WEBVTT - Mariana Mazzucato Thinks We Need More Moonshots

0:00:02.720 --> 0:00:14.000
<v Speaker 1>Bloomberg Audio Studios, Podcasts, Radio News.

0:00:18.440 --> 0:00:22.040
<v Speaker 2>Hello and welcome to another episode of the Odd Lawns Podcast.

0:00:22.120 --> 0:00:24.360
<v Speaker 3>I'm Jill Wisenthal and I'm Tracy Alloway.

0:00:24.440 --> 0:00:26.279
<v Speaker 2>We're still here in Madrid. Tracy, how are still here?

0:00:26.360 --> 0:00:27.080
<v Speaker 2>You have a good time?

0:00:27.360 --> 0:00:30.080
<v Speaker 3>I am. I've eaten a lot of ham and cheese

0:00:30.120 --> 0:00:31.920
<v Speaker 3>and that's pretty much all I can say.

0:00:32.000 --> 0:00:34.080
<v Speaker 2>Yeah, I'm going to turn into a hormone by the

0:00:34.120 --> 0:00:37.040
<v Speaker 2>time I leave. I'm certain of that. So we are

0:00:37.080 --> 0:00:40.040
<v Speaker 2>at the Bloomberg City Lab conference. You know, it's funny,

0:00:40.159 --> 0:00:43.360
<v Speaker 2>like the mayoral level of politics, not something we spend

0:00:43.400 --> 0:00:47.000
<v Speaker 2>a ton of time typically on, but I would say,

0:00:47.080 --> 0:00:49.320
<v Speaker 2>like it definitely. You know when I think about it,

0:00:49.360 --> 0:00:51.120
<v Speaker 2>when I'm like here and like listening to a lot

0:00:51.120 --> 0:00:54.320
<v Speaker 2>of the conversations, it's just so obviously like connected to

0:00:54.360 --> 0:00:56.520
<v Speaker 2>a lot of the themes we talk about, because so

0:00:56.680 --> 0:00:59.480
<v Speaker 2>much of our discussions have to do with something related

0:00:59.560 --> 0:01:04.560
<v Speaker 2>to you know, innovation or technology or implementation of policy

0:01:04.840 --> 0:01:07.720
<v Speaker 2>and how it spans both the public and private sectors. Yeah.

0:01:07.800 --> 0:01:09.480
<v Speaker 3>I mean also when I think about a lot of

0:01:09.520 --> 0:01:13.800
<v Speaker 3>a thloughts topics like AI or housing affordability or inequality

0:01:13.959 --> 0:01:17.000
<v Speaker 3>like cities, I think City lab actually use this phrase

0:01:17.000 --> 0:01:19.000
<v Speaker 3>at one point, but cities are really at the front

0:01:19.040 --> 0:01:22.080
<v Speaker 3>line of all of those challenges, right, and trying to

0:01:22.080 --> 0:01:24.520
<v Speaker 3>implement policy in that local level in a way that's

0:01:24.600 --> 0:01:28.360
<v Speaker 3>like very easy to see and observe and also to

0:01:28.480 --> 0:01:29.280
<v Speaker 3>judge totally.

0:01:29.480 --> 0:01:32.680
<v Speaker 2>Yeah, no, it's exactly right. And I think maybe there's

0:01:32.720 --> 0:01:35.920
<v Speaker 2>something like, you know, I don't it feels like to

0:01:35.959 --> 0:01:39.520
<v Speaker 2>some extent, the mayoral level of any governance to sort

0:01:39.560 --> 0:01:43.160
<v Speaker 2>of maybe the least ideological and the most like, you know,

0:01:43.240 --> 0:01:45.560
<v Speaker 2>we talked to the Baltimore mayor, for example, and so

0:01:45.680 --> 0:01:48.600
<v Speaker 2>much of his theme was just like talking to other mayors,

0:01:48.600 --> 0:01:51.000
<v Speaker 2>like what's working in your town, that's working in your city,

0:01:51.120 --> 0:01:53.240
<v Speaker 2>and what's not working and so forth. They all have

0:01:53.320 --> 0:01:56.440
<v Speaker 2>such similar challenges, so many things have been like repeated,

0:01:56.680 --> 0:01:59.360
<v Speaker 2>you know, one time after another that like they all

0:01:59.400 --> 0:02:01.880
<v Speaker 2>can sort of speak the same language and all have

0:02:01.880 --> 0:02:02.560
<v Speaker 2>the same issues.

0:02:02.720 --> 0:02:04.960
<v Speaker 3>Yeah, it's funny. You kind of got that local idea

0:02:05.120 --> 0:02:07.720
<v Speaker 3>swapping at a mayor a level that I cannot imagine

0:02:08.080 --> 0:02:11.200
<v Speaker 3>necessarily happening in national politics. Like can you imagine Trump

0:02:11.280 --> 0:02:13.240
<v Speaker 3>and Chi Himpin getting together and be like, oh, we

0:02:13.280 --> 0:02:17.680
<v Speaker 3>implemented this really cool, like national transportation program. Have you

0:02:17.760 --> 0:02:18.120
<v Speaker 3>tried it?

0:02:18.280 --> 0:02:20.639
<v Speaker 2>Yeah, you know, know you hear like these stories right

0:02:20.639 --> 0:02:23.640
<v Speaker 2>of a governor sometimes or a mayor will go to

0:02:23.680 --> 0:02:25.760
<v Speaker 2>like another country like oh we can like learn from

0:02:25.760 --> 0:02:28.440
<v Speaker 2>what the city did on transit or whatever. But no,

0:02:28.560 --> 0:02:31.240
<v Speaker 2>you don't really hear that the same way at the

0:02:31.280 --> 0:02:34.359
<v Speaker 2>real national level, where a lot of our discussions tend

0:02:34.360 --> 0:02:34.679
<v Speaker 2>to sit.

0:02:34.880 --> 0:02:36.520
<v Speaker 4>Absolutely Anyway, I'm really.

0:02:36.320 --> 0:02:39.080
<v Speaker 2>Excited about today's episode. We're going to be speaking with

0:02:39.120 --> 0:02:41.040
<v Speaker 2>a guest who I would say, like, since we've been

0:02:41.040 --> 0:02:45.119
<v Speaker 2>doing Odd Lives, is actually one of the more frequently requested,

0:02:45.320 --> 0:02:47.920
<v Speaker 2>long requested, and so it's sort of a failure on

0:02:47.960 --> 0:02:50.360
<v Speaker 2>our part that like we just like never made it

0:02:50.400 --> 0:02:54.360
<v Speaker 2>happen before. But yeah, someone who like really like those

0:02:54.440 --> 0:02:57.040
<v Speaker 2>whole career is like dedicated to a lot of odd,

0:02:57.080 --> 0:02:57.840
<v Speaker 2>lozzy things.

0:02:57.880 --> 0:02:59.960
<v Speaker 3>Well, we waited until we could do it at Madri,

0:03:00.120 --> 0:03:00.440
<v Speaker 3>but I.

0:03:00.400 --> 0:03:03.160
<v Speaker 2>Didn't want to just do it at any other random venue. Yes,

0:03:03.200 --> 0:03:06.320
<v Speaker 2>it was all very strategically designed. So we really do

0:03:06.440 --> 0:03:08.200
<v Speaker 2>have the perfect guest. Some of that A lot of

0:03:08.200 --> 0:03:10.080
<v Speaker 2>guests have wanted to listen to here from for a

0:03:10.080 --> 0:03:12.919
<v Speaker 2>long time. We're going to be speaking with Mariana Matzicato,

0:03:13.000 --> 0:03:16.000
<v Speaker 2>professor a University College London, founder of the Institute for

0:03:16.040 --> 0:03:19.280
<v Speaker 2>Public Purpose, author of several books sort of touching on

0:03:19.360 --> 0:03:23.799
<v Speaker 2>these themes of technology, public sector, private sector, the roots

0:03:23.800 --> 0:03:28.000
<v Speaker 2>of innovation, how these things actually get deployed. So, Professor Matzakato,

0:03:28.080 --> 0:03:32.799
<v Speaker 2>thank you so much for coming on ODL. Finally, finally,

0:03:33.800 --> 0:03:37.160
<v Speaker 2>are completely our fault for not having made it happen sooner.

0:03:37.160 --> 0:03:38.960
<v Speaker 2>But what do you just started? Like, what are you

0:03:39.040 --> 0:03:42.160
<v Speaker 2>doing here? What brings you to this particular conference a

0:03:42.920 --> 0:03:43.960
<v Speaker 2>what attracts you here?

0:03:44.120 --> 0:03:46.760
<v Speaker 4>Well, first of all, I'm here also because the government

0:03:46.800 --> 0:03:50.040
<v Speaker 4>of Spain is really kind of leading the way in

0:03:50.360 --> 0:03:52.920
<v Speaker 4>many areas that I'm very interested in, especially the kind

0:03:52.920 --> 0:03:55.760
<v Speaker 4>of new economic thinking that needs to underpin how we

0:03:55.760 --> 0:03:58.600
<v Speaker 4>rethink government. And so I was meeting with both the

0:03:58.680 --> 0:04:03.040
<v Speaker 4>Prime Minister and the Minister for the Economy, Carol Squerpo,

0:04:03.120 --> 0:04:05.920
<v Speaker 4>who I'm on a panel today with about a council

0:04:05.920 --> 0:04:07.560
<v Speaker 4>that we've just set up. It's called the Global Council

0:04:07.600 --> 0:04:10.320
<v Speaker 4>for a Common Good Economy anyway, And besides that, I'm

0:04:10.320 --> 0:04:13.760
<v Speaker 4>also here to speak at the Bloomberg City Labs event

0:04:13.880 --> 0:04:16.680
<v Speaker 4>about this new public sector Capability index that we've been

0:04:16.720 --> 0:04:19.680
<v Speaker 4>developing with them, as a partner, which is really about

0:04:20.080 --> 0:04:23.600
<v Speaker 4>reinvesting inside the civil service so that they can really

0:04:23.640 --> 0:04:26.880
<v Speaker 4>tackle those wicked complex problems instead of you know, hiring

0:04:26.920 --> 0:04:29.360
<v Speaker 4>Deloitte during COVID and giving them one point five million

0:04:29.600 --> 0:04:31.960
<v Speaker 4>a day to do test and trace, which they fail

0:04:32.040 --> 0:04:32.719
<v Speaker 4>at in the UK.

0:04:33.360 --> 0:04:36.040
<v Speaker 3>I definitely want to get you to go off on consultants.

0:04:37.040 --> 0:04:39.039
<v Speaker 3>But before we do, like when you meet with someone

0:04:39.080 --> 0:04:41.320
<v Speaker 3>like the Prime Minister of Spain, what is it that

0:04:41.360 --> 0:04:43.680
<v Speaker 3>they want to know from you? Like, what information or

0:04:43.680 --> 0:04:44.800
<v Speaker 3>expertise are they seeking?

0:04:44.960 --> 0:04:47.400
<v Speaker 4>Right? Well, I'm actually quite lucky that my books actually

0:04:47.440 --> 0:04:50.320
<v Speaker 4>get read by the Prime minister. So usually what happens

0:04:50.400 --> 0:04:53.320
<v Speaker 4>is that they've especially the Entrepreneurial State, which I know

0:04:53.360 --> 0:04:55.240
<v Speaker 4>rud in twenty thirteen that had quite a bit of

0:04:55.279 --> 0:04:57.760
<v Speaker 4>an effect here. They even wrote a report called el

0:04:58.880 --> 0:05:02.200
<v Speaker 4>Espae and they we really want to ask me, you know,

0:05:02.240 --> 0:05:04.560
<v Speaker 4>what does that mean? What does it mean for actually

0:05:04.600 --> 0:05:06.560
<v Speaker 4>even being able to fail? For example? Right, so a

0:05:06.640 --> 0:05:09.680
<v Speaker 4>venture capitalists are was bragging about all the failures that

0:05:09.720 --> 0:05:11.680
<v Speaker 4>they had in order to get a success, you know,

0:05:11.720 --> 0:05:13.719
<v Speaker 4>whereas as soon as a civil servant or a minister

0:05:13.760 --> 0:05:16.080
<v Speaker 4>fails or prime minister fails. Front page of the papers,

0:05:16.440 --> 0:05:19.640
<v Speaker 4>So they're very interested in the kind of narrative change,

0:05:19.680 --> 0:05:25.000
<v Speaker 4>but also well the cultural change, but especially the theoretical underpinning.

0:05:25.120 --> 0:05:27.960
<v Speaker 4>Would then say, a finance ministry or an economics ministry

0:05:28.040 --> 0:05:30.720
<v Speaker 4>that needs to then a company rethinking government, because otherwise,

0:05:30.720 --> 0:05:33.280
<v Speaker 4>if you continue to have the old economic models where

0:05:33.279 --> 0:05:36.640
<v Speaker 4>we judge things by cost benefit analysis and at present value,

0:05:36.640 --> 0:05:39.400
<v Speaker 4>all these really static metrics, we would have never even

0:05:39.440 --> 0:05:41.800
<v Speaker 4>bothered going to the moon. Okay, first of all, in

0:05:41.839 --> 0:05:43.839
<v Speaker 4>the nineteen sixties, had we thought of it as a

0:05:43.839 --> 0:05:47.560
<v Speaker 4>cost benefit calculation and so what should replace that? Right?

0:05:48.000 --> 0:05:51.520
<v Speaker 3>So you mentioned the Entrepreneurial State being published in twenty thirteen,

0:05:51.600 --> 0:05:53.680
<v Speaker 3>and I feel like I need to emphasize this because

0:05:53.960 --> 0:05:56.360
<v Speaker 3>there has been this mind shift since the twenty twenty

0:05:56.680 --> 0:05:59.600
<v Speaker 3>pandemic on industrial policy, and we kind of take it

0:06:00.040 --> 0:06:02.560
<v Speaker 3>almost as a given, especially on this show, that there

0:06:02.600 --> 0:06:04.600
<v Speaker 3>is a role for governments to play when it comes

0:06:04.600 --> 0:06:08.960
<v Speaker 3>to innovation and entrepreneurialism. But you were there very early.

0:06:09.560 --> 0:06:13.200
<v Speaker 3>Did you feel vindicated by the twenty twenty shift.

0:06:13.360 --> 0:06:15.279
<v Speaker 4>Well, I think there's a bit of a misunderstanding that

0:06:15.400 --> 0:06:17.800
<v Speaker 4>just because government's spending a lot of money, investing a

0:06:17.839 --> 0:06:20.040
<v Speaker 4>lot of money, whether it's the IRA or the next

0:06:20.080 --> 0:06:24.279
<v Speaker 4>GENUU to trillion recovery plan in Europe. That that means

0:06:24.279 --> 0:06:26.880
<v Speaker 4>that industrial strategy is back, or that you know, government

0:06:26.920 --> 0:06:30.000
<v Speaker 4>is being really strategic. It depends, And I mean that's

0:06:30.000 --> 0:06:31.719
<v Speaker 4>the whole point, right, you know, how are we actually

0:06:31.720 --> 0:06:33.960
<v Speaker 4>framing it? Is it just a lot of tax incentives?

0:06:34.040 --> 0:06:36.919
<v Speaker 4>Are we focused too much on sectors? To what degree

0:06:37.480 --> 0:06:41.600
<v Speaker 4>is industrial strategy actually helping to create a more inclusive, sustainable,

0:06:42.080 --> 0:06:45.880
<v Speaker 4>innovation driven, you know, economy, or is it just another

0:06:45.920 --> 0:06:49.080
<v Speaker 4>wave of handouts and subsidies to particular sectors and then

0:06:49.120 --> 0:06:52.599
<v Speaker 4>we end up socializing risks and privatizing rewards. And also,

0:06:52.640 --> 0:06:55.040
<v Speaker 4>I mean I used to joke that the US government

0:06:55.040 --> 0:06:57.200
<v Speaker 4>has always had an industrial strategy, but you know, pretended

0:06:57.279 --> 0:06:59.960
<v Speaker 4>not to. And they've always talked to the Jefferson talk

0:07:00.160 --> 0:07:04.159
<v Speaker 4>but acted the Hamilton talk or the Hamiltonian kind of

0:07:04.680 --> 0:07:09.880
<v Speaker 4>more proactive government strategy. But by pretending that wasn't there,

0:07:10.320 --> 0:07:12.800
<v Speaker 4>they kept a lot of things under the radar. And

0:07:13.000 --> 0:07:15.120
<v Speaker 4>the joke bit is just that finally people understood what

0:07:15.120 --> 0:07:17.840
<v Speaker 4>the hell was talking about because of the musical before

0:07:17.840 --> 0:07:21.800
<v Speaker 4>the musical came out Hamilton anyway, So I think that's

0:07:21.800 --> 0:07:25.240
<v Speaker 4>really important to recognize that industrial strategy has always been there,

0:07:25.720 --> 0:07:29.160
<v Speaker 4>except that in certain phases, including now in some countries,

0:07:29.600 --> 0:07:32.760
<v Speaker 4>it's not really strategy in terms of being driven by

0:07:32.840 --> 0:07:35.520
<v Speaker 4>public purpose, which as you said, is the title in

0:07:35.560 --> 0:07:37.840
<v Speaker 4>this Institute for Renovation of Public Purpose that I direct.

0:07:38.160 --> 0:07:42.480
<v Speaker 4>It's been just kind of vertical strategies focused on sectors, technologies,

0:07:42.600 --> 0:07:45.680
<v Speaker 4>types of firms, right, the whole focus on small, medium enterprises.

0:07:46.120 --> 0:07:47.480
<v Speaker 4>So what I've been trying to do is to say,

0:07:47.520 --> 0:07:52.240
<v Speaker 4>stop focusing on sectors, technologies and firms. Focus on big problems, right,

0:07:52.440 --> 0:07:54.520
<v Speaker 4>as bold as going to the moon and back at

0:07:54.560 --> 0:07:56.760
<v Speaker 4>a short amount of time, the mission idea, the missions

0:07:56.800 --> 0:08:00.360
<v Speaker 4>that then require sexual support. But you're not getting support

0:08:00.360 --> 0:08:03.120
<v Speaker 4>because you are a particular sector. You're getting support if

0:08:03.160 --> 0:08:05.800
<v Speaker 4>you're willing. So moving away from picking winners to picking

0:08:05.800 --> 0:08:08.160
<v Speaker 4>the willing, if you're willing to work with government around

0:08:08.200 --> 0:08:11.440
<v Speaker 4>these very difficult challenges, which could be as I don't

0:08:11.440 --> 0:08:14.240
<v Speaker 4>want to say simple, but as concrete as making sure

0:08:14.280 --> 0:08:17.800
<v Speaker 4>that every child in a country has healthy, tasty, sustainable

0:08:17.800 --> 0:08:20.040
<v Speaker 4>school lunch, right, not just school lunch. That was the

0:08:20.040 --> 0:08:21.880
<v Speaker 4>Reagan thing where he said ketchup is a vegetable, So

0:08:21.920 --> 0:08:24.480
<v Speaker 4>we can reduce the cost. We all had T shirts

0:08:24.480 --> 0:08:27.520
<v Speaker 4>of Reagan and ketchup which was the vegetable is what

0:08:27.560 --> 0:08:30.840
<v Speaker 4>the T shirt said. So having moonshots, even on something

0:08:30.840 --> 0:08:35.040
<v Speaker 4>as simple as the cafeteria, that then requires innovation across

0:08:35.120 --> 0:08:38.319
<v Speaker 4>many different areas. It requires government to wake up and

0:08:38.480 --> 0:08:40.960
<v Speaker 4>not just have that be done. For example, from the

0:08:40.960 --> 0:08:44.640
<v Speaker 4>Department of Education, you know, Department of Agriculture, Health, Education,

0:08:44.840 --> 0:08:48.360
<v Speaker 4>Finance would work together on a moonshot of healthy, tasty,

0:08:48.400 --> 0:08:52.280
<v Speaker 4>sustainable school lunch. So that interministerial coordination which we saw

0:08:52.360 --> 0:08:54.920
<v Speaker 4>during COVID, right, so we had the war room, the

0:08:54.960 --> 0:08:58.839
<v Speaker 4>situation room, you know, the military, education, health, and so

0:08:59.040 --> 0:09:02.160
<v Speaker 4>on together because we had these really difficult challenges. But

0:09:02.200 --> 0:09:04.120
<v Speaker 4>as soon as COVID stops, we go back to very

0:09:04.120 --> 0:09:05.280
<v Speaker 4>siloed ways of thinking.

0:09:05.520 --> 0:09:07.640
<v Speaker 2>As someone with two kids in the New York City

0:09:07.679 --> 0:09:12.960
<v Speaker 2>of public schools, I can absolutely confirm that the degree

0:09:13.120 --> 0:09:17.160
<v Speaker 2>to which they associate the mayor with school lunch policy

0:09:17.320 --> 0:09:20.520
<v Speaker 2>is extremely real. And they like talk about like, oh,

0:09:20.559 --> 0:09:22.960
<v Speaker 2>we used to have these like really nice waffles or something,

0:09:23.200 --> 0:09:25.280
<v Speaker 2>and then Eric Adams got rid of home, or like

0:09:25.280 --> 0:09:28.920
<v Speaker 2>they're really like key to single issue, the single issue.

0:09:29.160 --> 0:09:31.760
<v Speaker 2>They're like, really pay attention to the degree to where

0:09:31.800 --> 0:09:35.000
<v Speaker 2>school lunch policy shifts with administration, Like this is like

0:09:35.080 --> 0:09:38.959
<v Speaker 2>the really they really think? What is state capacity? We've

0:09:39.040 --> 0:09:41.480
<v Speaker 2>been using this term for years on the podcast and

0:09:41.520 --> 0:09:44.960
<v Speaker 2>we're like during COVID, we're like, no, it took a took,

0:09:45.040 --> 0:09:47.319
<v Speaker 2>you know, a long time to stand up testing facilities

0:09:47.320 --> 0:09:50.760
<v Speaker 2>for since and people's like, oh, well, lot lack state capacity,

0:09:50.800 --> 0:09:52.360
<v Speaker 2>But what is it? What's the definition?

0:09:52.520 --> 0:09:56.640
<v Speaker 4>We actually distinguish between the word capacity routines kind of

0:09:56.679 --> 0:10:00.480
<v Speaker 4>administrative routines and then capabilities. Okay, so what states are

0:10:00.480 --> 0:10:02.880
<v Speaker 4>often what governments are often lacking or those kind of

0:10:02.960 --> 0:10:06.600
<v Speaker 4>dynamic capability. So capacity partly is like literally do you

0:10:06.600 --> 0:10:08.840
<v Speaker 4>even have fiscal space? Do you have a budget? But

0:10:08.920 --> 0:10:12.080
<v Speaker 4>also how are you thinking about that budget in terms

0:10:12.080 --> 0:10:14.160
<v Speaker 4>of do you well put it this way? Capacity is

0:10:14.160 --> 0:10:16.480
<v Speaker 4>you know a number of people working in your administration,

0:10:16.960 --> 0:10:20.480
<v Speaker 4>the budget that's been allocated, perhaps also the training you

0:10:20.480 --> 0:10:24.160
<v Speaker 4>know that the civil service actually has. But capabilities are

0:10:24.160 --> 0:10:26.200
<v Speaker 4>what you actually then do with it. Are you agile?

0:10:26.280 --> 0:10:28.920
<v Speaker 4>Are you flexible? Are you able to pivot during COVID

0:10:28.960 --> 0:10:32.200
<v Speaker 4>and actually start working in this more again inter ministerial way.

0:10:32.720 --> 0:10:34.960
<v Speaker 4>Do you know how to work with others, right, you know,

0:10:34.960 --> 0:10:38.120
<v Speaker 4>do you set up good partnerships or they problematic partnerships?

0:10:38.520 --> 0:10:40.840
<v Speaker 4>And also you were talking before about what you're learning here,

0:10:40.920 --> 0:10:43.760
<v Speaker 4>which is fantastic about how mayors can learn from each other. Right,

0:10:44.160 --> 0:10:47.120
<v Speaker 4>have you invested in your ability to learn to adapt?

0:10:47.640 --> 0:10:50.760
<v Speaker 4>And so I think that Ladder, you know this, this

0:10:50.840 --> 0:10:54.520
<v Speaker 4>concept of dynamic capabilities is a much more complex area

0:10:54.600 --> 0:10:56.760
<v Speaker 4>to be investing in. And the only reason you would

0:10:56.760 --> 0:10:58.640
<v Speaker 4>do it is if you actually have a theory about

0:10:58.679 --> 0:11:01.959
<v Speaker 4>government that is more than what traditional economists think about government,

0:11:01.960 --> 0:11:04.079
<v Speaker 4>which is at best, well, at worst, get out of

0:11:04.080 --> 0:11:06.480
<v Speaker 4>the way, at best, fix the market failure. So as

0:11:06.520 --> 0:11:09.360
<v Speaker 4>soon as you say, actually, it's about shaping and co

0:11:09.480 --> 0:11:12.520
<v Speaker 4>creating a different type of economy and society that works

0:11:12.520 --> 0:11:14.800
<v Speaker 4>for people in planet, then the question is what does

0:11:14.840 --> 0:11:17.280
<v Speaker 4>that mean for the capabilities that you need. If you're

0:11:17.320 --> 0:11:19.320
<v Speaker 4>just fixing, then you just need a lot of bandages.

0:11:19.320 --> 0:11:21.120
<v Speaker 4>And that's in fact what we get. We get very

0:11:21.200 --> 0:11:23.800
<v Speaker 4>reactive kind of filling the gap kind of.

0:11:23.720 --> 0:11:27.360
<v Speaker 3>Policies, pendulum constantly swinging exactly exactly.

0:11:27.520 --> 0:11:30.080
<v Speaker 4>But I mean capacity, of course is essential. Without a

0:11:30.080 --> 0:11:32.440
<v Speaker 4>budget and fiscal space, you can do nothing. That third

0:11:32.440 --> 0:11:35.560
<v Speaker 4>category that I mentioned quickly administrative routines, that's you know,

0:11:35.640 --> 0:11:37.720
<v Speaker 4>are you also you know, do you have a stable

0:11:37.800 --> 0:11:40.920
<v Speaker 4>environment where you can learn by doing? Because if you're

0:11:40.920 --> 0:11:43.199
<v Speaker 4>constantly changing what you're doing, it's going to be hard

0:11:43.400 --> 0:11:45.520
<v Speaker 4>to have a learning by doing dynamics. So those kind

0:11:45.520 --> 0:11:48.120
<v Speaker 4>of administrative routines I even see this on my university,

0:11:48.360 --> 0:11:50.000
<v Speaker 4>where as soon as you get a lot of turnover,

0:11:50.440 --> 0:11:53.400
<v Speaker 4>even those kind of basic routines aren't there. But capability.

0:11:53.520 --> 0:11:58.160
<v Speaker 4>So these three areas, capacity, routines and capabilities are equally important,

0:11:58.160 --> 0:12:00.960
<v Speaker 4>but the capabilities are really what I find are lacking.

0:12:01.040 --> 0:12:03.320
<v Speaker 4>And it goes back, as I was mentioning before, to

0:12:03.400 --> 0:12:07.280
<v Speaker 4>the underlying economic dogma that has underpinned the way that

0:12:07.320 --> 0:12:11.280
<v Speaker 4>we think about policy government at different levels that by design,

0:12:11.360 --> 0:12:12.880
<v Speaker 4>not by coincidence, is reactive.

0:12:28.960 --> 0:12:33.320
<v Speaker 3>Have consultants become a substitute for state capacity slash routine

0:12:33.600 --> 0:12:35.199
<v Speaker 3>slash administrative ability?

0:12:35.679 --> 0:12:35.839
<v Speaker 4>Right?

0:12:35.880 --> 0:12:37.680
<v Speaker 3>I always wonder how we got to the point where

0:12:37.679 --> 0:12:40.320
<v Speaker 3>consultants are so big anyway, because it feels like every

0:12:40.320 --> 0:12:42.840
<v Speaker 3>time you hire a consultant, it's almost an admission of

0:12:43.200 --> 0:12:46.440
<v Speaker 3>failure on your part to be able to do something right.

0:12:46.520 --> 0:12:50.400
<v Speaker 3>And nevertheless, it's a widely accepted practice across governments.

0:12:50.760 --> 0:12:53.960
<v Speaker 4>So my last book actually was called The Big con

0:12:54.320 --> 0:12:58.040
<v Speaker 4>So Confort Consulting, and the subtitle was how We've weakened

0:12:58.520 --> 0:13:02.360
<v Speaker 4>businesses and fantalized governments and warped our economies basically due

0:13:02.400 --> 0:13:06.200
<v Speaker 4>to this consultification. I wouldn't blame the consultants. I mean

0:13:06.520 --> 0:13:09.480
<v Speaker 4>I actually blame governments, right, like, why are you opening

0:13:09.480 --> 0:13:12.680
<v Speaker 4>the door so wide to consultants? And it's fine to

0:13:12.720 --> 0:13:15.280
<v Speaker 4>have advisors and some consultants. The problem is when they

0:13:15.280 --> 0:13:18.440
<v Speaker 4>are actually doing the core tasks that government should do. Again,

0:13:18.520 --> 0:13:21.880
<v Speaker 4>test and trace during COVID was a core task. And

0:13:21.960 --> 0:13:25.920
<v Speaker 4>so I think it really stems from i'd say the

0:13:26.000 --> 0:13:29.720
<v Speaker 4>eighties when we you know, the kind of Reagan Thatcher years.

0:13:29.760 --> 0:13:32.120
<v Speaker 4>If you want, it always goes back to yeah, but

0:13:32.280 --> 0:13:35.959
<v Speaker 4>actually in the UK, for example, it even increased more

0:13:36.040 --> 0:13:38.800
<v Speaker 4>during the Labor government. So it's not it's not you know,

0:13:39.040 --> 0:13:41.120
<v Speaker 4>one party, but it did begin i'd say in the

0:13:41.160 --> 0:13:45.839
<v Speaker 4>eighties with this kind of downsizing of governments, which then

0:13:45.920 --> 0:13:48.840
<v Speaker 4>ironically cost them more. Because as soon as you start

0:13:48.880 --> 0:13:52.400
<v Speaker 4>downsizing without really strategically thinking what you need and what

0:13:52.440 --> 0:13:54.000
<v Speaker 4>you don't need, of course you should trim the fat.

0:13:54.040 --> 0:13:57.240
<v Speaker 4>There's no reason to have, you know, a bloated government structure.

0:13:57.280 --> 0:14:01.560
<v Speaker 4>But when it's done for ideological reasons and not strategic reasons,

0:14:01.640 --> 0:14:03.920
<v Speaker 4>then you know, ironically, then you end up not having

0:14:03.920 --> 0:14:05.760
<v Speaker 4>those capabilities that you need as soon as you have

0:14:05.800 --> 0:14:09.720
<v Speaker 4>a flood or you know, Brexit or COVID, And so

0:14:09.920 --> 0:14:12.960
<v Speaker 4>I think then what happens with the consultants is it's

0:14:13.000 --> 0:14:15.360
<v Speaker 4>not their fault that they're invited in. I do think

0:14:15.360 --> 0:14:17.760
<v Speaker 4>it's very problematic what they end up doing once they're in.

0:14:17.840 --> 0:14:21.080
<v Speaker 4>So there's huge conflicts of interest. Well, the biggest conflict

0:14:21.120 --> 0:14:23.600
<v Speaker 4>of interest being that they have no incentive really to

0:14:23.640 --> 0:14:26.440
<v Speaker 4>make government better later because they wouldn't have no contracts.

0:14:26.560 --> 0:14:29.280
<v Speaker 4>It'd be like having a therapist your whole life, that therapist,

0:14:29.360 --> 0:14:30.120
<v Speaker 4>which they're very.

0:14:30.040 --> 0:14:33.280
<v Speaker 2>Good, which is which is how the therapy models are.

0:14:33.560 --> 0:14:35.440
<v Speaker 3>Well, do you remember this came up in the episode

0:14:35.480 --> 0:14:38.800
<v Speaker 3>we did about construction in New York and this idea

0:14:38.840 --> 0:14:41.080
<v Speaker 3>that like one of the reasons it's so expensive and

0:14:41.120 --> 0:14:44.120
<v Speaker 3>takes so long for like public funded projects is because

0:14:44.120 --> 0:14:47.000
<v Speaker 3>consultants have no incentive to actually get the project done.

0:14:47.200 --> 0:14:49.720
<v Speaker 4>Yes, but also they're often working on both sides of

0:14:49.760 --> 0:14:52.240
<v Speaker 4>the street, right, so they'll be for example, consulting for

0:14:52.320 --> 0:14:54.600
<v Speaker 4>I don't know, a state own enterprise like ESCOM in

0:14:54.640 --> 0:14:57.200
<v Speaker 4>South Africa as well as the treasury. We should be

0:14:57.240 --> 0:15:00.800
<v Speaker 4>regulating ESCOM or in Australia. The it's a famous case

0:15:00.840 --> 0:15:04.160
<v Speaker 4>with PwC where they were consulting for a medical device

0:15:04.320 --> 0:15:07.160
<v Speaker 4>company as well as the regulators of the medical device

0:15:07.200 --> 0:15:09.560
<v Speaker 4>companies that come on. So that should just be illegal,

0:15:09.920 --> 0:15:12.320
<v Speaker 4>right and again you know, getting the right kind of

0:15:12.320 --> 0:15:14.360
<v Speaker 4>regulation that makes sure that we don't have these kind

0:15:14.360 --> 0:15:17.040
<v Speaker 4>of scams. So what we also argued was, you know,

0:15:17.080 --> 0:15:20.320
<v Speaker 4>the first thing is start investing back inside government so

0:15:20.400 --> 0:15:22.680
<v Speaker 4>you don't need so much consulting. But also when you

0:15:22.720 --> 0:15:25.280
<v Speaker 4>do bring in the consultants, make sure the contract's actually

0:15:25.280 --> 0:15:27.760
<v Speaker 4>in bed learning within them and that you are also

0:15:27.760 --> 0:15:29.720
<v Speaker 4>bringing in the right people. You know, if you have

0:15:29.760 --> 0:15:32.000
<v Speaker 4>an oncology strategy, of course you should get the top

0:15:32.000 --> 0:15:35.880
<v Speaker 4>doctors and consultants and cancer to advise. So the other

0:15:36.080 --> 0:15:38.400
<v Speaker 4>huge problem is that these consultants when they're coming in,

0:15:38.440 --> 0:15:40.800
<v Speaker 4>they often actually don't know very much and they end

0:15:40.920 --> 0:15:44.200
<v Speaker 4>up really bothering the poor public servants that end up

0:15:44.240 --> 0:15:46.800
<v Speaker 4>emailing oh would you mind telling me what you think

0:15:46.840 --> 0:15:49.160
<v Speaker 4>about or sending me your you know, plan that we

0:15:49.200 --> 0:15:51.320
<v Speaker 4>can study. It's like, why are you even working with

0:15:51.400 --> 0:15:54.240
<v Speaker 4>government if you don't have within the consulting companies that

0:15:54.360 --> 0:15:57.080
<v Speaker 4>deep expertise, which you know, I'm not saying this just

0:15:57.080 --> 0:15:59.280
<v Speaker 4>because I'm an academic, but I don't think academics are

0:15:59.320 --> 0:16:02.160
<v Speaker 4>used enough. You know, if you have a research center

0:16:02.200 --> 0:16:05.280
<v Speaker 4>that's been thinking about climate change for the last forty years,

0:16:05.760 --> 0:16:09.400
<v Speaker 4>use them. Don't ask McKenzie as Australia did to design

0:16:09.400 --> 0:16:11.960
<v Speaker 4>your climate strategy, which ended up, by the way, being terrible.

0:16:12.360 --> 0:16:14.640
<v Speaker 4>So there is a bit of why is it that

0:16:14.720 --> 0:16:18.160
<v Speaker 4>governments A don't invest in their own capacity capabilities, and

0:16:18.200 --> 0:16:20.320
<v Speaker 4>B when they do go out there and look for

0:16:20.360 --> 0:16:23.200
<v Speaker 4>the advisors and consultants are kind of getting the ones

0:16:23.240 --> 0:16:26.240
<v Speaker 4>that simply kind of provide a rubber stack right that

0:16:26.280 --> 0:16:28.200
<v Speaker 4>makes them feel more secure. They haven't even done the

0:16:28.200 --> 0:16:30.360
<v Speaker 4>homework to make sure they are getting the top people

0:16:30.760 --> 0:16:33.840
<v Speaker 4>in the world to help advise them on doing.

0:16:33.920 --> 0:16:36.360
<v Speaker 2>The process, just to take the other side of the client.

0:16:36.440 --> 0:16:39.400
<v Speaker 2>So recently in New York City it was I don't know,

0:16:39.520 --> 0:16:41.400
<v Speaker 2>I think scandal is too strong a word, but there

0:16:41.400 --> 0:16:43.840
<v Speaker 2>are a lot of headlines about how much the city

0:16:43.840 --> 0:16:47.720
<v Speaker 2>had paid consultants for working on redesigning the trash collection

0:16:48.200 --> 0:16:50.520
<v Speaker 2>system in the city. And on the one hand, it's

0:16:50.560 --> 0:16:53.400
<v Speaker 2>a trash collection core city function, why do you have

0:16:53.440 --> 0:16:57.040
<v Speaker 2>to bring in a consultant. On the other hand, reimagining

0:16:57.080 --> 0:16:59.760
<v Speaker 2>the trash collection system is like, that's a one time

0:17:00.240 --> 0:17:04.040
<v Speaker 2>so maintaining it, implementing it, servicing it, okay, that's like

0:17:04.080 --> 0:17:07.159
<v Speaker 2>a permanent government function. But the actual like, okay, we

0:17:07.240 --> 0:17:10.520
<v Speaker 2>have to do a redesign. That is that necessarily something

0:17:10.520 --> 0:17:13.280
<v Speaker 2>that like we need to have in house in government

0:17:13.480 --> 0:17:17.600
<v Speaker 2>that capacity, because do you want to permanently have that

0:17:17.840 --> 0:17:20.960
<v Speaker 2>muscle because that's a one shot thing, doesn't it? Like

0:17:21.080 --> 0:17:23.400
<v Speaker 2>to me, that makes sense? Is the time to bring in.

0:17:23.320 --> 0:17:25.760
<v Speaker 3>At argue for something like that. There's a value to

0:17:25.800 --> 0:17:28.120
<v Speaker 3>having an external viewpoint, right, that makes sense.

0:17:28.280 --> 0:17:31.600
<v Speaker 2>There's like the redesign that's a one time job. Like

0:17:31.760 --> 0:17:33.760
<v Speaker 2>to me, I was like, all right, that doesn't seem

0:17:33.800 --> 0:17:36.040
<v Speaker 2>crazy to bring in a third party to like help

0:17:36.080 --> 0:17:37.960
<v Speaker 2>figure out what that plan is exactly.

0:17:38.000 --> 0:17:40.760
<v Speaker 4>So that's the myth, right that somehow we're talking about

0:17:40.840 --> 0:17:44.520
<v Speaker 4>either government does everything, yeah, right, or even nationalize everything,

0:17:44.960 --> 0:17:47.320
<v Speaker 4>or it does nothing and it privatizes and brings them

0:17:47.320 --> 0:17:50.359
<v Speaker 4>the consultants. So the truth is obviously somewhere in the middle. So,

0:17:50.440 --> 0:17:52.920
<v Speaker 4>of course you're absolutely right. Government doesn't have to have

0:17:53.040 --> 0:17:55.840
<v Speaker 4>all those skills. It definitely needs the skills to know

0:17:56.080 --> 0:17:58.840
<v Speaker 4>who to work with outside of government, but it also

0:17:58.920 --> 0:18:02.960
<v Speaker 4>needs to even under stand that kind of outside landscape

0:18:02.960 --> 0:18:06.400
<v Speaker 4>to even think about what might we need, how might

0:18:06.480 --> 0:18:09.240
<v Speaker 4>we start developing a strategy that reimagines, say the trash

0:18:09.240 --> 0:18:12.840
<v Speaker 4>collection process. So that's why you talk about missions. So

0:18:13.200 --> 0:18:15.560
<v Speaker 4>when you know NASA wanted to go to the moon

0:18:15.600 --> 0:18:17.040
<v Speaker 4>and back at a short amount of time, they didn't

0:18:17.040 --> 0:18:18.639
<v Speaker 4>say we're going to do it all by ourselves. And

0:18:18.680 --> 0:18:20.159
<v Speaker 4>they also didn't say we're just going to do it

0:18:20.160 --> 0:18:22.200
<v Speaker 4>with the aerospace sector, right, They said, we're going to

0:18:22.280 --> 0:18:24.440
<v Speaker 4>have to work with so many different private sector people.

0:18:24.640 --> 0:18:26.600
<v Speaker 4>They ended up working with something like four hundred thousand

0:18:26.600 --> 0:18:29.000
<v Speaker 4>people in the private sector. They said, we have a

0:18:29.040 --> 0:18:31.320
<v Speaker 4>lot of problems, but we don't know the solutions, but

0:18:31.359 --> 0:18:35.600
<v Speaker 4>we're going to set very clearly a direction for working

0:18:35.600 --> 0:18:38.119
<v Speaker 4>with the private sector in a problem oriented way. So

0:18:38.160 --> 0:18:40.800
<v Speaker 4>the first thing they did was change procurement. Procurement, you know,

0:18:40.840 --> 0:18:43.800
<v Speaker 4>government purchasing is often like thirty percent of a government's budget.

0:18:43.920 --> 0:18:47.040
<v Speaker 4>It's a very important part of their budget, whether it's Barbados,

0:18:47.080 --> 0:18:50.360
<v Speaker 4>a small island state, or the US a very large government,

0:18:50.720 --> 0:18:53.440
<v Speaker 4>procurement is there. How were we using it? So they

0:18:53.480 --> 0:18:55.399
<v Speaker 4>realized they had the wrong type of procurement. It was

0:18:55.440 --> 0:18:58.720
<v Speaker 4>just again minimizing costs. It was cost plus procurement. They

0:18:58.800 --> 0:19:01.320
<v Speaker 4>changed it to outcomes into procurement and they started to

0:19:01.320 --> 0:19:03.639
<v Speaker 4>ask themselves, what are the outcomes that we need. We

0:19:03.720 --> 0:19:06.040
<v Speaker 4>need to figure out how are the astronauts going to

0:19:06.040 --> 0:19:07.840
<v Speaker 4>go to the bathroom? Right, which, by the way, was

0:19:07.880 --> 0:19:10.560
<v Speaker 4>just a problem again with Artemis the toilet, Oh is

0:19:10.560 --> 0:19:12.960
<v Speaker 4>a problem up in space? What are they going to eat?

0:19:13.119 --> 0:19:15.119
<v Speaker 4>What are they going to wear? How will we communicate

0:19:15.160 --> 0:19:18.119
<v Speaker 4>with them? And it was the solutions to those problems

0:19:18.600 --> 0:19:22.320
<v Speaker 4>that happened within mainly not only private sector institutions, with

0:19:22.600 --> 0:19:26.320
<v Speaker 4>NASA's also kind of leading investment, but especially leading kind

0:19:26.359 --> 0:19:29.240
<v Speaker 4>of thought process of what the problems were that ended

0:19:29.320 --> 0:19:32.760
<v Speaker 4>up getting US camera phones, foil blankets, home insulation software,

0:19:33.240 --> 0:19:38.880
<v Speaker 4>so many different innovations across many different sectors, aerospace, nutrition, materials, electronics.

0:19:39.400 --> 0:19:42.000
<v Speaker 4>That itself is what we're talking about, right, So, whether

0:19:42.000 --> 0:19:44.160
<v Speaker 4>it's going to the moon, whether it's trash collection, whether

0:19:44.200 --> 0:19:47.720
<v Speaker 4>it's school meals, whether it's getting prepared for the next pandemic,

0:19:47.760 --> 0:19:51.560
<v Speaker 4>which unfortunately the science tells us will happen. How were

0:19:51.560 --> 0:19:54.600
<v Speaker 4>we even thinking within government in a problem oriented way,

0:19:54.640 --> 0:19:57.040
<v Speaker 4>a solutions oriented way. And this, by the way, is

0:19:57.080 --> 0:19:59.960
<v Speaker 4>why the City Lab conference is so wonderful and bloom

0:20:00.000 --> 0:20:04.240
<v Speaker 4>Berg's Government Innovation Team is so important for so many cities,

0:20:04.400 --> 0:20:08.280
<v Speaker 4>is because they then share their experiences of solving problems

0:20:08.640 --> 0:20:10.480
<v Speaker 4>and then they ask and we're trying to help them

0:20:10.480 --> 0:20:13.080
<v Speaker 4>do this with this public sector Capability index. What did

0:20:13.080 --> 0:20:15.080
<v Speaker 4>we learn along the way that we were missing? Where

0:20:15.119 --> 0:20:17.840
<v Speaker 4>were the bottlenecks? What can we do better? But especially

0:20:17.840 --> 0:20:22.480
<v Speaker 4>in terms of that flexibility, adaptability, willingness to experiment. Right,

0:20:22.680 --> 0:20:25.000
<v Speaker 4>remember what Kennedy said, We're doing it because it's hard,

0:20:25.160 --> 0:20:28.080
<v Speaker 4>not because it's easy. Yet all the words and policy

0:20:28.119 --> 0:20:31.880
<v Speaker 4>papers are about making things easier. Facilitating. I'm Italian fatchia

0:20:32.200 --> 0:20:36.119
<v Speaker 4>or in Spain fascia. Right, So if you're facilitating someone,

0:20:36.400 --> 0:20:38.160
<v Speaker 4>it's not going to be a good contract. If you're

0:20:38.160 --> 0:20:40.240
<v Speaker 4>de risking someone, it's not going to be a good contract.

0:20:40.280 --> 0:20:43.359
<v Speaker 4>If you're simply enabling, facilitating fixing, it's going to be

0:20:43.400 --> 0:20:45.439
<v Speaker 4>a very bad public private relationship.

0:20:45.760 --> 0:20:47.639
<v Speaker 3>Just going back to consultants for a second, and I

0:20:47.640 --> 0:20:50.440
<v Speaker 3>think this is actually relevant to the discussion of having

0:20:50.480 --> 0:20:54.119
<v Speaker 3>cooperation among different parts of the government on big projects.

0:20:54.440 --> 0:20:56.880
<v Speaker 3>But how much of the consultants you fetish just has

0:20:56.920 --> 0:21:01.080
<v Speaker 3>to do with diffusing responsibilities. So I always think back

0:21:01.119 --> 0:21:04.880
<v Speaker 3>to the point the Olds saying about the purchasing manager thing,

0:21:04.920 --> 0:21:08.199
<v Speaker 3>you'll never get fired for buying IBM, right, Like, how

0:21:08.280 --> 0:21:09.919
<v Speaker 3>much of it is just like, well, you know, I

0:21:09.960 --> 0:21:12.159
<v Speaker 3>did my best, I hired McKenzie. What more can I

0:21:12.200 --> 0:21:13.160
<v Speaker 3>do if it goes wrong?

0:21:13.200 --> 0:21:15.120
<v Speaker 2>It's mckenney's accountability set.

0:21:15.200 --> 0:21:15.400
<v Speaker 1>Yeah.

0:21:15.400 --> 0:21:18.879
<v Speaker 4>Absolutely, So that's a really important point because you know,

0:21:18.960 --> 0:21:21.600
<v Speaker 4>one problem is when when government doesn't have those capabilities

0:21:21.640 --> 0:21:24.040
<v Speaker 4>for the reasons we said before. Another is, even when

0:21:24.040 --> 0:21:27.000
<v Speaker 4>they have it, why are they not using it. Australia

0:21:27.000 --> 0:21:30.000
<v Speaker 4>again is an interesting example because they had really interesting

0:21:30.040 --> 0:21:35.040
<v Speaker 4>capability within government with their Innovation Agency CSIRO, and yet

0:21:35.040 --> 0:21:37.679
<v Speaker 4>they gave this massive contract to McKinsey to do their

0:21:37.720 --> 0:21:41.879
<v Speaker 4>climate strategy. And it's absolutely about diffusing that responsibility. But

0:21:41.960 --> 0:21:44.320
<v Speaker 4>also because of the culture we have again within government,

0:21:44.359 --> 0:21:47.520
<v Speaker 4>where if they do make mistakes, unlike in the entrepreneurial

0:21:47.560 --> 0:21:50.359
<v Speaker 4>ecosystems and you know, VC and so on. We don't

0:21:50.359 --> 0:21:53.120
<v Speaker 4>accept that. But it's also in the private sector, right,

0:21:53.160 --> 0:21:55.480
<v Speaker 4>So we also talk in the book about the consultification

0:21:55.760 --> 0:21:58.560
<v Speaker 4>of management basically and there as well. You know, if

0:21:58.600 --> 0:22:01.080
<v Speaker 4>you're going to be doing amergere or downsize and we're

0:22:01.080 --> 0:22:03.359
<v Speaker 4>a massive share buyback scheme, isn't it great if you

0:22:03.440 --> 0:22:05.760
<v Speaker 4>have you know, McKenzie told us to do it. So

0:22:05.880 --> 0:22:08.159
<v Speaker 4>also just not taking on I mean it's kind of cowardly, right,

0:22:08.200 --> 0:22:10.800
<v Speaker 4>like you're not kind of owning your decisions. I do

0:22:10.840 --> 0:22:13.080
<v Speaker 4>think it's different in government. I think that you know,

0:22:13.240 --> 0:22:15.600
<v Speaker 4>changing that culture, having more gov labs like they have

0:22:15.680 --> 0:22:23.240
<v Speaker 4>in Chile. Everything sounds better than Spanish and Spanish I

0:22:23.320 --> 0:22:27.600
<v Speaker 4>always say that in Italian every time we have it's

0:22:27.640 --> 0:22:32.920
<v Speaker 4>public sector reform, it's just cuts, but it sounds nice.

0:22:33.880 --> 0:22:37.440
<v Speaker 4>It's literally just cuts. And so that idea that what

0:22:37.520 --> 0:22:40.800
<v Speaker 4>we need is kind of a laboratory within government but

0:22:40.800 --> 0:22:43.600
<v Speaker 4>also between governments, I think is really important. By the way,

0:22:43.680 --> 0:22:46.679
<v Speaker 4>the head of procurement in NASA, Ernest Brackett, in the

0:22:46.720 --> 0:22:49.640
<v Speaker 4>sixties with the Apollo program, not only did he help

0:22:49.760 --> 0:22:52.920
<v Speaker 4>change the procurement policy of NASA, but he also said,

0:22:53.200 --> 0:22:55.359
<v Speaker 4>we got to watch out. There's too many consultants in

0:22:55.359 --> 0:22:58.639
<v Speaker 4>these corridors. And his exact quote was, if this continues,

0:22:58.760 --> 0:23:01.919
<v Speaker 4>we will get captured by brochuremanship, which is kind of

0:23:02.000 --> 0:23:04.160
<v Speaker 4>endearing because they don't have powerpoints at the time, right,

0:23:04.200 --> 0:23:06.240
<v Speaker 4>So now the idea that you're ruling by a PowerPoint

0:23:06.240 --> 0:23:08.040
<v Speaker 4>and that's basically all they know how to do at

0:23:08.040 --> 0:23:12.000
<v Speaker 4>the time. It was kind of shiny bushures. But he

0:23:12.080 --> 0:23:14.320
<v Speaker 4>didn't say we don't want to work with the private sector, right,

0:23:14.359 --> 0:23:16.159
<v Speaker 4>He said, we won't know how to work with the

0:23:16.200 --> 0:23:18.240
<v Speaker 4>private sector. We won't know how to write the terms

0:23:18.240 --> 0:23:22.560
<v Speaker 4>of reference if our own brains are becoming weak. So

0:23:22.920 --> 0:23:26.720
<v Speaker 4>investing within in order to work also outside with others.

0:23:26.720 --> 0:23:29.720
<v Speaker 4>So it's not working with others, it's working smartly with them.

0:23:29.960 --> 0:23:31.840
<v Speaker 2>So this gets to the sort of one of the

0:23:32.000 --> 0:23:36.080
<v Speaker 2>big questions of the day obviously, and that is AI. Right,

0:23:36.119 --> 0:23:39.119
<v Speaker 2>And so you mentioned okay school lunches. You said a mission.

0:23:39.240 --> 0:23:41.480
<v Speaker 2>It doesn't mean like the private sector isn't going to

0:23:41.520 --> 0:23:44.320
<v Speaker 2>play a role in providing food or whatever. But first

0:23:44.359 --> 0:23:46.920
<v Speaker 2>you establish what the mission is, then you talk about

0:23:46.920 --> 0:23:48.960
<v Speaker 2>the moon. It doesn't mean that the private sector isn't

0:23:48.960 --> 0:23:51.639
<v Speaker 2>going to play a role. Private sector played a significant

0:23:51.680 --> 0:23:54.280
<v Speaker 2>role through various technologies of procurement, but there is an

0:23:54.320 --> 0:23:58.440
<v Speaker 2>overall mission. Well, how are you thinking about AI? Should

0:23:58.480 --> 0:24:02.840
<v Speaker 2>governments first decide like what is our mission for this?

0:24:03.000 --> 0:24:07.200
<v Speaker 2>What missions could it theoretically enable? Like does this feel

0:24:07.240 --> 0:24:09.760
<v Speaker 2>different than other endeavors? We obviously know a lot of

0:24:09.760 --> 0:24:13.320
<v Speaker 2>public sector money is going to wind its way up

0:24:13.359 --> 0:24:16.000
<v Speaker 2>in AI and already has a lot of it already has,

0:24:16.040 --> 0:24:18.080
<v Speaker 2>But how are you does this fit? Is this different?

0:24:18.119 --> 0:24:20.159
<v Speaker 2>Talk to us about how you think about this particular

0:24:20.680 --> 0:24:24.760
<v Speaker 2>moment of extreme sort of technological ambition.

0:24:24.760 --> 0:24:26.679
<v Speaker 4>Right, I mean, there's so much to say. So first,

0:24:26.840 --> 0:24:30.680
<v Speaker 4>the investments that went into what we call today artificial intelligence,

0:24:30.720 --> 0:24:35.520
<v Speaker 4>including you know LLM models, language models, speech recognition dates

0:24:35.600 --> 0:24:38.919
<v Speaker 4>you know, decades, and like so many other areas, that

0:24:39.000 --> 0:24:41.159
<v Speaker 4>was led by government. So if you look at even DARPA,

0:24:41.240 --> 0:24:44.680
<v Speaker 4>which as you know, was the lead investor in the Internet,

0:24:45.400 --> 0:24:49.720
<v Speaker 4>it came from problems mainly in the military industrial complex

0:24:49.720 --> 0:24:53.600
<v Speaker 4>that then required ultimately what we're calling artificial intelligence today.

0:24:53.640 --> 0:24:55.840
<v Speaker 4>But again in the entrepreneurial state. I talked about how

0:24:55.840 --> 0:24:58.440
<v Speaker 4>everything in our smartphones that make them smart, not stupid

0:24:58.440 --> 0:25:00.879
<v Speaker 4>Internet GPS, touch being series and so on, we're a

0:25:00.920 --> 0:25:04.760
<v Speaker 4>government finance. What's very scary today, what makes today different

0:25:04.800 --> 0:25:09.080
<v Speaker 4>with AI is that that's not really necessarily going to

0:25:09.240 --> 0:25:13.480
<v Speaker 4>be true much longer. Why because these massive economic rents

0:25:13.760 --> 0:25:16.800
<v Speaker 4>and I call them rents not profits, so excess profits

0:25:16.840 --> 0:25:19.520
<v Speaker 4>and excess of what these companies actually did, because we

0:25:19.600 --> 0:25:23.960
<v Speaker 4>privatized all the rewards from this massive social and collectively

0:25:24.000 --> 0:25:28.600
<v Speaker 4>created value in this area. They have so much money, right, trillions,

0:25:28.800 --> 0:25:32.560
<v Speaker 4>not billions, trillions, The salaries they are paying to the

0:25:32.600 --> 0:25:36.760
<v Speaker 4>top researchers in universities, both public and private universities, and

0:25:37.080 --> 0:25:40.600
<v Speaker 4>to people who used to work in the NASAs, the darpas,

0:25:40.640 --> 0:25:43.760
<v Speaker 4>the Kaffos in Chile, they are going now to work

0:25:43.760 --> 0:25:47.040
<v Speaker 4>in these companies, and that hemorrhaging of talent of top

0:25:47.080 --> 0:25:49.960
<v Speaker 4>research expertise. I don't think people are talking about this enough.

0:25:50.000 --> 0:25:53.679
<v Speaker 4>It literally is the biggest change, right because otherwise just

0:25:53.760 --> 0:25:55.560
<v Speaker 4>you know the fact that we've had, you know, big

0:25:55.600 --> 0:25:59.639
<v Speaker 4>technological changes, general purpose technology is completely affecting you know,

0:25:59.640 --> 0:26:02.399
<v Speaker 4>how we reduce, how we distribute, and you know, from

0:26:02.560 --> 0:26:04.520
<v Speaker 4>the rise of electrification so on.

0:26:04.560 --> 0:26:06.680
<v Speaker 2>The thing like at one point, I mean, I don't

0:26:06.680 --> 0:26:09.480
<v Speaker 2>think it actually panned out. They had great for them,

0:26:09.520 --> 0:26:14.120
<v Speaker 2>but didn't Uber hire the entire Carnegie Mellon robotics.

0:26:13.680 --> 0:26:16.080
<v Speaker 4>Team, and I think they did.

0:26:16.160 --> 0:26:19.600
<v Speaker 2>I think when when they were doing self driving car technology,

0:26:19.840 --> 0:26:22.439
<v Speaker 2>they just wrote a check for the entire faculty of

0:26:22.480 --> 0:26:24.880
<v Speaker 2>the CMU robotics team and it.

0:26:24.840 --> 0:26:26.679
<v Speaker 4>Was just but not enough people are talking about this,

0:26:26.720 --> 0:26:29.399
<v Speaker 4>so it's very hard to govern a process for good,

0:26:29.800 --> 0:26:32.600
<v Speaker 4>ethically and so on if you don't understand it. So

0:26:32.760 --> 0:26:37.080
<v Speaker 4>if this talent is in fact leaving these publicly financed institutions,

0:26:37.119 --> 0:26:40.399
<v Speaker 4>even private universities, most of the research, as you know,

0:26:40.520 --> 0:26:43.760
<v Speaker 4>has been funded by NSF and so on once they leave,

0:26:44.680 --> 0:26:49.160
<v Speaker 4>and the knowledge is so concentrated in these few AI companies,

0:26:49.200 --> 0:26:51.080
<v Speaker 4>I don't think we've thought about that enough. But sorry.

0:26:51.160 --> 0:26:53.240
<v Speaker 4>Just the other thing is just coming back to your question,

0:26:53.280 --> 0:26:55.720
<v Speaker 4>which I don't think I answered properly. Yes, of course

0:26:55.760 --> 0:26:58.760
<v Speaker 4>government should be thinking because of its at least a

0:26:58.800 --> 0:27:02.040
<v Speaker 4>democratically elected govern This is different for dictatorships what we

0:27:02.040 --> 0:27:05.240
<v Speaker 4>would expect from them, but we would expect governments to

0:27:05.280 --> 0:27:08.959
<v Speaker 4>make sure that any big change, large kind of opportunities

0:27:08.960 --> 0:27:11.320
<v Speaker 4>around technological change are done in ways that are again

0:27:11.359 --> 0:27:14.480
<v Speaker 4>good for people in planet right, But that requires not

0:27:14.520 --> 0:27:17.520
<v Speaker 4>only that capacity that, as I mentioned, is being decimated,

0:27:17.840 --> 0:27:21.680
<v Speaker 4>but also a certain type of regulation which is making

0:27:21.720 --> 0:27:25.920
<v Speaker 4>sure we even understand the process of, for example, how

0:27:25.960 --> 0:27:28.639
<v Speaker 4>algorithms are currently being designed, and whether we have a

0:27:28.640 --> 0:27:32.160
<v Speaker 4>situation like Shshana Zoobuff in her great book Surveillance Capitalism,

0:27:32.200 --> 0:27:34.240
<v Speaker 4>she says, you think you're searching Google for free, they're

0:27:34.240 --> 0:27:37.280
<v Speaker 4>searching you for free. That could have been avoided right

0:27:37.359 --> 0:27:39.920
<v Speaker 4>through the design of the algorithms. And given that the algorithms,

0:27:39.960 --> 0:27:43.439
<v Speaker 4>initially at least were publicly financed, there is this issue

0:27:43.440 --> 0:27:46.480
<v Speaker 4>of how do we in a predistributive way instead of

0:27:46.560 --> 0:27:50.320
<v Speaker 4>kind of exposts with redistribution or regulation or market fixing.

0:27:50.720 --> 0:27:54.200
<v Speaker 4>Think about innovation collaborations that have some of these really

0:27:54.200 --> 0:27:58.399
<v Speaker 4>important ethical concerns thought about upfront. And an example of

0:27:58.440 --> 0:28:01.520
<v Speaker 4>this would be during COVID, where you know, the vaccines

0:28:01.520 --> 0:28:04.399
<v Speaker 4>were not the mission. The mission was to allow these

0:28:04.480 --> 0:28:07.720
<v Speaker 4>vaccines to be produced and available globally. Given it was

0:28:07.760 --> 0:28:10.200
<v Speaker 4>a global health pandemic, we were all better off if

0:28:10.200 --> 0:28:13.840
<v Speaker 4>the world was vaccinated. And yet only one of the vaccines,

0:28:13.920 --> 0:28:18.320
<v Speaker 4>the one that was the collaboration between Oxford University and Astrosenica,

0:28:18.560 --> 0:28:22.000
<v Speaker 4>had that kind of conditionality about what good looks like

0:28:22.200 --> 0:28:24.560
<v Speaker 4>at the start in terms of how they collaborated. So

0:28:24.640 --> 0:28:27.600
<v Speaker 4>it was the publicly financed researchers. Oxford is a state

0:28:27.600 --> 0:28:31.000
<v Speaker 4>school that put that as a condition with their relationship

0:28:31.080 --> 0:28:33.679
<v Speaker 4>with astra Zenica, that they would share the knowledge, that

0:28:33.920 --> 0:28:36.160
<v Speaker 4>they would join the patent pool keep costing price as well.

0:28:36.400 --> 0:28:37.280
<v Speaker 4>So more of that.

0:28:37.960 --> 0:28:40.600
<v Speaker 2>Every time I hear you know, Tracy like someone talk

0:28:40.640 --> 0:28:44.000
<v Speaker 2>about studying AI and college and like their professors, I'm like,

0:28:44.040 --> 0:28:45.960
<v Speaker 2>that's great, but why are those professors not in the

0:28:46.000 --> 0:28:48.160
<v Speaker 2>private sector making one hundred times? I mean, many of

0:28:48.200 --> 0:28:51.239
<v Speaker 2>them are, but I'm always like amazed that given how

0:28:51.280 --> 0:28:53.440
<v Speaker 2>much money you go money on the table, Yeah, what

0:28:53.480 --> 0:28:55.720
<v Speaker 2>are you doing at a university you'd brib making ten times?

0:28:55.920 --> 0:28:58.280
<v Speaker 4>Where did that money come from? As the issue? Right,

0:28:58.360 --> 0:29:01.520
<v Speaker 4>So this money that's being used to pay these very

0:29:01.560 --> 0:29:04.520
<v Speaker 4>large salaries that you're talking about, it's very important to

0:29:04.600 --> 0:29:07.239
<v Speaker 4>recognize that that didn't come about because of you know,

0:29:07.560 --> 0:29:10.840
<v Speaker 4>early on this amazing kind of entrepreneurship and all the

0:29:10.880 --> 0:29:13.640
<v Speaker 4>knowledge was in these companies. They gathered that knowledge. Now

0:29:13.640 --> 0:29:15.480
<v Speaker 4>they're using it. Of course they're pushing the frontier. Of

0:29:15.520 --> 0:29:18.240
<v Speaker 4>course they're doing research, but that idea of also making

0:29:18.240 --> 0:29:22.000
<v Speaker 4>sure that companies are not earning in excess, right, So

0:29:22.320 --> 0:29:25.600
<v Speaker 4>why did the public person not benefit in those early days?

0:29:25.600 --> 0:29:28.760
<v Speaker 4>Why are they evading so much tax? I mean literally

0:29:28.840 --> 0:29:32.080
<v Speaker 4>in so many countries paying almost no tax. You know,

0:29:32.200 --> 0:29:35.239
<v Speaker 4>also labor exploitation in the case of Amazon. You know,

0:29:35.440 --> 0:29:36.960
<v Speaker 4>you don't hear it from me. You hear it from

0:29:37.000 --> 0:29:40.000
<v Speaker 4>all sorts of different investigations, even during COVID by the

0:29:40.000 --> 0:29:42.360
<v Speaker 4>way that they wouldn't even put the ambulances apparently outside

0:29:42.400 --> 0:29:43.880
<v Speaker 4>the warehouse. I don't I've read that. I'm not sure

0:29:43.880 --> 0:29:46.200
<v Speaker 4>if it's true, But anyway, the point is that they're

0:29:46.240 --> 0:29:48.360
<v Speaker 4>you know, what does a good company look like? And

0:29:48.400 --> 0:29:51.360
<v Speaker 4>how does that then affect the returns that they're earning?

0:29:51.400 --> 0:29:54.880
<v Speaker 4>And what is a just return versus these excess returns

0:29:54.880 --> 0:29:58.160
<v Speaker 4>that now are being used to you know, hire in You.

0:29:58.120 --> 0:30:02.120
<v Speaker 3>Know, you mentioned the black box of the algorithms, which

0:30:02.120 --> 0:30:04.719
<v Speaker 3>I think is a really interesting point. And we did

0:30:04.760 --> 0:30:08.720
<v Speaker 3>an episode with the CTO of Goldman Sachs recently and

0:30:08.760 --> 0:30:11.760
<v Speaker 3>we asked him, like, Goldman Sachs is a highly regulated bank.

0:30:11.840 --> 0:30:14.600
<v Speaker 3>When you have bank supervisors who go in and want

0:30:14.600 --> 0:30:18.760
<v Speaker 3>to understand your AI system, what are they actually understanding

0:30:19.160 --> 0:30:22.000
<v Speaker 3>Do they like understand the underlying code that's driving the

0:30:22.000 --> 0:30:24.760
<v Speaker 3>algorithm And the answer was, well, no, not really. You

0:30:24.800 --> 0:30:27.480
<v Speaker 3>can't expect them to understand all that stuff. It's more

0:30:27.520 --> 0:30:31.040
<v Speaker 3>about having the right controls in place that prevent the

0:30:31.120 --> 0:30:34.000
<v Speaker 3>altgoth from running amok. And so my question is with AI,

0:30:34.880 --> 0:30:38.560
<v Speaker 3>where we have a lot of experts, highly paid experts

0:30:38.560 --> 0:30:41.719
<v Speaker 3>and engineers in the private sector developing all this new stuff,

0:30:41.840 --> 0:30:45.600
<v Speaker 3>versus a shrinking body of government officials, like, what should

0:30:45.600 --> 0:30:49.080
<v Speaker 3>our expectation be about how much they understand this technology?

0:30:49.200 --> 0:30:52.000
<v Speaker 4>Right? Well, it actually comes back also to that previous point.

0:30:52.040 --> 0:30:55.080
<v Speaker 4>Do you need all that expertise inside or also how

0:30:55.080 --> 0:30:57.240
<v Speaker 4>do you regulate this in such a way that also

0:30:57.280 --> 0:30:59.560
<v Speaker 4>stimulates more innovation, because you don't want to put a

0:30:59.560 --> 0:31:02.200
<v Speaker 4>cap on the innovation just by overregulating it. This is where,

0:31:02.240 --> 0:31:05.040
<v Speaker 4>by the way, I disagree with the abundance theorem, which

0:31:05.080 --> 0:31:07.200
<v Speaker 4>makes it sound like, you know, there's all these opportunities

0:31:07.200 --> 0:31:09.080
<v Speaker 4>out there, and it was regulation and too much planning

0:31:09.080 --> 0:31:11.680
<v Speaker 4>and too many conditions that kind of hurt that, which

0:31:11.720 --> 0:31:15.880
<v Speaker 4>I think actually corporate governance and shareholder value maximization as

0:31:15.920 --> 0:31:19.440
<v Speaker 4>really actually stifled the opportunities that we have today, so

0:31:19.800 --> 0:31:22.280
<v Speaker 4>they don't have to of course understand the algorithms, but

0:31:22.360 --> 0:31:24.200
<v Speaker 4>they do need to do exactly as you said, like

0:31:24.240 --> 0:31:27.280
<v Speaker 4>we do with climate right where there's climate disclosures, we

0:31:27.360 --> 0:31:30.640
<v Speaker 4>need to know what it is that we want to

0:31:30.680 --> 0:31:33.040
<v Speaker 4>be disclosed. In fact, we have a project that we

0:31:33.160 --> 0:31:35.640
<v Speaker 4>just did that we just finished with, do you know

0:31:35.680 --> 0:31:39.840
<v Speaker 4>Tim Moriley. Yeah, So it was Tim and myself with

0:31:40.160 --> 0:31:43.000
<v Speaker 4>a grant from the Amitior Foundation, a project we called

0:31:43.040 --> 0:31:46.880
<v Speaker 4>Algorithmic Rents and how to reduce these rents and how

0:31:46.920 --> 0:31:50.640
<v Speaker 4>we're designing algorithms also through disclosures. So we thought about

0:31:50.680 --> 0:31:54.520
<v Speaker 4>what would be the equivalent of AI related disclosures that

0:31:54.560 --> 0:31:56.920
<v Speaker 4>could do exactly as you said, be almost the equivalent

0:31:56.960 --> 0:31:58.840
<v Speaker 4>of what banks now have to do, but also companies

0:31:58.880 --> 0:32:02.160
<v Speaker 4>have to do around g kind of metrics. And so

0:32:02.360 --> 0:32:05.560
<v Speaker 4>I mean the project is still you know, underway, and

0:32:05.640 --> 0:32:08.440
<v Speaker 4>what we want is actually to find kind of a

0:32:08.440 --> 0:32:11.120
<v Speaker 4>coalition of AI companies that would be willing to think

0:32:11.160 --> 0:32:14.880
<v Speaker 4>about this with us. But that assumes, right that there's

0:32:14.920 --> 0:32:17.840
<v Speaker 4>also enough of the science as there has been with

0:32:17.960 --> 0:32:21.080
<v Speaker 4>climate change, which said this is an urgent problem and

0:32:21.160 --> 0:32:23.040
<v Speaker 4>unless we fix it now, we're going to reach a

0:32:23.080 --> 0:32:25.480
<v Speaker 4>tipping point where there's no coming back. That's really when

0:32:25.520 --> 0:32:28.640
<v Speaker 4>things started to change around the climate disclosures. We haven't

0:32:28.800 --> 0:32:31.840
<v Speaker 4>for some reason, reached that yet, even though there's such

0:32:31.840 --> 0:32:33.920
<v Speaker 4>a link also by the way, by the way, between

0:32:33.960 --> 0:32:36.240
<v Speaker 4>AI and climate, like in terms of these data centers

0:32:36.280 --> 0:32:39.360
<v Speaker 4>guzzling you know, like for every you know, chat, GPT

0:32:39.520 --> 0:32:42.880
<v Speaker 4>search you do, apparently it's it's like using a bottle

0:32:42.920 --> 0:32:45.320
<v Speaker 4>of water, like the small plastic bottles of water, Like

0:32:45.360 --> 0:32:48.640
<v Speaker 4>that's literally how much we're using. And yet you know,

0:32:48.960 --> 0:32:52.000
<v Speaker 4>we're not making that kind of systemic understanding of you know,

0:32:52.120 --> 0:32:55.239
<v Speaker 4>AI problems and how they are connected to climate and

0:32:55.280 --> 0:32:58.200
<v Speaker 4>water problems and so on. And that requires again government

0:32:58.240 --> 0:33:00.560
<v Speaker 4>not just having an indicator like GDP to think about,

0:33:00.560 --> 0:33:02.800
<v Speaker 4>but a dashboard. Right when you're driving your car, if

0:33:02.800 --> 0:33:04.880
<v Speaker 4>you had one number, you know, how much gas you

0:33:04.920 --> 0:33:06.560
<v Speaker 4>have or how fast you're going, you would crash it.

0:33:06.840 --> 0:33:10.360
<v Speaker 4>So what does a dashboard look like? You know? For government,

0:33:10.400 --> 0:33:12.280
<v Speaker 4>that would allow it to make sure it's on track

0:33:12.320 --> 0:33:14.720
<v Speaker 4>to making sure that also with the evolution of technology,

0:33:15.080 --> 0:33:18.160
<v Speaker 4>it's thinking about these kind of more systemic features and

0:33:18.200 --> 0:33:34.360
<v Speaker 4>not just thinking about it as innovation policy.

0:33:36.440 --> 0:33:39.480
<v Speaker 2>Just from a pure sort of history of technology standpoint,

0:33:39.640 --> 0:33:40.760
<v Speaker 2>does AI feel different?

0:33:41.200 --> 0:33:44.120
<v Speaker 4>I think it definitely fits with the kind of characteristics

0:33:44.160 --> 0:33:46.280
<v Speaker 4>of a general purpose technology in the sense that it

0:33:46.320 --> 0:33:49.680
<v Speaker 4>really does kind of change everything. However, there's also a

0:33:49.720 --> 0:33:52.200
<v Speaker 4>lot of kind of myths around that kind of a

0:33:52.240 --> 0:33:54.520
<v Speaker 4>bubble in terms of how we're thinking, not only in

0:33:54.600 --> 0:33:57.479
<v Speaker 4>terms of the financial market bubble around it. But you know,

0:33:57.560 --> 0:34:00.160
<v Speaker 4>just like with electricity, it took about thirty years to

0:34:00.200 --> 0:34:04.280
<v Speaker 4>actually really affect how governments were operating. Similarly with the Internet,

0:34:04.320 --> 0:34:07.080
<v Speaker 4>you'll remember when Robert Solo was saying, you know, there's

0:34:07.120 --> 0:34:10.279
<v Speaker 4>computers everywhere except in the productivity statistics. I think we're

0:34:10.360 --> 0:34:13.960
<v Speaker 4>still very early in the phase with AI in terms

0:34:13.960 --> 0:34:18.919
<v Speaker 4>of it having a really meaningful impact on improving Again,

0:34:18.920 --> 0:34:21.200
<v Speaker 4>coming back to the point about problems, right, because ultimately

0:34:21.200 --> 0:34:24.799
<v Speaker 4>should be helping us solve problems? Which problems is AI

0:34:24.960 --> 0:34:27.759
<v Speaker 4>really helping us to solve in a systemic way that

0:34:27.800 --> 0:34:31.760
<v Speaker 4>can scale that there's learning between governments. We're definitely using AI.

0:34:32.600 --> 0:34:35.200
<v Speaker 4>Is it actually helping us solve some of the biggest

0:34:35.200 --> 0:34:39.360
<v Speaker 4>problems of our time again? Health problems, climate problems? Surely

0:34:39.560 --> 0:34:42.600
<v Speaker 4>there's some of that, But until we manage this process,

0:34:42.640 --> 0:34:45.000
<v Speaker 4>until we govern it both ethically but also in a

0:34:45.040 --> 0:34:47.880
<v Speaker 4>way that is with government instead of kind of you know,

0:34:47.960 --> 0:34:50.839
<v Speaker 4>sidetracking government in order to extract these mega rents. Then

0:34:50.920 --> 0:34:52.080
<v Speaker 4>we're going to have a huge problem.

0:34:52.520 --> 0:34:55.560
<v Speaker 3>Why do you think that hasn't happened yet or governments

0:34:55.560 --> 0:34:57.800
<v Speaker 3>haven't stepped in faster, because I do think AI is

0:34:57.920 --> 0:35:00.360
<v Speaker 3>kind of unusual in the sense that, you know, you

0:35:00.400 --> 0:35:04.000
<v Speaker 3>have people like Sam Altman who will say very publicly

0:35:04.000 --> 0:35:07.160
<v Speaker 3>in interviews like, yeah, this creates a lot of negative externalities,

0:35:07.160 --> 0:35:09.480
<v Speaker 3>and society is going to have to figure out how

0:35:09.480 --> 0:35:11.799
<v Speaker 3>to deal with this, and governments are going to have

0:35:11.840 --> 0:35:14.799
<v Speaker 3>to figure out how to actually best deploy this technology.

0:35:14.920 --> 0:35:20.160
<v Speaker 3>Open AI publish a big industrial policy document, which again

0:35:20.239 --> 0:35:23.759
<v Speaker 3>I think is kind of unusual to previous technological developments.

0:35:23.800 --> 0:35:28.080
<v Speaker 3>And yet governments seem kind of slow. I don't want

0:35:28.080 --> 0:35:30.680
<v Speaker 3>to generalize too much, but many governments seem kind of

0:35:30.719 --> 0:35:33.359
<v Speaker 3>slow to get in and really start shaping what they

0:35:33.360 --> 0:35:34.160
<v Speaker 3>want to do with AI.

0:35:34.360 --> 0:35:36.279
<v Speaker 4>Yeah. I mean, I think again, it seems like I'm

0:35:36.280 --> 0:35:38.520
<v Speaker 4>saying the same thing, but I really it's it's because

0:35:38.560 --> 0:35:41.560
<v Speaker 4>I believe in it. This technology on its own will

0:35:41.560 --> 0:35:45.000
<v Speaker 4>not solve anything if it's accompanied by a strong For example,

0:35:45.040 --> 0:35:49.080
<v Speaker 4>health system that with AI thinking about health problems, then

0:35:49.120 --> 0:35:52.640
<v Speaker 4>I can see that being absolutely revolutionary. And in fact,

0:35:52.760 --> 0:35:56.440
<v Speaker 4>I once heard a really interesting discussion between Nandan Nilekani,

0:35:56.719 --> 0:36:00.759
<v Speaker 4>you know, it's an incredible entrepreneur of computer systems. He

0:36:00.800 --> 0:36:03.759
<v Speaker 4>was one of the co founders of Inphasis in India,

0:36:03.920 --> 0:36:07.120
<v Speaker 4>and Eric Schmidt at one of these dialogues we have

0:36:07.200 --> 0:36:09.680
<v Speaker 4>in Bilajo, this beautiful villa in Lake Como run by

0:36:09.680 --> 0:36:13.000
<v Speaker 4>the Brockefeller Foundation, and we had kind of Eric Schmidt

0:36:13.000 --> 0:36:14.680
<v Speaker 4>on the one hand saying, you know, in the future,

0:36:14.680 --> 0:36:16.120
<v Speaker 4>all we're going to really need is an app, a

0:36:16.200 --> 0:36:18.840
<v Speaker 4>health app, and that's going to be fine. And Nandan Nilkani,

0:36:18.880 --> 0:36:21.880
<v Speaker 4>who really is one of the biggest innovators around computing,

0:36:22.000 --> 0:36:24.920
<v Speaker 4>was like, what, like, let me tell you in India,

0:36:24.960 --> 0:36:27.440
<v Speaker 4>without a proper health system, no matter how many apps

0:36:27.480 --> 0:36:30.360
<v Speaker 4>you have, we will continue to have misery. And so

0:36:30.480 --> 0:36:32.279
<v Speaker 4>it's not one or the other. But what you need

0:36:32.360 --> 0:36:34.520
<v Speaker 4>is more people like Nandan who think about what is

0:36:34.560 --> 0:36:38.960
<v Speaker 4>the relationship between you know, the power of AI and

0:36:39.239 --> 0:36:42.560
<v Speaker 4>the structure of a health system and who's thinking about

0:36:42.560 --> 0:36:44.600
<v Speaker 4>that and if we do have at the same time,

0:36:44.760 --> 0:36:48.320
<v Speaker 4>not just austerity, but this you know kind of dumbing

0:36:48.360 --> 0:36:50.960
<v Speaker 4>down of what we think government is for. So even

0:36:51.000 --> 0:36:53.120
<v Speaker 4>the health systems we have are not kind of you know,

0:36:53.120 --> 0:36:55.520
<v Speaker 4>fit for purpose. Then I don't see any sort of

0:36:55.520 --> 0:36:58.760
<v Speaker 4>future of AI kind of helping us with health problems.

0:36:58.880 --> 0:37:00.640
<v Speaker 4>And by the way, just look at I mean, like

0:37:00.680 --> 0:37:03.200
<v Speaker 4>fifty five percent of the global food system right now

0:37:03.239 --> 0:37:05.200
<v Speaker 4>is at risk because of how we're treating the global

0:37:05.280 --> 0:37:09.000
<v Speaker 4>hydrological cycle. You know, biodiversity loss also in the Amazon

0:37:09.080 --> 0:37:12.200
<v Speaker 4>is affecting droughts and floods in other parts of the world.

0:37:12.200 --> 0:37:15.760
<v Speaker 4>That's a huge problem. To what degree are we really

0:37:15.840 --> 0:37:19.520
<v Speaker 4>using AI to you know, fix that problem. Not much.

0:37:19.719 --> 0:37:22.680
<v Speaker 4>So it's also about where we're putting kind of the emphasis,

0:37:22.719 --> 0:37:24.759
<v Speaker 4>and for that, I think we do need these moonshots

0:37:24.960 --> 0:37:28.359
<v Speaker 4>government led working with the private sector and again using

0:37:28.400 --> 0:37:32.280
<v Speaker 4>the power of AI well regulated to solve very concrete problems.

0:37:32.440 --> 0:37:35.800
<v Speaker 3>Yeah, Joe, I was thinking about this specifically related to

0:37:35.880 --> 0:37:39.040
<v Speaker 3>healthcare recently, because I've seen a bunch of startups that

0:37:39.080 --> 0:37:41.960
<v Speaker 3>are saying they're going to simplify the billing process for hospitals.

0:37:42.120 --> 0:37:43.760
<v Speaker 3>And then you also know that there are a bunch

0:37:43.800 --> 0:37:48.200
<v Speaker 3>of insurance companies that are also using AI, and it's like, well,

0:37:48.719 --> 0:37:49.680
<v Speaker 3>if We're just going to have.

0:37:49.960 --> 0:37:51.640
<v Speaker 2>More suters debating with computers.

0:37:51.680 --> 0:37:54.360
<v Speaker 3>Yeah, exactly, And like if the system itself doesn't change,

0:37:54.360 --> 0:37:55.640
<v Speaker 3>nothing's going to improve, right.

0:37:56.239 --> 0:37:58.680
<v Speaker 2>No, I've totally thought about the same thing where it

0:37:58.840 --> 0:38:00.960
<v Speaker 2>just like feels like we're going to have this arms

0:38:01.040 --> 0:38:03.720
<v Speaker 2>race where it's like my bot will argue with your bot,

0:38:03.760 --> 0:38:07.080
<v Speaker 2>and then the only entities that make any money are

0:38:07.520 --> 0:38:10.160
<v Speaker 2>the volt makers, the voughtmakers.

0:38:10.840 --> 0:38:14.760
<v Speaker 4>You know that who was the mayor of Barcelona, another

0:38:14.760 --> 0:38:17.120
<v Speaker 4>city here in Spain that you know, well, she when

0:38:17.120 --> 0:38:19.719
<v Speaker 4>she was mayor, she came from a housing movement, so

0:38:19.800 --> 0:38:23.000
<v Speaker 4>she was really really concerned with housing issues, but also

0:38:23.040 --> 0:38:25.400
<v Speaker 4>you know, public transport, public schools, and so on. And

0:38:25.440 --> 0:38:28.480
<v Speaker 4>her thing was, why is it that when the citizens

0:38:28.520 --> 0:38:32.120
<v Speaker 4>of Barcelona, you know, like click on Uber or city Mapper,

0:38:32.440 --> 0:38:35.000
<v Speaker 4>this data that's created from that, Right, every time we

0:38:35.040 --> 0:38:37.680
<v Speaker 4>click on something, data's created. She said, why aren't we

0:38:37.719 --> 0:38:41.080
<v Speaker 4>in the city using that data to improve our decisions

0:38:41.080 --> 0:38:44.440
<v Speaker 4>and understanding of our public transport and public housing challenges?

0:38:44.800 --> 0:38:47.759
<v Speaker 4>And so she ended up hiring computer hackers into the

0:38:47.760 --> 0:38:50.640
<v Speaker 4>city government. It made it a really cool place to work.

0:38:51.120 --> 0:38:53.680
<v Speaker 4>And I think that again kind of insourcing back in

0:38:53.760 --> 0:38:56.719
<v Speaker 4>those kind of you know, cool hackers that currently are

0:38:56.760 --> 0:38:58.799
<v Speaker 4>working in these companies, but to come and work with

0:38:58.840 --> 0:39:01.640
<v Speaker 4>the city administration that says, we want you to come

0:39:01.640 --> 0:39:05.000
<v Speaker 4>in fail but help you know, like don't worry about failings.

0:39:05.040 --> 0:39:06.520
<v Speaker 4>Are you not fail, but you know, take risks to

0:39:06.560 --> 0:39:10.520
<v Speaker 4>help us though, kind of really target our big challenges

0:39:10.560 --> 0:39:14.800
<v Speaker 4>around housing, transport and so on, inequality in terms of access.

0:39:15.040 --> 0:39:17.640
<v Speaker 2>So obviously we're talking about the public sector. We're talking

0:39:17.680 --> 0:39:22.840
<v Speaker 2>about the government's role in facilitating or guiding various technologies.

0:39:23.040 --> 0:39:27.360
<v Speaker 2>But there's also just like politics, right, winning elections and

0:39:27.440 --> 0:39:30.440
<v Speaker 2>the fact that you know, as you mentioned, failures become

0:39:30.480 --> 0:39:32.759
<v Speaker 2>a scandal and they're on the paper, and maybe like

0:39:32.840 --> 0:39:36.400
<v Speaker 2>politicians lose their jobs, then someone comes in when you

0:39:36.520 --> 0:39:38.640
<v Speaker 2>just in your own personal work, when you like think

0:39:38.640 --> 0:39:41.520
<v Speaker 2>about this stuff, like how much do you have to

0:39:41.600 --> 0:39:46.360
<v Speaker 2>calculate the reality that one big job of politicians is

0:39:46.400 --> 0:39:50.480
<v Speaker 2>to win reelection and that a loss of election has

0:39:50.560 --> 0:39:53.440
<v Speaker 2>the potential to just take the government in ninety or

0:39:53.440 --> 0:39:55.680
<v Speaker 2>one hundred and eighty degree turn from whatever the previous

0:39:55.719 --> 0:39:58.520
<v Speaker 2>administration at any level in any country does, And how

0:39:58.600 --> 0:40:01.399
<v Speaker 2>much do you like think about that reality when you're

0:40:01.440 --> 0:40:03.880
<v Speaker 2>thinking about strengthening government.

0:40:04.120 --> 0:40:06.480
<v Speaker 4>So The first time it started to work on missions

0:40:06.560 --> 0:40:09.120
<v Speaker 4>wasn't on mission oriented policy, it was on mission oriented

0:40:09.200 --> 0:40:13.160
<v Speaker 4>organizations right to better understand the DARPA kind of organization. Right,

0:40:13.680 --> 0:40:18.359
<v Speaker 4>CORTFO in Chile is similar, CITRA in Finland, mind Lab

0:40:18.360 --> 0:40:22.160
<v Speaker 4>in Denmark, Lenova and Sweden. These are innovation agencies that

0:40:22.280 --> 0:40:25.200
<v Speaker 4>are in fact making these big bets that are mission oriented.

0:40:25.400 --> 0:40:27.360
<v Speaker 4>But my question was how are they organized? You know,

0:40:27.440 --> 0:40:30.319
<v Speaker 4>are they also unstable due to the electoral cycle? And

0:40:30.360 --> 0:40:32.279
<v Speaker 4>they had thought about this. I mean, it's not a

0:40:32.320 --> 0:40:35.080
<v Speaker 4>coincidence that DARPA, for example, people come in for five years,

0:40:35.080 --> 0:40:37.440
<v Speaker 4>so it's not the four year electoral cycle. They're actually

0:40:37.440 --> 0:40:40.160
<v Speaker 4>told come in and do take risks. That's how you'll

0:40:40.200 --> 0:40:43.400
<v Speaker 4>be evaluated, you know, not by just if you're succeeding

0:40:43.400 --> 0:40:45.200
<v Speaker 4>all the time that means you're not taking those risks,

0:40:45.480 --> 0:40:49.200
<v Speaker 4>but also the impact that your successes have, and so

0:40:49.239 --> 0:40:51.680
<v Speaker 4>that kind of cultural shift, but also the fact that

0:40:52.000 --> 0:40:54.120
<v Speaker 4>people are coming in kind of on se conment. You know,

0:40:54.160 --> 0:40:56.640
<v Speaker 4>they're not there to be a civil service civil servant

0:40:56.680 --> 0:41:01.920
<v Speaker 4>their whole life. So we started studying Well, for some areas,

0:41:01.920 --> 0:41:04.359
<v Speaker 4>I think that's fine, especially around innovation. Right, you want

0:41:04.400 --> 0:41:06.440
<v Speaker 4>to coming back to the idea that we want to

0:41:06.480 --> 0:41:09.560
<v Speaker 4>bring in and crowd in the top talent into government,

0:41:09.600 --> 0:41:11.279
<v Speaker 4>you know, having like a five year period that you're

0:41:11.320 --> 0:41:13.920
<v Speaker 4>going to help as a civil servant paid by the government,

0:41:14.120 --> 0:41:16.400
<v Speaker 4>not as a consultant, you know, working with not at

0:41:16.680 --> 0:41:18.879
<v Speaker 4>the civil service. I do think there's lots of kind

0:41:18.880 --> 0:41:21.960
<v Speaker 4>of room for that. So that idea that because we

0:41:22.120 --> 0:41:25.279
<v Speaker 4>value the private sector, there has been for example, think

0:41:25.280 --> 0:41:27.400
<v Speaker 4>of Harvard Business School where they have this case study

0:41:27.400 --> 0:41:31.240
<v Speaker 4>methodology of businesses. We've never really done that with government

0:41:31.440 --> 0:41:36.160
<v Speaker 4>entities because we don't value basically government as a value creators,

0:41:36.160 --> 0:41:38.920
<v Speaker 4>just seen as a redistributor, a fixer, a facilitator and

0:41:39.080 --> 0:41:41.239
<v Speaker 4>enabler of the private sector. And that's of course where

0:41:41.280 --> 0:41:44.239
<v Speaker 4>then we expect creativity and value to be created, which

0:41:44.280 --> 0:41:46.799
<v Speaker 4>is not right. And so one of the things that

0:41:46.800 --> 0:41:48.720
<v Speaker 4>we do in the Institute, which is actually a department,

0:41:48.719 --> 0:41:50.880
<v Speaker 4>so we train up civil servants around the world also

0:41:51.000 --> 0:41:54.040
<v Speaker 4>you know through our own MPa Masters and public administration,

0:41:54.080 --> 0:41:57.720
<v Speaker 4>but also through applied learning programs, was to start developing

0:41:57.719 --> 0:41:59.840
<v Speaker 4>these cases. You know, what do we know about the BBC,

0:42:00.239 --> 0:42:02.560
<v Speaker 4>You know, how is it different from other public broadcasters.

0:42:02.560 --> 0:42:05.160
<v Speaker 4>How do they measure what they call public value. What

0:42:05.280 --> 0:42:08.640
<v Speaker 4>is public value? So even having you know, comparison learning

0:42:08.680 --> 0:42:12.400
<v Speaker 4>between say a public bank, the BBC, a government digital agency,

0:42:12.680 --> 0:42:14.600
<v Speaker 4>on what it means to crowd in or crowd out

0:42:14.640 --> 0:42:17.279
<v Speaker 4>their private sector, what it means to shape markets not

0:42:17.320 --> 0:42:19.400
<v Speaker 4>fix them. What does it mean to have a culture

0:42:19.400 --> 0:42:22.920
<v Speaker 4>of experimentation versus this huge risk averseness that, as we

0:42:22.960 --> 0:42:25.880
<v Speaker 4>said before, is a cause for the consultification. So I

0:42:25.880 --> 0:42:28.200
<v Speaker 4>think a lot about that, but it's not you know,

0:42:28.239 --> 0:42:30.720
<v Speaker 4>there's so much instability obviously also in the private sector,

0:42:31.000 --> 0:42:32.400
<v Speaker 4>So there is a bit of a myth that it's

0:42:32.440 --> 0:42:35.160
<v Speaker 4>all unstable in the public sector because of electoral turnover.

0:42:35.719 --> 0:42:40.000
<v Speaker 4>We can't shape these bureaucracies to be creative bureaucracies, resilient bureaucracies.

0:42:40.000 --> 0:42:43.000
<v Speaker 4>They don't have to be vertical and so inertial. But

0:42:43.080 --> 0:42:45.319
<v Speaker 4>the other point, I think that's sort of stemming. I

0:42:45.320 --> 0:42:47.000
<v Speaker 4>think in your question, tell me if this is not

0:42:47.040 --> 0:42:52.160
<v Speaker 4>related is literally winning the election? What are we learning globally?

0:42:52.520 --> 0:42:55.719
<v Speaker 4>You know, why is it that Biden, whose economic policies

0:42:55.800 --> 0:42:58.799
<v Speaker 4>were actually quite successful in the red states at least

0:42:58.800 --> 0:43:01.680
<v Speaker 4>starting to be quite successful, Well, why in those states

0:43:01.719 --> 0:43:04.520
<v Speaker 4>did he not win? And I think there's something going

0:43:04.560 --> 0:43:06.839
<v Speaker 4>on in a lot of countries, definitely also in Italy

0:43:06.920 --> 0:43:10.080
<v Speaker 4>in the UK where people who have been let's just

0:43:10.160 --> 0:43:12.760
<v Speaker 4>use the concept left behind on terms of the economic

0:43:12.800 --> 0:43:15.760
<v Speaker 4>benefits at least in the past. Even when new economic

0:43:15.800 --> 0:43:19.360
<v Speaker 4>policies work, that's not enough if people don't feel valued,

0:43:19.480 --> 0:43:21.800
<v Speaker 4>if they don't have their dignity back, if they continue

0:43:21.800 --> 0:43:24.279
<v Speaker 4>to feel condescended upon. So one of the really cool

0:43:24.320 --> 0:43:27.120
<v Speaker 4>things I've been working on with city governments but even councils.

0:43:27.120 --> 0:43:29.839
<v Speaker 4>So my neighborhood in London is called Camden, It's about

0:43:29.840 --> 0:43:32.560
<v Speaker 4>two hundred and fifty thousand people. I worked with the

0:43:32.560 --> 0:43:36.840
<v Speaker 4>council on mission oriented procurement for adult social care across

0:43:36.840 --> 0:43:39.400
<v Speaker 4>ten housing estates what you call projects in the US,

0:43:39.760 --> 0:43:42.719
<v Speaker 4>and we brought the careers and the careys to the

0:43:42.719 --> 0:43:47.480
<v Speaker 4>table to design that policy. So working with people really

0:43:47.560 --> 0:43:51.560
<v Speaker 4>valuing their lived experience to help its design policies that

0:43:51.640 --> 0:43:55.799
<v Speaker 4>are meaningful and will improve their lives, I think it's

0:43:55.880 --> 0:43:59.120
<v Speaker 4>just so important firstly to get those policies to be

0:43:59.200 --> 0:44:02.440
<v Speaker 4>designed right, but also to give people again dignity and

0:44:02.440 --> 0:44:04.840
<v Speaker 4>self worth. And I've seen it also, you know, because

0:44:04.840 --> 0:44:07.880
<v Speaker 4>we have so much inequality in the UK, unfortunately we

0:44:07.920 --> 0:44:09.960
<v Speaker 4>have food banks, which is barbaric if you think about it.

0:44:09.960 --> 0:44:11.840
<v Speaker 4>In the twenty first century, food banks, like you know,

0:44:11.880 --> 0:44:14.360
<v Speaker 4>we should not have that. People should have food, you know,

0:44:14.480 --> 0:44:17.640
<v Speaker 4>on the table, enough and healthy food. We don't have that.

0:44:18.000 --> 0:44:22.239
<v Speaker 4>So transforming food banks into food cooperatives, green food cooperatives,

0:44:22.239 --> 0:44:25.719
<v Speaker 4>where the people benefiting from the what was a food

0:44:25.760 --> 0:44:28.120
<v Speaker 4>bank are now also in the place of governing, of

0:44:28.160 --> 0:44:31.319
<v Speaker 4>having real deliberation, of thinking together. I can tell you

0:44:31.440 --> 0:44:33.520
<v Speaker 4>the people I saw working in the food banks who

0:44:33.520 --> 0:44:37.440
<v Speaker 4>are also receiving the food. The facial expression, the dignity,

0:44:37.520 --> 0:44:40.919
<v Speaker 4>just even how people are standing is completely different from

0:44:40.960 --> 0:44:42.040
<v Speaker 4>a system where.

0:44:42.200 --> 0:44:46.560
<v Speaker 3>You know, you here, someone's expired, like yeah, exactly from

0:44:46.640 --> 0:44:47.440
<v Speaker 3>last Thanksgiving.

0:44:47.480 --> 0:44:50.240
<v Speaker 4>No, but even if it's good food, you know, having again,

0:44:50.320 --> 0:44:54.040
<v Speaker 4>you know, bringing back dignity and value it. It's so important,

0:44:54.080 --> 0:44:55.400
<v Speaker 4>I think to fight populism.

0:44:56.640 --> 0:44:58.799
<v Speaker 3>I'm going to ask what is potentially an unfair and

0:44:58.880 --> 0:45:01.520
<v Speaker 3>loaded question, but I think it might be quite illustrative

0:45:01.520 --> 0:45:03.960
<v Speaker 3>of everything that we've been discussing. When you look across

0:45:04.000 --> 0:45:08.080
<v Speaker 3>the world, are there particular countries or cities that you

0:45:08.200 --> 0:45:11.400
<v Speaker 3>think are doing industrial policy right in the sense that

0:45:11.400 --> 0:45:14.960
<v Speaker 3>they're taking maybe a holistic approach with a defined strategy

0:45:15.000 --> 0:45:15.720
<v Speaker 3>slash mission.

0:45:16.400 --> 0:45:19.200
<v Speaker 4>So I tend to also look at very specific things

0:45:19.200 --> 0:45:21.040
<v Speaker 4>that a government did instead of just saying the whole

0:45:21.080 --> 0:45:24.239
<v Speaker 4>government's perfect right. So, for example, in Brazil, something they've

0:45:24.239 --> 0:45:26.319
<v Speaker 4>done that I think has been very positive is that

0:45:26.320 --> 0:45:29.200
<v Speaker 4>they've put what I call missions at the center of government,

0:45:29.400 --> 0:45:32.399
<v Speaker 4>so the ecological transition is at the center, and that

0:45:32.440 --> 0:45:36.239
<v Speaker 4>then required the Department of Finance, for example, to rethink

0:45:36.320 --> 0:45:40.200
<v Speaker 4>its own tools. For example, public bank right so BNDS,

0:45:40.239 --> 0:45:42.400
<v Speaker 4>which is one of the largest public banks in the world.

0:45:42.880 --> 0:45:44.839
<v Speaker 4>It can either just again give money out to say

0:45:44.840 --> 0:45:48.040
<v Speaker 4>the agrobusiness industry or save the steel industry when it's

0:45:48.080 --> 0:45:51.759
<v Speaker 4>going bust, or because there's an ecological transition, it can

0:45:51.760 --> 0:45:55.480
<v Speaker 4>think about how these sectors themselves need to change in

0:45:55.560 --> 0:45:58.600
<v Speaker 4>order also to access the loans that the bank is giving. Germany,

0:45:58.600 --> 0:45:59.920
<v Speaker 4>by the way, did that when they had the end

0:46:00.120 --> 0:46:04.080
<v Speaker 4>Givende policy. They're public bank, the KfW. The way, they

0:46:04.120 --> 0:46:06.600
<v Speaker 4>provided support to the steel sector, which in the US

0:46:06.680 --> 0:46:09.880
<v Speaker 4>and the UK and so many countries steel is under pressure.

0:46:10.239 --> 0:46:12.880
<v Speaker 4>The loans to the steel sector were conditional that the

0:46:12.920 --> 0:46:16.200
<v Speaker 4>sector lower the material content of production, which they did

0:46:16.400 --> 0:46:18.400
<v Speaker 4>in their own way. Had government told them how to

0:46:18.440 --> 0:46:23.240
<v Speaker 4>do it, You kill innovation, but strong direction, conditional loans,

0:46:23.560 --> 0:46:26.279
<v Speaker 4>and they ended up now having the greenest steel in

0:46:26.320 --> 0:46:28.319
<v Speaker 4>the world. It might not be competitive yet, and that's

0:46:28.360 --> 0:46:30.680
<v Speaker 4>a scale issue that has also to do with regulation.

0:46:31.200 --> 0:46:35.600
<v Speaker 4>But you know, repurpose, reuse, recycle technology in steel only

0:46:35.680 --> 0:46:38.600
<v Speaker 4>happened because the public bank that was mission aligned. So

0:46:38.640 --> 0:46:42.800
<v Speaker 4>I'm very interested in procurement. Public loans stayed on enterprises, digital,

0:46:42.800 --> 0:46:46.359
<v Speaker 4>public infrastructure examples where they're not just things that are there,

0:46:46.760 --> 0:46:51.040
<v Speaker 4>but they're used to really transform and help development. Sweden

0:46:51.120 --> 0:46:54.799
<v Speaker 4>is also really interesting because they had a high level challenge.

0:46:55.239 --> 0:46:57.719
<v Speaker 4>Missions are somewhere between the challenge like the space race

0:46:57.880 --> 0:47:00.760
<v Speaker 4>and the sector like aerospace, right, so the Moon mission

0:47:00.800 --> 0:47:03.120
<v Speaker 4>required lots of different sectors, but it was very concrete.

0:47:03.160 --> 0:47:05.560
<v Speaker 4>Was the challenge of say, climate change or all the

0:47:05.600 --> 0:47:08.000
<v Speaker 4>sustainable development goals, those are kind of very broad, so

0:47:08.080 --> 0:47:11.040
<v Speaker 4>transforming them into missions and their challenge was I think

0:47:11.040 --> 0:47:14.080
<v Speaker 4>they said they wanted a fossil free welfare state, and

0:47:14.120 --> 0:47:16.600
<v Speaker 4>that's why then they said, well what are the missions.

0:47:16.680 --> 0:47:18.359
<v Speaker 4>We were working with them on this and so we

0:47:18.360 --> 0:47:20.680
<v Speaker 4>were kind of stimulating some of this thought through Venova.

0:47:20.719 --> 0:47:23.120
<v Speaker 4>Their Innovation Agency, what are the missions that will help

0:47:23.239 --> 0:47:26.320
<v Speaker 4>us achieve that? And that's where then the Healthy, Tasty,

0:47:26.360 --> 0:47:29.279
<v Speaker 4>Sustainable school Meals policy came from. We worked with them

0:47:29.280 --> 0:47:31.279
<v Speaker 4>on that also in Brazil. We just actually put out

0:47:31.280 --> 0:47:33.759
<v Speaker 4>a report about this with the World Food Program. But

0:47:33.800 --> 0:47:36.840
<v Speaker 4>what was interesting again was that then that required government

0:47:36.880 --> 0:47:41.840
<v Speaker 4>to work in a different way again interminousterely catalyzing bottom

0:47:41.920 --> 0:47:46.120
<v Speaker 4>up experimentation, local manufacturing, but through also the redesign of

0:47:46.160 --> 0:47:48.960
<v Speaker 4>the tools themselves. The UK, which I don't think is

0:47:49.000 --> 0:47:51.040
<v Speaker 4>a very good example right now. I mean there's lots

0:47:51.040 --> 0:47:54.920
<v Speaker 4>of instability. There's also been fourteen years of austerity. Some

0:47:55.000 --> 0:47:57.759
<v Speaker 4>things that were really interesting, and this is why I

0:47:57.760 --> 0:48:00.640
<v Speaker 4>look more at the organizational kind of examples is Government

0:48:00.680 --> 0:48:06.880
<v Speaker 4>Digital Services GDS, which basically began by government back in

0:48:06.920 --> 0:48:09.000
<v Speaker 4>the early two thousand saying why does everyone have to

0:48:09.040 --> 0:48:11.080
<v Speaker 4>go to say Google to download a white paper, Why

0:48:11.080 --> 0:48:13.239
<v Speaker 4>don't we have our own kind of digital platform. They

0:48:13.239 --> 0:48:16.360
<v Speaker 4>did what most governments do, outsourced it to a company

0:48:16.360 --> 0:48:19.400
<v Speaker 4>called Circo, which is not a very innovative company at all,

0:48:19.480 --> 0:48:22.839
<v Speaker 4>gets lots of government contracts. They failed miserably, and then

0:48:22.840 --> 0:48:26.919
<v Speaker 4>people from the iPlayer team and the BBC said we'll

0:48:26.920 --> 0:48:29.120
<v Speaker 4>do it, So they went over to the Cabinet Office

0:48:29.120 --> 0:48:32.320
<v Speaker 4>set up Government Digital Services, came up with this incredible

0:48:32.320 --> 0:48:35.239
<v Speaker 4>digital platform called gov dot UK, which won an International

0:48:35.280 --> 0:48:37.759
<v Speaker 4>Design Award. But what was interesting to me from that

0:48:37.840 --> 0:48:40.200
<v Speaker 4>example was that the first thing they did was look

0:48:40.239 --> 0:48:43.880
<v Speaker 4>out the window and said, with arrows pointing out the window,

0:48:44.000 --> 0:48:47.279
<v Speaker 4>those are not clients and customers. Let's stop talking about

0:48:47.320 --> 0:48:50.600
<v Speaker 4>people as clients and customers. Their users with human rights

0:48:50.880 --> 0:48:54.160
<v Speaker 4>and how they will access their driver's license, their paths

0:48:54.160 --> 0:48:58.480
<v Speaker 4>for their voter registration has to enhance their like their souls,

0:48:58.480 --> 0:49:00.360
<v Speaker 4>and I make them want to die. You see the

0:49:00.400 --> 0:49:02.560
<v Speaker 4>kind Looach movies where you know, people literally want to

0:49:02.560 --> 0:49:04.920
<v Speaker 4>die when they're accessing their welfare payments because of just

0:49:05.000 --> 0:49:08.480
<v Speaker 4>the complications around it. And so making you know, having

0:49:08.560 --> 0:49:11.719
<v Speaker 4>kind of like a user friendly government digital platform that

0:49:11.920 --> 0:49:15.400
<v Speaker 4>changes the experience of a citizen with those rights that

0:49:15.440 --> 0:49:18.760
<v Speaker 4>they have through the technology just requires a very different

0:49:19.000 --> 0:49:21.479
<v Speaker 4>kind of mind shift. And it became the coolest place

0:49:21.520 --> 0:49:23.760
<v Speaker 4>to work. So if you were taught you know, software

0:49:23.760 --> 0:49:26.640
<v Speaker 4>engineer or even you know whatever, these hackers that add

0:49:26.640 --> 0:49:29.319
<v Speaker 4>the cola wanted to hire. That's where they wanted to work.

0:49:29.520 --> 0:49:31.640
<v Speaker 4>To the point that lots of private companies were having

0:49:31.640 --> 0:49:33.480
<v Speaker 4>a hard time finding the top talent because they all

0:49:33.480 --> 0:49:36.080
<v Speaker 4>wanted to work in and gidah. So again, those are

0:49:36.080 --> 0:49:38.360
<v Speaker 4>the examples I think we need to look for, not

0:49:38.520 --> 0:49:41.240
<v Speaker 4>like which is the government. This thing everything perfectly.

0:49:41.080 --> 0:49:44.279
<v Speaker 2>All right, Professor Matchakato, thank you so much. Great to

0:49:44.360 --> 0:49:46.200
<v Speaker 2>finally catch up with you. It took us all like

0:49:46.520 --> 0:49:50.400
<v Speaker 2>randomly being in the same location. But thank you so pleasure.

0:49:50.560 --> 0:49:51.640
<v Speaker 2>Thank you so much for coming on.

0:49:51.600 --> 0:49:53.360
<v Speaker 4>Oudlocks, thank you so much for having the.

0:50:05.760 --> 0:50:10.160
<v Speaker 2>Tracy. I'm glad we finally, professor the place to do it.

0:50:10.239 --> 0:50:12.160
<v Speaker 2>This is definitely the place to do it. I think

0:50:12.160 --> 0:50:14.520
<v Speaker 2>it really did. Her framing makes a lot of sense.

0:50:15.000 --> 0:50:19.840
<v Speaker 2>This idea that like outsourcing is not per se bad.

0:50:20.440 --> 0:50:23.960
<v Speaker 2>That obviously any major mission is going to have to

0:50:24.000 --> 0:50:28.319
<v Speaker 2>have significant private sector involvement and innovation, even if it's

0:50:28.360 --> 0:50:32.480
<v Speaker 2>somehow publicly led, but that there's no chance of going

0:50:32.520 --> 0:50:36.160
<v Speaker 2>anywhere if there's you know, the public sector doesn't have

0:50:36.200 --> 0:50:38.759
<v Speaker 2>the internal muscle of who to talk to or to

0:50:38.880 --> 0:50:39.680
<v Speaker 2>talk to at.

0:50:39.520 --> 0:50:40.080
<v Speaker 4>The right time.

0:50:40.120 --> 0:50:41.280
<v Speaker 3>How to judge performance.

0:50:41.280 --> 0:50:44.400
<v Speaker 2>How to judge performance seems absolutely a key question.

0:50:44.239 --> 0:50:46.840
<v Speaker 3>And that kind of gets back to the mission idea,

0:50:46.880 --> 0:50:48.719
<v Speaker 3>which I did. I really I like the idea of

0:50:48.760 --> 0:50:51.440
<v Speaker 3>focusing on what you're trying to achieve rather than just

0:50:51.680 --> 0:50:55.399
<v Speaker 3>how you're actually going about achieving it. Like that makes

0:50:55.440 --> 0:50:57.879
<v Speaker 3>a lot of sense to me if you're dealing with

0:50:58.280 --> 0:51:02.560
<v Speaker 3>a vast bureaucracy with lots of different silos. And also,

0:51:02.640 --> 0:51:05.560
<v Speaker 3>I think like getting back to that expertise point does

0:51:05.680 --> 0:51:09.560
<v Speaker 3>mean that you do develop that muscle internally within the

0:51:09.640 --> 0:51:12.960
<v Speaker 3>organization rather than just like, Okay, we're going to hire

0:51:13.520 --> 0:51:17.200
<v Speaker 3>McKenzie to figure out how we're going to do something.

0:51:17.320 --> 0:51:20.160
<v Speaker 3>Instead you say, well, we want to do X, let's

0:51:20.360 --> 0:51:22.400
<v Speaker 3>all get together and figure out how to do it.

0:51:22.760 --> 0:51:25.319
<v Speaker 2>You know, AI seems like a weird thing as a

0:51:26.120 --> 0:51:30.000
<v Speaker 2>technology because all right, on the one hand, you could say, like,

0:51:30.000 --> 0:51:32.319
<v Speaker 2>all right, we want to massively improve our healthcare, so

0:51:32.400 --> 0:51:35.359
<v Speaker 2>we want to massively improve healthcare outcomes. And I think

0:51:35.360 --> 0:51:37.880
<v Speaker 2>you could like very easily say well, AI is going

0:51:37.920 --> 0:51:40.280
<v Speaker 2>to be really big part of that, right, and maybe

0:51:40.320 --> 0:51:43.760
<v Speaker 2>make things a lot more efficient, maybe give information access

0:51:43.800 --> 0:51:45.879
<v Speaker 2>to a lot of people, identify experts, et.

0:51:45.880 --> 0:51:47.840
<v Speaker 3>Cetera, the results to develop new medicines.

0:51:48.239 --> 0:51:50.719
<v Speaker 2>Yeah, totally, it's so great. So maybe the mission has

0:51:50.719 --> 0:51:53.800
<v Speaker 2>something to do with health, and AI plays an important

0:51:53.800 --> 0:51:56.879
<v Speaker 2>component of it. I guess what's strange though, is that

0:51:57.360 --> 0:52:01.879
<v Speaker 2>AI itself creates its own potential pitfalls. I mean, the industry,

0:52:02.200 --> 0:52:05.000
<v Speaker 2>as you mentioned, is obsessed with the pitfalls of its

0:52:05.000 --> 0:52:07.520
<v Speaker 2>own making, right, Yeah, and so there is almost no

0:52:07.600 --> 0:52:10.680
<v Speaker 2>way that AI can just be a tool in the

0:52:10.840 --> 0:52:14.720
<v Speaker 2>service of some other mission because almost everyone who knows

0:52:14.760 --> 0:52:21.360
<v Speaker 2>something about AI sees potential for extreme exacerbation of inequality,

0:52:21.640 --> 0:52:25.800
<v Speaker 2>potentially AI robots that will be misaligned and want to

0:52:25.880 --> 0:52:29.680
<v Speaker 2>kill us all when they have sufficient capabilities. Yeah, right,

0:52:29.760 --> 0:52:32.279
<v Speaker 2>and so like on the one hand, like, yes, as

0:52:32.280 --> 0:52:34.480
<v Speaker 2>the technology, it might fit into some of these other

0:52:34.520 --> 0:52:36.880
<v Speaker 2>big missions, But on the other hand, it sort of

0:52:36.920 --> 0:52:38.920
<v Speaker 2>feels like it has there has to be some like

0:52:39.480 --> 0:52:42.520
<v Speaker 2>AI specific goal of like where do we want this

0:52:42.600 --> 0:52:44.719
<v Speaker 2>technology to go or how do we how do we

0:52:44.880 --> 0:52:49.240
<v Speaker 2>curb it or whatever it is. It seems very distinct.

0:52:48.800 --> 0:52:51.080
<v Speaker 3>No, totally, and I do think the unusual part of

0:52:51.120 --> 0:52:53.439
<v Speaker 3>this moment in time, and a lot of people will

0:52:53.800 --> 0:52:56.120
<v Speaker 3>argue that maybe it's marketing or whatever, but you do

0:52:56.200 --> 0:52:58.600
<v Speaker 3>see the big Tech CEO is like basically going on

0:52:58.640 --> 0:53:02.719
<v Speaker 3>TV and saying like, we as a whole society need

0:53:02.760 --> 0:53:04.680
<v Speaker 3>to figure out what we want to do here.

0:53:04.840 --> 0:53:07.520
<v Speaker 2>And I don't think it is marketing or just marketing

0:53:07.680 --> 0:53:11.000
<v Speaker 2>because A there's already this very big tech backlash, right,

0:53:11.160 --> 0:53:13.920
<v Speaker 2>so like if we're like, it's not working, you know,

0:53:14.040 --> 0:53:17.280
<v Speaker 2>if the idea is, oh, we want to plump our valuations,

0:53:17.480 --> 0:53:20.040
<v Speaker 2>so we do that by saying that TAM is all

0:53:20.160 --> 0:53:21.279
<v Speaker 2>human labor.

0:53:21.800 --> 0:53:22.600
<v Speaker 3>And human life.

0:53:22.760 --> 0:53:25.759
<v Speaker 2>Yeah, well, you're really upsetting a lot of people by

0:53:25.800 --> 0:53:27.960
<v Speaker 2>saying this. It's not that's not obviously good, and b

0:53:28.680 --> 0:53:31.680
<v Speaker 2>you know, it's we've written about or talked about. You know,

0:53:31.840 --> 0:53:34.160
<v Speaker 2>some of these big labs, like they were founded from

0:53:34.239 --> 0:53:37.520
<v Speaker 2>day one with the premise that this is not normal technology,

0:53:37.560 --> 0:53:40.000
<v Speaker 2>which is why it's like housed in a nonprofit or

0:53:40.040 --> 0:53:42.600
<v Speaker 2>something like this. So I tend to think that when

0:53:42.719 --> 0:53:45.920
<v Speaker 2>the CEOs of these companies talk about this stuff, they

0:53:46.000 --> 0:53:48.719
<v Speaker 2>kind of mean what they say. They two are they

0:53:48.719 --> 0:53:49.400
<v Speaker 2>two are concerned.

0:53:49.480 --> 0:53:52.360
<v Speaker 3>I mean I also worry without some sort of government

0:53:52.600 --> 0:53:56.520
<v Speaker 3>intervention or government strategy here, we are going to get

0:53:56.520 --> 0:54:00.279
<v Speaker 3>to that situation where we deploy AI and because we're

0:54:00.280 --> 0:54:03.520
<v Speaker 3>not fixing the underlying system, we're just sort of nippling

0:54:03.520 --> 0:54:06.880
<v Speaker 3>at the edges and making it worse. Per that idea

0:54:07.040 --> 0:54:09.319
<v Speaker 3>of like, Okay, the insurance bot is going to talk

0:54:09.320 --> 0:54:11.560
<v Speaker 3>to the hospital bot and both of them are going

0:54:11.600 --> 0:54:15.560
<v Speaker 3>to say that they're streamlining the billing process for medical services.

0:54:15.600 --> 0:54:18.360
<v Speaker 3>But because we're all doing the same thing without actually

0:54:18.480 --> 0:54:22.040
<v Speaker 3>fixing how medical bills work and who pays for what

0:54:22.400 --> 0:54:24.719
<v Speaker 3>in the US, like, it's just going to be bots

0:54:24.760 --> 0:54:26.520
<v Speaker 3>fighting bots. No one's going to benefit from that.

0:54:26.719 --> 0:54:29.000
<v Speaker 2>No, and most likely there will be sort of you know,

0:54:29.120 --> 0:54:33.439
<v Speaker 2>just ongoing increase complexity. It's bots all the way bot's

0:54:33.440 --> 0:54:34.000
<v Speaker 2>all the way down.

0:54:34.000 --> 0:54:34.880
<v Speaker 3>All right, shall we leave it there?

0:54:35.000 --> 0:54:35.560
<v Speaker 2>Let's leave it there.

0:54:35.560 --> 0:54:35.799
<v Speaker 4>Okay.

0:54:35.840 --> 0:54:38.399
<v Speaker 3>This has been another episode of the Authoughts podcast. I'm

0:54:38.480 --> 0:54:41.200
<v Speaker 3>Tracy Alloway. You can follow me at Tracy Alloway.

0:54:40.960 --> 0:54:44.080
<v Speaker 2>And I'm Jill Wisenthal. You can follow me at the Stalwart.

0:54:44.520 --> 0:54:48.480
<v Speaker 2>Follow our guest Mariana Matsukato at Matsukato m follow our

0:54:48.520 --> 0:54:52.239
<v Speaker 2>producers Carmen Rodriguez at Kerman armand dash Ol Bennett at Dashbot,

0:54:52.320 --> 0:54:55.439
<v Speaker 2>Cale Brooks at Kale Brooks and Kevin Lizano at Kevin

0:54:55.520 --> 0:54:58.080
<v Speaker 2>Lloyd Lisano. And for more odd Laws content, go to

0:54:58.120 --> 0:55:01.000
<v Speaker 2>Bloomberg dot com slash odd Lots for the daily newsletter

0:55:01.040 --> 0:55:03.200
<v Speaker 2>and all of our episodes, and you can chat about

0:55:03.200 --> 0:55:05.200
<v Speaker 2>all of these topics twenty four to seven in our

0:55:05.320 --> 0:55:08.560
<v Speaker 2>discord Discord dot gg slash out Lots.

0:55:08.480 --> 0:55:10.319
<v Speaker 3>And if you enjoy odd Lots, if you like it

0:55:10.360 --> 0:55:13.040
<v Speaker 3>when we define state capacity, then please leave us a

0:55:13.120 --> 0:55:16.440
<v Speaker 3>positive review on your favorite podcast platform. And remember, if

0:55:16.480 --> 0:55:18.920
<v Speaker 3>you are a Bloomberg subscriber, you can listen to all

0:55:18.960 --> 0:55:21.640
<v Speaker 3>of our episodes absolutely ad free. All you need to

0:55:21.680 --> 0:55:24.319
<v Speaker 3>do is find the Bloomberg channel on Apple Podcasts and

0:55:24.400 --> 0:55:26.840
<v Speaker 3>follow the instructions there. Thanks for listening.