: is this mean your policies aren't working? And he got
• 4:38
  Speaker 1: defensive immediately, Right, he is clearly not going to be
• 4:42
  Speaker 1: his party's best messenger on the economy, especially since this
• 4:46
  Speaker 1: economy is in worse shape than when he got it
• 4:50
  Speaker 1: because of the things he's done, the tariffs having contributed
• 4:55
  Speaker 1: to inflation, the war of choice with Iran has had
• 4:59
  Speaker 1: a mass, massive impact on inflation, and we're not even
• 5:03
  Speaker 1: done yet. This is why it was so important for
• 5:05
  Speaker 1: me to get the Mark Xandy interview on the books.
• 5:09
  Speaker 1: We are only at the beginning of this inflation pain. Unfortunately,
• 5:13
  Speaker 1: it's it's going to get worse before it gets better. Politically,
• 5:17
  Speaker 1: it means we already know that what the November economic
• 5:20
  Speaker 1: outlook looks like, and this president has zero answers for this.
• 5:24
  Speaker 1: He got very defensive with the question. He says, before
• 5:27
  Speaker 1: the war with Iran, it was at one point, you know,
• 5:29
  Speaker 1: eight percent, everything was going fine. That wasn't true. As usual,
• 5:32
  Speaker 1: he always It's like when he used to talk about
• 5:34
  Speaker 1: how great his economy was pre COVID, he would always
• 5:37
  Speaker 1: sort of, you know, the fish gets bigger, right, That
• 5:39
  Speaker 1: is the classic Donald Trump ism. You know, if he
• 5:42
  Speaker 1: caught a five inch fish by the time he tells
• 5:45
  Speaker 1: you the story the first time, it's a foot and
• 5:46
  Speaker 1: a half later it becomes eight feet, ten feet, et cetera.
• 5:51
  Speaker 1: That's you know him and his really bad math. Right,
• 5:54
  Speaker 1: when you save nine hundred percent on something, which means
• 5:56
  Speaker 1: somehow people would be paying you to get to get
• 6:01
  Speaker 1: whatever it is. That that's being discounted. But I digress
• 6:05
  Speaker 1: him in the English language. I think they're I think
• 6:08
  Speaker 1: they occasionally meet each other, but I'm not sure. I'm
• 6:12
  Speaker 1: not sure it's his native tongue. But at this point
• 6:18
  Speaker 1: I think Ai slop when he can't sleep is his
• 6:21
  Speaker 1: new language of choice these days. But he gets really
• 6:25
  Speaker 1: defensive and then he starts saying, well, you know, then
• 6:27
  Speaker 1: we thought the stock market was going to go down,
• 6:29
  Speaker 1: and now it's at its highest levels, which it is
• 6:30
  Speaker 1: not right, it is still not cracked fifty Dow fifty
• 6:34
  Speaker 1: thousand again since that time, Pambondi, who was Attorney General
• 6:38
  Speaker 1: at the time, didn't like the question she was getting
• 6:40
  Speaker 1: on the Epstein files and said, you won't ask about
• 6:42
  Speaker 1: Dow fifty thousand. Well, we're still have not gotten back
• 6:47
  Speaker 1: over the fifty thousand mark. We've gotten close, right this AI.
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  Speaker 1: You know, the essentially the AI investments have totally overwhelmed
• 6:58
  Speaker 1: what normally would probably probably be market setbacks due to
• 7:03
  Speaker 1: this war. And frankly, it's still a bigger possibility that
• 7:07
  Speaker 1: that's going to happen than not. Yes, there's a lot
• 7:10
  Speaker 1: of stimulus money into the into the into the economy. Uh,
• 7:15
  Speaker 1: this is a case of it's not stimulus from the
• 7:17
  Speaker 1: public sector. In this case, it is stimulus from the
• 7:20
  Speaker 1: private sector. Just think a couple of weeks ago, three
• 7:23
  Speaker 1: different earnings reports indicated it combined seven hundred billion dollars
• 7:28
  Speaker 1: of investment investments into AI infrastructure. Whether it was Microsoft, Amazon,
• 7:32
  Speaker 1: I think, and Alphabet those three alone. I think it
• 7:37
  Speaker 1: was their collective investments in that. And that's you know,
• 7:41
  Speaker 1: any public sector stimulus package. That's about the size of
• 7:45
  Speaker 1: the last one that we did when we got into
• 7:47
  Speaker 1: a recession. So there's no doubt this is keeping us
• 7:50
  Speaker 1: out of recession territory. But the day to day costs
• 7:56
  Speaker 1: and this economy is getting more expensive, inflation and now
• 7:59
  Speaker 1: stagflation is more likely. He's not a good messenger, and
• 8:05
  Speaker 1: now we have the economy you're going to have for
• 8:08
  Speaker 1: the election. Right, We've been sort of holding off, but
• 8:11
  Speaker 1: it is pretty clear we're nowhere near this war. Is
• 8:15
  Speaker 1: this war is not going to end tomorrow. We're weeks
• 8:18
  Speaker 1: away at best having some resolution on what traffic's going
• 8:23
  Speaker 1: to look like in the straight of horm moves, and
• 8:25
  Speaker 1: if for weeks away from that. Even under the best
• 8:29
  Speaker 1: case scenario, the energy supply chain doesn't get back to
• 8:33
  Speaker 1: normal until maybe the end of this calendar, but more
• 8:36
  Speaker 1: likely the early part of twenty seven. So we know
• 8:39
  Speaker 1: this is not going to be a good economy for
• 8:43
  Speaker 1: the elections, that's not good for the incumbent party. What
• 8:46
  Speaker 1: we don't know is how big is this floodwall, this
• 8:49
  Speaker 1: redistricting floodwall, How big is it? You know, those are
• 8:53
  Speaker 1: the cour and the fact that this Senate map is
• 8:56
  Speaker 1: a map that's being fought more in light red territory
• 8:59
  Speaker 1: than it is in purple or light blue territory. Right
• 9:02
  Speaker 1: it is. There is certainly a higher bar Democrats have
• 9:05
  Speaker 1: to get to to win a governing majority in the
• 9:08
  Speaker 1: House and to win a majority in the Senate. But
• 9:12
  Speaker 1: essentially they've got they've got plenty of fodder to start using.
• 9:19
  Speaker 1: I mean, you know you've got the two eight. Now,
• 9:24
  Speaker 1: that doesn't mean that Democrats don't have their own problems, right,
• 9:27
  Speaker 1: It's not exactly breaking news that the Democratic Party has
• 9:30
  Speaker 1: a brand problem. Everybody knows it. Democrats know it, Republicans
• 9:34
  Speaker 1: know it. Republicans are counting on that brand problem to
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  Speaker 1: limit their losses in twenty twenty six. Independents certainly know it.
• 9:45
  Speaker 1: But we have to remember, no matter what happens in
• 9:46
  Speaker 1: twenty twenty six. That brand problem is not going to
• 9:48
  Speaker 1: get resolved this year. And in fact, they can have
• 9:52
  Speaker 1: a brand problem, be underwater and unpopular with the public
• 9:56
  Speaker 1: and still win big majorities in the House and get
• 10:01
  Speaker 1: four or five or even six Senate seats. That's how
• 10:04
  Speaker 1: unpopular the president has become. That's how unpopular this economy
• 10:09
  Speaker 1: is likely to be by November. Right, you think this
• 10:12
  Speaker 1: is the beginning of a surging inflation issue, is what
• 10:18
  Speaker 1: point is We're only at the beginning of this inflation
• 10:21
  Speaker 1: problem in day to day goods. It is only going
• 10:24
  Speaker 1: to get worse, particularly on food, not only in gas. Right,
• 10:28
  Speaker 1: it is just the high diesel prices. They're just now
• 10:31
  Speaker 1: being passed into the economy. So we are all we
• 10:35
  Speaker 1: are all not there. So the terrain is what it is.
• 10:40
  Speaker 1: The politics of twenty twenty six on a messaging level
• 10:43
  Speaker 1: are just straightforward. Right now, Democrats have the case to
• 10:51
  Speaker 1: make against Trump if simply you broke your two of
• 10:54
  Speaker 1: your three basic promises. Right, he promised lower costs. Everything's higher, Like,
• 11:00
  Speaker 1: there's nothing that is lower anymore except maybe his gold phone,
• 11:05
  Speaker 1: which I don't know if you can purchase. But if
• 11:06
  Speaker 1: you purchase, you're still not going to get one. The
• 11:10
  Speaker 1: country feels unstable. Donald Trump promised no more wars, no
• 11:15
  Speaker 1: more stupid Middle East wars. His son even as a
• 11:17
  Speaker 1: tweet that's been making the rounds in the fall of
• 11:19
  Speaker 1: twenty twenty four bragging about how the only way to
• 11:22
  Speaker 1: stay out of a war with Iran is to elect
• 11:26
  Speaker 1: his father. The Iran conflict has made that promise a
• 11:31
  Speaker 1: lot harder to sell politically. So the opening for Democrats
• 11:35
  Speaker 1: is obvious. They don't have to make a four case,
• 11:38
  Speaker 1: and midterms are never four cases. They're against cases. All
• 11:42
  Speaker 1: they have to do is run against the higher costs,
• 11:45
  Speaker 1: the economic anxiety, the global instability, and another oversehas conflict.
• 11:51
  Speaker 1: And by the way, that's a message that can if
• 11:53
  Speaker 1: Democrats choose to do this work everywhere. Urban districts, suburban districts,
• 11:58
  Speaker 1: working class districts ex. Surban districts, rural districts. Now, we
• 12:03
  Speaker 1: don't know whether Democrats will actually have strong enough candidates
• 12:06
  Speaker 1: to execute that strategy competently. That's what the campaigns are for.
• 12:11
  Speaker 1: We'll find out in the next six months. There's probably
• 12:13
  Speaker 1: going to be some Democrat none of us have talked
• 12:15
  Speaker 1: about that's going to win in a ruby red area
• 12:19
  Speaker 1: because they're really good at messaging and they really come
• 12:23
  Speaker 1: across trustworthy when they make this message. This isn't a
• 12:26
  Speaker 1: hard message to sell whether you're in Idaho, Iowa, Miami,
• 12:31
  Speaker 1: or northern Virginia. What's hard is being a candidate that's
• 12:35
  Speaker 1: credible enough to sell it in some places. So the
• 12:40
  Speaker 1: bigger variable in twenty twenty six may not even be messaging, right,
• 12:44
  Speaker 1: It may simply be what does the political map actually
• 12:46
  Speaker 1: look like by election day? Right? That's the thing that's
• 12:49
  Speaker 1: up that we don't know. Is it that the max?
• 12:54
  Speaker 1: You know we're going to have maybe thirty we may
• 12:56
  Speaker 1: only have thirty competitive house seats total. I saw one
• 13:00
  Speaker 1: estimate that put it at thirty one to travesty, right,
• 13:05
  Speaker 1: that is not That is when you're asking yourself, we're
• 13:09
  Speaker 1: not a democracy. We're to cartographers here, and then we're
• 13:13
  Speaker 1: like arguing over the last bits of you know, border
• 13:17
  Speaker 1: disputes between the two parties. With these thirty congressional seats,
• 13:21
  Speaker 1: Democrats aren't going to win all thirty. So you're looking at,
• 13:24
  Speaker 1: you know, can they get to two hundred and thirty
• 13:26
  Speaker 1: house seats and be picked up about fifteen, sixteen, seventeen seats,
• 13:30
  Speaker 1: you know, but that's a big night for them with
• 13:33
  Speaker 1: a flood wall this high on that front. But here's
• 13:43
  Speaker 1: the thing. Even if Democrats have a good twenty twenty six,
• 13:46
  Speaker 1: even if they win the House, even if Trump's numbers
• 13:49
  Speaker 1: deteriorate further, there is a larger issues that is hanging
• 13:53
  Speaker 1: over the party that's not going away. What is the
• 13:56
  Speaker 1: Democratic Party now? What does it actually stand for? Or
• 14:01
  Speaker 1: what is its identity? That's what I made my substack
• 14:04
  Speaker 1: this week, the Democratic Party's identity crisis, because they still
• 14:08
  Speaker 1: have one, and they're going to have one now. I
• 14:11
  Speaker 1: think that question, more than any midterm result, is going
• 14:14
  Speaker 1: to become the defining argument of the twenty twenty eight
• 14:17
  Speaker 1: Democratic primary. And honestly, that primary effectively begins the moment
• 14:22
  Speaker 1: polls close this November. You will have whether it's JB. Pritzker,
• 14:27
  Speaker 1: Gavin Newsom, Rama Manual Lisa Slock, and they will all
• 14:31
  Speaker 1: be ready to talk and suddenly talk about running in
• 14:34
  Speaker 1: twenty twenty eight. Immediately, everybody now knows early bird, early
• 14:40
  Speaker 1: bird matters, especially for those that have never run before.
• 14:45
  Speaker 1: The only people that have the luxury of waiting are
• 14:47
  Speaker 1: the ones that have run before. So the ones that
• 14:49
  Speaker 1: have never run before got to jump in early, and
• 14:51
  Speaker 1: they're going to And while nothing happening this year is
• 14:55
  Speaker 1: necessarily definitional for the Democratic Party long term, it's a
• 14:59
  Speaker 1: midterm ore. It's like I said, it's an against case,
• 15:02
  Speaker 1: not a four case. I will say that the events
• 15:06
  Speaker 1: of the last few weeks have reminded me of the
• 15:09
  Speaker 1: deeper challenge Democrats face. And I think the Virginia issue,
• 15:16
  Speaker 1: I don't know what else to refer to it. At
• 15:17
  Speaker 1: the Virginia remap attempt accidentally exposed this problem because what
• 15:24
  Speaker 1: happened in Virginia was ostensibly about redistricting, but the reaction
• 15:27
  Speaker 1: to it revealed something bigger, something deeper, and I think
• 15:31
  Speaker 1: it gets to the core identity crisis now sitting inside
• 15:34
  Speaker 1: the Democratic Party. The controversy started with maps. Obviously, Virginia
• 15:39
  Speaker 1: Democrats pursued a strategy designed a counter Republican jerrymandering elsewhere,
• 15:45
  Speaker 1: and the Virginia Supreme Court, of course, ultimately rejected the
• 15:47
  Speaker 1: process that produced the maps, ruling the constitutional procedure itself
• 15:52
  Speaker 1: was flawed, not the maps but the procedure. But what
• 15:55
  Speaker 1: followed was revealing. There was anger not simply at Republicans,
• 15:59
  Speaker 1: but at the court itself. There was complaints about the
• 16:02
  Speaker 1: legitimacy of the ruling, not from every corner of the left,
• 16:04
  Speaker 1: but from quite a few, and there were complaints about process.
• 16:07
  Speaker 1: And then there was that ridiculous idea in some democratic
• 16:10
  Speaker 1: circles that apparently became Jeffries was a part of about
• 16:15
  Speaker 1: some dramatic institutional responses to the court ruling in Virginia,
• 16:19
  Speaker 1: including ideas that would have effectively forced the Virginia Supreme
• 16:22
  Speaker 1: Court into retirement and allowed it to be essentially restructured
• 16:26
  Speaker 1: or reappointed. So let's stop here for a second, because
• 16:30
  Speaker 1: I think the fact that that reaction had made its
• 16:34
  Speaker 1: way into the democratic leadership conversation. I'm not saying Jeffries
• 16:37
  Speaker 1: endorsed the concept, but it was during his apparently these
• 16:42
  Speaker 1: venting sessions. That reaction tells you something not just about Democrats,
• 16:48
  Speaker 1: but about American politics more broadly at the moment, because
• 16:52
  Speaker 1: increasingly both parties sound a lot less like reform movements,
• 16:57
  Speaker 1: which is what a political party should be at its court,
• 17:00
  Speaker 1: or that's what parties are supposed to be, but these
• 17:04
  Speaker 1: parties now behave more like institutional combatants. Trying to preserve
• 17:09
  Speaker 1: advantage inside a system that fewer and fewer people trust,
• 17:15
  Speaker 1: and Democrats in particular now seem caught in a contradiction
• 17:18
  Speaker 1: that I don't think they have fully reckoned with. So,
• 17:21
  Speaker 1: for instance, the Democrats, I think do a good job
• 17:24
  Speaker 1: of speaking the language of insurgency, resistance, movement politics, protecting democracy,
• 17:29
  Speaker 1: fighting for the future. But increasingly the voters see a
• 17:32
  Speaker 1: party deeply intertwined with the country's institutional architecture universities, nonprofits, legacy,
• 17:39
  Speaker 1: media and public sector systems, professional class, governance structures, that
• 17:44
  Speaker 1: sort of management class has become a Democratic party base,
• 17:48
  Speaker 1: and federal agencies. In other words, Democrats often want to
• 17:51
  Speaker 1: sound revolutionary while behaving institutionally, and I think voters can
• 17:57
  Speaker 1: feel that contradiction. Now, to be clear, none of this
• 18:02
  Speaker 1: means Republicans are somehow better actors. They're worse actors in this,
• 18:06
  Speaker 1: but they don't pretend to be better actors. In many states,
• 18:09
  Speaker 1: Republicans remain far more aggressive practitioners of this raw partisan
• 18:13
  Speaker 1: jerrymandering in Texas and Florida. We saw it with the
• 18:16
  Speaker 1: North Carolina Republican controlled state legislature, Tennessee, Missouri, just you know, straight.
• 18:23
  Speaker 1: You know, it's interesting where there was resistance by the
• 18:26
  Speaker 1: way the South Carolina State Senate, the fact that just
• 18:31
  Speaker 1: Enough said no. They made a decision that I think
• 18:35
  Speaker 1: was in the best interests of the Republican Party. You
• 18:38
  Speaker 1: carve up Cliburn Sea, I think you put two districts
• 18:41
  Speaker 1: in play. Now Democrats may end up with two South
• 18:44
  Speaker 1: Carolina districts anyway, They may win the Charleston seat, that's
• 18:48
  Speaker 1: Nancy Mace's open seat. But you try to carve up
• 18:52
  Speaker 1: Cliburn District and you start to distribute it everywhere else.
• 18:56
  Speaker 1: South Carolina is not that Republican enough they could put
• 18:59
  Speaker 1: two or three. I mean before the majority minority reapportionment
• 19:06
  Speaker 1: deal that the Bush forty one Justice Department cut with
• 19:10
  Speaker 1: the Congressional Black Caucus. South Carolina had a lot more
• 19:14
  Speaker 1: swinging districts in it back in the day and had
• 19:17
  Speaker 1: its share of Democratic These were they were the bunch swinginess.
• 19:23
  Speaker 1: But creating you know, sort of packing a lot of
• 19:27
  Speaker 1: African American Democrats into the Claborate seat has created safer
• 19:32
  Speaker 1: seats around it. So I do think it's one of
• 19:34
  Speaker 1: those where and it was really the real argument that
• 19:41
  Speaker 1: the Indiana Republicans were making, they weren't making some sort
• 19:44
  Speaker 1: of they might look. I don't know. I'm not going
• 19:48
  Speaker 1: to question somebody's motive. Some of them may have been
• 19:51
  Speaker 1: principled about it others, but there was a pragmatic reason
• 19:54
  Speaker 1: for it too. They might actually make more congressional seats vulnerable,
• 19:57
  Speaker 1: not fewer. Well. This episode of the Chuck Podcast is
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  Speaker 1: and guess what time is money? So with shipstation, everything
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• 21:45
  Speaker 1: So that's shipstation dot com toodcast. Shipstation dot com use
• 21:51
  Speaker 1: the code toodcast. The question I have in all of
• 21:57
  Speaker 1: these places where they've done this remap, where I do
• 21:59
  Speaker 1: think they've made at least some places where if Democrats
• 22:03
  Speaker 1: found the right candidate. Now, maybe it's too late in
• 22:06
  Speaker 1: this cycle. By twenty eighth they money. I just wouldn't
• 22:10
  Speaker 1: write off this. There's this broad assumption in legacy media
• 22:15
  Speaker 1: that the all of the voting rights it is. Look,
• 22:17
  Speaker 1: this is not good for African American representation in the
• 22:22
  Speaker 1: South in Congress at the moment, But I think this
• 22:26
  Speaker 1: is not going It's sort of one of those when
• 22:29
  Speaker 1: when everybody actually sees the numbers and realizes you may
• 22:33
  Speaker 1: have to shift your messaging a little bit, you may
• 22:36
  Speaker 1: have to shift your candidate recruitment a little bit. But
• 22:38
  Speaker 1: I think you're going to see in some of these
• 22:42
  Speaker 1: states more competition in some of these places. I think,
• 22:47
  Speaker 1: not everywhere, somewhere. But of course, the real representation problem
• 22:53
  Speaker 1: with Congress is the it needs to be right sized
• 22:56
  Speaker 1: with the country. But I'm not going to go down
• 22:57
  Speaker 1: that rabbit hole of those. Maybe your listeners can start
• 23:02
  Speaker 1: creating me uncap the house as a drinking game. How
• 23:05
  Speaker 1: many episodes in a row can I can? I talk
• 23:08
  Speaker 1: about it? But the real question isn't simply who abuses
• 23:13
  Speaker 1: this system more aggressively. The deeper question is why do
• 23:16
  Speaker 1: both parties seem so unwilling to rethink a system where
• 23:19
  Speaker 1: manipulating a handful of district lines can fundamentally distort national representation.
• 23:25
  Speaker 1: In the first place, that's a reform question, and increasingly
• 23:29
  Speaker 1: Democrats seem less comfortable asking reform questions than preservation once
• 23:35
  Speaker 1: and that may be the real identity crisis facing the party.
• 23:38
  Speaker 1: Not whether Democrats are too progressive or too moderate, not
• 23:41
  Speaker 1: whether they need younger leaders or better messaging, but whether
• 23:45
  Speaker 1: the party is slowly transformed from a reform movement into
• 23:49
  Speaker 1: a preservation movement. And honestly, once you start looking at
• 23:54
  Speaker 1: the current American political landscape through that lens, a bunch
• 23:58
  Speaker 1: of things suddenly make a bit more sense. Because the
• 24:01
  Speaker 1: redistricting wars are not really about maps, they're about incentives.
• 24:04
  Speaker 1: Think about what the current system actually requires. A country
• 24:07
  Speaker 1: of more than three hundred and forty million people still
• 24:11
  Speaker 1: electing only forty one hundred and thirty five members of
• 24:13
  Speaker 1: the House of Representatives. I gave you another shot, the
• 24:17
  Speaker 1: exact same number it added when the country's population was
• 24:20
  Speaker 1: barely a third of its size. So our congressional districts
• 24:23
  Speaker 1: are massive, they're less personal, less local, more abstract. And
• 24:27
  Speaker 1: then you put that in a stew of hyperpartisan primaries
• 24:33
  Speaker 1: rewarding ideological intensity over broad representation. Then we layer in
• 24:38
  Speaker 1: modern data analytics, polarized media ecosystems, and we've nationalized all
• 24:44
  Speaker 1: of our politics, and you end up with a system
• 24:45
  Speaker 1: where drawing a handful of district lines can dramatically alter
• 24:49
  Speaker 1: the balance of power in Washington. Right, the fact that
• 24:52
  Speaker 1: you can change six seats alters the powers kind of
• 24:56
  Speaker 1: that's that's a problem. And yet most political stops at
• 25:01
  Speaker 1: who's abusing this system more aggressively. That's not reform thinking,
• 25:05
  Speaker 1: that's preservation thinking. A reformer asks why are the incentives broken?
• 25:11
  Speaker 1: To begin with? And for most of modern American history
• 25:16
  Speaker 1: twentieth century forward, the Democratic Party actually did ask reform questions.
• 25:22
  Speaker 1: Franklin Roosevelt's Democrats sought to reform capitalism after economic collapse.
• 25:27
  Speaker 1: Post Watergate, Democrats position themselves as reformers of government ethics
• 25:33
  Speaker 1: and executive accountability. The New Democrats of the nineties promised
• 25:37
  Speaker 1: modernization and reinvention. Barack Obama's coalition was fueled by reform
• 25:42
  Speaker 1: language as well opposition to the Iraq War, changing Washington,
• 25:47
  Speaker 1: rebuilding trust, updating institutions, essentially bringing the government into the
• 25:56
  Speaker 1: twenty first century. Now, obviously those movements were ideologically different
• 26:01
  Speaker 1: from each other, but they shared a common premise the
• 26:09
  Speaker 1: system was failing ordinary Americans and needed structural change. But
• 26:14
  Speaker 1: over the last decade something shifted. In part it's Trump right,
• 26:19
  Speaker 1: Democrats sound less like the party seeking to redesign institutions
• 26:22
  Speaker 1: and they're more like a party trying to defend institutional
• 26:25
  Speaker 1: legitimacy itself. Now, some of this transformation is simply understandable
• 26:31
  Speaker 1: Donald Trump. The Trump errors pushed Democrats into becoming defenders
• 26:35
  Speaker 1: of democratic norms, institutions, election courts, alliances, procedural stability, constitutional guardrails.
• 26:44
  Speaker 1: It's a very rational response to Trump. Please, it's what
• 26:47
  Speaker 1: we need, still what we need. But politically for the
• 26:51
  Speaker 1: Democratic Party brand wise, there was a trade off party
• 26:55
  Speaker 1: that once defined itself through reform, where every new Democratic
• 26:59
  Speaker 1: presidency was bringing a new movement with them. That stopped
• 27:04
  Speaker 1: with Joe Biden because Joe Biden ran on preservation, and
• 27:13
  Speaker 1: that becomes dangerous at a moment when public trust in
• 27:16
  Speaker 1: the institutions that you're trying to preserve is collapsing almost
• 27:21
  Speaker 1: everywhere Congress, media, universities. During COVID, it was public health officials,
• 27:26
  Speaker 1: corporate leadership, both political parties and once voters lose trust
• 27:31
  Speaker 1: and institutions. Generally, the party most associated with defending those
• 27:36
  Speaker 1: institutions eventually has to absorb the frustration with them. That's
• 27:40
  Speaker 1: the trap that Democrats increasingly find themselves in. And that's
• 27:45
  Speaker 1: in some ways it animates these divides, right, because I
• 27:48
  Speaker 1: do think the leadership is I think at times thinking
• 27:51
  Speaker 1: about like, look, we've got to bring some rationality of things.
• 27:54
  Speaker 1: So we just need to get stability, very rational thing
• 27:59
  Speaker 1: to do. Others in the progressive movement are going Jesus crime, Andy,
• 28:03
  Speaker 1: Look he's now made it worse. We really got to
• 28:05
  Speaker 1: hurry up and do this bigger change. But it doesn't
• 28:10
  Speaker 1: come across this change. It just comes across this reactionary politics.
• 28:14
  Speaker 1: And even when Democrats are right about this on the
• 28:17
  Speaker 1: substance and about the Republican abuses, their response sounds reactive
• 28:22
  Speaker 1: rather than transformational. Right, protect maps or protect the norms,
• 28:28
  Speaker 1: protect the procedures, protect the institutions. But what is the
• 28:32
  Speaker 1: larger reform vision? That's the question voters increasingly seem to
• 28:36
  Speaker 1: be asking. And there's another warning sign here that I
• 28:39
  Speaker 1: honestly think both parties, but especially Democrats, are underestimating, and
• 28:44
  Speaker 1: that is why is there a rise of independence? Why
• 28:46
  Speaker 1: is there a rise People need to ask this question
• 28:49
  Speaker 1: more of independent voters, why do you choose not to
• 28:51
  Speaker 1: identify with one the two major parties? And I think
• 28:56
  Speaker 1: one of the answers we're going to get is the
• 28:57
  Speaker 1: rise of voters registering with no party officials at all.
• 29:00
  Speaker 1: That these are that these are voters who are trying
• 29:06
  Speaker 1: to send a message to the two parties and this
• 29:08
  Speaker 1: is their only form of protests that's available to them.
• 29:12
  Speaker 1: That's it. I think too many political professionals misunderstand this
• 29:17
  Speaker 1: rise of independence. They think it just simply means that's
• 29:21
  Speaker 1: part of the polarization. They're just turned off by it.
• 29:24
  Speaker 1: And I think these are people exhausted from institutions. So
• 29:32
  Speaker 1: if you look at this rise of new independent voters,
• 29:35
  Speaker 1: and especially when you see young people, why are they
• 29:37
  Speaker 1: making decisions to not register with either party? I mean,
• 29:42
  Speaker 1: look at all the institutions that failed them, beginning with COVID.
• 29:48
  Speaker 1: So I think registering as an independent is a protest
• 29:50
  Speaker 1: against institutionalized partisanship. And I actually should concern the Democrats
• 29:56
  Speaker 1: more than even more so than the Republicans, because of
• 29:59
  Speaker 1: the Democrat truly occupied the reform space in American politics.
• 30:04
  Speaker 1: You would expect at least some portion of those disaffected
• 30:07
  Speaker 1: voters to migrate towards the party as an agent of
• 30:10
  Speaker 1: structural change. Instead, many of those folks are simply opting
• 30:14
  Speaker 1: out a partisan identity altogether. And to me, that suggests
• 30:18
  Speaker 1: something deeper is happening. It suggests millions of voters increasingly
• 30:22
  Speaker 1: see both parties not as competing reform movements, but as
• 30:26
  Speaker 1: competing management teams for a political system they no longer trust.
• 30:31
  Speaker 1: And this is where I think the redistricting wars become
• 30:33
  Speaker 1: much bigger than the mats, because they point toward what
• 30:37
  Speaker 1: a genuine reform identity could actually look like, move democratic
• 30:42
  Speaker 1: power closer to the public. That's the connective tissue. That's
• 30:47
  Speaker 1: the north star. Not left versus right, progressive versus moderate
• 30:51
  Speaker 1: versus conservative, not institutional destruction versus institutional defense. Democratic small
• 30:58
  Speaker 1: the responsiveness politics built around reducing the distance between institutions
• 31:04
  Speaker 1: and the people they represent. That's how you rebuild trust,
• 31:09
  Speaker 1: is people seeing these institutions being rebuilt or built anew
• 31:14
  Speaker 1: That means asking structural questions open primaries, for instance, that's
• 31:18
  Speaker 1: not just a procedural tweak. That's an attempt to force
• 31:22
  Speaker 1: candidates compete for a broader public support instead of only
• 31:25
  Speaker 1: appealing to the most ideologically intense voters inside party primaries.
• 31:30
  Speaker 1: Expanding the House of Representatives is another example. Drink. The
• 31:33
  Speaker 1: House was capped in nineteen twenty nine when the country
• 31:35
  Speaker 1: was dramatically smaller and much less diverse. Now, congressional districts
• 31:40
  Speaker 1: are so large the representation itself feels abstract and nationalized.
• 31:44
  Speaker 1: People don't know who their congressmen are is anymore. Now.
• 31:48
  Speaker 1: A larger House isn't going to magically fix polarization, but
• 31:51
  Speaker 1: it would reduce the concentration of political power and make
• 31:54
  Speaker 1: representation feel more local and responsive. Again, that same logic
• 31:58
  Speaker 1: applies to nonpartisan redistrict commissions, congressional modernization, and reforms designed
• 32:03
  Speaker 1: to make government feel less distant and less procedural. And
• 32:06
  Speaker 1: I know none of this is sexy enough for some people.
• 32:08
  Speaker 1: I've just been in some rooms where people they're looking
• 32:10
  Speaker 1: for the great individual hope to fix this system. One
• 32:16
  Speaker 1: person can make a house from collapsing. Okay, we have
• 32:21
  Speaker 1: an infrastructure problem. And these ideas are not ideological in
• 32:25
  Speaker 1: the traditional sense. They are structural. They are rooted in
• 32:29
  Speaker 1: a very old American small d democratic instinct. Institutions survive
• 32:34
  Speaker 1: only if the public continues believing they are responsive, accountable,
• 32:37
  Speaker 1: and close enough to ordinary life to deserve trust. And
• 32:40
  Speaker 1: right now, millions of Americans no longer believe that to
• 32:43
  Speaker 1: be the case for each political party. And that's why
• 32:45
  Speaker 1: I think the democratic parties problem may not ultimately be
• 32:48
  Speaker 1: ideological at all. It may be existential because the party
• 32:53
  Speaker 1: that once asked how do we reform broken institutions? Increasingly
• 32:57
  Speaker 1: is asking, and in some way Trump is baiting them
• 33:01
  Speaker 1: to do this, how do we protect institutions from collapse?
• 33:05
  Speaker 1: There's a whole bunch of people on the left that
• 33:07
  Speaker 1: wanted to see these institutions collapse. That maybe not the
• 33:09
  Speaker 1: same ones that Trump got right of, but some of them,
• 33:18
  Speaker 1: those are not the same missions for a party, and
• 33:19
  Speaker 1: the redisseriting wars to me exposed that tension perfectly. Democrats
• 33:24
  Speaker 1: are correct to object to the partisan map manipulation, but
• 33:27
  Speaker 1: if their answer stops at preserving the existing structure, rather
• 33:31
  Speaker 1: than asking how do we redesign a failing, small D
• 33:34
  Speaker 1: democratic system itself, then they risk becoming something reform movements
• 33:39
  Speaker 1: often become if they stay in power long enough. Custodians
• 33:43
  Speaker 1: of a system, voters no longer trust and in American politics,
• 33:47
  Speaker 1: parties that become too closely associated with maintaining a distrusted
• 33:51
  Speaker 1: system eventually discover something dangerous. Voters stop hearing them as
• 33:56
  Speaker 1: agents have change, no matter how urgent their warnings. The
• 34:00
  Speaker 1: alternative maybe. So look, I know some of this is
• 34:07
  Speaker 1: to some of you is repetitive. But you know, the
• 34:10
  Speaker 1: one thing I've learned, you can't just say something once.
• 34:14
  Speaker 1: And there are different moments where I'm trying to use
• 34:17
  Speaker 1: the new moment to reinforce the argument, the larger argument
• 34:25
  Speaker 1: that I hope people come away with here. We've got
• 34:27
  Speaker 1: a lot of issues, but small d democratic reform, and
• 34:33
  Speaker 1: the opening is there. And this is why I think
• 34:36
  Speaker 1: the Democratic Party not being the party change in reforms
• 34:42
  Speaker 1: that needs that. In theory, was the identity they always
• 34:46
  Speaker 1: strove for. I'm not saying they always had it, but
• 34:49
  Speaker 1: they always strove for it, which you would expect from
• 34:52
  Speaker 1: the liberal party, right. The Conservative Party, by definition in
• 34:56
  Speaker 1: theory is the one that's supposed to be the protector
• 35:00
  Speaker 1: of the institutions. So we're sort of got discombobulated by Trump.
• 35:09
  Speaker 1: The question is, did it make Democrats so take their
• 35:12
  Speaker 1: eye off their old balls there No, I made myself
• 35:20
  Speaker 1: laugh and I did not. I have no idea why
• 35:22
  Speaker 1: I was going, but essentially taking their eye off the
• 35:24
  Speaker 1: ball of what they used to be. All right, coming up,
• 35:33
  Speaker 1: I've got a so I spent the my newsfeed Newsphere
• 35:40
  Speaker 1: episode was a deep dive on one topic, all things
• 35:46
  Speaker 1: artificial intelligence AI, governance and the growing trust crisis surrounding
• 35:50
  Speaker 1: the technology that I think is going to be a
• 35:52
  Speaker 1: huge part of campaign twenty twenty eight. And we're already
• 35:55
  Speaker 1: seeing many campaigns in twenty twenty six where AI is
• 35:59
  Speaker 1: sort of making its way, not just in the use
• 36:03
  Speaker 1: of creation of just a lot of sloppy TV ads,
• 36:06
  Speaker 1: but the frustrations over the policies themselves and look in
• 36:12
  Speaker 1: the when it comes to governance of a new technology
• 36:18
  Speaker 1: to protect consumers. This may be the most important conversation
• 36:21
  Speaker 1: that's happening at the moment. AIS moved beyond theoretical. We
• 36:25
  Speaker 1: are far away from there. It's no more future tends debate.
• 36:28
  Speaker 1: AI is already changing how we work, how we search
• 36:31
  Speaker 1: for information, how wars are fought, right we have seen
• 36:34
  Speaker 1: it in real time and the Ukraine War and the
• 36:36
  Speaker 1: war with Iran, how companies hire employees, how governments surveil
• 36:40
  Speaker 1: threats and increasingly, how human beings interact with one another.
• 36:45
  Speaker 1: And yet at the exact moment we're being asked to
• 36:47
  Speaker 1: trust this new technology and to trust AI more and more,
• 36:51
  Speaker 1: the public's trust and the people building it may actually
• 36:54
  Speaker 1: be collapsing, which brings me to what's happening right now
• 36:57
  Speaker 1: in a federal court room. Mint Overly, the musk Altman
• 37:01
  Speaker 1: trial has become something far bigger than a billionaire grudge match.
• 37:04
  Speaker 1: It's turned into a public autopsy of the values, motives,
• 37:07
  Speaker 1: and personalities behind the AI revolution itself. And if you're
• 37:12
  Speaker 1: wondering why the public feels skeptical about AI saving humanity,
• 37:16
  Speaker 1: I think this trial is basically exhibit a. Think about
• 37:20
  Speaker 1: what we've heard under oath over the last few days.
• 37:23
  Speaker 1: Ilia should Skiver, not a critic from the outside, but
• 37:26
  Speaker 1: one of the actual architects of the modern AI and
• 37:30
  Speaker 1: Open AI's former chief scientists, testified that Sam Altman demonstrated
• 37:34
  Speaker 1: what he described as a quote consistent pattern of lying,
• 37:38
  Speaker 1: undermining executives, and pitting people against each other. Internally, the
• 37:41
  Speaker 1: former CTO, Mira Muradi described an atmosphere of chaos where
• 37:46
  Speaker 1: executives were hearing different stories from the same CEO depending
• 37:50
  Speaker 1: on who was in the room. Even Microsoft's current CEO,
• 37:53
  Speaker 1: Satya Nadella, whose company has poured tens of billions of
• 37:56
  Speaker 1: dollars into open Ai, testify that the them is twenty
• 38:00
  Speaker 1: twenty three boardroom coup. The temporarily ousted Altman was quote
• 38:05
  Speaker 1: amateur city. He admitted that even Microsoft never got a
• 38:08
  Speaker 1: straight answer about why Altman was fired in the first place.
• 38:12
  Speaker 1: And then there are the internal documents now surfacing in discovery.
• 38:15
  Speaker 1: Private notes from open Ai president Greg Brockman reportedly included
• 38:18
  Speaker 1: lines like financially, what will it take me to get
• 38:21
  Speaker 1: a billion dollars? Another internal note acknowledge that publicly presenting
• 38:24
  Speaker 1: open Ai is fully committed to a nonprofit structure, while
• 38:27
  Speaker 1: privately discussing a future for profit pivot was quote a lie. Meanwhile,
• 38:32
  Speaker 1: Mosque is accusing Altman of effectively stealing a nonprofit built
• 38:35
  Speaker 1: to protect humanity and turning into a trillion dollar corporate empire.
• 38:39
  Speaker 1: And what's Altman's response That Musk himself tried to seize
• 38:42
  Speaker 1: control years ago and become hostile when he couldn't get it.
• 38:45
  Speaker 1: So there's a ton of tech ego here and We're
• 38:48
  Speaker 1: like you two are going to design the technology for
• 38:52
  Speaker 1: the rest of us. Great, we know there's money, there's pettiness,
• 38:55
  Speaker 1: courtroom theater, but see this, This is the issue underneath
• 39:01
  Speaker 1: all of that is something much more important.
• 39:03
  Speaker 2: Trust.
• 39:04
  Speaker 1: We spend a lot of time talking about AI alignment,
• 39:07
  Speaker 1: whether the machines will align with human values, But what
• 39:10
  Speaker 1: this trials is exposing is something arguably more immediate. What
• 39:14
  Speaker 1: if the humans running the AI revolution aren't aligned with
• 39:17
  Speaker 1: each other or even with the public. Because here's the problem.
• 39:21
  Speaker 1: The average American already feels burned by the last generation
• 39:24
  Speaker 1: of technology. Search engines became polluted with ads and algorithmic gaming.
• 39:28
  Speaker 1: Social media promise connection and delivered polarization, loneliness, and rage.
• 39:33
  Speaker 1: Online platforms that once felt consumer friendly increasingly feel manipulative
• 39:38
  Speaker 1: and extractive. Gone on Amazon lately, there's all these ads
• 39:42
  Speaker 1: before you get to the product you're searching for. So
• 39:45
  Speaker 1: when the same ecosystem now says trust us with AI,
• 39:48
  Speaker 1: skepticism starts to feel less paranoid and more rational. And
• 39:52
  Speaker 1: this is where today's conversations become so important. So you're
• 39:55
  Speaker 1: going to hear two interviews that approach AI from two
• 39:59
  Speaker 1: completely different but together, they paint the full picture of
• 40:02
  Speaker 1: the challenge ahead. Mariam Vogel she joins me first. She
• 40:06
  Speaker 1: chairs the National AI Advisory Committee and runs an organization
• 40:10
  Speaker 1: called Equal AI. Her focus is domestic governance, consumer trust, bias,
• 40:15
  Speaker 1: civil rights transparency in the question of how do small,
• 40:17
  Speaker 1: de democratic societies build guardrails around technologies evolving faster than
• 40:22
  Speaker 1: the regulators themselves can keep up. Then my conversations with
• 40:27
  Speaker 1: the second conversation on AI is with Ann Newburger. She
• 40:30
  Speaker 1: joins me for the geopolitical side of the equation. AI
• 40:33
  Speaker 1: is now a national security weapon. AI is also cyber defense.
• 40:37
  Speaker 1: AI is also infrastructure protection. AI as the next major
• 40:41
  Speaker 1: battleground between the United States and China. You see where
• 40:43
  Speaker 1: I'm going here, and that really is the larger theme
• 40:46
  Speaker 1: connecting both conversations. Mariam Vogel is trying to make sure
• 40:48
  Speaker 1: AI does an unfairly deny you a mortgage or a
• 40:51
  Speaker 1: job interview, and Newburger is trying to make sure a
• 40:54
  Speaker 1: foreign adversary can't use AI to shut down the bank altogether,
• 40:58
  Speaker 1: same technology to very different battles fields. One is consumer protection,
• 41:02
  Speaker 1: one is sort of nation state protection, and somewhere in
• 41:06
  Speaker 1: the middle it's the rest of us. It's the question
• 41:09
  Speaker 1: of every government, company and citizen now struggling to answer,
• 41:12
  Speaker 1: how do we put guardrails around a technology that is
• 41:15
  Speaker 1: evolving faster than the institution's designed to regulate it. Do know?
• 41:21
  Speaker 1: I take my news for your interviews always in person
• 41:23
  Speaker 1: and usually in a restaurant, so the audio is going
• 41:26
  Speaker 1: to be a little bit different. It's more of an
• 41:28
  Speaker 1: open air setting in each of the cases, so the
• 41:30
  Speaker 1: audio will sound a little bit different with the content,
• 41:34
  Speaker 1: I'm sure, trust me, it's good stuff. I have a
• 41:40
  Speaker 1: little comment about the interviews, but we'll talk about it
• 41:44
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  Speaker 1: am a customer. Hello there, I'm Chuck Todd and welcome
• 43:27
  Speaker 1: to another episode of Sunday Night Tonight. It's a one
• 43:31
  Speaker 1: topic deep dive on artificial intelligence, and maybe the simplest
• 43:35
  Speaker 1: way to frame the AI debate right now is this,
• 43:39
  Speaker 1: Americans are being asked to trust a new technological revolution
• 43:43
  Speaker 1: at a moment when they're not entirely convinced the last
• 43:46
  Speaker 1: one worked out so well. Think about it. Search engines
• 43:49
  Speaker 1: once felt empowering, social media once felt connective, online marketplaces
• 43:55
  Speaker 1: once felt simpler and more useful, But over time, many
• 43:59
  Speaker 1: of those same technologies became harder to trust, distorted by algorithms, advertising, misinformation, polarization,
• 44:06
  Speaker 1: and the constant incentive to monetize our attention. So when
• 44:10
  Speaker 1: Selagon Valley tells the public, don't worry, this next technological
• 44:14
  Speaker 1: leap will change everything for the better, it's understandable that
• 44:18
  Speaker 1: many of us respond with a little skepticism, or maybe
• 44:22
  Speaker 1: a lot of skepticism, because AI isn't some distant concept anymore.
• 44:27
  Speaker 1: It's already shaping classrooms, workplaces, financial systems, warfare, and even
• 44:32
  Speaker 1: the information we consume every day, which raises two very
• 44:36
  Speaker 1: different but deeply connected questions. One, how do we protect
• 44:41
  Speaker 1: consumers from AI? And two how do we protect countries
• 44:46
  Speaker 1: from AI? So tonight we're going to explore both sides
• 44:49
  Speaker 1: of this challenge. Miriam Vogel joins me first. She chairs
• 44:53
  Speaker 1: the National AI Advisory Committee and leads an organization called
• 44:57
  Speaker 1: Equal AI that's focused on governm fairness and consumer trust.
• 45:02
  Speaker 1: She's trying to answer the question, how do we build
• 45:04
  Speaker 1: guardrails around AI before the technology outruns the public's confidence
• 45:10
  Speaker 1: in it. Then I'll be joined by a Newburger on
• 45:13
  Speaker 1: the issue of global security, because while Miriam Vogel is
• 45:17
  Speaker 1: trying to make sure AI doesn't discriminate against you when
• 45:19
  Speaker 1: you apply for a mortgage, and Newburger is trying to
• 45:22
  Speaker 1: make sure that same technology isn't used by a foreign
• 45:25
  Speaker 1: adversary to shut down the bank. Altogether, it's the same technology.
• 45:30
  Speaker 1: It's two completely different battlefields, and somewhere between innovation and regulation,
• 45:36
  Speaker 1: between opportunity and fear, is the question governments around the
• 45:40
  Speaker 1: world are now struggling to answer in real time, how
• 45:44
  Speaker 1: do you govern a technology that evolves faster than governments themselves.
• 45:50
  Speaker 1: Tonight's conversation comes to you from the Unconventional Diner. It's
• 45:54
  Speaker 1: one of Washington's great neighborhood spots known for taking classic
• 45:57
  Speaker 1: American comfort food and giving it an inventive twist, which
• 46:01
  Speaker 1: rankfully feels like the perfect backdrop for a conversation about
• 46:05
  Speaker 1: technology trying to reinvent itself in our everyday life. So
• 46:09
  Speaker 1: let's get started, very vogal, it's nice to see you.
• 46:13
  Speaker 1: Let me start with tell me a little something about
• 46:17
  Speaker 1: what equal AI is supposed to be.
• 46:20
  Speaker 3: So we created equal AI seven and a half years
• 46:23
  Speaker 3: ago because we saw the emergence of AI. We saw
• 46:26
  Speaker 3: that there was a deep enthusiasm starting to root across
• 46:30
  Speaker 3: the country and the globe, but without a lot of
• 46:33
  Speaker 3: understanding of the potential risks and the need for guardrails.
• 46:37
  Speaker 3: And so we created that time more of a temporary
• 46:40
  Speaker 3: place where companies, policymakers, lawyers, other key stakeholders could align
• 46:46
  Speaker 3: on guardrails. How do we make sure that this really
• 46:49
  Speaker 3: serves people? How do we contain risks and make sure
• 46:52
  Speaker 3: that we can optimize use. So flash forward seven and
• 46:55
  Speaker 3: a half years. It turns out we have not gone
• 46:58
  Speaker 3: out of style in terms of eating the big place
• 47:01
  Speaker 3: to align on guardrails and best practices.
• 47:04
  Speaker 1: The American electorates skepticism and AI seems very rational to me,
• 47:09
  Speaker 1: when you look at Web one point zero search. In commerce,
• 47:13
  Speaker 1: the user experience at first was great, then.
• 47:15
  Speaker 2: The user became the product. Social media, the.
• 47:19
  Speaker 1: Initial launch seemed great, building up communities. Then what happened algorithms,
• 47:25
  Speaker 1: the user becomes the product, and so we don't like
• 47:29
  Speaker 1: social media. We're more frustrated than ever with how the
• 47:32
  Speaker 1: regular old Internet works, how Amazon or any of the
• 47:36
  Speaker 1: online commerce marketplaces work. And so to me, it's very
• 47:40
  Speaker 1: rational that they look at AI and go, oh, great,
• 47:43
  Speaker 1: yet another way that just is going to exploit us.
• 47:46
  Speaker 3: I think you're absolutely right. We bring a lot of
• 47:49
  Speaker 3: tech baggage to this conversation, and I think there's another
• 47:52
  Speaker 3: layer of a problem here, and that's that we're not
• 47:54
  Speaker 3: listening to people. We're expecting them to adopt AI. We're
• 47:58
  Speaker 3: talking about this we who.
• 48:00
  Speaker 2: Do you feel like you're speaking for when you say.
• 48:02
  Speaker 3: Week leadership in general, corporate leadership, policymakers, I think civil society.
• 48:08
  Speaker 3: I think we all need to do a better job
• 48:10
  Speaker 3: of listening to people.
• 48:12
  Speaker 1: Know.
• 48:12
  Speaker 3: We've published a book in October called Governing the Machine
• 48:15
  Speaker 3: where we outline nine categories of risk, and each of
• 48:18
  Speaker 3: those categories is very meaningful, and we need to be
• 48:22
  Speaker 3: taking those into account when we're talking about how people
• 48:24
  Speaker 3: and why people should be using AI. So if your
• 48:29
  Speaker 3: concern is privacy, we can't dismiss that. We need to
• 48:32
  Speaker 3: talk about how we're going to address your privacy concerns
• 48:35
  Speaker 3: before we can expect you to be using it. I
• 48:37
  Speaker 3: think we need to be doing a better job of
• 48:40
  Speaker 3: having a nuanced conversation. Well, first of all, we're telling
• 48:43
  Speaker 3: people how we're using AI. Too many people don't know
• 48:46
  Speaker 3: that they have been using it all day, every day,
• 48:49
  Speaker 3: unlocking their phones, reading their news feeds, scrolling through social media.
• 48:53
  Speaker 3: We need to let people know that they are using it.
• 48:57
  Speaker 3: Then we need to let people know what safe use looks.
• 49:00
  Speaker 3: It's like we need to be establishing what the frameworks
• 49:03
  Speaker 3: are that companies and organizations are putting in place so
• 49:06
  Speaker 3: they know who to trust and what trustworthy governmance looks.
• 49:09
  Speaker 1: Like. All of this makes sense, except it doesn't look
• 49:12
  Speaker 1: like anybody in the industry is even remotely thinking about this.
• 49:17
  Speaker 2: Whether it's Open AI, whether it's.
• 49:18
  Speaker 1: Clawed, whether it's the other Gemini, whether it's rock everybody.
• 49:25
  Speaker 1: I mean, when you look at the amount of money
• 49:27
  Speaker 1: being invested in infrastructure to build out even more AI.
• 49:31
  Speaker 1: That means there's a whole bunch of investors looking to
• 49:33
  Speaker 1: get their money extract profits out of this. Nobody seems
• 49:37
  Speaker 1: to be worried about guardrails. In fact, I look at
• 49:40
  Speaker 1: the whenever a new update comes out, it feels like,
• 49:45
  Speaker 1: you know, they's we're so powerful, we're not sure we
• 49:49
  Speaker 1: can you know, we're not sure that the new cybersecurity
• 49:52
  Speaker 1: can handle it. It's like a marketing employ not actually
• 49:55
  Speaker 1: a serious attempt to padd.
• 50:01
  Speaker 2: Doing baby steps.
• 50:02
  Speaker 3: Well, you're not wrong. A report last year from McKenzie
• 50:05
  Speaker 3: said that over eighty eight percent of companies are using
• 50:07
  Speaker 3: AI in at least one pivotal function. That was a
• 50:10
  Speaker 3: year ago. It's probably a much higher number now, but
• 50:13
  Speaker 3: at that point only a third had any AI governance
• 50:16
  Speaker 3: in place. The World Economic Forum had a report earlier
• 50:19
  Speaker 3: this year that said only less than one percent of
• 50:23
  Speaker 3: companies have strong AI governance frameworks in place. So you
• 50:28
  Speaker 3: are correct that it is not something we're seeing a
• 50:30
  Speaker 3: lot of our hearing a lot about. Although I have
• 50:34
  Speaker 3: the privilege of working with companies that really do prioritize
• 50:36
  Speaker 3: AI governance, so I can tell you the good news
• 50:39
  Speaker 3: is there is alignment across industry for companies, for leaders
• 50:44
  Speaker 3: that care about AI governance, You'll not see a lot
• 50:47
  Speaker 3: of distinction between what those best practices are. Across the
• 50:51
  Speaker 3: companies and organizations that have strong AI governance frameworks, You'll
• 50:55
  Speaker 3: see visibility into how they're using AI. You'll see accountability
• 51:00
  Speaker 3: on the top. It has to start at the top,
• 51:02
  Speaker 3: but then across divisions so people understand who's the point
• 51:05
  Speaker 3: person what they should be looking for. You'll see not
• 51:08
  Speaker 3: just AI principles, but operationalization.
• 51:11
  Speaker 1: I feel like you're describing what a company that might
• 51:15
  Speaker 1: adopt an AI platform into their business and integrate it,
• 51:19
  Speaker 1: that they may be taking care in trying to do
• 51:23
  Speaker 1: these things. That's not who I'm talking about. I'm talking
• 51:26
  Speaker 1: about the purveyors themselves, whether it's Open AI, anthropic Google,
• 51:31
  Speaker 1: with Gemini or ix whatever.
• 51:34
  Speaker 2: We're calling the Elon Musk operation these days.
• 51:40
  Speaker 1: What evidence that there is any interest in good governance
• 51:44
  Speaker 1: in those florentities.
• 51:45
  Speaker 3: I can tell you about the ones that I work
• 51:46
  Speaker 3: with so in our Badge program for senior executives. In
• 51:50
  Speaker 3: our Agentic AI summit we had this week, we had
• 51:53
  Speaker 3: some of the best minds at Google, Deep Mind, at
• 51:55
  Speaker 3: AWS and Amazon, Microsoft who are being very intentional about
• 52:00
  Speaker 3: their governance frameworks. You can look online to see what
• 52:03
  Speaker 3: they've implemented. You can talk to their senior executives who
• 52:06
  Speaker 3: will be very well versed in what they are doing
• 52:09
  Speaker 3: intentionally and across their companies to make sure they have
• 52:12
  Speaker 3: strong governance in place. But I don't want to dismiss
• 52:15
  Speaker 3: the deployer role because most of their applications that will
• 52:18
  Speaker 3: have access to and that we're currently using, are from
• 52:21
  Speaker 3: those large companies small companies that are using AI, who
• 52:24
  Speaker 3: also have a key role in making sure that it's safe.
• 52:29
  Speaker 1: If the industry is so concerned about governance, why are
• 52:33
  Speaker 1: they fighting, Why are they fighting state based regulation? Why
• 52:36
  Speaker 1: is it so important to them to convince the Trump
• 52:38
  Speaker 1: administration to do whatever it takes to prevent what many
• 52:43
  Speaker 1: of us refer to as the laboratories of democracy and
• 52:45
  Speaker 1: state government's figuring out a way to protect consumers.
• 52:49
  Speaker 2: From the state level.
• 52:50
  Speaker 3: Yeah, and it's a fair question. I think, first of all,
• 52:53
  Speaker 3: there's nuance in what different companies are and are not
• 52:55
  Speaker 3: pushing for. But to your question about state versus federal
• 53:00
  Speaker 3: I'm a former general counsel, so I have sympathy into
• 53:02
  Speaker 3: how hard it is to respond to a patchwork of laws.
• 53:05
  Speaker 3: I think it's in everyone's best interest that there are
• 53:07
  Speaker 3: certainty and clarity, not just across the country, but across
• 53:10
  Speaker 3: the globe. I mean, we're talking about AI. It doesn't
• 53:13
  Speaker 3: have boundaries, and users across the globe are going to
• 53:16
  Speaker 3: need that is safe and lawful. So the war we
• 53:20
  Speaker 3: have clarity and certainty and uniformity, the easier it is
• 53:23
  Speaker 3: to be compliant.
• 53:25
  Speaker 2: I understand that.
• 53:26
  Speaker 1: But if you have a dysfunctional Congress, it is not
• 53:31
  Speaker 1: a functioning body of government. They're at war with each other. A.
• 53:37
  Speaker 1: We don't have a federal government interested in these safeguards,
• 53:41
  Speaker 1: so why step on the state governments from Tronta, I.
• 53:44
  Speaker 4: Can't speak to that.
• 53:45
  Speaker 3: What I can say is I do personally have some
• 53:48
  Speaker 3: great experience of good things happening, the very thoughtful, proactive
• 53:52
  Speaker 3: things happening in the government space. So for instance, at
• 53:56
  Speaker 3: our agentic AI summit this week, we got to talk
• 53:59
  Speaker 3: with the Acting Secretary of Labor who's being very forward
• 54:03
  Speaker 3: thinking and proactive about preparing the workforce and employers for
• 54:07
  Speaker 3: an AI economy. They have an AI literacy framework. Most
• 54:11
  Speaker 3: people don't know what AI literacy is, and so they've
• 54:13
  Speaker 3: broken it down for employers so they can adopt and
• 54:16
  Speaker 3: learn from this framework. They have text based AI literacy tools,
• 54:20
  Speaker 3: and that's really important because when we're thinking about AI literacy,
• 54:25
  Speaker 3: not every American has access to li FI, and so
• 54:28
  Speaker 3: if you have an application online, many people will not
• 54:33
  Speaker 3: have access to it. So they've created a digestible text
• 54:36
  Speaker 3: based program where people can get a ten minute overview
• 54:39
  Speaker 3: and introduction to AI. That will not make everybody AI
• 54:43
  Speaker 3: ready workforce in terms of being an engineer or a
• 54:46
  Speaker 3: computer scientist, but at least gets people over the hump
• 54:49
  Speaker 3: of knowing what AI is and how they're using it.
• 54:51
  Speaker 1: I feel like we're trying to do multiple things here.
• 54:54
  Speaker 1: That sounds like we're on the education side, how to
• 54:57
  Speaker 1: get people up to speed, how to get people comfortable
• 55:00
  Speaker 1: using if it was like trying to teach me bodies
• 55:02
  Speaker 1: a personal computer.
• 55:04
  Speaker 2: Well, what about the consumer protection?
• 55:07
  Speaker 1: And that's where it seems as if the industry is
• 55:11
  Speaker 1: petrified in any attempt at a regulation that's consumer protection
• 55:17
  Speaker 1: because they say, well, that's stepping on our ability to
• 55:20
  Speaker 1: be able to either beat China in the AI race
• 55:25
  Speaker 1: or keep up with China.
• 55:27
  Speaker 3: You're right, we need to have our eye on the
• 55:29
  Speaker 3: state houses and the congresses across the globe to understand
• 55:33
  Speaker 3: what new laws are coming down. But we also should
• 55:36
  Speaker 3: not lose sight of where I think most of this
• 55:38
  Speaker 3: plays out, and that's in the courthouses. I think most
• 55:41
  Speaker 3: of how AI is regulated will come down to how
• 55:45
  Speaker 3: courts are deciding how current laws on the books will
• 55:48
  Speaker 3: be applied to AI use. We have three chapters in
• 55:51
  Speaker 3: the book on how different countries across the globe have
• 55:57
  Speaker 3: laws currently in place that will be impactful. We've seen
• 56:00
  Speaker 3: it play out in IP and copyright that will only
• 56:03
  Speaker 3: increase in the years to come. We've seen it in
• 56:07
  Speaker 3: several other privacy areas and so forth. I think we
• 56:10
  Speaker 3: can expect they are all eminating out of Europe. Right
• 56:12
  Speaker 3: we have no way of case law here in the
• 56:14
  Speaker 3: US as well. For sure, I think will increasingly see
• 56:17
  Speaker 3: torts law, consumer protection laws, contract laws where we'll be
• 56:23
  Speaker 3: deciding who has liability because the lawyers are catching on
• 56:27
  Speaker 3: to this and they will make sure that there is
• 56:30
  Speaker 3: liability for those that are taking their eye off the
• 56:32
  Speaker 3: ball in terms of safety and what the negative risks
• 56:37
  Speaker 3: and impacts could result in.
• 56:39
  Speaker 1: Let's assume we had a functioning federal legislative branch that
• 56:44
  Speaker 1: was going to look at this not as seeing which
• 56:46
  Speaker 1: side is going to contribute the most amount of money
• 56:48
  Speaker 1: to their mentorm because that's the other part of this.
• 56:50
  Speaker 1: All of the AI associated super PACs I think are
• 56:55
  Speaker 1: sort of warping the conversation on regulation. Let's assume we
• 56:58
  Speaker 1: didn't have this political cloud hanging over what would what
• 57:05
  Speaker 1: is a recommendation of what first step regulation.
• 57:10
  Speaker 2: Would look like with AI poduts and what.
• 57:15
  Speaker 1: Entity in the government is best equipped to regulate these ais.
• 57:20
  Speaker 3: It's a great question. I think there's more. We need
• 57:25
  Speaker 3: more certainty on what the expectations are out of companies.
• 57:29
  Speaker 3: We need to understand the basic question with AI use
• 57:34
  Speaker 3: that we always need to be able to answer, which
• 57:36
  Speaker 3: is for who could this fail? We need to make
• 57:38
  Speaker 3: sure that AI deployment are designed around thinking about what
• 57:42
  Speaker 3: the human use cases are and what the actual applications are.
• 57:46
  Speaker 3: And I think there's a role for every agency and government.
• 57:50
  Speaker 3: They're all going to be using AI personally if they're
• 57:52
  Speaker 3: not already. We know there's an executive order mandating it
• 57:55
  Speaker 3: being used across agencies as well as the oversight, but
• 57:58
  Speaker 3: I don't want to lose sight of the other ways
• 58:01
  Speaker 3: that this is where leadership is popping up. So with
• 58:05
  Speaker 3: equal AI, we've been doing an AI literacy tour across
• 58:08
  Speaker 3: the country to listen to people, to hear what they're seeing,
• 58:11
  Speaker 3: what they're worried about, but also to elevate leadership. What
• 58:15
  Speaker 3: it looks like when AI leadership is what it looks
• 58:21
  Speaker 3: like when we have AI leadership. So for instance, we've
• 58:24
  Speaker 3: been to Tennessee, We've been to Arizona. We're having conversations
• 58:28
  Speaker 3: and cities across the country where we're seeing mayors who
• 58:31
  Speaker 3: are using it for smart traffic management, creating resource hubs
• 58:35
  Speaker 3: so that small businesses are in touch with academics training
• 58:39
  Speaker 3: our next gen, but also getting small businesses AI ready.
• 58:44
  Speaker 3: I think there's a lot of tools that we have
• 58:46
  Speaker 3: now at our disposal where we have foundations of leadership,
• 58:50
  Speaker 3: and so we just need to understand what does that
• 58:52
  Speaker 3: look like. You know, at ASU where they are leaning
• 58:56
  Speaker 3: into AI use, they are giving students the capabilities of
• 59:00
  Speaker 3: generative models and even how will I am teaching agentic
• 59:04
  Speaker 3: AI used to their students. So I think we actually
• 59:08
  Speaker 3: have a lot of opportunities for leadership that we shouldn't
• 59:11
  Speaker 3: be overlooking.
• 59:12
  Speaker 1: I hear you, but this I mean, talk about scattershot
• 59:14
  Speaker 1: like you just described, seems the scatter shot and frankly,
• 59:21
  Speaker 1: and again I'm liking you'd like defend all of these
• 59:24
  Speaker 1: and and I don't, I don't mean to try to
• 59:26
  Speaker 1: put you on the defensive, but it does appear to
• 59:29
  Speaker 1: be that it's all scattershot, and it's really those that
• 59:32
  Speaker 1: have the ability to to maybe even curiosity to be
• 59:38
  Speaker 1: first movers and to learn this stuff. We'll do it,
• 59:42
  Speaker 1: but we I mean, it does feel as if this
• 59:45
  Speaker 1: is way ahead of anny guardrails that are even remotely
• 59:49
  Speaker 1: ready to be used.
• 59:50
  Speaker 3: You know, I think you're getting at something check that
• 59:52
  Speaker 3: we need to be prepared for. AI is a disruptor,
• 59:56
  Speaker 3: and I think we need to look at this as
• 59:58
  Speaker 3: a disruption for good. We can't operate in silos anymore.
• 1:00:01
  Speaker 3: AI connects us all and makes us all dependent on
• 1:00:05
  Speaker 3: one another to ensure that we know how each other
• 1:00:08
  Speaker 3: fit into the use cases. We can't imagine that only
• 1:00:12
  Speaker 3: within our company are we going to be impacted by
• 1:00:14
  Speaker 3: our AI use We can't imagine only within our state.
• 1:00:17
  Speaker 3: There's overlap across boundaries when we're talking about AI, and
• 1:00:21
  Speaker 3: so we're going to have to break silos We're going
• 1:00:23
  Speaker 3: to have to rethink culture in organizations where you can't
• 1:00:27
  Speaker 3: just pinpoint which agency or which department is in charge
• 1:00:32
  Speaker 3: of AI. It is across organizations, it is across states,
• 1:00:36
  Speaker 3: and you're right, it's dissipated. It's not the way we're constructed.
• 1:00:39
  Speaker 3: But we're going to have to rethink that's.
• 1:00:41
  Speaker 1: Talking about it.
• 1:00:43
  Speaker 2: I guess, agentic AI, do you.
• 1:00:46
  Speaker 1: Really think we're ready for AI to make decisions without
• 1:00:51
  Speaker 1: a human interface?
• 1:00:52
  Speaker 3: I think there are a lot of concerns about the
• 1:00:56
  Speaker 3: state of readiness with agendic AI because of this statistics.
• 1:01:00
  Speaker 3: We talked about that if less than one percent of
• 1:01:03
  Speaker 3: companies have strong AI governance in place, they are not
• 1:01:07
  Speaker 3: prepared for AI deployment, let alone agentic AI deployment. I
• 1:01:11
  Speaker 3: mentioned we had an agentic AI summit this week where
• 1:01:14
  Speaker 3: we were looking at what is the optimal use cases
• 1:01:17
  Speaker 3: of a dentic AI. What does it look like if
• 1:01:20
  Speaker 3: we get this right. We looked at challenges, We looked
• 1:01:23
  Speaker 3: at the map between where we are today and how
• 1:01:26
  Speaker 3: we will need to prioritize the steps to get to
• 1:01:29
  Speaker 3: the optimal end state. And you can only do this
• 1:01:32
  Speaker 3: if you have strong governance in place. And again I
• 1:01:35
  Speaker 3: think we need to break down what we mean by governance.
• 1:01:38
  Speaker 3: You know, too many people think it's a government responsibility
• 1:01:42
  Speaker 3: or a stop gapped innovation. We really need to understand
• 1:01:46
  Speaker 3: that governance is something that leadership needs to be held
• 1:01:50
  Speaker 3: accountable for and take ownership of whatever your organization is,
• 1:01:54
  Speaker 3: because you're going to be using AI, and we need
• 1:01:57
  Speaker 3: to be realizing that it is the norms culture that
• 1:02:00
  Speaker 3: practices that build trust and really unlock the benefits of
• 1:02:05
  Speaker 3: this innovation.
• 1:02:07
  Speaker 1: Is you know if and this could happen because of
• 1:02:11
  Speaker 1: the populist backlash that I think is coming right now
• 1:02:13
  Speaker 1: with AI. Right some of it has to do with
• 1:02:15
  Speaker 1: what I talked about social media. Others will be fear
• 1:02:17
  Speaker 1: of AI job displacement. And you can just feel that
• 1:02:20
  Speaker 1: there is certainly exploitable anger out there in our politics
• 1:02:24
  Speaker 1: that you could see if Congress passed the law next
• 1:02:28
  Speaker 1: that said no AI, you cannot use agentic AI.
• 1:02:37
  Speaker 2: Period.
• 1:02:37
  Speaker 1: There has to be a human interface at the very
• 1:02:40
  Speaker 1: very end, whether it's confirming a purchase, confirming a decision
• 1:02:47
  Speaker 1: that it cannot be left only to the AI platform.
• 1:02:55
  Speaker 2: What would the industry say to something.
• 1:02:57
  Speaker 3: I think it would say, you're a little late because
• 1:02:59
  Speaker 3: it is being deployed. So we cannot slow down innovation.
• 1:03:03
  Speaker 3: We can speed up governance. That's our only option. Governance
• 1:03:08
  Speaker 3: is the seatbelts in a car. It's the speed limits,
• 1:03:12
  Speaker 3: it's knowing there's an a doometer. We wouldn't get in
• 1:03:14
  Speaker 3: a car if we wouldn't if we weren't sure that
• 1:03:18
  Speaker 3: we have these.
• 1:03:18
  Speaker 1: The industry fought seatbelts literally until the debts piled up.
• 1:03:23
  Speaker 1: I mean, are we going to have the industry fight
• 1:03:26
  Speaker 1: regulation literally until there are what we have right now
• 1:03:31
  Speaker 1: with social media a pile up of lawsuits that hey,
• 1:03:35
  Speaker 1: they made a defective product.
• 1:03:37
  Speaker 3: Well, that's why we need to have more of alignment
• 1:03:40
  Speaker 3: on what these best practices are, What are the safeguards
• 1:03:44
  Speaker 3: that everyone should be adopting when they're using AI, because
• 1:03:47
  Speaker 3: then we know what it looks like to be doing this. Well.
• 1:03:50
  Speaker 3: I think at the end of the day, we've seen
• 1:03:53
  Speaker 3: time and again that people will not adopt innovation. I mean,
• 1:03:57
  Speaker 3: look at the ROI on investment. You see tremendous investment
• 1:04:01
  Speaker 3: in AI. We're not seeing the ROI for many companies,
• 1:04:04
  Speaker 3: and I'm very convinced, and the data show it's because
• 1:04:08
  Speaker 3: they don't have governance in place. And because they haven't
• 1:04:10
  Speaker 3: taken the time to deploy AI literacy.
• 1:04:14
  Speaker 1: Is there anything to be learned as we as we
• 1:04:17
  Speaker 1: try to catch up on governments governance with AI about
• 1:04:20
  Speaker 1: what we didn't do with social media.
• 1:04:24
  Speaker 3: Yeah, there's a lot of lessons to be learned. Where
• 1:04:26
  Speaker 3: to begin, We need to first of all, understand the
• 1:04:30
  Speaker 3: pace we are removed quickly with social media. I think
• 1:04:36
  Speaker 3: that innovation was adopted in record speed. For past innovations,
• 1:04:42
  Speaker 3: usually it takes decades for adoption that happened in a
• 1:04:45
  Speaker 3: pretty integrated way within a decade. Within less than that,
• 1:04:48
  Speaker 3: AI will continue to scale at a pace that is
• 1:04:51
  Speaker 3: exponentially higher than that. So I think any comfort people
• 1:04:55
  Speaker 3: can take in waiting should be disabused. That there's no
• 1:05:00
  Speaker 3: opportunity to wait. AI is being used in our daily
• 1:05:05
  Speaker 3: life every day. It is being used in our workplaces,
• 1:05:08
  Speaker 3: and so there needs to be a clear path towards
• 1:05:12
  Speaker 3: ensuring its safety and ensuring there's more agency that more
• 1:05:15
  Speaker 3: people understand why and how to use AI. I mean,
• 1:05:19
  Speaker 3: we're seeing these very problematic adoption gaps, not just across
• 1:05:22
  Speaker 3: the fifty percent of the US that is not interested
• 1:05:25
  Speaker 3: in adopting AI, but we see a gender gap in
• 1:05:29
  Speaker 3: age gap, education and wealth, and even a regional gap
• 1:05:33
  Speaker 3: where in the middle of the country there's more anxiety
• 1:05:37
  Speaker 3: towards AI than on the coasts. These are all understandable.
• 1:05:40
  Speaker 3: It's communities that have deep concerns that need to be
• 1:05:43
  Speaker 3: heard and addressed before they're going to be going to
• 1:05:45
  Speaker 3: use AI.
• 1:05:48
  Speaker 1: Have you had any luck with the AI platform companies
• 1:05:53
  Speaker 1: in understanding what they have or do you feel like
• 1:05:55
  Speaker 1: they're just in a hurried interday.
• 1:05:58
  Speaker 3: I think there's several common versations going on right now.
• 1:06:01
  Speaker 3: There's certainly that competition once amongst one another, with amongst.
• 1:06:07
  Speaker 1: Us open AI trial. It's not reassuring to watch all
• 1:06:14
  Speaker 1: of this sort of dirt get circulated out, but you're
• 1:06:17
  Speaker 1: just sitting there going it's just a bunch.
• 1:06:20
  Speaker 2: Of people trying to make more money off of us.
• 1:06:21
  Speaker 1: Again, this doesn't feel like anybody's actually been concerned about
• 1:06:25
  Speaker 1: what the technology is.
• 1:06:25
  Speaker 2: Going to do to the public.
• 1:06:27
  Speaker 3: Well, I think the more we can do to empower
• 1:06:29
  Speaker 3: the public, policymakers, lawyers to understand what good outcomes look like,
• 1:06:35
  Speaker 3: the better off we are. I think you know it's
• 1:06:39
  Speaker 3: in You're right, It's an interesting look into what's happening
• 1:06:41
  Speaker 3: under the hood. But again, people have agency here and
• 1:06:45
  Speaker 3: there's many leaders across the spectrum. Journalists have brought it
• 1:06:49
  Speaker 3: to account many of the AI use cases that have
• 1:06:51
  Speaker 3: been problematic, and that's where you see changes. So the
• 1:06:54
  Speaker 3: more there's clarity in what good looks like and the
• 1:06:58
  Speaker 3: more we're able to pressure tests what some of these
• 1:07:01
  Speaker 3: problematic outcomes look like, the more we can have our
• 1:07:05
  Speaker 3: expectations in place. But again, I wouldn't lose sight of
• 1:07:08
  Speaker 3: some of the forces, the market forces we have in place,
• 1:07:12
  Speaker 3: whether it's ROI or the litigation we're seeing increasingly in
• 1:07:15
  Speaker 3: the ports. Last year there was a the AI Index report.
• 1:07:19
  Speaker 3: They said there was a six times increase in litigation
• 1:07:22
  Speaker 3: over sixty years. I'm curious to see how much exponentially
• 1:07:26
  Speaker 3: higher that is now.
• 1:07:27
  Speaker 1: All right, let's try to let's try to end on.
• 1:07:30
  Speaker 1: Give me some best practices of entities out there that
• 1:07:35
  Speaker 1: do seem to be prioritizing governments.
• 1:07:37
  Speaker 3: When you're seeing governance, there's at least five overlapping indicators.
• 1:07:43
  Speaker 3: There's visibility. Most companies have not done a survey to
• 1:07:47
  Speaker 3: understand where they are using AI across enterprise.
• 1:07:52
  Speaker 1: And you think there's some companies their CEO doesn't even
• 1:07:55
  Speaker 1: know where yeah AI is being deployed.
• 1:07:57
  Speaker 3: It was a very problematic study out year ago where
• 1:08:01
  Speaker 3: they looked for at h R uses of AI, which
• 1:08:04
  Speaker 3: is one of the most predominant use cases of AI.
• 1:08:07
  Speaker 3: They surveyed the global companies and about eighty eight percent
• 1:08:10
  Speaker 3: of the chief HR officers confirm they're using AI in
• 1:08:13
  Speaker 3: HR functions. At those same companies, about sixty two sixty
• 1:08:17
  Speaker 3: four percent of CEOs indicated they were using AI and
• 1:08:20
  Speaker 3: their HAAR functions. Forty eight percent of general counsels indicated
• 1:08:25
  Speaker 3: the same. So yes, I think there is a huge
• 1:08:29
  Speaker 3: problem of people not knowing, not having visibility into how AIUS.
• 1:08:33
  Speaker 1: Is inside their own inside their own companies.
• 1:08:37
  Speaker 3: We can do this in our own homes too. Second
• 1:08:40
  Speaker 3: of all, you have to have accountability. You have to
• 1:08:42
  Speaker 3: have someone in your C suite who cares about this,
• 1:08:45
  Speaker 3: who takes ownership of this, who make sure that there's
• 1:08:47
  Speaker 3: the budget. But even equally important is that there's alignment
• 1:08:51
  Speaker 3: across entervice. Too many people think that this is the
• 1:08:54
  Speaker 3: innovations of the past where you can assign it to
• 1:08:57
  Speaker 3: one department, and AI doesn't work that way. AI is every.
• 1:09:01
  Speaker 1: News media will have a digital team it's like all
• 1:09:03
  Speaker 1: media is on digital. I remember thinking that back then. So, yeah,
• 1:09:07
  Speaker 1: there's such an AI team. It's like saying you're.
• 1:09:11
  Speaker 3: Going to have a deskot you got it, you got it.
• 1:09:14
  Speaker 3: You have to have that C suite level buy in
• 1:09:18
  Speaker 3: and interest. But then you also need that because a
• 1:09:22
  Speaker 3: lot of this is going to play out in the
• 1:09:23
  Speaker 3: front lines. Your employees, your consumers are going to find
• 1:09:27
  Speaker 3: some of the errors play out, and you need them
• 1:09:30
  Speaker 3: to know who to report them to and that it's
• 1:09:32
  Speaker 3: safe to be reported.
• 1:09:33
  Speaker 1: Up the play is the realistic first regulation, then just
• 1:09:37
  Speaker 1: simply transparency.
• 1:09:39
  Speaker 3: Transparency. I think that's a complicated issue because it has
• 1:09:42
  Speaker 3: to be stated in such a way that could be
• 1:09:44
  Speaker 3: understood meaningfully.
• 1:09:46
  Speaker 2: Well, take surveillance pricing.
• 1:09:48
  Speaker 1: I know New York State passed the law about surveillance
• 1:09:50
  Speaker 1: pricing that if it was done with AI, it had
• 1:09:53
  Speaker 1: to be set had to say so, and so New
• 1:09:56
  Speaker 1: York does this regulation. But even if you've got to,
• 1:09:59
  Speaker 1: you know, the a good example to wash it post
• 1:10:01
  Speaker 1: it had to put a little disclaimer that they were
• 1:10:05
  Speaker 1: using surveillance pricing on their subscription services. And somebody who
• 1:10:09
  Speaker 1: lived in Oklahoma got that warning. Even though Oklahoma didn't
• 1:10:13
  Speaker 1: have that law. New York State has that law. But
• 1:10:15
  Speaker 1: it felt like, well, all right, that's a case where
• 1:10:17
  Speaker 1: transparency at least is.
• 1:10:19
  Speaker 2: A way to at least get the consumers something.
• 1:10:22
  Speaker 3: Transparency is a start, but we don't want the human
• 1:10:25
  Speaker 3: fatigue of checking. I'll accept the cookies so I can
• 1:10:28
  Speaker 3: get quickly to the website of where I want to go,
• 1:10:31
  Speaker 3: and we don't want it to be written in a
• 1:10:34
  Speaker 3: way that they can't understand. So I think absolutely transparency
• 1:10:38
  Speaker 3: is key. Where are you using AI? What have you
• 1:10:41
  Speaker 3: tested for? I mean, let's talk about in the medical
• 1:10:43
  Speaker 3: use cases, which are some of the most exciting use
• 1:10:45
  Speaker 3: cases of AI. If you're going to tell me that
• 1:10:47
  Speaker 3: your cancer detection is eighty eight percent successful, I need
• 1:10:51
  Speaker 3: to know for whom. I need to know if that
• 1:10:53
  Speaker 3: is true, for the patients that you're talking to, were
• 1:10:56
  Speaker 3: they appropriately represented in the satisfaction rate, in the success
• 1:11:01
  Speaker 3: rate of that product? For whom could this fail?
• 1:11:05
  Speaker 1: Are we going to get most regulation due to court
• 1:11:07
  Speaker 1: fights rather than due to legislation? Is that your is
• 1:11:10
  Speaker 1: that real mean? And what that means is civil litigation?
• 1:11:13
  Speaker 3: I think in the short term there's a lot happening
• 1:11:16
  Speaker 3: in the courts that people should not overlook a lot
• 1:11:18
  Speaker 3: that will impact their use, their rights, their company. That
• 1:11:22
  Speaker 3: if they are not keeping their eye on what's happening
• 1:11:25
  Speaker 3: across the country and frankly across the globe in the courthouses,
• 1:11:28
  Speaker 3: they're missing a lot of the liabilities they will be
• 1:11:30
  Speaker 3: walking into if they do not have good governance in place.
• 1:11:33
  Speaker 1: I'll say this, if you're a legislator, then you're watching
• 1:11:36
  Speaker 1: this get Her book because it does sort of in
• 1:11:41
  Speaker 1: a very thought in a good way, layout, sort of
• 1:11:45
  Speaker 1: how garden. You're trying to figure out what guardrails to build,
• 1:11:49
  Speaker 1: and I feel like your book does sort of layout.
• 1:11:52
  Speaker 2: Okay, if you want to do this guardrail, this is
• 1:11:54
  Speaker 2: the way to do it. Thank you, check Ary, appreciate.
• 1:11:56
  Speaker 1: You saying that.
• 1:11:57
  Speaker 3: Thank you so much for having me.
• 1:12:08
  Speaker 1: All right, you have transitioned from governments into the private sector.
• 1:12:12
  Speaker 1: Still in the AI space, let's talk about AI security,
• 1:12:15
  Speaker 1: especially We've got this China summit coming up between she
• 1:12:19
  Speaker 1: and Trump and apparently AI governance is now going to
• 1:12:23
  Speaker 1: be on the agenda, So let's start there. What should
• 1:12:27
  Speaker 1: global AI governance look like between superpowers and how and
• 1:12:32
  Speaker 1: is nuclear proliferation or non proliferation the model.
• 1:12:38
  Speaker 5: So, first, when we think about AI security, there's really
• 1:12:41
  Speaker 5: two lenses.
• 1:12:43
  Speaker 4: To think about it through.
• 1:12:44
  Speaker 5: One is the risk that AI brings, for example, in
• 1:12:48
  Speaker 5: accelerating the depth and speed of cyber attacks. And the
• 1:12:52
  Speaker 5: second is the risk of AI if models are not secure,
• 1:12:56
  Speaker 5: if models can be poisoned.
• 1:12:59
  Speaker 4: Them.
• 1:13:00
  Speaker 5: And then if they're embedded into whether it's a decision
• 1:13:03
  Speaker 5: about whether to loan somebody money or decision about we're
• 1:13:06
  Speaker 5: in the electricity grid.
• 1:13:07
  Speaker 4: Thank you so much.
• 1:13:09
  Speaker 5: One optimizes, then they bring additional risks. So we think
• 1:13:13
  Speaker 5: about it in both.
• 1:13:14
  Speaker 4: Of those lenses.
• 1:13:16
  Speaker 5: And to your point about global governance, it's the question
• 1:13:19
  Speaker 5: we used to have often about cyber governance.
• 1:13:22
  Speaker 4: What are the rules in the room? How can countries
• 1:13:25
  Speaker 4: use these duel use technologies.
• 1:13:27
  Speaker 5: They're both defensive they help us secure infrastructure, for example,
• 1:13:31
  Speaker 5: and they're offensive they help between countries. They maybe used
• 1:13:35
  Speaker 5: offensively in the context of a crisis or conflict to
• 1:13:37
  Speaker 5: destabilize an infrastructure.
• 1:13:39
  Speaker 4: So what should the rules of the will be.
• 1:13:40
  Speaker 5: When fundamentally there are no borders of the rules.
• 1:13:43
  Speaker 1: Well, it's similar to nukes, right, we had nuclear energy
• 1:13:46
  Speaker 1: and one set of rules versus nuclear weapons, right, positive
• 1:13:49
  Speaker 1: and negative.
• 1:13:51
  Speaker 5: It's very different in that it is a private sector
• 1:13:55
  Speaker 5: developed technology that's broadly available versus nukes that are prime
• 1:14:00
  Speaker 5: gmarily developed by governments, was very strict rules.
• 1:14:03
  Speaker 4: Around for the creation.
• 1:14:03
  Speaker 1: Funny you say that I've talked to I have a
• 1:14:05
  Speaker 1: retired general friend of mine who is obsessed with the
• 1:14:11
  Speaker 1: fact that he thinks AI never should have been allowed
• 1:14:15
  Speaker 1: to be developed with the private sector first, that there
• 1:14:18
  Speaker 1: always should have been like with nuclear technology, where it
• 1:14:22
  Speaker 1: was essentially government driven with academic research and sort of
• 1:14:26
  Speaker 1: bringing the private sector into the government sphere and the
• 1:14:29
  Speaker 1: internet itself private sector into the government sphere. It's too
• 1:14:34
  Speaker 1: late to go there now with AI. But was that
• 1:14:35
  Speaker 1: a mistake? You know?
• 1:14:37
  Speaker 4: The power of the American innovation system is.
• 1:14:40
  Speaker 5: That we have the laws, the financial markets, and the
• 1:14:47
  Speaker 5: investment in R and D that happens in the private sector.
• 1:14:49
  Speaker 4: That means technology by.
• 1:14:50
  Speaker 5: Drug r and D drugs is primarily coming out of
• 1:14:53
  Speaker 5: the private sector. Yes, there's some investment from government, but
• 1:14:57
  Speaker 5: it's mostly there. So I think the strength of our
• 1:14:59
  Speaker 5: system is that innovation comes out of the private sector.
• 1:15:03
  Speaker 4: So should have could a I think it's just it's
• 1:15:07
  Speaker 4: it doesn't.
• 1:15:08
  Speaker 1: Matter what the philosophy is. We are where we are. So,
• 1:15:13
  Speaker 1: so let's talk about you talk about cyber and a
• 1:15:16
  Speaker 1: global and you try you develop something in the Biden
• 1:15:21
  Speaker 1: administration having to do with at least coming to a
• 1:15:26
  Speaker 1: collective agreement on RANSI splain.
• 1:15:29
  Speaker 5: Absolutely gold apply for AI, right, it's an interesting approach.
• 1:15:33
  Speaker 4: You're right to apply to AI. You know.
• 1:15:35
  Speaker 5: So in the past, we would often think about the
• 1:15:37
  Speaker 5: big risk of cyber as espionage. We talked for years
• 1:15:40
  Speaker 5: about how China was growing at strategic technology sector by
• 1:15:44
  Speaker 5: stealing intellectual property from America. And you know, governments have
• 1:15:48
  Speaker 5: been trying to steal each other's secrets, whether.
• 1:15:51
  Speaker 4: As human assets as five. But if we're saying that
• 1:15:54
  Speaker 4: moved to digital because it's so much easier. You don't
• 1:15:56
  Speaker 4: have to get a guy into a it's as old
• 1:15:57
  Speaker 4: as a country.
• 1:15:58
  Speaker 1: Bad borders on country exactly. I'm sure the feudal lords
• 1:16:02
  Speaker 1: were also spying on each other, and it's so.
• 1:16:04
  Speaker 4: Much easier in cyberspace.
• 1:16:06
  Speaker 5: You don't have to get a human past a fingerprint
• 1:16:08
  Speaker 5: check into a country. So that was the way we
• 1:16:11
  Speaker 5: looked at it. It changed with the advent of two things.
• 1:16:16
  Speaker 5: One is cryptocurrency and the second a criminal ecosystem that
• 1:16:21
  Speaker 5: essentially built out cyber tools and that enable them to
• 1:16:27
  Speaker 5: use those tools to disrupt companies, infrastructure, hospitals around the
• 1:16:32
  Speaker 5: world and get paid for it easily.
• 1:16:34
  Speaker 1: It's the so called dark web with the dark.
• 1:16:37
  Speaker 5: Web plus the financing right, because the dark web is
• 1:16:41
  Speaker 5: a way that people can just communicate outside the formal
• 1:16:44
  Speaker 5: Internet ecosystem.
• 1:16:46
  Speaker 4: Essentially, as you know.
• 1:16:47
  Speaker 5: Every IP address has a matching mean that makes it
• 1:16:51
  Speaker 5: easier for us to find Amazon dot Com without necessarily
• 1:16:53
  Speaker 5: knowing its Internet from right.
• 1:16:54
  Speaker 2: That's everybody's address exactly right on.
• 1:16:56
  Speaker 5: The Internet dark web, there's just the addresses without the
• 1:16:59
  Speaker 5: match to it is, so people have to know where
• 1:17:01
  Speaker 5: they're going. What changed in ransomware to your point, was
• 1:17:05
  Speaker 5: that you had a criminal ecosystem and now had a
• 1:17:07
  Speaker 5: way to move money outside traditional banking systems and in
• 1:17:11
  Speaker 5: many ways. While there are rules around cryptocurrency anti money
• 1:17:14
  Speaker 5: laundering done by the Financial Action Task Force, they are
• 1:17:18
  Speaker 5: not implemented around the world for various reasons. So as
• 1:17:21
  Speaker 5: a result, you wouldn't have these safe and some countries
• 1:17:24
  Speaker 5: provided safe haven. So Russia, for example, looked away or
• 1:17:28
  Speaker 5: quietly enabled criminals.
• 1:17:31
  Speaker 4: With some ties to their.
• 1:17:34
  Speaker 1: Korea. There was a whole sort of access of maybe
• 1:17:38
  Speaker 1: unfriendly countries to.
• 1:17:39
  Speaker 5: The west that were doing this right exactly, and those
• 1:17:42
  Speaker 5: actors ended up disrupting infrastructure to get paid a ransom,
• 1:17:46
  Speaker 5: and in many cases, like when you think about Britain's
• 1:17:48
  Speaker 5: National Health system, disrupted the operations of hospitals.
• 1:17:52
  Speaker 4: So to them, they're ready to pay.
• 1:17:54
  Speaker 5: So the debate became while for one entity paying a
• 1:17:58
  Speaker 5: ransom could be the fastest way to get back on line,
• 1:18:00
  Speaker 5: every payment.
• 1:18:01
  Speaker 4: Fuels the ecosystem.
• 1:18:02
  Speaker 5: So overall we're enabling these attackers to do more and
• 1:18:06
  Speaker 5: more of these attacks. It's essentially incentivizing them. So in
• 1:18:10
  Speaker 5: the last administration, we formed something called.
• 1:18:12
  Speaker 4: The Counter Ransom Initiative.
• 1:18:14
  Speaker 5: We said, we need a way to coordinate among countries
• 1:18:17
  Speaker 5: to put it in place the practices, getting countries to
• 1:18:20
  Speaker 5: implement anti monitor laundering rules for cryptocurrency, disrupting the operations
• 1:18:25
  Speaker 5: of these ransomware attackers, and fundamentally in each of our countries,
• 1:18:29
  Speaker 5: trying to put in place policies to not allow ransoms.
• 1:18:33
  Speaker 1: How hard is it though, to get I mean, does
• 1:18:36
  Speaker 1: that need to be like a again, does that look
• 1:18:38
  Speaker 1: like a treaty like we have with nuclear weapons and
• 1:18:42
  Speaker 1: what we have with biological weapons is that what this
• 1:18:45
  Speaker 1: would eventually look like.
• 1:18:47
  Speaker 4: So it's a really good question.
• 1:18:49
  Speaker 5: On the positive side, we formed the Counter Ransom are
• 1:18:53
  Speaker 5: Innership that grew to eighty countries, and we had working
• 1:18:56
  Speaker 5: groups that did things like countries sharing with each other's
• 1:18:59
  Speaker 5: threat information. So if a particular technique was used against
• 1:19:01
  Speaker 5: the hospital in the UK, that was shared across the
• 1:19:04
  Speaker 5: governments so that another country would then inform their hospitals
• 1:19:08
  Speaker 5: keep an eye out for that protect against this. In
• 1:19:10
  Speaker 5: that way, that was successful because it was sensitive sharing
• 1:19:13
  Speaker 5: and it expanded.
• 1:19:14
  Speaker 4: It to more countries than had ever been shared together before.
• 1:19:17
  Speaker 5: A second success was in training countries and how to
• 1:19:22
  Speaker 5: look for cryptocurrency money laundering. Cryptocurrency enables cheaper and faster
• 1:19:27
  Speaker 5: transactions for all kinds of people, people sending remittances back home,
• 1:19:30
  Speaker 5: for example, but it also enables payment of ransoms quickly.
• 1:19:34
  Speaker 5: So we among different countries who had more sophisticated systems,
• 1:19:38
  Speaker 5: we trained other countries, and we could also use more
• 1:19:41
  Speaker 5: offensive capabilities to say if a given country is not acting,
• 1:19:45
  Speaker 5: it can be put on a gray list, to say
• 1:19:47
  Speaker 5: other countries say we're not going to do business with you.
• 1:19:50
  Speaker 1: Because you really need to stick.
• 1:19:53
  Speaker 5: The stick is essentially doing routine business transactions not in cryptocurrency.
• 1:19:59
  Speaker 5: So nobody wants wants to be on a gray list,
• 1:20:01
  Speaker 5: which says they're not following the rules of anti money
• 1:20:03
  Speaker 5: laundering because it puts their entire financial system under question.
• 1:20:08
  Speaker 5: As well as another stick, which is sanctioning some of
• 1:20:11
  Speaker 5: these exchanges that were moving a preponderance of illicit money.
• 1:20:15
  Speaker 5: One was called Tornado dot cash, and we did the
• 1:20:17
  Speaker 5: first ever sanctioning of that entity to say we're going
• 1:20:20
  Speaker 5: to bring the traditional rules of enforcing the rules for
• 1:20:24
  Speaker 5: banks to cryptocurrency virtual asset service providers. So we extended
• 1:20:28
  Speaker 5: the traditional rules for fiat currency to cryptocurrency.
• 1:20:31
  Speaker 4: So that's where it worked.
• 1:20:33
  Speaker 1: Where didn't it.
• 1:20:34
  Speaker 5: Work, Yeah, And I guess actually a third one where
• 1:20:36
  Speaker 5: at worked is the governments agreed that no governments would
• 1:20:38
  Speaker 5: pay ransoms.
• 1:20:39
  Speaker 4: That was the third way.
• 1:20:40
  Speaker 5: We got agreement and a public statement saying we all agree,
• 1:20:42
  Speaker 5: and the public statement was important because then we hauled
• 1:20:44
  Speaker 5: ourselves accountable. Where we had more trouble was a fierce
• 1:20:49
  Speaker 5: debate about what countries do to actually disincentivize ransom payments
• 1:20:57
  Speaker 5: by private sector actors. So in the US it was
• 1:21:00
  Speaker 5: a fierce policy debate what we wanted to do was
• 1:21:03
  Speaker 5: say we would announce in six months that ransom payments
• 1:21:07
  Speaker 5: were not permitted unless a permission was requested from the
• 1:21:11
  Speaker 5: Department of Justice for a national security emergency.
• 1:21:13
  Speaker 1: Could be illegal.
• 1:21:15
  Speaker 4: It would be yes, essentially, so.
• 1:21:17
  Speaker 1: I paid a ransom, charges would be brought against the
• 1:21:20
  Speaker 1: person that paid the ransom or they You wanted.
• 1:21:22
  Speaker 5: To pay a ransom, you'd have to come to the
• 1:21:23
  Speaker 5: Department of Justice and they might see that. For example,
• 1:21:26
  Speaker 5: if a hospital wanted to pay a ransom. What we
• 1:21:28
  Speaker 5: wanted to do the goal of this was not only
• 1:21:31
  Speaker 5: to disincentivize paying ransoms, but to incentivize putting in place
• 1:21:35
  Speaker 5: the cybersecurity practices that enabled entities to recover without paying
• 1:21:39
  Speaker 5: a ransom. What do I mean if you have a
• 1:21:41
  Speaker 5: good backup, if you've encrypted your data so even if
• 1:21:44
  Speaker 5: the attackers get it, they can't use it to blackmail you,
• 1:21:47
  Speaker 5: that they have a bunch of sensitive medical information or
• 1:21:49
  Speaker 5: your client's you know, wire instructions that's sensitive. So a
• 1:21:53
  Speaker 5: few practices like that help a company recover without having
• 1:21:58
  Speaker 5: to pay a ransom.
• 1:21:59
  Speaker 4: And what we wanted to do.
• 1:22:00
  Speaker 5: Was essentially say okay, in six months, the easy out
• 1:22:03
  Speaker 5: of a ransom payment is going away.
• 1:22:05
  Speaker 4: Come on, folks, do what you need to do so
• 1:22:07
  Speaker 4: you can recover without it.
• 1:22:09
  Speaker 1: So that puts the burden on the company to have
• 1:22:13
  Speaker 1: as most the most up to date security possible.
• 1:22:19
  Speaker 2: In theory, I get it. On the other hand, you.
• 1:22:24
  Speaker 1: Know, is it should should that fall on the company
• 1:22:28
  Speaker 1: or should that fall on the governments?
• 1:22:33
  Speaker 5: That is one of the core policy debates in cybersecurity. Now,
• 1:22:38
  Speaker 5: to that point, there was responsibility for each and I
• 1:22:41
  Speaker 5: think when you think about the physical world, to your point,
• 1:22:43
  Speaker 5: when you walk into a large corporate building, there are
• 1:22:46
  Speaker 5: guards there that are paid for, you know, by the
• 1:22:49
  Speaker 5: owners of the building, but you then have a police
• 1:22:52
  Speaker 5: department right there, right, so you have both with rules,
• 1:22:55
  Speaker 5: and I think that's very similar in cyber space. So
• 1:22:57
  Speaker 5: in the case of governments, you know, we were conducting
• 1:23:01
  Speaker 5: at that point offensive cyber operations to disrupt the infrastructure
• 1:23:06
  Speaker 5: of these criminals around the world. We were working with
• 1:23:08
  Speaker 5: governments around there were a number of coordinated attempts to
• 1:23:11
  Speaker 5: arrest people. So we'd share quietly, you know, the names
• 1:23:14
  Speaker 5: of people and if they got on a plane, they
• 1:23:16
  Speaker 5: went on vacation, or they tried to you know, enjoy
• 1:23:18
  Speaker 5: their illicit gains in Dubai, you know, they'd be arrested.
• 1:23:21
  Speaker 5: Among the members of the Counter Ransomware Initiative were law enforcement, cooperation,
• 1:23:26
  Speaker 5: and finally government, like I said, creative forums like that
• 1:23:29
  Speaker 5: for information sharing, released advisories and took those steps.
• 1:23:34
  Speaker 4: But on the private.
• 1:23:35
  Speaker 5: Sector side, there is the pretty in this case, basic
• 1:23:38
  Speaker 5: steps like have backups, encrypt your data, make yourselves a
• 1:23:42
  Speaker 5: harder target that when we think about the physical world,
• 1:23:45
  Speaker 5: is very much the equivalent in the digital world.
• 1:23:48
  Speaker 1: Let's go back to so one of the one of
• 1:23:52
  Speaker 1: the reasons that the industry has fought regulation in these
• 1:23:56
  Speaker 1: early days AI adoption has been with this idea that
• 1:24:00
  Speaker 1: we're in a race with China and yet at the
• 1:24:04
  Speaker 1: same time that there's no cooperation on how governments use
• 1:24:09
  Speaker 1: for particularly how they weaponize AIM. We could be in
• 1:24:14
  Speaker 1: a we've already seen some asymmetric warfare successes thanks to
• 1:24:20
  Speaker 1: AI for you know.
• 1:24:22
  Speaker 2: Essentially a smaller country being able to you know, operate
• 1:24:28
  Speaker 2: with the with the bigger countries.
• 1:24:31
  Speaker 1: What do you envision is realistic in trying to have
• 1:24:35
  Speaker 1: some sort of AI red funk between China and the
• 1:24:40
  Speaker 1: United States.
• 1:24:40
  Speaker 2: I mean, is that what we're looking for here.
• 1:24:42
  Speaker 5: So first let's unpack the race with China, because I
• 1:24:44
  Speaker 5: think you're right that term was used a lot and
• 1:24:47
  Speaker 5: we should ask what does that really mean. So from
• 1:24:49
  Speaker 5: an AI perspective, there is AI that's helping in the
• 1:24:52
  Speaker 5: fields of drug discovery.
• 1:24:53
  Speaker 4: I mean, they're currently drug trials. You can accelerate the.
• 1:24:57
  Speaker 1: T should be a border there should be borderless in competition.
• 1:25:01
  Speaker 5: Because today, unfortunately, there are more diseases than there are
• 1:25:05
  Speaker 5: vaccines for than there are drugs for. So that would
• 1:25:08
  Speaker 5: be something where if it brings down the cost of
• 1:25:10
  Speaker 5: drug production enables triality faster, that's a win for all
• 1:25:13
  Speaker 5: of us.
• 1:25:13
  Speaker 4: So in that case, I think the race is a
• 1:25:15
  Speaker 4: race that's arm in arm.
• 1:25:17
  Speaker 5: How do we make the most of this technology for
• 1:25:19
  Speaker 5: the benefit of mankind. Similarly, there's many kinds of positive
• 1:25:25
  Speaker 5: uses of AI. Frankly, there's positive use of AI for cybersecurity.
• 1:25:29
  Speaker 5: It's hard to build secure code. Using AII that's trained
• 1:25:34
  Speaker 5: on more secure code or on some malicious practices can
• 1:25:37
  Speaker 5: then help ensure that code is generated securely against known
• 1:25:40
  Speaker 5: threats and then can be tested as well before deployed.
• 1:25:43
  Speaker 4: That's again a win win for all of us.
• 1:25:47
  Speaker 5: There's the discussion of a race is essentially adoption of
• 1:25:52
  Speaker 5: the most capable AI in national security fields, for example,
• 1:25:56
  Speaker 5: in intelligence collection. In for example and China, here's where
• 1:26:01
  Speaker 5: an authoritarian country has an edge over a democracy. China
• 1:26:04
  Speaker 5: has millions of cameras deployed around the country, Chinese technology
• 1:26:08
  Speaker 5: is deployed around the world.
• 1:26:09
  Speaker 1: They're going to probably surpass us on facial technology simply
• 1:26:13
  Speaker 1: because of their system.
• 1:26:14
  Speaker 5: Of government exactly, and I don't think we would trade
• 1:26:16
  Speaker 5: our system of government. On the other hand, let's recognize
• 1:26:19
  Speaker 5: that an American human spy traveling around the world is
• 1:26:23
  Speaker 5: at greater risk as China trains facial recognition models.
• 1:26:27
  Speaker 4: Then a reverse.
• 1:26:29
  Speaker 5: Case, a Chinese spy would be because the US both
• 1:26:32
  Speaker 5: did not, and we should talk about that. US technologies,
• 1:26:35
  Speaker 5: let's say, in strategic areas like telecommunications, were overcome by
• 1:26:40
  Speaker 5: the Chinese playbooks. So if you go around the world,
• 1:26:42
  Speaker 5: it's wahwack, it's not ericson. It's certainly not.
• 1:26:45
  Speaker 4: Motorola, which was put or put out of business.
• 1:26:49
  Speaker 1: We attempted, the United States did to try to hamstring
• 1:26:54
  Speaker 1: quawe just failed.
• 1:26:57
  Speaker 5: So let's come back to that, because I want to
• 1:26:58
  Speaker 5: make sure I answer the prior. You know, it's so
• 1:27:01
  Speaker 5: when we talk about the race, that's where we mean
• 1:27:03
  Speaker 5: in deployment of AI and national security areas like intelligence
• 1:27:08
  Speaker 5: like by the military, where AI can make a differences.
• 1:27:11
  Speaker 1: I mean, you know, it's funny, it's this is race,
• 1:27:14
  Speaker 1: but you know it's always funny. And there's sometimes the
• 1:27:17
  Speaker 1: arroganinst the west right, where we assume that the other
• 1:27:19
  Speaker 1: side is to see the potential advantage or disadvantage.
• 1:27:23
  Speaker 2: If they if they allow.
• 1:27:25
  Speaker 1: But with AI, the speed of innovation and frankly the
• 1:27:34
  Speaker 1: speed with which you could counter the innovation is all
• 1:27:38
  Speaker 1: happening so fast it feels like an unwinnable race. Meaning
• 1:27:41
  Speaker 1: even if you think you there's no finish line. You
• 1:27:44
  Speaker 1: may be here and in other country is here. But
• 1:27:48
  Speaker 1: they may do this because we've seen these we've seen
• 1:27:51
  Speaker 1: the AI models.
• 1:27:52
  Speaker 2: They all leave each other.
• 1:27:53
  Speaker 1: Who's to say Chinese is a Chinese deepmine model isn't
• 1:27:56
  Speaker 1: going to do the same thing.
• 1:27:57
  Speaker 5: So that's exactly the way to think about your question
• 1:28:01
  Speaker 5: about governance, because I think when we think about AI
• 1:28:04
  Speaker 5: for all the positive use cases, let's arm.
• 1:28:06
  Speaker 4: In arm for the benefit of humanity.
• 1:28:08
  Speaker 5: When we think about the case of AI deployed in military,
• 1:28:13
  Speaker 5: in weapons that's where, harkening back.
• 1:28:16
  Speaker 4: To your question around nuclear technologies, they had the same
• 1:28:20
  Speaker 4: back and forth.
• 1:28:21
  Speaker 5: Right, we were attempting to detect Soviet nuclear submarines, they
• 1:28:25
  Speaker 5: were attempting to detect ours, and generally we would have
• 1:28:28
  Speaker 5: a flywheel, whereas our own detection technologies improved and became
• 1:28:32
  Speaker 5: more sophisticated, we deployed better stealth on our own subs
• 1:28:36
  Speaker 5: as well to protect against theirs. Now, clearly the pace
• 1:28:39
  Speaker 5: of tech was far slower in nuclear.
• 1:28:41
  Speaker 1: Technologies, so we could have a five year advantage a
• 1:28:44
  Speaker 1: ten year advantage, it seems with this at best you're
• 1:28:47
  Speaker 1: lucky to.
• 1:28:47
  Speaker 5: Have a five month anw and the degree of depth
• 1:28:50
  Speaker 5: potentially of incorporation of AI into military decision making can
• 1:28:54
  Speaker 5: be significant.
• 1:28:55
  Speaker 4: Now, I want to be.
• 1:28:56
  Speaker 5: Clear and say military culture around the world world is
• 1:29:01
  Speaker 5: generally more conservative.
• 1:29:03
  Speaker 4: These are people who are trained in the laws of war.
• 1:29:05
  Speaker 5: These are people who know what it means to lose
• 1:29:07
  Speaker 5: a life, and they also know that any technology use
• 1:29:10
  Speaker 5: on offense it's likely to come back to that you
• 1:29:12
  Speaker 5: have to defend against as well. So it's not as
• 1:29:15
  Speaker 5: if I think military communities anywhere around the world rush
• 1:29:19
  Speaker 5: to deploy a new technology that's not fully understood. With
• 1:29:23
  Speaker 5: that said, that is where as China and the US
• 1:29:26
  Speaker 5: talk discussions about how will we incorporate AI into our
• 1:29:33
  Speaker 5: military decision making and most importantly, if there is a misunderstanding,
• 1:29:38
  Speaker 5: how do we communicate. One of the troubling things about
• 1:29:41
  Speaker 5: US China relations is that we haven't had a military.
• 1:29:44
  Speaker 2: To red phone.
• 1:29:45
  Speaker 4: We don't have the exactly you know, the metaphorical right exactly.
• 1:29:49
  Speaker 5: And in the past, with our last peer adversary, the
• 1:29:52
  Speaker 5: Soviet Union, we had both a military red phone and
• 1:29:54
  Speaker 5: a political line.
• 1:30:06
  Speaker 1: Yeah, but we didn't get it until after we hit
• 1:30:09
  Speaker 1: almost a confrontation. It took a crisis to create those safeguards.
• 1:30:15
  Speaker 5: And to be clear, the US has attempted to put
• 1:30:17
  Speaker 5: that in place. The onus is really the Chinese have
• 1:30:19
  Speaker 5: not wanted to put it in place. And the concern
• 1:30:21
  Speaker 5: really is that as a result, as each of us
• 1:30:24
  Speaker 5: start to deploy AI in sensitive areas, there is the
• 1:30:28
  Speaker 5: opportunity for miscommunication and there isn't necessarily the channel to
• 1:30:32
  Speaker 5: resolve it. And that's where discussions among leaders are important,
• 1:30:37
  Speaker 5: as well as putting in place the detection technologies so
• 1:30:42
  Speaker 5: that we and really the intelligence capabilities to try to
• 1:30:45
  Speaker 5: understand how competitors are using AI in their own ecosystem,
• 1:30:49
  Speaker 5: so we can be aware as well and know and
• 1:30:52
  Speaker 5: try our best not to misinterpret. But an ideal world,
• 1:30:55
  Speaker 5: that's where you want the governance in place.
• 1:30:59
  Speaker 1: We go to a large your issue, but you're now
• 1:31:02
  Speaker 1: in the private sector.
• 1:31:06
  Speaker 4: There has been hard always stays in the national security.
• 1:31:09
  Speaker 1: I hear you, I hear you. There is this, there
• 1:31:11
  Speaker 1: is there is The industry is petrified of any regulation
• 1:31:17
  Speaker 1: at the moment. And I am cranky, cynical reporter who
• 1:31:22
  Speaker 1: says tech industry, you you gave us social media and
• 1:31:27
  Speaker 1: totally destroy the information ecosystem and we're supposed to trust
• 1:31:31
  Speaker 1: you with AI. The industry, I feel like, is not
• 1:31:34
  Speaker 1: fully self aware as to how they have brought up.
• 1:31:38
  Speaker 1: The skepticism that is out there about the technology exists
• 1:31:43
  Speaker 1: because of essentially their bad behavior and the lack of
• 1:31:49
  Speaker 1: lack of regulatory or any sort of significant regulation coming
• 1:31:53
  Speaker 1: from the government. And now we're jumping to an entirely
• 1:31:57
  Speaker 1: new technology this field. This feels like this just feels
• 1:32:05
  Speaker 1: like government has no chance to sort of get its monetaries.
• 1:32:11
  Speaker 5: It is always a hard area to think about how
• 1:32:14
  Speaker 5: to regulate a technology that's evolving so quickly, and I
• 1:32:18
  Speaker 5: think there are some lessons we can learn from cyberspace
• 1:32:21
  Speaker 5: and some that are very new. What do I mean,
• 1:32:25
  Speaker 5: As you said, the US government failed to put in
• 1:32:27
  Speaker 5: place regulations for cyberspace for a decade. The last attempt
• 1:32:32
  Speaker 5: with a Lieberman Collins bill in twenty fifteen that's failed.
• 1:32:35
  Speaker 5: After the Colonial Pipeline incident, the President turned to me and.
• 1:32:39
  Speaker 4: Said, and how is this happening?
• 1:32:42
  Speaker 5: How can it be that we have one major pipeline,
• 1:32:45
  Speaker 5: one major oil and gas pipeline supplying the entire East coast,
• 1:32:49
  Speaker 5: only one, and a group of ransomware attackers sitting in
• 1:32:55
  Speaker 5: Saint Petersburg.
• 1:32:56
  Speaker 4: Can can conduct an attack that leaves the company to
• 1:33:00
  Speaker 4: take it offline.
• 1:33:02
  Speaker 5: And as you know, that led to you know, Americans
• 1:33:04
  Speaker 5: at gasoline stations.
• 1:33:05
  Speaker 4: One of the things we learned is never.
• 1:33:06
  Speaker 5: Tell Americans please don't line up and get your gas
• 1:33:08
  Speaker 5: all will be well, because then they immediately will go
• 1:33:12
  Speaker 5: refill their pumps. And at the time we realized were
• 1:33:17
  Speaker 5: reflected on the President's question and said, you know, let's
• 1:33:21
  Speaker 5: do a scrub and see are there regulations that already
• 1:33:24
  Speaker 5: exist that apply. And what we found was that in
• 1:33:27
  Speaker 5: pretty much every sector of critical infrastructure, there were old
• 1:33:31
  Speaker 5: safety regulations that could be reinterpreted with the digital age.
• 1:33:35
  Speaker 4: What do I mean?
• 1:33:36
  Speaker 5: Railroad signaling systems already had regulations to ensure that when
• 1:33:40
  Speaker 5: they were mechanical, the mechanical box was properly secured.
• 1:33:44
  Speaker 4: Who could have access to that? Who could have the key?
• 1:33:47
  Speaker 5: So we worked with TSA, who's the regulator for all railroads,
• 1:33:50
  Speaker 5: took those regulations and updated them for the digital age
• 1:33:54
  Speaker 5: to say, you know, you need multi factor authentication, not
• 1:33:57
  Speaker 5: a password because everybody's passwords had been compromised. You need
• 1:34:00
  Speaker 5: to ensure you have a monitoring system for your signaling system.
• 1:34:04
  Speaker 5: And initially there was some pushback from the sector exactly
• 1:34:07
  Speaker 5: as you said, and we realized that we had failed
• 1:34:09
  Speaker 5: to properly engage them. So we invited the fifty seven
• 1:34:12
  Speaker 5: railroad CEOs in the country to come in and we
• 1:34:16
  Speaker 5: gave them briefings on the security threat, and we said,
• 1:34:20
  Speaker 5: here are the security things that we think are needed.
• 1:34:23
  Speaker 5: Let's have a discussion of that right balance of cost
• 1:34:26
  Speaker 5: and impact, because if the threat is here and railroad
• 1:34:29
  Speaker 5: signaling systems are here, we can't jump here in one leap,
• 1:34:33
  Speaker 5: but we can jump here show the impact, show how
• 1:34:37
  Speaker 5: we're reducing the cost of an attack, which is significant,
• 1:34:39
  Speaker 5: and then do that in degrees. We did it for pipelines,
• 1:34:43
  Speaker 5: we did it for ports, we did it for airports.
• 1:34:46
  Speaker 5: We did it for water systems using existing regulators and
• 1:34:50
  Speaker 5: existing regulations, and I think there's a lot we can
• 1:34:52
  Speaker 5: learn from that because there's no one size fits all.
• 1:34:55
  Speaker 5: I visited water systems in San Jose. Securing those water
• 1:34:58
  Speaker 5: systems to Americans have safe water is very different from
• 1:35:01
  Speaker 5: securing an oil and gas pipeline, and the regulators know
• 1:35:04
  Speaker 5: their sectors well and know what's reasonable in terms of
• 1:35:07
  Speaker 5: the cost burden for impact in terms of driving down
• 1:35:10
  Speaker 5: the threat.
• 1:35:10
  Speaker 4: So I just to close on that. I think there's
• 1:35:12
  Speaker 4: some lessons to.
• 1:35:13
  Speaker 5: Be learned in the case of AI, right Like, for example,
• 1:35:16
  Speaker 5: if you think about people are worried that AI is
• 1:35:19
  Speaker 5: used to determine if you or I should get alone,
• 1:35:21
  Speaker 5: and they want to make sure that the data that's
• 1:35:23
  Speaker 5: trained on is not biased and that the recommendation is explainable,
• 1:35:27
  Speaker 5: so a human looking at it can say why trust
• 1:35:30
  Speaker 5: chock or why not trust And there are existing regulations
• 1:35:33
  Speaker 5: that do that. They have to be updated for the
• 1:35:36
  Speaker 5: use of AI. Many of them, or they exist so
• 1:35:38
  Speaker 5: many are adequate. That needs to be done for every sector.
• 1:35:42
  Speaker 5: And then going back to the first question you asked
• 1:35:44
  Speaker 5: me that talks about the risk AI brings separately, there
• 1:35:49
  Speaker 5: are approaches we need to do to make sure the
• 1:35:50
  Speaker 5: AI models that are deployed are safe themselves.
• 1:35:54
  Speaker 1: So this gets back to you, We don't you know,
• 1:35:56
  Speaker 1: we still don't regulate algorithms. Algorithms. Many companies believe their
• 1:36:01
  Speaker 1: algorithms are this proprietary thing and we don't know whether
• 1:36:04
  Speaker 1: it's being used for predatory practices. For because it's a
• 1:36:09
  Speaker 1: it's an algorithm that could make that decision about a
• 1:36:11
  Speaker 1: mortgage or about a loan. Sometimes after the fact, maybe
• 1:36:15
  Speaker 1: a civil lawsuit is brought and then you can somehow
• 1:36:18
  Speaker 1: claim that they violated the law. I get that the
• 1:36:20
  Speaker 1: law is there eventually, but is there a proactive way
• 1:36:24
  Speaker 1: to essentially, Hey, we've got a new algorithm that's gonna
• 1:36:27
  Speaker 1: it's going to help us get through these mortgage applications faster.
• 1:36:35
  Speaker 1: Let's make sure it's approved by the government the same
• 1:36:37
  Speaker 1: way we would have proven new drug before it was
• 1:36:40
  Speaker 1: circulated on the market, sold as as a as A
• 1:36:44
  Speaker 1: as a pharmaceutical. UH you know, answer to some disease.
• 1:36:50
  Speaker 4: It's a good question.
• 1:36:51
  Speaker 5: And the big difference I think between an AI model
• 1:36:53
  Speaker 5: or an algorithm, to your point, and a drug is
• 1:36:56
  Speaker 5: one changes so continuously and one takes time to develop
• 1:36:59
  Speaker 5: and test.
• 1:37:00
  Speaker 4: It has IP protection attacked.
• 1:37:02
  Speaker 1: I admit, but I you know, actually the speed of
• 1:37:06
  Speaker 1: prescription drugs is going faster. I mean, I could make
• 1:37:09
  Speaker 1: an argument that FDA and drugs AI models. You know,
• 1:37:13
  Speaker 1: why shouldn't there be an FDA or AM And I think.
• 1:37:17
  Speaker 5: It's I think to your point, there's a tension between
• 1:37:20
  Speaker 5: the innovation and regulation, right because regulation often is slow
• 1:37:24
  Speaker 5: to adapt to adapt to changing technology. And in fact,
• 1:37:28
  Speaker 5: I think, frankly, if you look at the difference between
• 1:37:29
  Speaker 5: the European Union and the United States, European Union is
• 1:37:32
  Speaker 5: a country that puts regulations first and innovation second.
• 1:37:35
  Speaker 1: I get it. It's what's the line? Yeah, well, right now,
• 1:37:38
  Speaker 1: there's no line. And I think we're not even attempting
• 1:37:41
  Speaker 1: any of that because the industry has got aggressive politically
• 1:37:45
  Speaker 1: and has gotten essentially made a political bargain.
• 1:37:47
  Speaker 2: With this admistry.
• 1:37:48
  Speaker 5: And I think there's a balance between the how we
• 1:37:53
  Speaker 5: approach AI models themselves and then how do we approach
• 1:37:57
  Speaker 5: when they're deployed in sectors where regulations like, for example,
• 1:38:01
  Speaker 5: we'll just go use our loan example again, So if
• 1:38:04
  Speaker 5: somebody is deploying an AI model to determine who gets
• 1:38:07
  Speaker 5: a loan, there are regulations around explaining how a decision
• 1:38:13
  Speaker 5: is made coming out of an algorithm or model, and
• 1:38:17
  Speaker 5: around what data that's trained on, So that you need
• 1:38:21
  Speaker 5: transparency on the data that's trained on and explainability of
• 1:38:24
  Speaker 5: how that decision is made that exists in that sector.
• 1:38:27
  Speaker 5: It doesn't exist in every sector, and that's really what
• 1:38:29
  Speaker 5: we need. We need the transparency on the data models
• 1:38:32
  Speaker 5: trained on to see is it trained on data that
• 1:38:35
  Speaker 5: fundamentally was.
• 1:38:37
  Speaker 1: Do we need a new law in the books for this?
• 1:38:41
  Speaker 5: I usually default to say, given that laws trail tech
• 1:38:45
  Speaker 5: by such a long time, are there ways that we
• 1:38:48
  Speaker 5: can achieve what we want, which is protecting the population
• 1:38:52
  Speaker 5: from a new technology's most significant risks in a way
• 1:38:56
  Speaker 5: that's also adaptable and changes quickly.
• 1:38:59
  Speaker 4: And I think to your point.
• 1:39:02
  Speaker 5: Looking at the AI models and saying what is the
• 1:39:06
  Speaker 5: delta harm they bring to different areas, and then what's
• 1:39:11
  Speaker 5: the best way.
• 1:39:12
  Speaker 4: To control against that harm? That's what's needed.
• 1:39:14
  Speaker 1: Look a month ago, Anthropic came out and said, our
• 1:39:18
  Speaker 1: new AI model is so powerful, we're not sure that
• 1:39:23
  Speaker 1: that the current cybersecurity infrastructure is going to be able
• 1:39:27
  Speaker 1: to defend against people deciding to use our model to
• 1:39:32
  Speaker 1: potentially attack. And there's a part of me that says,
• 1:39:36
  Speaker 1: so why release the model? Like should this? But again
• 1:39:43
  Speaker 1: there's no law in the books that says they can't
• 1:39:44
  Speaker 1: release the model.
• 1:39:46
  Speaker 5: So yes, And you know that's a fierce debate in
• 1:39:48
  Speaker 5: the cybersetriity community.
• 1:39:49
  Speaker 4: How much of that was anthropic marketing?
• 1:39:51
  Speaker 1: And all I saw debate, I think it is enough.
• 1:39:56
  Speaker 1: It's no different than claiming that your prescription drug, if
• 1:40:00
  Speaker 1: it works properly but for longer than four hours, call
• 1:40:03
  Speaker 1: a doctor. Was that a side effect?
• 1:40:05
  Speaker 2: Was that a marketing part?
• 1:40:07
  Speaker 3: You know?
• 1:40:07
  Speaker 4: So it's so interesting.
• 1:40:08
  Speaker 5: I've had the privilege of leading teams conducting offensive operations,
• 1:40:11
  Speaker 5: and I also, as you know, led defensive head of cybersecurity,
• 1:40:14
  Speaker 5: and let's say, and.
• 1:40:15
  Speaker 4: Then led this work at the White House. And I will.
• 1:40:18
  Speaker 5: Say that I really believe AI models will transform cybersecurity
• 1:40:23
  Speaker 5: on defense, but it's a painful path there, and that's
• 1:40:27
  Speaker 5: what we need to control for what do I mean?
• 1:40:30
  Speaker 5: It is far easier to attack than to defend. An
• 1:40:32
  Speaker 5: attacker has to find one way in a defender has
• 1:40:34
  Speaker 5: to be checking every door window and feeling job.
• 1:40:38
  Speaker 1: In America's homeland security yeah, because ninety nine percent.
• 1:40:43
  Speaker 5: Is not going to happen, and being a SISO is
• 1:40:45
  Speaker 5: a really tough job. I mean, there's often discussions in
• 1:40:47
  Speaker 5: that community around just how difficult, how much people know
• 1:40:51
  Speaker 5: exactly for this, it's terrible.
• 1:40:54
  Speaker 4: Now, what AI.
• 1:40:56
  Speaker 5: Allows is attackers to jiggle every door knob continuously in
• 1:40:59
  Speaker 5: that scale. So it really does enable attackers. But what
• 1:41:02
  Speaker 5: allows defenders to do if they're doing the same thing,
• 1:41:05
  Speaker 5: if they're jiggling every doorknob in their infrastructure in advance
• 1:41:09
  Speaker 5: and at scale, and AI then helps generate patches or
• 1:41:14
  Speaker 5: controls to compensate, that can be significant. Today, the model's
• 1:41:18
  Speaker 5: capabilities on generating patches, etc. Need to be better. They're there,
• 1:41:24
  Speaker 5: but they need to be better. So the approach that said,
• 1:41:28
  Speaker 5: let's get the core companies producing digital infrastructure that everyone
• 1:41:32
  Speaker 5: uses to use the models to find and fix vulnerabilities
• 1:41:37
  Speaker 5: and deploy them via existing patches is a smart one
• 1:41:42
  Speaker 5: because it starts locking down common infrastructure. What's missing today
• 1:41:45
  Speaker 5: and what we need is that in all of our
• 1:41:48
  Speaker 5: critical sectors.
• 1:41:49
  Speaker 4: Hospitals are a good one.
• 1:41:51
  Speaker 5: There's also a stack that rides on top of the
• 1:41:54
  Speaker 5: core infrastructure, and that is often what's used to compromise
• 1:41:58
  Speaker 5: a hospital to disrupt itsself operations.
• 1:42:01
  Speaker 4: That's missing, and I think that's what we need.
• 1:42:03
  Speaker 5: To be able to say within each sector, what does
• 1:42:05
  Speaker 5: the stack look like and in some cases those are
• 1:42:08
  Speaker 5: stacks that aren't updated and secure them quickly.
• 1:42:12
  Speaker 1: Is government behind or industry being obstinate?
• 1:42:17
  Speaker 5: Government needs to be doing convening, and I see the
• 1:42:20
  Speaker 5: power of government convening is significant when you bring everybody
• 1:42:23
  Speaker 5: around the table and you say, look, we can regulate
• 1:42:27
  Speaker 5: this or these are the things we.
• 1:42:29
  Speaker 4: Need to see you get done.
• 1:42:31
  Speaker 5: Particularly when companies are out there saying this is such
• 1:42:34
  Speaker 5: a powerful weapon, this is so concerning, Well, then act
• 1:42:37
  Speaker 5: it out.
• 1:42:37
  Speaker 4: Then work with.
• 1:42:39
  Speaker 5: Us in team to ensure that we can equip defenders
• 1:42:42
  Speaker 5: to be ready because let's be honest, Chinese open source
• 1:42:45
  Speaker 5: models follow by six months and that's a threat that's significant.
• 1:42:50
  Speaker 5: So we have a window of time for models, for
• 1:42:54
  Speaker 5: frontier model companies to be working, and frankly for government
• 1:42:57
  Speaker 5: to be helping convene the open source and the open
• 1:43:01
  Speaker 5: source community to be getting access to the models, because,
• 1:43:04
  Speaker 5: as you know, open source, unlike a Cisco or Microsoft,
• 1:43:08
  Speaker 5: is developed often by anyone, but broadly deployed in our infrastructure.
• 1:43:13
  Speaker 4: So I think that's starting. You see, the White House
• 1:43:16
  Speaker 4: has been bringing companies together.
• 1:43:17
  Speaker 5: You see Project Last Wing, you see opening eyes approach
• 1:43:20
  Speaker 5: to say we'll approve people because.
• 1:43:22
  Speaker 3: We wanted to know your customer.
• 1:43:23
  Speaker 5: We want to know are you as SISO, are you
• 1:43:25
  Speaker 5: a head of cyber RAI for a country who's setting strategy,
• 1:43:28
  Speaker 5: and if so, will come up with ways to have
• 1:43:30
  Speaker 5: you use the model in a way that's.
• 1:43:32
  Speaker 4: Safe and doesn't broadly distribute it. But the race is on.
• 1:43:36
  Speaker 5: And to be clear, even though you know, I do
• 1:43:39
  Speaker 5: believe it's going to be a game changer on cybersecurity,
• 1:43:42
  Speaker 5: we've got to ensure that models are in the hands
• 1:43:44
  Speaker 5: of defenders quickly. And we've got to keep the pressure
• 1:43:48
  Speaker 5: on companies that build digital infrastructure to be getting those
• 1:43:51
  Speaker 5: patches out and figuring out for infrastructure that is difficult
• 1:43:56
  Speaker 5: to patch. You know, it's not so easy to just
• 1:43:59
  Speaker 5: push a patch on my manufacturing plan. You know, it
• 1:44:01
  Speaker 5: sometimes has side effects that we can use AI, for example,
• 1:44:07
  Speaker 5: to simulate those patches to ensure that they're working right,
• 1:44:09
  Speaker 5: to give users more confidence to deploy them.
• 1:44:12
  Speaker 4: So there's a lot that needs to get done.
• 1:44:13
  Speaker 1: You're outlining a lot that we need to do. Color
• 1:44:17
  Speaker 1: me skeptical that we have the current governmental infrastructure to
• 1:44:21
  Speaker 1: to respond in the ways that maybe the public needs
• 1:44:25
  Speaker 1: it to respond.
• 1:44:26
  Speaker 5: You know, the first step is saying here's where we
• 1:44:28
  Speaker 5: need to go. The second step is rallying a community.
• 1:44:32
  Speaker 5: The nice part is there are lots of people across
• 1:44:35
  Speaker 5: the tech community or ready to roll up their sleeves
• 1:44:38
  Speaker 5: and can be self organizing on this too.
• 1:44:40
  Speaker 4: But you're right, governments, and.
• 1:44:43
  Speaker 1: Yet we're all watching as voyeurs this Elon musk open
• 1:44:48
  Speaker 1: Ai trial and it doesn't give a lot of confidence
• 1:44:52
  Speaker 1: in some of these companies.
• 1:44:53
  Speaker 5: You're right that the role of government inconvening, and I
• 1:44:56
  Speaker 5: do believe the White House has been doing convenience, bringing
• 1:44:58
  Speaker 5: companies together and trying to get action out of them.
• 1:45:02
  Speaker 5: And in fact, companies are moving at I've talked to
• 1:45:04
  Speaker 5: a number of companies participating in Glass Wing. They're doing
• 1:45:07
  Speaker 5: the work, they're building the patches, they're planning to get
• 1:45:09
  Speaker 5: them out to customers, pressing them on psycho.
• 1:45:12
  Speaker 1: The initial models are not the trustworthy enterprise. It's one
• 1:45:15
  Speaker 1: thing for Microsoft, JP Morgan, some of these companies to
• 1:45:19
  Speaker 1: be responsible with how they're using these models, but it
• 1:45:23
  Speaker 1: feels like the companies that are making the models don't
• 1:45:27
  Speaker 1: necessarily they seem to be more a bit self absorbed.
• 1:45:30
  Speaker 5: There's a tension between the commercial value and the national
• 1:45:33
  Speaker 5: security risk, and typically government makes that determination. What's so
• 1:45:40
  Speaker 5: different here is the tech is coming out of the
• 1:45:41
  Speaker 5: private sector, and it is important that government come out
• 1:45:45
  Speaker 5: and clearly say here's where national security risk is significant.
• 1:45:49
  Speaker 4: Here's an approach that ensure as we still.
• 1:45:50
  Speaker 5: Need on innovation, but we drive down the risk to
• 1:45:53
  Speaker 5: an acceptable level along the way.
• 1:45:56
  Speaker 2: And you've got a big job.
• 1:45:58
  Speaker 1: It's luck with trying to bridge this divide.
• 1:46:00
  Speaker 5: It's a large community, and you know, I always believe
• 1:46:04
  Speaker 5: with tech, there's nothing wrong with tech that can be
• 1:46:06
  Speaker 5: fixed with those threat.
• 1:46:06
  Speaker 1: I will say this, I think there's government is skeptical,
• 1:46:10
  Speaker 1: a tech is skeptical a government.
• 1:46:12
  Speaker 2: And yet they have to work together.
• 1:46:14
  Speaker 5: In world fred I very much agree with that, and
• 1:46:17
  Speaker 5: I think quite frankly, those relationships. When I think back
• 1:46:21
  Speaker 5: to the Snowden period, the divide between Washington and Silicon
• 1:46:25
  Speaker 5: Valley was incredibly sharp, and that came from a sense
• 1:46:29
  Speaker 5: that government surveillance wasn't following laws.
• 1:46:31
  Speaker 4: And policies of the country as a democracy.
• 1:46:34
  Speaker 5: And frankly, you know, at the time, I after that,
• 1:46:37
  Speaker 5: I was asked to be NASA's first chief risk officer,
• 1:46:39
  Speaker 5: and I remember flying back and forth across the country
• 1:46:41
  Speaker 5: and seeing how sharp the divide was. Folks in the
• 1:46:44
  Speaker 5: national security community were saying, why don't people trust us?
• 1:46:46
  Speaker 5: We're the good guys here, and folks in the private
• 1:46:48
  Speaker 5: sector were like, Okay, how does this intelligence community work
• 1:46:52
  Speaker 5: and doesn't really respect my values? And it took a
• 1:46:54
  Speaker 5: series of conversations, you know, over the last decade to
• 1:46:58
  Speaker 5: heal that.
• 1:46:58
  Speaker 4: I think we're at the same place now.
• 1:47:00
  Speaker 1: Well, it's funny you bring up values. What are the
• 1:47:02
  Speaker 1: values of these companies? I don't know sometimes and are
• 1:47:04
  Speaker 1: they our values? I think there's a concern about that.
• 1:47:08
  Speaker 1: But this is just the beginning. And thanks for your time.
• 1:47:13
  Speaker 2: Thank you, Thanks.
• 1:47:23
  Speaker 1: Well, I hope you enjoyed those conversations. My thanks to
• 1:47:26
  Speaker 1: my friends at newsphere. As you know, I love doing
• 1:47:28
  Speaker 1: what we're doing over there, but this was something you know,
• 1:47:32
  Speaker 1: every once in a while, I want to. I'm gonna,
• 1:47:35
  Speaker 1: you know, take a little something behind the paywall that's
• 1:47:38
  Speaker 1: behind a paywall and share it with you guys for
• 1:47:40
  Speaker 1: free here. That's why I hear everything. I'm never putting
• 1:47:43
  Speaker 1: this podcast behind a paywall. Yes, I'm going to be
• 1:47:48
  Speaker 1: reading sponsor advertising, and yes you're gonna have that stuff,
• 1:47:53
  Speaker 1: you know, because it's all designed to keep everything that
• 1:47:57
  Speaker 1: I do here and substack just to keep it all free.
• 1:48:01
  Speaker 1: I'm not going to extract direct direct contributions out of
• 1:48:05
  Speaker 1: you there. Newsphere is another story. We're supporting a lot
• 1:48:08
  Speaker 1: of working journalists there, and so I really encourage it.
• 1:48:11
  Speaker 1: But every once in a while, when I can, I
• 1:48:13
  Speaker 1: want to share a little something because hopefully it encourages
• 1:48:15
  Speaker 1: you to go to go take a look at newsphare.
• 1:48:18
  Speaker 1: I'll be honest. I enjoyed both interviews. But I don't
• 1:48:22
  Speaker 1: know about you, but I heard the caution in their voice.
• 1:48:25
  Speaker 1: It is the most difficult part of regulating AI is
• 1:48:29
  Speaker 1: going to is going to be, you know, the carrot
• 1:48:34
  Speaker 1: and stick approach and regulation to these AI companies. They're
• 1:48:36
  Speaker 1: pretty powerful already, they're pretty and they're going to become
• 1:48:39
  Speaker 1: so wealthy and big that they're going to be larger
• 1:48:41
  Speaker 1: than most nation states. And you could hear you know,
• 1:48:45
  Speaker 1: nobody wants to single out any of these companies, and
• 1:48:48
  Speaker 1: none of them wanted to take the bait that I
• 1:48:50
  Speaker 1: had on the trial, as will come through in the conversation.
• 1:48:53
  Speaker 1: I'm sure you notice that in the conversation, and I
• 1:48:58
  Speaker 1: think it just tells you how fragile the egos are
• 1:49:01
  Speaker 1: of these of these sort of three or four entities
• 1:49:03
  Speaker 1: that are that are sort of the chief the chieftains
• 1:49:06
  Speaker 1: right now of AI. That's a little scary, right, And
• 1:49:13
  Speaker 1: so you know, because you kind of don't want to
• 1:49:19
  Speaker 1: feel like all of this is being built on the
• 1:49:21
  Speaker 1: whims of somebody's mood on a given day about about
• 1:49:25
  Speaker 1: how they feel about one person or the other. But anyway,
• 1:49:29
  Speaker 1: all right, let's do some top five lists. So I
• 1:49:30
  Speaker 1: got a fun one top fe top This is total
• 1:49:39
  Speaker 1: and I know what I'm doing and you're dying right
• 1:49:41
  Speaker 1: I'm doing it, which is I am throwing some fun
• 1:49:44
  Speaker 1: candy at you. This is this is some sugar. It's
• 1:49:47
  Speaker 1: all twenty twenty eight stuff. And I've been in and
• 1:49:50
  Speaker 1: around a bunch of people who are thinking about running
• 1:49:53
  Speaker 1: for president who've done it before who've helped you know,
• 1:49:56
  Speaker 1: people run before. So I thought I do. I'm actually
• 1:49:59
  Speaker 1: gonna do two top five lists on the Democratic side
• 1:50:03
  Speaker 1: of the aisle because there's that many candidates, and I
• 1:50:05
  Speaker 1: want to split it into two separate fields. Field one
• 1:50:08
  Speaker 1: are candidates that have never run for president before. So
• 1:50:11
  Speaker 1: I want to give you my current top five who
• 1:50:15
  Speaker 1: are most likely, in my view, most likely could get
• 1:50:18
  Speaker 1: the nomination. I'm not saying they should. Okay. You know,
• 1:50:25
  Speaker 1: my friend over at the Bullwark, Jonathan Last, wrote a
• 1:50:27
  Speaker 1: piece about Graham Plattner, and people thought he was endorsing
• 1:50:30
  Speaker 1: Graham Platner for president. He was not endorsing Grand Platner
• 1:50:33
  Speaker 1: for president. He was just laying out, don't underestimate somebody
• 1:50:37
  Speaker 1: Graham Platner or somebody like him who connects with people
• 1:50:40
  Speaker 1: in twenty twenty six could easily, you know, show up
• 1:50:43
  Speaker 1: and become a bull in the China shop in the
• 1:50:46
  Speaker 1: primary and shock the world. Right. It's not the craziest thought.
• 1:50:50
  Speaker 1: It was funny to me, how it. You know. Look,
• 1:50:53
  Speaker 1: I love my friends at the bull work. I think
• 1:50:57
  Speaker 1: they get a little too reactionary and resistance sometimes, but
• 1:51:02
  Speaker 1: that's sometimes in the you know, that's there's still a
• 1:51:06
  Speaker 1: lot of really smart stuff that they do every day
• 1:51:08
  Speaker 1: in their newsletters and all these things. And I thought
• 1:51:12
  Speaker 1: the Grand Platinum point was a really shrewd point by Jonathan,
• 1:51:14
  Speaker 1: and I'm gonna get to that in a minute. It
• 1:51:16
  Speaker 1: actually inspired this. So my first list to top five
• 1:51:19
  Speaker 1: is top five who've never run for president before who
• 1:51:23
  Speaker 1: I think right now are best position to potentially get
• 1:51:26
  Speaker 1: the nomination. And then the other one is top five
• 1:51:30
  Speaker 1: candidates who have run before who are best positioned to
• 1:51:36
  Speaker 1: get the nomination. And again, just because I rank you
• 1:51:41
  Speaker 1: number one, doesn't mean that's who I want or I
• 1:51:44
  Speaker 1: believe who I think should be. It's just simply my
• 1:51:48
  Speaker 1: political analysis in this moment where I think, I think
• 1:51:53
  Speaker 1: I know where things stand. Okay, So getting those caveats
• 1:51:57
  Speaker 1: ei of the way, But before I get to my lists,
• 1:52:01
  Speaker 1: I want to remind you of an interesting statistic about
• 1:52:05
  Speaker 1: democratic presidents starting in nineteen sixty and I'm just going
• 1:52:10
  Speaker 1: to go through this history lesson, because then you can
• 1:52:14
  Speaker 1: absorb these top five lists mocorp with a little more
• 1:52:20
  Speaker 1: strategicy in your head when you listen to him. John
• 1:52:23
  Speaker 1: Kennedy wins the president in sixties, first time he ever
• 1:52:26
  Speaker 1: ran for president. Sixty four is the reelect sitting vice
• 1:52:30
  Speaker 1: president that there was no primary, so the Johnson thing
• 1:52:33
  Speaker 1: rules out. Humphrey's a nominee in sixty eight. He ran
• 1:52:36
  Speaker 1: for president in sixty Democrats lose McGovern First time he
• 1:52:41
  Speaker 1: ran was in seventy two. He lost Carter. First time
• 1:52:45
  Speaker 1: he ran was seventy six, and he won loses reelection Mondale.
• 1:52:54
  Speaker 1: It's hard to say. It was the first time he
• 1:52:56
  Speaker 1: ran since he was the sitting vice president, so it's
• 1:53:03
  Speaker 1: he never technically ran for president before, so you put
• 1:53:08
  Speaker 1: him in. First time he runs, he gets the nomination,
• 1:53:10
  Speaker 1: but he loses. Michael Ducaccas. First time he runs, he
• 1:53:15
  Speaker 1: wins the nomination. Nineteen ninety two, Bill Clinton. First time
• 1:53:18
  Speaker 1: he runs, he wins the nomination. Two thousand, Al Gore.
• 1:53:22
  Speaker 1: That was actually the second time he ran. He ran
• 1:53:24
  Speaker 1: in eighty eight. In two thousand and he gets the nomination,
• 1:53:29
  Speaker 1: he loses. Two thousand and four. First time John Carrey ran,
• 1:53:32
  Speaker 1: wins the nomination, he loses. Two thousand and eight. Barack
• 1:53:35
  Speaker 1: Obama first time nomination, wins. Twenty sixteen. Hillary Clinton second
• 1:53:41
  Speaker 1: time gets nomination, loses twenty twenty. Joe Biden third time
• 1:53:46
  Speaker 1: gets the nomination wins twenty twenty four. Kamala Harris technically
• 1:53:51
  Speaker 1: second time, yes, convoluted way, but she had run once.
• 1:53:56
  Speaker 1: Didn't get it in theory, essentially got got it kind
• 1:54:01
  Speaker 1: of sort of second time. Did you pick up on
• 1:54:04
  Speaker 1: something there? Kennedy, Carter, Clinton, Obama. Up until Joe Biden,
• 1:54:16
  Speaker 1: the previous four successful Democratic presidential nominees won the presidency
• 1:54:25
  Speaker 1: the first time they ever ran for president, the only
• 1:54:28
  Speaker 1: one since nineteen six, the only ones since FDR and
• 1:54:39
  Speaker 1: FDR technically first time he ran for president now is
• 1:54:42
  Speaker 1: the way vice president of the way conventions worked. I
• 1:54:44
  Speaker 1: guess you could say he was technically on the ticket
• 1:54:47
  Speaker 1: in is loss, but even you could even throw FDR
• 1:54:49
  Speaker 1: in there. Joe Biden did something that hadn't hadn't been
• 1:54:54
  Speaker 1: done in the Democratic side. And I think over one
• 1:54:57
  Speaker 1: hundred years, which is when the president and say the
• 1:55:00
  Speaker 1: second time they ran for president. I'm just saying on
• 1:55:05
  Speaker 1: the Democratic side, we can get in there. There's some
• 1:55:08
  Speaker 1: the Republican rules are slightly different. But I say this
• 1:55:11
  Speaker 1: in that I'd rather be I in my assumption, in
• 1:55:18
  Speaker 1: my you know, if you were to do your financial handicapping,
• 1:55:25
  Speaker 1: it's more likely. You know, if put it this way,
• 1:55:27
  Speaker 1: if you if you matched up the will the Democratic
• 1:55:32
  Speaker 1: nominee be somebody who's never run for president before twenty
• 1:55:34
  Speaker 1: twenty eight or who did run for president before twenty
• 1:55:37
  Speaker 1: twenty eight. I'd rather be on the had never run before.
• 1:55:44
  Speaker 1: And my guess is that should that should price at
• 1:55:46
  Speaker 1: the moment like fifty eight to forty two, fifty eight
• 1:55:51
  Speaker 1: cents to forty two cents if you were playing the
• 1:55:53
  Speaker 1: Coushi game, or I guess that's you know, but it
• 1:55:57
  Speaker 1: would be I would be somewhere in the I think
• 1:55:59
  Speaker 1: the it's a better greater than fifty to fifty chance.
• 1:56:03
  Speaker 1: You're just going to have more candidates who didn't run
• 1:56:04
  Speaker 1: before run. You'll have fewer candidates running that have run before.
• 1:56:10
  Speaker 1: So I throw that. I just wanted to give you
• 1:56:12
  Speaker 1: that little history lesson so that you can absorb these
• 1:56:15
  Speaker 1: lists a little bit better. So my right now five
• 1:56:22
  Speaker 1: most likely candidates who've never run for president before. So
• 1:56:26
  Speaker 1: it perhaps I'm going to name people that have never run,
• 1:56:28
  Speaker 1: which means I'm going to update this list as we
• 1:56:30
  Speaker 1: go very now. And then in my number five slot
• 1:56:34
  Speaker 1: is I'm going to call it twenty twenty six TBD.
• 1:56:41
  Speaker 1: The point being is there is going to be a
• 1:56:45
  Speaker 1: major candidate for president that fits one of the following
• 1:56:49
  Speaker 1: two criteria. One is they ran in twenty twenty six
• 1:56:54
  Speaker 1: and captured the imagination because they won one in a
• 1:56:57
  Speaker 1: unique way, did something we hadn't seen before. Think better
• 1:57:02
  Speaker 1: or Rourke twenty eighteen. He didn't even win, but his
• 1:57:06
  Speaker 1: run was so impressive it made people think, Hey, maybe
• 1:57:09
  Speaker 1: that guy ought to run for president. So he jumped
• 1:57:12
  Speaker 1: in and was like a front runner for about three days.
• 1:57:18
  Speaker 1: Somebody's going to be in that is that Grand Platner.
• 1:57:22
  Speaker 1: I'm more skeptical of that. I don't think the Democrats
• 1:57:24
  Speaker 1: are going to go down a Platiner road, you know,
• 1:57:27
  Speaker 1: suddenly go down that road. And he's still got a
• 1:57:31
  Speaker 1: tough race to win. But maybe Rob saying, if he
• 1:57:36
  Speaker 1: wins the governorship in Iowa, would he suddenly you know,
• 1:57:41
  Speaker 1: when you see what he does at his rallies, Rob Saying,
• 1:57:48
  Speaker 1: gets everybody at his rallies. He does this interesting thing
• 1:57:53
  Speaker 1: he raises. He does these town halls and he wants
• 1:57:58
  Speaker 1: to emphasize how diverse politically diverse his coalition is. And
• 1:58:03
  Speaker 1: they'll say, how many of you are are are Republicans
• 1:58:08
  Speaker 1: here for you know, coming to see me. You know,
• 1:58:10
  Speaker 1: people raise their hands. Great. He goes, let's clap and
• 1:58:13
  Speaker 1: does the same to Independence, the same to Democrats, and
• 1:58:15
  Speaker 1: he goes and he goes, let's start out with something
• 1:58:18
  Speaker 1: I think we all can agree on, and he says,
• 1:58:22
  Speaker 1: in America the Beautiful one of the best tunes we
• 1:58:25
  Speaker 1: got going on here? It does anybody know how to sing?
• 1:58:28
  Speaker 1: All right? Get us started? And he just gets everybody
• 1:58:31
  Speaker 1: to sing America the Beautiful. And you can sit here
• 1:58:35
  Speaker 1: and say, oh, that's shticky, participate and then tell me
• 1:58:42
  Speaker 1: whether it's shticky. It He did it in this room
• 1:58:46
  Speaker 1: of very cynical people that I was in, and it
• 1:58:50
  Speaker 1: didn't feel sticky, and yet it did. At the start
• 1:58:53
  Speaker 1: I thought, oh, you know, my eyes were going to
• 1:58:55
  Speaker 1: begin to roll, and it just clicked. So the point is,
• 1:59:01
  Speaker 1: you don't know, could be Talla Rica, could be Stephen
• 1:59:05
  Speaker 1: Colbert right that the second he's you know, this is
• 1:59:08
  Speaker 1: his you know, Swan song month, and then all of
• 1:59:11
  Speaker 1: a sudden, you know he's you know, pivoting something. You know.
• 1:59:14
  Speaker 1: The point is in my five slot right now is TBD,
• 1:59:19
  Speaker 1: because it's going to be somebody none of us are
• 1:59:21
  Speaker 1: talking about. It's quite possibly Mallory mc morrow's another one
• 1:59:25
  Speaker 1: i'd put in there is a nominee in this certain place.
• 1:59:27
  Speaker 1: So so number five for me is the cop out
• 1:59:30
  Speaker 1: is twenty twenty six TVD. It is somebody who sort
• 1:59:34
  Speaker 1: of comes out of nowhere this year and becomes this
• 1:59:39
  Speaker 1: sort of sticky person kind of the way. Remember how
• 1:59:44
  Speaker 1: intrigued folks were about Fetterman on the left. Now it's
• 1:59:48
  Speaker 1: the right that's obsessed with Fetterman in a positive way
• 1:59:50
  Speaker 1: these days. But remember early on there was a lot
• 1:59:53
  Speaker 1: of talk with maybe Fetterman ought to run for president anyway.
• 1:59:58
  Speaker 1: Let me just really, so that's in my f I
• 2:00:00
  Speaker 1: sat in my fore slot at this point, I'm going
• 2:00:03
  Speaker 1: to put Josh Shapiro. He's raising a ton of money.
• 2:00:13
  Speaker 1: I know there's some question, you know, how are Jewish
• 2:00:15
  Speaker 1: Democrats going to do in a Democratic primary. I'm there's
• 2:00:20
  Speaker 1: going to be three or four Jewish Democrats running. I
• 2:00:24
  Speaker 1: kind of think that it's just because there's going to
• 2:00:26
  Speaker 1: be multiple Jewish Democrats running, well, the subject is going
• 2:00:29
  Speaker 1: to be brought up. I think it gets I think
• 2:00:31
  Speaker 1: this becomes the story people think is going to be
• 2:00:34
  Speaker 1: a story that isn't or maybe I'm just being wishful
• 2:00:39
  Speaker 1: thinking there, but you got Pritzker, Shapiro, rom Emmanuel all
• 2:00:42
  Speaker 1: going to be running. But right now. That's why I
• 2:00:45
  Speaker 1: think Shapiro put him on the fore slot. I think
• 2:00:48
  Speaker 1: he's sort of structurally has thought about this that matters.
• 2:00:51
  Speaker 1: Bill Clinton. Bill Clinton was planning his ninety two presidential
• 2:00:54
  Speaker 1: campaign in nineteen eighty two, you know, and that frankly,
• 2:00:57
  Speaker 1: that that's a those candidates do better, do better than
• 2:01:03
  Speaker 1: you think. In the three slot for me is uh
• 2:01:11
  Speaker 1: is h Gavin news Look, he's had a he had
• 2:01:16
  Speaker 1: a great twenty twenty five In to some corners of
• 2:01:21
  Speaker 1: the Democratic Party. He's going to be seen as the
• 2:01:23
  Speaker 1: only guy that was able to successfully push back at
• 2:01:26
  Speaker 1: the gerrymander. That's going to matter to some voters and
• 2:01:30
  Speaker 1: it gives him something. I the reason I'm not putting
• 2:01:32
  Speaker 1: him in the one slot is I just think the
• 2:01:35
  Speaker 1: California gubernatorial campaign has not served him well. It is
• 2:01:40
  Speaker 1: not people nobody is running on. Isn't everything going great?
• 2:01:45
  Speaker 1: That's not great for the Gavin Newsome record that he's
• 2:01:49
  Speaker 1: got to start to have to sell when he starts
• 2:01:51
  Speaker 1: running for president about why you Okay, you you were
• 2:01:54
  Speaker 1: in charge of America's large estate, but did you do
• 2:01:56
  Speaker 1: a good job. So I think the fact that this
• 2:02:00
  Speaker 1: campaign is, you know, whether it's the nobody's running on
• 2:02:05
  Speaker 1: the Gavin's Newsome slate. So I think that that's why
• 2:02:07
  Speaker 1: I put him at three. But I can't sit here
• 2:02:10
  Speaker 1: and say he has built a huge online army. He
• 2:02:12
  Speaker 1: has built a huge online following, so I think that
• 2:02:15
  Speaker 1: he's done quite a bit. Number two for me right
• 2:02:19
  Speaker 1: now is Wes Moore. I know he's technically said, you know,
• 2:02:24
  Speaker 1: I'm not running for president and you know, but he's
• 2:02:26
  Speaker 1: been part those statements. He seems to leave himself just
• 2:02:31
  Speaker 1: enough wiggle room. And for a guy who's not thinking
• 2:02:33
  Speaker 1: about running for president, he does show up at every
• 2:02:37
  Speaker 1: place you should be showing up, whether it's South Carolina,
• 2:02:39
  Speaker 1: whether it's certain spots. So and he's another one that
• 2:02:46
  Speaker 1: I just think structurally is you know he's going to
• 2:02:50
  Speaker 1: be where he's going to run a very competent campaign.
• 2:02:52
  Speaker 1: But number one right now because I think, you know,
• 2:02:55
  Speaker 1: I'm I'm you know, if you're if you're asked, made
• 2:02:57
  Speaker 1: of bet and the choice is sort of some by
• 2:03:00
  Speaker 1: from the pragmatic wing of the party like Wes Moore
• 2:03:05
  Speaker 1: or Joshapiro, or somebody from the more resistance or progressive
• 2:03:11
  Speaker 1: wing of the party, Gavin Newsom or my number one
• 2:03:13
  Speaker 1: person right over here, AOSI I'm not even sure she runs.
• 2:03:19
  Speaker 1: In fact, I think if you actually track her carefully,
• 2:03:22
  Speaker 1: she seems to be getting to know the state of
• 2:03:25
  Speaker 1: New York in a lot of detail, and has even said,
• 2:03:30
  Speaker 1: you know the fact that when she gets asked about
• 2:03:32
  Speaker 1: running about twenty twenty eight, she's the one that offers up.
• 2:03:36
  Speaker 1: There's a lot of ways she can exert influence. It
• 2:03:40
  Speaker 1: feels like she's almost trying to steer people away from
• 2:03:42
  Speaker 1: the idea. But I don't think if she decides to run,
• 2:03:48
  Speaker 1: I think she starts. You know, she will inherit the Bernie,
• 2:03:52
  Speaker 1: a lot of the Bernie support, and that's a big
• 2:03:55
  Speaker 1: base to start from. And nobody else of these newcomers
• 2:04:00
  Speaker 1: I just said, we'll be close to her early in
• 2:04:02
  Speaker 1: this campaign. I'm not saying one of them doesn't end
• 2:04:04
  Speaker 1: up eventually become the candidate surpass them, but they don't
• 2:04:07
  Speaker 1: start out. She's going to start out, you know, in
• 2:04:11
  Speaker 1: the top tier, which for a first time candidate, you know,
• 2:04:14
  Speaker 1: and I'm not even sure Gavin does. They may financially
• 2:04:17
  Speaker 1: start out in the quote unquote top tier, and Gavin
• 2:04:19
  Speaker 1: in the polling may show up in the top tier.
• 2:04:22
  Speaker 1: But AOC is going to have a little bit of
• 2:04:23
  Speaker 1: both on that. But she may not run. In fact,
• 2:04:29
  Speaker 1: I think it's more likely she runs her Senate. She's
• 2:04:31
  Speaker 1: behaving as somebody that's thinking about not being in a
• 2:04:35
  Speaker 1: hurry and not being one hundred percent sure this is
• 2:04:40
  Speaker 1: the moment for her politics, and I think, you know,
• 2:04:44
  Speaker 1: one thing that I've come to admire is that I
• 2:04:47
  Speaker 1: do feel like she is she picks her spots really well.
• 2:04:51
  Speaker 1: But so there you go, AOC, Wes Moore, Gavin Newsom,
• 2:04:56
  Speaker 1: Jos Shapiro, TBD, we'll call it Stephen Colbert, Platner, Graham.
• 2:05:04
  Speaker 1: But the twenty twenty six wild card, that's my five
• 2:05:07
  Speaker 1: most likely who have never run. Now, I'm gonna go
• 2:05:10
  Speaker 1: quicker here in the top five who have run, who
• 2:05:14
  Speaker 1: right now I think are in the best position to
• 2:05:16
  Speaker 1: be the nominee. And let's start at five. At five,
• 2:05:21
  Speaker 1: I'm putting Amy Klobe Shark. I think if she becomes governor,
• 2:05:27
  Speaker 1: I think she's tempted. James Carvell has this great line
• 2:05:31
  Speaker 1: about running for president. It's kind of like sex. You
• 2:05:34
  Speaker 1: don't just do it once unless you succeed the first time.
• 2:05:39
  Speaker 1: And so I'm pretty confident if Amy Klobishar wins the governorship,
• 2:05:43
  Speaker 1: she's going to run for president again. I'm less confident
• 2:05:46
  Speaker 1: it's in twenty twenty eight, because it's tough to run
• 2:05:51
  Speaker 1: for a new office and then immediately turn around and
• 2:05:52
  Speaker 1: start running for president. But she's so established in the
• 2:05:57
  Speaker 1: state she could pull that off. But I only think
• 2:06:01
  Speaker 1: she does it if she really thinks she can win,
• 2:06:03
  Speaker 1: and I'm not sure she's got the path. There was
• 2:06:05
  Speaker 1: arguably a better path for her last time. I'm not
• 2:06:07
  Speaker 1: sure it's there this time. But governor's a better title
• 2:06:10
  Speaker 1: to run for president from than senator. So she's coming again.
• 2:06:14
  Speaker 1: Number four on my list is Corey Booker. He clearly
• 2:06:20
  Speaker 1: wants to run again. And you know, he is somebody
• 2:06:26
  Speaker 1: that I never understood why he didn't get more traction.
• 2:06:29
  Speaker 1: I thought he was. I thought he did a better
• 2:06:31
  Speaker 1: job of running on Biden's message than Biden did. He
• 2:06:37
  Speaker 1: was a better version of the Joe Biden sort of
• 2:06:39
  Speaker 1: candidacy with a you know, with like slightly more change rhetoric.
• 2:06:44
  Speaker 1: To it, but I thought he was sort of he
• 2:06:48
  Speaker 1: would at times, he would do a better job defending
• 2:06:51
  Speaker 1: Biden's stances on certain things during those debates than Biden himself.
• 2:06:57
  Speaker 1: But it never connected. You know, people in and around
• 2:07:01
  Speaker 1: Booker have a theory that you know that he was
• 2:07:04
  Speaker 1: just seen as you know, you know, because he wasn't historic,
• 2:07:09
  Speaker 1: They weren't ready to make history twice. I don't know.
• 2:07:12
  Speaker 1: I don't know why Corey Booker didn't do as I
• 2:07:17
  Speaker 1: thought as far as a political performer, athlete. Now, maybe
• 2:07:22
  Speaker 1: maybe it was behind the scenes, Maybe it was the
• 2:07:24
  Speaker 1: blocking and tackling. Maybe it was a campaign structure that
• 2:07:27
  Speaker 1: wasn't as good as it could have been. He didn't
• 2:07:29
  Speaker 1: raise the money. I think that he thought he was
• 2:07:30
  Speaker 1: going to raise and that maybe maybe the donor community
• 2:07:33
  Speaker 1: just viewed him as sort of, well, we've already done Obama,
• 2:07:36
  Speaker 1: let's do this, Or they were more namored with Pete,
• 2:07:38
  Speaker 1: or they were more namored with some other candidates. So
• 2:07:41
  Speaker 1: I think Booker just feels like it was a campaign
• 2:07:44
  Speaker 1: that was unfinished. So he's a guy that I definitely
• 2:07:47
  Speaker 1: think is going to run again, and frankly not twenty
• 2:07:50
  Speaker 1: eight win. So and i'd put him in the four slot,
• 2:07:53
  Speaker 1: number three. Pete Pudagic, He's another one that his look
• 2:08:00
  Speaker 1: he was you could argue, I think if you take
• 2:08:04
  Speaker 1: COVID away, I'm not as convinced. You know, there's no COVID.
• 2:08:11
  Speaker 1: It's not happening. If there wasn't this like quick consolidation,
• 2:08:17
  Speaker 1: there's another world where that it is. It is Bernie
• 2:08:21
  Speaker 1: and Pete that are the final two going to the convention.
• 2:08:24
  Speaker 1: This is a world without COVID. I will always believe
• 2:08:29
  Speaker 1: that it was COVID plus Kai Cliburn that sort of
• 2:08:31
  Speaker 1: and then everybody just decided to drop consolidate, and it
• 2:08:34
  Speaker 1: was this stop burning movement essentially, and the Biden you
• 2:08:37
  Speaker 1: know Biden folks, it was Cliburn in some ways in
• 2:08:40
  Speaker 1: the institutionalists of the Democratic Party that sort of rallied
• 2:08:43
  Speaker 1: this because they knew it was going to go all
• 2:08:44
  Speaker 1: the way to the convention, and they knew the only
• 2:08:46
  Speaker 1: candidate that all the younger ones would drop out for
• 2:08:48
  Speaker 1: was Biden. But Pete was going to be the you know,
• 2:08:54
  Speaker 1: I think if we the the the what if? For me,
• 2:08:56
  Speaker 1: I think it's Pete's versus Bernie going into that twenty
• 2:08:59
  Speaker 1: convention without COVID. My guess is Pete narrowly wins it
• 2:09:04
  Speaker 1: just because there would have been a pretty strong anti
• 2:09:07
  Speaker 1: Bernie faction in the party that would have would have
• 2:09:09
  Speaker 1: would have succeeded. That's been my theory in that. But
• 2:09:13
  Speaker 1: I think anyway, so look, Pete's going to have there's
• 2:09:16
  Speaker 1: the old Obama team is still sort of the Pete
• 2:09:18
  Speaker 1: inner circle, and they'll be formidable. Number two in the
• 2:09:22
  Speaker 1: list is Bernie Sanders. I don't know if he's running,
• 2:09:27
  Speaker 1: but if he runs, he's a front runner, and it's
• 2:09:31
  Speaker 1: very possible that, you know, this is the one that
• 2:09:33
  Speaker 1: breaks through. I think we all should be skeptical that
• 2:09:37
  Speaker 1: somehow the party's going to go to an eighty year old, right,
• 2:09:39
  Speaker 1: that seems nonsensical. It seems nonsensical. But if AOC doesn't run,
• 2:09:45
  Speaker 1: I don't know if Bernie is going to want to
• 2:09:47
  Speaker 1: hand the Batonda anybody else. I think he's willing to
• 2:09:49
  Speaker 1: sit this one out for her. I don't know if
• 2:09:52
  Speaker 1: he is for Rocanna. I don't know if he is
• 2:09:54
  Speaker 1: for JB. Pritzker. Kritzker's somebody that is in four point
• 2:09:59
  Speaker 1: five on my list, by the way, I think he's
• 2:10:01
  Speaker 1: I think he's going to be a pretty formidable candidate,
• 2:10:06
  Speaker 1: I do, but he would. I think he's more formidable
• 2:10:12
  Speaker 1: if there's no AOC and no burning because I think
• 2:10:15
  Speaker 1: he wants to claim that lane, and I think he
• 2:10:17
  Speaker 1: could buy that lane if he had to. But number
• 2:10:21
  Speaker 1: one on my list of those that have run before,
• 2:10:24
  Speaker 1: who's most who's I think best position to get the nomination,
• 2:10:26
  Speaker 1: it's Kamala Harris. I think she's got more institutional support
• 2:10:31
  Speaker 1: than people realize. I think the I think the African
• 2:10:35
  Speaker 1: American community is I think certainly in the Democratic Party
• 2:10:42
  Speaker 1: would stick by her at at the start, and if
• 2:10:45
  Speaker 1: she could show strength, it becomes I think there's a
• 2:10:50
  Speaker 1: lot of women in general feel like she was. She
• 2:10:54
  Speaker 1: didn't get her real shot, and she, you know, deserves
• 2:10:58
  Speaker 1: a fresh shot at this. I think her I told
• 2:11:01
  Speaker 1: you so messaging might be quite effective in a primary. Right.
• 2:11:06
  Speaker 1: She made all of these predictions about Trump, and they
• 2:11:08
  Speaker 1: all look very prescient today when you replay them. So tactically,
• 2:11:13
  Speaker 1: her campaign didn't age well at all, but some of
• 2:11:16
  Speaker 1: the lines she did are aging really well. Right, Some
• 2:11:19
  Speaker 1: of the attack lines on Trump her debate performances are
• 2:11:22
  Speaker 1: going to are aging well. So it's another reason I
• 2:11:27
  Speaker 1: wanted to do this list. I think people are underestimating
• 2:11:31
  Speaker 1: the strength of Kamala Harrison a presidential primary big time.
• 2:11:35
  Speaker 1: I'm not saying there isn't a faction that of donors
• 2:11:37
  Speaker 1: who definitely want to turn the page do something new.
• 2:11:40
  Speaker 1: Anybody's associate with and I personally, I still think it's
• 2:11:43
  Speaker 1: more likely to be somebody who didn't run before this
• 2:11:45
  Speaker 1: company nominate, but underestimate Kamala Harris.
• 2:11:47
  Speaker 3: At your own per.
• 2:11:55
  Speaker 4: Ask Chuck.
• 2:11:58
  Speaker 1: All Right, we're gonna just it's been a long episode,
• 2:12:01
  Speaker 1: so I'm going to do four questions here, So we'll
• 2:12:04
  Speaker 1: start with Joe b. He goes first time riding in
• 2:12:07
  Speaker 1: Big Fan, going back to your NBC days and the
• 2:12:09
  Speaker 1: podcast has been a great companion during commutes and even
• 2:12:12
  Speaker 1: a recent hospital stay. Well, I'm glad to know you're
• 2:12:15
  Speaker 1: out of the hospital. After reading The Power Broker, I
• 2:12:18
  Speaker 1: couldn't help but notice parallels between Robert Moses tactics and
• 2:12:20
  Speaker 1: some of Trump's approach to power. You've mentioned we maybe
• 2:12:23
  Speaker 1: do for a reform era. What do you see as
• 2:12:25
  Speaker 1: today's equivalent of the good government groups that helped drive
• 2:12:27
  Speaker 1: reform in the early twentieth century. Thank you, Joe b
• 2:12:34
  Speaker 1: You know, that's an interesting conundrum because I think that's
• 2:12:38
  Speaker 1: it goes to sort of the point I was making
• 2:12:41
  Speaker 1: at the top of this podcast about the Democratic Party's identity.
• 2:12:44
  Speaker 1: I kind of think they, you know, I think there
• 2:12:47
  Speaker 1: needs to be some new reform groups. I think we need.
• 2:12:49
  Speaker 1: I think we don't trust the old right. You can't
• 2:12:52
  Speaker 1: go back and hope that Common Cause and the NAACP
• 2:12:56
  Speaker 1: can pick up the mantle here, the ACLU or the
• 2:12:59
  Speaker 1: Southern Popy Law Center right, they're fairly or unfairly I
• 2:13:03
  Speaker 1: think these and especially among millennials and Gen Z and
• 2:13:09
  Speaker 1: particularly whether they're they're highly engaged members of that generation
• 2:13:13
  Speaker 1: or low engagement voters of that generation. I think those
• 2:13:17
  Speaker 1: groups mean nothing to them, and so I think you're
• 2:13:20
  Speaker 1: better off going with new ones, right. I'm and and
• 2:13:25
  Speaker 1: I kind of think we you know, I know there's
• 2:13:27
  Speaker 1: some fledgling groups because they've contacted me about uncapping the House.
• 2:13:31
  Speaker 1: I think it's called no cap and I want to
• 2:13:33
  Speaker 1: engage with them. I've just been overextended, so I haven't
• 2:13:36
  Speaker 1: been able to give them the give them my attention
• 2:13:41
  Speaker 1: the way I want. I'm doing some other political form
• 2:13:43
  Speaker 1: efforts that I do that I am engaged in open primaries,
• 2:13:49
  Speaker 1: Unite America. There's a few of these tactical groups that
• 2:13:52
  Speaker 1: are trying to get at the infrastructure. And there's more
• 2:13:56
  Speaker 1: partisan leading ones, you know, but there's some different ones,
• 2:14:00
  Speaker 1: I think within each party. There's some different think tanks
• 2:14:06
  Speaker 1: that are trying to, you know, say hey, maybe we
• 2:14:09
  Speaker 1: should try a project twenty twenty nine, or maybe we
• 2:14:12
  Speaker 1: should try so like you have the the former Harry
• 2:14:17
  Speaker 1: Reid staffer Adam Gentilsen, who I interviewed here search Light Institute.
• 2:14:21
  Speaker 1: He wants to be I think, a place to you know,
• 2:14:25
  Speaker 1: help Democrats talk to more voters that they don't normally
• 2:14:28
  Speaker 1: talk to. I don't know if that's a reform movement.
• 2:14:31
  Speaker 1: That's a reform movement inside the Democratic Party. You know,
• 2:14:36
  Speaker 1: you do have the Pete Peterson Foundation who's trying to
• 2:14:38
  Speaker 1: get people more engaged on the debt, and they're trying
• 2:14:41
  Speaker 1: to do some different things it. But I go there aren't.
• 2:14:46
  Speaker 1: I think the problem is, you know, these some of
• 2:14:49
  Speaker 1: these institutions atrophied a little bit. Some of them went
• 2:14:54
  Speaker 1: super Trump resistance and then sort of lost their own
• 2:14:57
  Speaker 1: way a little bit. Some of them just got are
• 2:14:59
  Speaker 1: overwhelmed with having to deal with Trump, Trump reactors and stuff.
• 2:15:04
  Speaker 1: See the ACOU that they're not really focused on sort
• 2:15:07
  Speaker 1: of reform stuff. So I kind of think that, you know,
• 2:15:11
  Speaker 1: I would, you know, I'm waiting to see the presidential candidate.
• 2:15:17
  Speaker 1: Maybe it's an independent candidate that sort of runs on
• 2:15:21
  Speaker 1: a reform movement and runs on an almost on an
• 2:15:26
  Speaker 1: specific idea. When Andrew Yang was sort of trying to
• 2:15:36
  Speaker 1: differentiate his candidacy, were talking about universal basic income. Well,
• 2:15:39
  Speaker 1: I don't think that issue ended up with the traction.
• 2:15:43
  Speaker 1: It was a big idea and it was a reform response.
• 2:15:47
  Speaker 1: It was response to what's coming with AI and stuff.
• 2:15:50
  Speaker 1: But it's you know, he sort of in some ways
• 2:15:53
  Speaker 1: organized his candidacy around the idea. That's where I think
• 2:15:56
  Speaker 1: could be an effective reform movement is to run run
• 2:16:03
  Speaker 1: on that. And Citizens United is started as a campaign
• 2:16:08
  Speaker 1: finance group. I feel like they've drifted a bit into
• 2:16:12
  Speaker 1: the more partisan lane a little bit. I think we
• 2:16:15
  Speaker 1: are due for a for a truly either by cross partisan,
• 2:16:19
  Speaker 1: which is the phrasing I like to use better now
• 2:16:21
  Speaker 1: than bipartisan, because there are plenty of independence who fit
• 2:16:24
  Speaker 1: into the cross partisan mindset. We need a cross partisan
• 2:16:28
  Speaker 1: reform entity on money right. I think right now you
• 2:16:32
  Speaker 1: have some of the older campaign finance reform groups are
• 2:16:34
  Speaker 1: all sort of more associated with the left. But I
• 2:16:36
  Speaker 1: think there is real support on the right now for this,
• 2:16:39
  Speaker 1: and I think you in somebody's need to rebrand those
• 2:16:41
  Speaker 1: movements too. Anyway, it's a good question. You's a bit challenging, Joe,
• 2:16:47
  Speaker 1: I'll admit I want to think that through even more.
• 2:16:51
  Speaker 1: Next question comes from Mike, who's also a Tony Kornheiser listener.
• 2:16:55
  Speaker 1: I can tell by the way he said it gave
• 2:16:57
  Speaker 1: me a little lichies y. He goes, Hey, I enjoy
• 2:16:59
  Speaker 1: your conversations with Chrystalizab, but I was struck by what
• 2:17:02
  Speaker 1: felt like a tension in a recent episode. Ooh tension.
• 2:17:04
  Speaker 1: On one hand, you said Democrats shouldn't tray their principles
• 2:17:06
  Speaker 1: when elections. On the other you discussed the need to
• 2:17:08
  Speaker 1: move away from certain positions who appeal to swing voters.
• 2:17:10
  Speaker 1: How do you draw that line when when is it
• 2:17:12
  Speaker 1: a strategic adjustment versus compromising core values. I'm genuinely curious
• 2:17:16
  Speaker 1: how you think about that balance. I don't think you
• 2:17:19
  Speaker 1: compromise your values, but I think you accept the premise
• 2:17:23
  Speaker 1: that some things some change is slower than others. And
• 2:17:27
  Speaker 1: I go back to a phrase, I like, I'm probably
• 2:17:29
  Speaker 1: over using incrementalism. I think we you know, I think
• 2:17:34
  Speaker 1: when you're trying to make big chains, incrementalism sounds too
• 2:17:37
  Speaker 1: small ball on this or that. But you know, this
• 2:17:39
  Speaker 1: is sort of your classic tortoise hair, right if you
• 2:17:43
  Speaker 1: if you, if you approach I mean take solose security,
• 2:17:46
  Speaker 1: I would argue we did that via incrementalism and started
• 2:17:48
  Speaker 1: just with widows, right, you know, women over sixty five,
• 2:17:54
  Speaker 1: and then slowly it expanded. It was you. Had you
• 2:17:58
  Speaker 1: come out and say we were going to go from
• 2:18:01
  Speaker 1: no social security to what it is today, that program
• 2:18:05
  Speaker 1: would have been extraordinarily unpopular, might not have ever made.
• 2:18:08
  Speaker 1: It might not have ever But if you want to
• 2:18:14
  Speaker 1: test out a premise, you start small and you move incrementally,
• 2:18:18
  Speaker 1: and suddenly you can make a big change. I mean,
• 2:18:21
  Speaker 1: what we did with poverty amongst seniors was transformational and
• 2:18:25
  Speaker 1: it was necessary. So so it's about what issues are
• 2:18:32
  Speaker 1: you going to emphasize and which ones aren't you going
• 2:18:34
  Speaker 1: to emphasize? Which ones are in your under your purview.
• 2:18:41
  Speaker 1: You don't have to when you're running the country as president.
• 2:18:44
  Speaker 1: You don't have to engage in every cultural issue, and
• 2:18:50
  Speaker 1: I can't wait for the and for whatever reasons, presidents
• 2:18:53
  Speaker 1: can't bring themselves to do this. But someday a president's
• 2:18:55
  Speaker 1: going to say I got a strong opinion about that,
• 2:18:58
  Speaker 1: but I don't want to insert myself to this because
• 2:19:01
  Speaker 1: whatever I say is going to get overinterpreted. So it's
• 2:19:05
  Speaker 1: a no win and I don't want to do It's
• 2:19:07
  Speaker 1: not fair to insert. Right, But every president feels like, well,
• 2:19:14
  Speaker 1: it makes me more human. Right, I have an opinion too,
• 2:19:17
  Speaker 1: But in some ways it actually, you know you can.
• 2:19:22
  Speaker 1: I think that you know you could do it. It's
• 2:19:24
  Speaker 1: in some ways it's a better way to appeal to
• 2:19:26
  Speaker 1: some in the middle. So that's the line. It's to me,
• 2:19:30
  Speaker 1: it's values, and you don't in its emphasis. It's not
• 2:19:36
  Speaker 1: about throwing entities under the bus. It's not sister soldiers.
• 2:19:40
  Speaker 1: You know, we talk about that such a soldier moment,
• 2:19:42
  Speaker 1: which was this Bill Clinton thing in nineteen ninety two
• 2:19:44
  Speaker 1: where he was trying to and he sort of picked
• 2:19:46
  Speaker 1: on one artist. That isn't the way I would do it.
• 2:19:54
  Speaker 1: I mean, it wasn't effective, but that isn't the way
• 2:19:56
  Speaker 1: you'd probably wish. You wouldn't do it. Next question comes
• 2:20:01
  Speaker 1: from Mark h Allen, Texas, and he's hopeful that this
• 2:20:03
  Speaker 1: is number five that he has made it into the
• 2:20:05
  Speaker 1: five timers club. Hey goes. Love to hear in your
• 2:20:08
  Speaker 1: conversation with Kevin Williamson. It felt like a true crossover
• 2:20:10
  Speaker 1: episode for me. I recently heard the argument that socially
• 2:20:12
  Speaker 1: liberal fiscally conservative voters actually are the smallest political group,
• 2:20:15
  Speaker 1: which surprised me since it feels common in my own circles. Ah,
• 2:20:18
  Speaker 1: it's your bubble, right brother. Anyway? Is that kind of
• 2:20:21
  Speaker 1: platform a political dead end or could it actually serve
• 2:20:24
  Speaker 1: as a bridge between parties and help reset some of
• 2:20:26
  Speaker 1: today's polarization. Mark h Alan, Texas. I look, I think
• 2:20:31
  Speaker 1: it could serve as a bridge. I really want to see.
• 2:20:35
  Speaker 1: I think the old look. We're not going to get
• 2:20:38
  Speaker 1: rid of the two parties. I would like to create
• 2:20:42
  Speaker 1: the conditions to make it easier for third and fourth
• 2:20:45
  Speaker 1: parties and independent candidates to compete in the free market
• 2:20:49
  Speaker 1: marketplace of ideas. But we are not a free market
• 2:20:51
  Speaker 1: system when it comes to the ideas, and we're not
• 2:20:54
  Speaker 1: We're duopoly. And I am more the the movements I'm
• 2:21:01
  Speaker 1: involved in are about opening ballots up and opening primaries.
• 2:21:04
  Speaker 1: Up right, I am biased towards voters. I think more
• 2:21:09
  Speaker 1: voters should be involved in more races. Hard stop call
• 2:21:13
  Speaker 1: me biased. I am. I have this bias towards the
• 2:21:17
  Speaker 1: small de democracy. Anyway, I really hope there's an independent
• 2:21:22
  Speaker 1: candidate that basically goes that. Is this candidate socially liberal,
• 2:21:28
  Speaker 1: you know, in some form of this fiscally conservative incrementalism
• 2:21:33
  Speaker 1: sort of like let's you know, little Eisenhower ish little
• 2:21:36
  Speaker 1: maybe it's a military veteran, something like that, to sort
• 2:21:41
  Speaker 1: of recalibrate the other two parties. The only way you're
• 2:21:44
  Speaker 1: going to get the two parties to reform themselves is
• 2:21:46
  Speaker 1: that they're threatened by a third. That's the lesson I've
• 2:21:50
  Speaker 1: always taken away from the Pro campaign is that the
• 2:21:55
  Speaker 1: a independent campaign doesn't have to win to be successful.
• 2:21:58
  Speaker 1: Ross Pro didn't have to win, and he was quite successful.
• 2:22:02
  Speaker 1: I think it's at a minimum a model I like
• 2:22:04
  Speaker 1: to see attempted in twenty eight. So Mark, is that
• 2:22:09
  Speaker 1: you are you going to be that candidate? Maybe it's
• 2:22:13
  Speaker 1: a maybe, it's it's Kevin's got to smile more right,
• 2:22:17
  Speaker 1: We could, we could, we could talk Kevin Williamson. He's
• 2:22:20
  Speaker 1: a new old young father right. Next question. Last question,
• 2:22:27
  Speaker 1: I recently saw the idea of turning a company like
• 2:22:29
  Speaker 1: Spirit Airlines into a co op, and it made me
• 2:22:32
  Speaker 1: think about how communities use co ops to fill gaps
• 2:22:34
  Speaker 1: when corporations or government fall short. Do you think co
• 2:22:37
  Speaker 1: ops could be a viable solution to some of today's
• 2:22:39
  Speaker 1: economic challenges or are there limits to how far that
• 2:22:42
  Speaker 1: model can go, and if not, what alternatives do you
• 2:22:44
  Speaker 1: see for addressing these gaps. Thanks Sarah, Kay Lansing, Michigan. Oh, Sarah,
• 2:22:48
  Speaker 1: I love me a good co op. I think, in fact,
• 2:22:54
  Speaker 1: my favorite football team is in theory a co op. Right,
• 2:22:58
  Speaker 1: It's Green Bay Packers owned by the community. I think
• 2:23:03
  Speaker 1: there are certain things I think the answer on local
• 2:23:06
  Speaker 1: news is co ops, local co ops where it's owned
• 2:23:10
  Speaker 1: by the community. It was one of the ideas spitballed that.
• 2:23:17
  Speaker 1: I think Kerri Swisher and I spitballed this during a
• 2:23:21
  Speaker 1: news Fair episode. The community of Washington is still today
• 2:23:25
  Speaker 1: feels like it owns the Washington Post. So let the
• 2:23:28
  Speaker 1: community own it, community owned board and stuff like this.
• 2:23:31
  Speaker 1: I think for certain institutions that are like essentially private
• 2:23:36
  Speaker 1: institutions that are really important to the public world, which
• 2:23:43
  Speaker 1: is local news organizations. I think as a co op.
• 2:23:47
  Speaker 1: And it could be that that's the better model for
• 2:23:50
  Speaker 1: an MPR. Is that I don't think it works everywhere,
• 2:23:54
  Speaker 1: but I think it can work in media. I think
• 2:23:58
  Speaker 1: it absolutely would be how the sports world works, right
• 2:24:03
  Speaker 1: it It really bugs me. And obviously, being a Packer fan,
• 2:24:07
  Speaker 1: I can stand on ceremony on this. I don't think
• 2:24:12
  Speaker 1: the value, you know, the owner's value. You know, the
• 2:24:18
  Speaker 1: sports owner team is only valuable because of the league
• 2:24:24
  Speaker 1: and the city and the value of that league in city.
• 2:24:28
  Speaker 1: Right it is. It is There's only so much you
• 2:24:31
  Speaker 1: can do as an individual team. So and in some
• 2:24:35
  Speaker 1: ways the city matters more to the to the value
• 2:24:39
  Speaker 1: of the team in time than anything else. The community.
• 2:24:44
  Speaker 1: I mean, you know, I I I know that. You
• 2:24:49
  Speaker 1: know we could have many we could We could still
• 2:24:51
  Speaker 1: be angry at the gm WE Packer fans can get
• 2:24:53
  Speaker 1: angry at our gm WE Packer fans can get angry
• 2:24:55
  Speaker 1: at the president. Right, there's still people to get mad
• 2:24:58
  Speaker 1: at if you don't like how the team's been run.
• 2:25:03
  Speaker 1: But I'm a non football stuff you know, the community
• 2:25:05
  Speaker 1: auto ought to be in charge of the teams too,
• 2:25:09
  Speaker 1: So I guess it's the private institutions that are part
• 2:25:13
  Speaker 1: of the civic world, right, professional sports or that news organizations.
• 2:25:24
  Speaker 1: I think could be that. I'm not sure, you know,
• 2:25:29
  Speaker 1: I actually think a co op could work with an
• 2:25:31
  Speaker 1: airline because an airline, right, you need, it's not fully
• 2:25:36
  Speaker 1: a private entity. I mean, obviously each airline is a
• 2:25:38
  Speaker 1: private entity, but they can't function without government, right. They
• 2:25:45
  Speaker 1: can't function without air traffic controllers. They can't function without airports,
• 2:25:48
  Speaker 1: which are run by local governments. So I think it
• 2:25:51
  Speaker 1: actually could work in the airline space. But to me,
• 2:25:54
  Speaker 1: that's the space that it works best. It's the space
• 2:25:57
  Speaker 1: where it's a private enterprise, where non that isn't quite
• 2:26:00
  Speaker 1: the answer. You don't know if you want a single
• 2:26:03
  Speaker 1: individual or private equity of doing it right. You want
• 2:26:07
  Speaker 1: sort of this feeling that they're looking out for the
• 2:26:09
  Speaker 1: best interest of the community, and that's where I think
• 2:26:12
  Speaker 1: co op starts to make the most sense. It's not
• 2:26:16
  Speaker 1: for every entity, but I could argue that airlines would
• 2:26:20
  Speaker 1: fit my definition. Curious your feedback on that answer, Sarah,
• 2:26:25
  Speaker 1: So I'd love to hear back from you. Hey, thanks
• 2:26:27
  Speaker 1: everybody for listening. I will put a pin in this episode.
• 2:26:31
  Speaker 1: Good news is, we'll be coming back to you in
• 2:26:33
  Speaker 1: twenty four hours. Don't forget to like and subscribe and
• 2:26:36
  Speaker 1: I'll see that