Welcome back to the Ten Blocks podcast.

This is Brian Anderson, the editor of City Journal.

Joining me on the show today is

Danny Crichton. Danny's a fellow at the Manhattan Institute, where he analyzes technology,

growth, and economics. And he's the head of editorial at the VC firm Lux Capital, where he

publishes the excellent risk gaming newsletter and podcast. He's written regularly for City Journal.

Today, though, we're going to discuss the case for using artificial intelligence in government,

a topic he explores in a fascinating essay in City Journal's summer issue entitled

United States of Algorithms. So, Danny, thanks very much for joining us.

Thanks, Brian. As you note in this essay, algorithmic decision making touches virtually every

aspect of our daily lives now, particularly in the private sector. Artificially intelligent

systems, you know, they recommend the news items people read, the products they buy. These days, even the people they date. And we've largely grown comfortable with that, though some exceptions hold there. But as you've noted in this essay, the government's been very slow to adopt these

new technologies. So I wonder, you know, if you could outline first why that matters and what it has

cost us. Right. I mean, when you look at the private sector, there's obviously immense competition

between different firms and an industry. And so automation, the ability to lower labor costs to provide a better

customer service experience for consumers, obviously is a very high priority. And so CEOs over the last

20, 30 years have moved quickly to move automation, as you noted, across finance. So when you apply

for a mortgage, a lot of that is now automated.

When you apply for relief from a customer service agent when you're flying on an airline,

almost all that is automated behind the scenes these days.

But then you get to government.

And obviously, the government has a monopoly.

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