Alex Karp is here. He is the co-founder and CEO of Palantir Technologies. The company's data mining software is used by various government agencies in the United States, including the CIA, FBI, and NYPD.

It's also used by hedge funds and other financial firms. Karp is a Stanford graduate and co-founder of the company with ex-PayPal engineers.

I am pleased to have him here at this table for the first time. He does not do many television interviews, and for that, I'm also pleased to have him here.

Welcome. Thank you for having me. Let me talk a bit about the background, which is interesting. Stanford Law, wasn't it?

It was Stanford Law. Uh, and then, and then you went to Frankfurt. Then I went to Frankfurt. PhD, neoclassical, uh, social philosophy, which is a fancy way of saying a quick path to being unemployed, certainly to be the highest educated, least earning person on the planet.

And why did you do that? Um, well, the same reason I, I got involved in founding Palantir. I, I was really passionate about the issues.

I largely wasn't putting money ahead of what I thought was important. Um, some of the ideas I dealt with were actually quite important. How what does it mean to know something?

How does it, what does it mean to communicate it? Um, what is the foundation of Western society? Uh, can we participate as citizens and how?

I was very passionate about those ideas, just like I'm passionate about, uh, my business, Palantir, and, and also about anti-Semitism and other issues that you thought needed to be written about and discussed.

I published widely on both technical issues, uh, kind of issues involving the convergence of Neocon philosophy and Freud, and on discrimination, and on civil liberties, and on anything that anyone would read, uh, which is what you do when you're an aspiring academic with essentially an interest in writing, um, and then I migrated into a business context.

Well, you know, the interesting thing about academia is that it's more interesting to the people in it than it is to anyone else. Uh, you know, and the impact, yes, you end up fighting about small things that may be fairly unimportant to other people.

And I I thought that while the ideas were important, that the actual impact they were going to have was was going to be very small.

I mean, the kind of work I did was intelligible to probably 30, 40 people in the world. So, um, it it seemed more interesting and compelling to do something else, get involved in business and see how that worked out.

And some of the issues in business are actually, from an academic perspective, also quite compelling.

So where did you migrate to? Well, it turned out I had a facility for I was pretty good at making money, and um,  I was very bad at getting paid.

So I basically turned the ability to make money and get paid into a business where I look for other people who were good at making money and bad at getting paid, and I taught them how to make money quicker and to get paid fairly.

This was kind of a venture capital kind of operation or, um, basically my own business which I built.

And, uh, we went I went around looking for motley people who had academic proclivities and were interested in business, and I would approach them and say, why don't you build a business?

I'll help you. And, uh, and I did that for a couple years, and, uh, and then I reconnected with Peter, Peter Thiel, um, and, uh, we began, along with a couple other guys, to build this company, and while there you had the idea for Palantir.

Yeah, well, I, you know, post-9/11, I think the idea again, it was Silicon Valley ought to be involved in in in fighting terrorism and protecting our civil liberties.

Um, and uh, and you know, terrorism is asymmetric. Asymmetry presupposes software because you're finding needles in haystacks, actually using an approach that's not exactly like data mining.

It was a critique on some of the data mining approaches uh that had been used at PayPal, and we thought that that approach would be very effective in this context and would do two things.

It would allow humans to find needles in haystacks, so make the data intelligible to you and me, which it's not.

And by doing that, it would allow them to find bad people trying to destroy our society and could be used also to protect civil liberties by making the datasets transparent so that you could it was very clear what the government is doing and how they're doing it, which is a particular passion of our company.

So the the basic idea is that the West or Western values will win if we and the West believe in what we're doing.

There's no point in having a war on terrorism if civil liberties are being undermined to the extent that we aren't willing to fight that war. And this is particularly true in the cyber context.

It turned out that the approach that was used at PayPal was essentially an anti-data mining approach. It was anti-data mining in the sense that data mining uses algorithms across large datasets, and what we do is we use what legal scholars call predicate-based search.

So we would look at you and then we would go out and say, oh, there's lots of different things in your life that may be indicative of someone being someone involved in bad behavior.

But it would also be very clear how the government looked at you.

It wouldn't be a wide net cast into a sea of data that brings back all of our, all the innocent citizens that are touched by that net.

It would be a very precise, very precise operation, and each step in that operation is documented. How much of your business is finding terrorists for the U.S. government or whoever wants to hire you?

Most of our business is in government, and it all involves both sides of this equation.

Uh, finding uh, people who are up to essentially bad things, both in the anti-terror area, in cyber, in financial malfeasance, mortgage fraud, but also making sure the data is tagged in a way that allows agencies to collaborate with one another, which is one of the big findings in the 9/11 Commission.

Why weren't people able to collaborate? People tend to focus on the policy issues, but there are also massive technical issues that had to be solved, and solved in a way where you can just install it.

We do that. And the second piece is, how do you do it so that when the government is looking at you or me, it's clear that they're looking at you and me for a reason.

If they bring a case against us, what is the case? Where did the evidence come from? Did it come from sources they were allowed to say?

Did they migrate from the source of one piece of evidence into another source? These are the kind of questions that that Americans care a lot about.

Why can't the government do this themselves? We, first of all, we are a piece of the hardworking and tremendously impressive people that you meet when you're in this business are the most important part.

Our part is to provide world-class software.

This is something America, by the way, is very good at. Silicon Valley is especially good at, and that will continue. In your judgment, in America's leadership in creating software, I think software is probably an area where America will continue to lead.

I think Silicon Valley will be at the tip of that, of that movement.

Uh, it's, it's, it's the place we've excelled at. Of the software products you like to use, your audience likes to use, they're mostly American.

And they don't use it because it's built in America.

They use it because it's the best. And why is that? Well, you know, the thing is we, it's, of course, we have enormously talented people, but what makes a software product work is an ability to build a business around a compelling idea.

And that's that while this seems obvious in America and especially in Silicon Valley, in almost every other place, if you want to build a business, people will say, 'Well, how are you going to make money tomorrow?

' In Silicon Valley, we build businesses around an idea, and then we figure out how we're going to make money. And this is incredibly important because if you want something to really work, something really complicated, you cannot hire people who are motivated by paycheck.

They have to live and breathe it. They have to do it over a long period of time.

You have to be willing to... Our company took three years to build before we even went to market.

Three years, no revenue. In any other part of the world, people would laugh you out of the room. But not in the venture capital world, but not in Silicon Valley.

It's a rare place where somewhere else, it doesn't have to be Silicon Valley for venture capital to say, you're not going to make revenue for three years, and but then we believe that you have the seed to grow into something big.

Venture capital exists everywhere, but the companies that have invested using that capital exist in America by and large, and particularly in Silicon Valley.

And it's, I believe it's, it's not because we're smarter, it's because we work better together, because we're more likely to be compelled by a big idea and put monetization second.

And this is, this is the secret to our company. And you know, even when we went to market, we didn't hire sales.

We still don't have salespeople. We have no salespeople working for us at Palantir. We sell the product by exposing clients to it and saying, compare us to what you have.

So what's the compelling business idea here? The compelling business idea is, uh, if you want to make data, if you want to interact with data in a way that's intelligible to you, so the data that's around you, and you're the government, it's a very hard thing to do at scale.

So let's just say you go to the market and you buy something, you talk on your cell phone, you send an SMS, you send every little kind of, you write a report.

It's very hard for you to see that as a pattern. Well, if I'm looking at the government trying to figure that out, it's very hard to do.

What's done currently is they hire a team of computer scientists who write algorithms that none of us understand, right?

And then they come back and say, oh, well, maybe do you believe the computer scientists they hire or would you rather see it yourself?

And that's what we offer. We offer a way to just plug on our platform and you can be a leading expert in finding patterns in large data sets, whether those patterns are terrorists, they're cyber attackers, they're people again in financial malfeasance, or we, the people who want to look at what the government is doing in one form or another, either through Congress or through our attorneys, we can then see what the government is doing.

This is very important. We also allow people to collaborate, which is an enormously important problem. When people look at what happened on 9/11, the conclusion was it happened because people weren't collaborating.

And they focused on kind of especially the CIA and FBI agencies did not effectively collaborate.

And people focus on the policy and inability to work together, but there's also a massive technical issue. How do you work in a massive data set and take out the two pieces of data that the FBI is allowed to see?

It's very tough. And that's something we, we turn, we have a turnkey approach to that.

You can put our product on top of your servers and you can collaborate tomorrow.

What patterns have you discovered about terrorists? Well, you know, obviously, you know, we don't discuss exactly what we've done in, in a classified context, nor am I allowed to.

But, but for example, in the Syar case, which is a case that was discussed in the public, uh, we took a data set that lots of people looked at, some of the world's experts, and we found that there was a group of people that lived in a village that was responsible for most of the attacks in Iraq, and we found out they were responsible for most of the money and most of the attacks.

And that's very valuable and highly actionable information.

If you know, if you know all the real attacks are coming from one source, there's a lot you can do about that.

And this is typical for the kind of things, or when we looked at the Dalai Lama case, which we've got a lot of public attention.

We partnered with Citizen Lab in Canada, and um, we discovered that the Dalai Lama had been infiltrated by one of the world's most sophisticated and uh, uh, largest uh, cyber networks.

And we discovered that working at the service of someone else, working at the service of somebody else, a government, that part we were not clear about.

But we are clear. One of the very interesting things about cyber is this whole issue of attribution. Um, I think the metaphor that one could use in talking about cyber is maybe less cyber war but the democratization of spy techniques.

So in the '80s and the '70s, only large governments could pull off spy operations.

Now teenagers in a basement with a computer can pull off a spy operation, and it's very unclear if it's them or someone else.

And the diagnostic you use is very, very complicated. It's not like someone breaks into your home; they leave a footprint or a handprint, or they leave a hair behind, or you take a picture of it.

It's very, very tough to find out who they are. But what we can allow people to do is get a much better sense of what the evidence is, where it points to.

The reason, the simple reason why simple data mining doesn't work, even leaving aside the moral issues it raises, is it uses a static algorithm against a non-static and highly entrepreneurial uh adversary, that would be the terrorist.

That's the terrorist. And so what you need to do is have a platform that allows you to interact with the data and see the patterns before they realize they're giving off the patterns.

So it's non-algorithmic, it's not static. And what we allow people to do is we allow the actual person doing the work, the analyst, the targeter, to get ahead of the terrorist.

To see patterns the terrorist doesn't realize they're giving off.

And this is this is what now. How good is the terrorist to there? You have to think of terrorists as entrepreneurs, and they tend to be, I think, very good at what they do.

And my view is we need to put our best entrepreneurs against their best entrepreneurs.

That's how we win because they all stopped using cell phones the way they used to, and all those kinds of things.

You can think, you can think of any approach you use as a static approach. They will figure that out. They, this person gets taken away, they do a diagnostic: how did that person get caught?

And they change their patterns immediately. What we need to do is is game them, is be ahead of whatever their technique is.

And that requires people that are very flexible, agile, the kind of people that build weird companies in the valley. You put them against these people, and that's by the way, in these pockets in government, that's what you find entrepreneurial people going after their entre.

If we as a country understand what the danger is, and we as a country understand the kind of uh that it's possible to fight this without giving up our civil liberties, we win.

If we underestimate the danger or we perceive this as a war that will be costly to who we are, we'll lose.

Democracies tend to win when the country gets behind it. We are kind of the greatest democracy in the world and we tend to win wars where the people believe in what they're doing.

Where the people think that there's a trade-off between civil liberties and fighting cyber terrorists, it's going to be very hard to win.

As long as we have computers that are turned on, there will be people that penetrate them. Every time we find a way to block them, they'll find a way in.

The danger is is real and it's going to be with us the rest of our life.

Now, the question is, if the danger is real and it's with us for the rest of our life, what can we as citizens do? We as Americans do that allows us to experience the liberty we want and stop them.

And I think unless that educational piece is really addressed directly, uh, we will have a problem educating the public about the threat, both the threat and the necessity of taking certain approaches.

Obviously, I'm biased and I think, you know, Palantir's ability to tag data and show what the government has done is enormously important.

But you have to explain, if it's, if this is explained where there's a contradiction between our liberty and protecting ourselves, we're going to have a real problem.

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