Am I exposing government spending? I'm exposing misconduct. I'm exposing possible fraud. The crazy exanthropic guy, he was part of this left-wing NGO. They're going from one version of Doom to another. We run these long-running AI queries 24, 48, 72 hours connecting the dots between all of these financial payments.
You won an IOI gold medal as a competitive programmer.
The people that I did IOI with, some of them founded billion dollar companies. Some of them made a theoretical breakthrough and here I am in the dirty news business.
We're excited to have you here to break your latest story. Brian, what did you uncover? Let's highlight a few other recent investigations.
They funded the journalist writing the article, the publisher, the subject of the article, and all three experts quoted in the article. There are people who will complain about this, but I think this kind of transparency will be embraced as just like a fixture of reality.
CEO and co-founder is a partner of BC. Now I'm here co-founder.
Brian Chow was the youngest American to win an IOI gold medal. One of the top programmers in the world at a young age. A lot of his friends have gone on to build companies worth tens of billions of dollars, have solved important math and physics problems. He's taken a different direction. He's an investigative journalist who started Effort News. Why is he doing investigative journalism? Well, it turns out there's new possibilities with AI that can look at government data, look what's going on in our society and find all sorts of crazy stories, tens of billions of dollars of grift, all sorts of schemes none of us have heard about. Brian's getting a huge amount of attention for his journalism, which you hear about the one we're going to break today on the episode. Really excited to have with us today Brian Chow of Effort News. Brian, thanks for joining us.
Brian, you won an IOI gold medal as a competitive programmer. You were in Forbidden Courses at UHX a while ago is how we originally met you, our university's program, a few years ago. Welcome to the show. Tell us a bit about your background. Where you from?
Yeah, so it's always interesting when people ask me this because I have very few memories of my childhood, but I was born in San Jose. When I went to high school, my parents moved me to this magnet school in Canada called Waterloo Collegiate Institute, which was known for two things. It was known for producing something like 20% of Canada's IOI medalists, this like big international programming contest. And it was known for doing something similar with robotics. So, I did that. I did that program, ended up being the youngest person in North America to win an IOI gold medal.
How old were you when you won?
Very good. Wow. And then you went to the University of Waterloo for a bit in machine learning, but then you left to work on AI policy in DC. Tell us about that.
Yeah, it was this very crazy time because when I was studying and then going into machine learning, it was not a political issue at all. It was just like, oh, it was just something you did. It was kind of like, you know, writing software. I was like, you know, writing like Postgres, something like that. And it was not a particularly political issue. But then around 2023, it really went into the spotlight or 2022, I think, really went into the spotlight first with Biden's AI executive order, which did all sorts of crazy stuff, and then with ChatGPT and that entire release into the public sphere. And at the time I had just been writing like a political theory blog about like Leo Strauss and Carl Schmitt and all these thinkers that people read about in theory that went viral for all sorts of other reasons. And I ended up being in a place where I was talking a lot increasingly about machine learning and what was happening and this increasing wave of precensorship that was happening in DC. And at one point I was just getting really frustrated and I wrote out like my entire plan of how I think an organization in DC to fight against this stuff would work. And fortunately some people actually offered me money to run this organization that I think was wildly successful. The organization was called Alliance for the Future. We ended up doing a lot of work in repealing the Biden executive order but also putting together the directives that would make sure that that entire apparatus that it created in the executive branch would end up being repealed and the equity mandates being removed and all these other mandates being removed.
And what did you learn about journalism when you were running Alliance for the Future that led to Effort News? Because right now you're doing just amazing work we're going to talk about today in investigative journalism. How did that come about?
Yeah, I think the biggest takeaway was from the other side of the desk was that more than 80% of news stories are solicited. A source comes to you, they say, I want you to run this story. And I actually don't blame most journalists for doing that. That's like a lot of the time that's a real newsworthy story, right? That's a real source. That's a real document. It's not entirely fake, but it distorts what people see. And what we ended up doing now with Effort News is querying all of these massive government databases using AI because there was this promise since the Nixon era basically that you know sunlight would be the best disinfectant that you would have all of these public disclosures, legal requirements and that would push all the information into the public and then the people would know. But it didn't happen because people didn't have the effort, people didn't have the time. People didn't really look into these documents.
So, no one's putting in the effort to take in all these like messy PDFs and databases that are public. So, you're putting in the effort. That's why the name, huh?
Yeah. Yeah. That's why it's Effort News. And we run these long-running AI queries 24, 48, 72 hours putting together connecting the dots between all these financial payments. So there are large government databases in HHS with Medicare and Medicaid with defense spending all of these large central databases of how the US spends its money and when we queried these records it was originally the original idea was that we were ramping up to something like audit preparation that we'd be able to have these big aggregate statistics and that would really teach us something about how the government works. But what we found was actually a lot more extreme than that. I started out by just looking for some wild cases. I essentially put the prompt I had done some optimizations for this search process both in terms of cost and in terms of how much it was searching. But the question that I asked it was essentially find me new news story items, newsworthy items from the HHS grant table. Find grants that expanded a lot in terms of absolute or relative value.
And then it found all of these stories that I started asking around to a lot of journalists on areas like immigration or DEI, like the biggest news areas basically in the entire country, in the world. And it found brand new stories that no one had ever heard of. So people were getting back to me. They were saying like, I have no idea what this is. And at that point, my jaw was just on the floor. I thought, Oh, the crown is totally in the gutter. I just need to do this 24/7.
I love it. And why was this not possible a few years ago? I mean, it seems like this is something that AI has just gotten better, right? Like what's AI able to do now that it wasn't before?
Yes. Part of it is the long context breakthroughs. Part of it is that you can just run the LLMs in these what are called, you know, long time window tasks, something like, you know, two or three days or even longer. And that's been useful in all sorts of areas, right? That's been useful in proving these open problems in math, that's been useful in doing drug discovery, and it's also useful here. But actually, it's interesting to me. I theorized that this kind of company would exist for basically like 3 or 4 years from now. So, I thought this would materialize a lot sooner than it actually did. And I think the reason why it didn't is that the skill sets to pull off this kind of thing they just very rarely come together where I don't know it just seems like that a lot of people who are good at the technical side are kind of okay with slop writing and a lot of the people who are good at writing don't really get the technicals.
That's right. It's two very different circles as well in my experience. So people who can win an IOI gold medal and then people who like care about HHS, you know, wasting tens of billions of dollars on some grift scheme that the Biden administration set up like for whatever reason in my life, you're one of the very probably the only person actually in those two specific diagrams, which is great, right? And so I think we all have kind of unique interests and passions and because you have both, you do something that no one else in the country is doing, it seems.
Yeah. The people that I did IOI or US nationals with some of them founded you know 20 billion dollar companies some of them you know made a theoretical breakthrough in how fast you can run Dijkstra's algorithm and here I am you know in the dirty news business.
I love it I love it and I want to ask you Brian do you think of Effort News as nonpartisan I mean media is so tribal today obviously you found probably more things that the left did recently they are the ones in charge you were watching recently. Are you going to look into things the right's doing as well? Like how do you handle this?
Yeah, we publish everything that's fit to print and we published an investigation for example on Freedom Fuel, which was this like Trump connected set of gas stations. I think that we broke a lot more stuff than was previously reported on that, but it just kind of didn't really go anywhere. In general, our philosophy is that there's all this information hiding in plain sight and what might come out of it might just be that like reality has a bias. There was this phrase that became popular around the Vietnam War of there's no such thing as a pro-war war documentary, right? The idea was you show people the footage and everyone or at least like 99% of people are going to be like, Oh, I don't want to be in the Vietnam War anymore. This is not going well for us. And I think it's the same thing where if you actually show people the financials, if you show people the documents that the government mandates itself to publish, actually very very few people would agree with this.
And then there are people who are benefiting from it or there are people who have disproportionately succeeded in the old media system who will complain about this. But I think we are actually shifting into a completely new equilibrium where this kind of transparency will be embraced as just like a fixture of reality. It will no longer it will maybe be considered partisan in the short term, but it will not be considered partisan in the long term.
I love it. Well, somebody who thinks there's massive amounts of waste in defense spending and HHS and so many other areas and so much grift. I love this. And you know, I think we're excited to tell our listeners. We're actually going to break some news with you today. So, let's do it. All right. You know, we're excited to have you here to break your latest story on HI equity incentives. It's called how COVID era financial engineering created the $21 billion racial wealth transfer. Brian, what did you uncover? What is this?
Yeah, this is this fascinating story about how health policy or policy more broadly works because it was this sweeping wave around the era of COVID and BLM that kind of came together, right? It was the medical and it was the racial stuff. And the net output of that is that there are these programs across the country, including in many red states, which was totally surprising to me, that pay providers to reduce the health disparities. And what that means is essentially that the more providers provide disproportionate care to black and Hispanic people and, you know, implicitly less care to white and Asian people, the more they get paid by these incentives. And that's a total of a $21 billion pool across all these state programs, almost all of which are taking federal Medicaid and Medicare dollars. And using them to create these incentives for providers to selectively deny or grant care based on race.
And this is absolutely crazy. So they're focusing on race. I mean, I think we were in a healthy place, I think, 20 or 30 years ago where we were focusing less on race and you treat people based on their character and who they are and you don't focus on their race and they went all the way back the opposite direction so far as to say we're going to give you more money if you treat more people of a certain race and less people of another race is blatantly illegal, isn't it?
Yes. So, under the plain text of the Civil Rights Act, this is illegal. Actually, at the time, this was a debate that came up because there were critics of the Civil Rights Act who thought, well, this could be used preferentially. This could be used against white people especially. And the authors of the bill insisted that actually this applied in every direction. You could totally sue for anti-white discrimination. And in practice, that wasn't enforced for a long time. In 2025, that changed. The DOJ announced a revision to its guidance which included that for basically the first time we would begin they would begin enforcing these judgments and enforcing the letter of the law against or in favor of people who are discriminated against from any race. And in 2025 and 2026, they had settlements in two cases like this or they had reviews in two cases like this where they dealt with a health program in Minnesota and a loan program in Illinois. They opened up a review and forced those programs to remove the racial requirements. So I think something like that could happen here where DOJ civil rights division under Harmeet Dhillon could step in could open a review with all of these programs and could first of all impose these requirements and if those requirements aren't met actually work with the Center for Medicare and Medicaid Services to cut off the federal funding because all these programs are receiving Medicare and Medicaid funding and then using this to create these incentives for what is in effect racial discrimination.
This is great. Well, we're friends with Dr. Oz who runs CMS. We should talk to him about this. I have a question for you on this, Brian, because you've been studying these things. Why does it seem like the left is so much more competent at like setting up these kind of grift schemes than the right? Is it stopping them? Like is it in balance? Is it just my impression being on the right that I see the left doing them more or they actually doing them a lot more?
It was really competent and that's the history that we dive into in this article where these programs even though it seemed like at the time they were all springing up around COVID and BLM and this was this like sudden like big paranoia you know social cascade. In fact, the groundwork and the reports have been laid for more than 10 years. Obamacare created these funding programs for health incentive research which of course they put out these grants. They paid for example the Rand Corporation. They paid a bunch of other NGOs to put out these reports of like oh this is how you should do racial incentive programs. And then those reports then paid the salaries of a bunch of activists who all advocated for those things. And Massachusetts actually brought in an organization of a hundred different of these NGOs to sort of advocate for these programs which eventually passed and became the second largest of these programs next to California in the country.
This is like a massive activist scheme where they planned it for years is what you're saying. And how did you uncover this to write about it when no one else has been talking about this?
We just asked for racial discrimination in Medicare and Medicaid grant tables. So there's a federal Medicare and Medicaid reimbursement centralized database and we had the infrastructure open and we just launch these like big open queries and that's something where I think investigative journalism will completely change because with the total amount of effort that humans can put in even the maximum amount even if you're working 24 hours a day you could not go through the entire table but for us we can have thousands of misses the AIs will pass over the misses and all the hits are manually reviewed but we can have like a thousand misses for every hit and we can exhaustively search the table and this is what we found.
I love it. Let's highlight a few other recent investigations. You recently published an investigation into the United Kingdom's rapidly expanding counterterrorism program but it's not actually going after actual terrorists. What's going on in the UK?
Yeah, this was fascinating. So the thing that we really added is that so we found that of the identifiable motivations of the terrorist attacks where a motive was identified 97% were some form of Islamist terrorism and 3% would be even by the most expansive definition some form of far-right or right-wing terror. But in practice, that enforcement is done completely differently because there are multiple reports now of these programs that were focused on targeting what they would call the extreme right-wing terrorism. And we can actually go into what they would consider extreme right. I think it's very different than what you or I would consider they consider Douglas Murray extreme right.
Douglas Murray, he's like a mainstream figure who's mocking them. So that's what they don't like. Huh.
Yeah. It's funny because now he's seen as like the sort of centrist guy, right? He's now in the conflict of people who are more right. I still don't think, you know, those people are terrorists, but you know now in conflict with people who many people would consider to the right of Douglas in the US.
But he's like honestly like kind of premodern figure. And they're also going after, interestingly, parts of the political canon, including John Locke, Thomas Hobbes, and George Orwell. They literally put 1984 on the list of books that made you a suspect for terrorism.
This is like this parody of themselves that they're saying that if you read 1984, you're a suspect. It's like the ultimate big brother. And by the way, don't read 1984. My first time I ever got a B in a class was at Stanford. And it was I wrote a defense of John Locke and the teacher was so angry that I would defend the man by the way who because the core of the Enlightenment, life, liberty, and property, like a big part of how our civilization works is John Locke. The fact that's considered far I mean she didn't like it either. She was far left. But the fact that's considered officially now tied to the extreme right is crazy.
Yeah. And it is this incredibly disproportionate.
I have to interrupt. I got this prize for a speech I gave like some years ago. This is John Locke in Latin right here. That's good. So I guess by having his picture here, I'm.
Oh, no. You're part of the extreme right terror. Yeah, extreme right.
They're going to send you to the prevent to prevent.
They got to come. They got to come watch me here in Texas. Oh my goodness.
They'll lock you in the gulags with Douglas.
