Trump’s War on Data and Rise of the Pricing Bots

Summary

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Podcast Summary: Everybody's Business

Episode: Trump’s War on Data and Rise of the Pricing Bots
Hosts: Max Chafkin & Stacey Vanek Smith
Date: August 8, 2025

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Brief Overview

This episode explores the increasing politicization of information, from government data to consumer advertising, and examines the often-invisible influence of AI on everyday pricing. Hosts Max Chafkin and Stacey Vanek Smith unpack the political firestorm around government employment data, the Sydney Sweeney "great jeans" ad controversy, and the ways in which AI is quietly reshaping how much we pay for everything from airline tickets to groceries. The show also ends with a lighter, surprising story about how drones and pop culture are being used to scare off wolves from cattle ranches.

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Key Discussion Points & Insights

1. The Politicization of Consumption and Advertising

[02:56 – 08:20]

• Sydney Sweeney x American Eagle Ad:

  • The controversy centers on an ad campaign with actress Sydney Sweeney and its wordplay "great jeans/genes," which was criticized for alleged eugenicist undertones. Some perceive it as a subtle nod to white supremacy (D: 03:53).
  • Quote:

    “In the ad, she’s like, jeans are the thing that give you your skin color and your hair color and even your eyes. And then it says, Sydney Sweeney has great jeans, and she is blonde with blue eyes. And so people are saying this is like a nod to eugenics or white supremacy.”
    — Stacey Vanek Smith [04:03]

  • The reaction was amplified when Donald Trump weighed in, explicitly endorsing the ad after learning Sweeney is a registered Republican.
  • Quote:

    “If Sydney Sweeney is a registered Republican, I think her ad is fantastic.”
    — Max Chafkin, quoting Trump [05:46]

  • Discussion about whether consumers’ politics now influence purchasing decisions, referencing examples like Bud Light, Target, Tesla, and firsthand street interviews in NYC about the ad’s impact on shoppers.

• Consumer Reactions:

  • Shoppers vary in their awareness and level of concern; some are highly sensitive to brand politics, others less so.
  • Quote:

    “As an African American … everything seems small until it’s not anymore. Me personally, I wouldn’t shop here.”
    — Street interviewee [07:20]

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2. Trump’s “War on Data”: Politicizing Government Statistics

[11:04 – 26:54]

• Trump Fires BLS Head:

  • Trump’s firing of the Bureau of Labor Statistics (BLS) commissioner after a lackluster jobs report is viewed as unprecedented and alarming by both the hosts and expert guest.
  • Quote:

    “It’s so unprecedented… A line has been breached that had never been breached before. Presidents have tried to manipulate BLS data, but they’ve always been stopped.”
    — Erica Groshen, Former BLS Commissioner [12:58]

• Why Employment Data Matters:

  • Max and Stacey stress that the integrity of employment and inflation data from the BLS is crucial — informing everything from Social Security payouts to business compensation planning.
  • Quote:

    “Think about Social Security benefits … If the CPI is wrong by a tenth of 1%, the federal government will overpay or underpay recipients by about a billion dollars.”
    — Erica Groshen [24:12]

• How BLS Data Is Collected:

  • Groshen explains the process: surveys from 120,000 employers, feeding data from over 600,000 establishments. Revisions occur because not all data is in by the early deadline; roughly 30-40% must be extrapolated.
  • The BLS’s reliability is under stress due to understaffing, budget cuts, and diminished advisory resources, but Groshen insists the data remains trustworthy — for now.

• International Precedents and Risks:

  • Reference to other countries (Greece, Argentina, China) where manipulated economic statistics led to higher borrowing costs and widespread mistrust.
  • Groshen is optimistic about the near term but warns that repeated breaches may do long-term damage to U.S. data credibility.

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3. AI’s “War on Your Wallet”: Rise of Pricing Bots

[28:09 – 38:37]

• Dynamic Pricing Gets Personal:

  • Max reports on the accelerating use of AI for price discrimination in industries from air travel to housing rentals.
  • Airlines (like Delta) and retailers now use algorithms that can set prices at the highest point they think a particular customer will pay, based on personal behavior and possibly personal data.
  • Quote:

    “They’re all just going to basically make our airline tickets more expensive.”
    — Max Chafkin [29:09]

  • He references internal sales materials from the company Fetcher, which markets “alien superintelligence” tools adapted from high-frequency trading to consumer pricing.

• Potential for Abuse:

  • Nightmare scenarios include AI detecting urgency (funeral, medical emergencies) and spiking prices, or rideshare algorithms depressing pay for desperate drivers.
  • Many companies, including Amazon, already practice dynamic pricing, sometimes with unclear boundaries on the use of personal data.
  • Quote:

    “We are just more predictable than we realize... [They] know what your exact situation is and are able to use that to their advantage.”
    — Max Chafkin [34:25]

• AI Collusion:

  • Discussion of academic research and FTC complaints suggesting AI pricing bots at different companies can collude, raising prices industry-wide even without explicit instruction.
  • Quote:

    “The two algorithms would start colluding with one another to raise prices.”
    — Max Chafkin [36:16]

• How Can Consumers Respond?:

  • Tips include clearing cookies, using different browsers, and shopping around — even when options seem limited.
  • There’s hope that new consumer-side AI tools could help customers outsmart corporate pricing bots in the future.
  • Quote:

    “We’re going to have our own algorithms, I hope, to try to overcome those. Like, we’ll have to act like our own hackers.”
    — Max Chafkin [38:18]

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4. Underreported Story: Drones, Wolves, and AC/DC

[38:59 – End]

• Innovative Rancher Solutions:
  • Stacey’s “favorite story of 2025”: Western ranchers are using heat-seeking drones to detect wolves and then playing loud noises to scare them off.
  • Unexpectedly, AC/DC’s "Thunderstruck" and audio from the film "Marriage Story" (particularly a fight scene between Adam Driver and Scarlett Johansson) are effective at frightening wolves away from cattle herds.
  • Quote:

    “They play that fight scene to scare off wolves. … If you and your significant other are hiking and you see a mountain lion, just start fighting.”
    — Stacey Vanek Smith [41:20, 42:25]

  • The segment closes with hosts joking about what other sounds might scare off predators, including their own podcast.

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Notable Quotes & Memorable Moments

• On Social Trust and Data:

  • “We have crossed a line that’s never been crossed before.”
    — Erica Groshen [22:44]

• On AI Price Gouging:

  • “You could imagine, one of those [fare classes] is, like, desperate bereaved traveler; one is, like, broke Uber driver.”
    — Max Chafkin [35:03]

• On Collusive Algorithms:

  • “The only thing that is stopping companies from doing more of this … is embarrassment.”
    — Max Chafkin [36:38]

• On Scaring Off Wolves:

  • “Wolves are like, it’s time for some self-care. I just, I can’t even eat right now.”
    — Stacey Vanek Smith [42:01]

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Timestamps for Key Segments

• [02:56] — Main theme setup: Advertising, politics, tariffs
• [03:53] — Sydney Sweeney American Eagle ad controversy
• [05:46] — Trump’s endorsement of Sweeney & ad politicization
• [07:00-08:20] — Consumer interviews: are politics influencing buying?
• [11:04] — Transition to the politicization of government data
• [12:58] — Interview with former BLS Commissioner Erica Groshen
• [14:46] — The impact and process of BLS labor/inflation data
• [19:51] — Why BLS revises its initial employment data
• [22:44] — Erosion of trust in official statistics & dangers
• [24:12] — Concrete consequences for bad data: Social Security example
• [28:09] — AI & ‘superintelligence’ in consumer pricing
• [30:36] — Nightmare scenarios of personal pricing algorithms
• [34:24] — AI colluding to fix prices
• [36:32] — Consumer strategies & possible AI “arms race”
• [38:59] — Cattle ranchers’ high-tech battle against wolves (drones, AC/DC, and “Marriage Story”)
• [41:20] — Playing movie fight scenes to scare wolves

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Tone and Style

• The conversation is lively, conversational, and playful, but underpinned by serious economic, political, and ethical concerns.
• Max frequently adopts a cynically humorous or slightly alarmist tech-reporter voice, while Stacey toggles between explanatory journalism and lighthearted banter.

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For Further Listening

Fans are encouraged to email their own stories of AI pricing–or creative predator deterrents–to everybody'[e-mail].

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Transcript

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[A]

Bloomberg Audio Studios podcasts, Radio.

[C]

News this is everybody's business from Bloomberg Business Week. I'm Max Chaffkin.

[D]

And I'm Stacey Vanek Smith. Max, I think the theme of this week is war. We've got the newest iteration in the trade war. Trump's new tariff deadlines this week. India, Switzerland, all this news coming in hot.

[C]

Oh my God. Tariffs.

[D]

Okay.

[C]

We also have the war on government data. We're going to do a deep dive into the unemployment data, the data that's at the center of all these controversies with a former head of the Bureau of Labor statistics.

[D]

And then AI's war on your wallet. You might be asking ChatGPT for tips on like, setting better boundaries with your family. Meanwhile, it is silently mining your data and figuring out how much it can overcharge you for going home to visit your family for the holidays.

[C]

Maybe we'll talk about that. And finally, Stacy, the underrated story of the week, which I actually, I have no idea what it is.

[D]

I know. I'm very excited. I've kept it a secret. Here is what I'm going to tell you. Max, how do you fight off one of the biggest, baddest, deadliest apex predators on the planet? I will give you a hint. Stick around. All will be revealed. Oh, Max, another week, another round of tariff news. This week is no exception. Another big tariff deadline. Lots of negotiations happening. India, Switzerland, it's, it's a lot.

[C]

Yeah. Meanwhile, you have these, like, tech companies. Apple getting out of tariffs. We're Gonna have to come back to this. I don't know, probably as soon as next week, Stacy. But now we wanted to talk about politics, right? The politics of consumption.

[D]

Yes. Because another one of the big stories this week had to do with Sydney Sweeney and the American Eagle ad. Did you see this ad? I don't very world weary right now, Max.

[C]

Yes, I have seen the ad. I have. I've absorbed the discourse somewhat unwillingly, but I guess. Should I summarize it?

[D]

Yeah, summarize it for in case people have been paying attention to more substantive stories.

[C]

Actress of euphoria is in an advertisement created by American Eagle to sell a new line of dungarees. And the. The ads.

[D]

Is that a word for jeans that they used in the 30s or something?

[C]

Okay, so the ads play on jeans. The pants you wear and jeans, the genetic code in your body. The tagline is, Sydney Sweeney has great jeans. This has become controversial, I think mostly because MAGA loves Sydney Sweeney.

[D]

No, it's become controversial because in the ad, she's like, jeans are the thing that give you your skin color and your hair color and even your eyes. And then it says, sydney Sweeney has great jeans, and she is blonde with blue eyes. And so people are saying this is like a nod to eugenics or white supremacy, things like that.

[A]

Genes are passed down from parents to.

[D]

Offspring, often determining traits like hair color, personality, and even eye color.

[E]

My jeans are blue.

[C]

I don't think there are that many people in the world who interpreted it that way. And there are so many people in.

[D]

The world that interpreted.

[C]

That was a huge controversy. Not only that, I don't think they would have if there. If a bunch of mag accounts hadn't kind of stirred this, you know, controversy out of nowhere. For people who are sort of invested in the culture wars, Sydney Sweeney is this symbol of a thing that they feel is under attack. I think they managed to provoke a response from some very, very, very narrow corner of the left. And now all of a sudden, here we are talking about whether or not this ad is like a eugenicist thing or not.

[D]

Have you seen the ad?

[C]

I have seen the very.

[E]

Sarah.

[C]

Several versions of the ad.

[D]

I have actually seen the ad, and it's. It is notable. I was kind of. I. I thought it was maybe overhyped, but there. It's. It's quite. I was surprised when I saw it.

[C]

I'm not saying there isn't an undertone of something here. I just think that we are living in this moment where it is very easy to sort of spin up a Controversy out of essentially nothing. I don't think American Eagle thought that this was going to happen when they created the ad.

[D]

Maybe not. Well. However, Sydney Sweeney, as it turned out, was registered Republican in.

[C]

As I said, MAGA loves her.

[D]

Yes, well, and now Donald Trump has weighed in on the American Eagle ad. Here's what he said.

[C]

If Sydney Sweeney is a registered Republican, I think her ad is fantastic.

[D]

So things are getting very political. Like you said, all these things are very supercharged right now. So I got curious about if politics are weighing into people's buying decisions. There's been some of this with Target and Tesla and other things.

[C]

Bud Light, remember a few years back.

[D]

People are buying or not buying things based on politics. So I wanted to see New York's big shopping capital. There are lots of tourists here right now. It's in August, so a lot of, lot of people shopping. I went to an American Eagle store in soho. They have ad is huge. It's all on this big window. It says Sydney Sweeney has great jeans. She's there, like not much except for jeans and her hair and all these people coming in and out of the store. And so I asked them what they thought about the ad and if politics was informing their shopping. And here's what they said. Do you know about the whole Sydney Sweeney controversy?

[C]

I don't. I try not to look into the politics things.

[D]

What are the things that do factor into your decision when you're thinking about buying something style? I heard about the ad when I walked across the street and saw it in gigantic letters. I was like, I think it's pretty disgusting, honestly. Do, like, politics ever factor into what you're buying? Yes. As an African American whose family has been here for a very long time, it's like everything seems small until it's not anymore. Me personally, I wouldn't shop here. Do politics ever influence what you buy? Yes, I like to buy local. My mom owns a small business owner. So I see how the struggle is when you're competing with these really big companies. Do you ever buy things or not buy things because of the brand's politics? Not at all. I just buy it because I want it. Target used to be my go to store. And then after like the whole like, DEI initiative, I honestly haven't been in Target all year. I feel like the only way big companies see things is through like dollars and cents. And so if their sales goes down, then it's like, okay, that was a bad ad and maybe let's not do it again.

[C]

All right, well, that was, I mean, I feel like clearly this, this thing has broken through. Was anyone like, what are you even talking about here?

[D]

Yes. Several people actually had no idea what I was talking about. It was interesting.

[C]

You know, it's weird. I saw this on Twitter because I'm like terminally addicted to Twitter. It was only after Donald Trump weighed in on the controversy that people in the real world, in my real world anyway, started talking about like I had not had a real life conversation with anybody about this ad until earlier this week and the ad has been around for a couple of weeks.

[D]

So I had.

[C]

Really? Okay.

[D]

Yeah. In my real world.

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[D]

So, Max, it does seem like shopping has gotten political. One thing that in my career covering business and economics for a while that I have always thought of as kind of not political is data.

[C]

I feel like that's wishful thinking, Stacey, but I do see your point. There's something about these numbers, whether it's the stock market, whether it's the prices. Like, the numbers don't lie, the data doesn't lie, the unemployment rate doesn't lie.

[D]

Spin the numbers in some way or another, or say, well, this number means that, or they can argue over that. But like the numbers themselves, I feel like they're sort of like the neutral party in the middle.

[C]

However, turns out that actually you can argue about them. As we learn last week, on Friday, just as our last week show was going live, Donald Trump showed up and said, hold my beer, Stacey Vanek Smith, and went after the Bureau of Labor Statistics, which had just released a kind of meh jobs report.

[D]

He went, yeah, it's pretty disappointing, and had revised down the other job reports. It was not good. He fired the head of the Bureau of Labor Statistics, Erica McIntarfer, and truthed out, tweeted out on social media that the data was rigged.

[C]

Right. And we wanted to talk about this with somebody who actually understood what this data is and how it's collected. Can you even rig it? And also, if Donald Trump succeeds in politicizing this, what does that mean for the US Economy, for businesses, for all of us?

[D]

Yes. We were very lucky to have Erica Groschen. She headed the Bureau of Labor statistics from 2013 to 2017. A different Erica, but also had that top job. She's now an economic advisor at Cornell. Hi, Erica.

[E]

Hello. Glad to be here.

[D]

So what went through your head when you heard this information? What were your thoughts about, first of all, the data getting accused of being corrupt, and then this firing.

[E]

It's so unprecedented that I had a zillion different thoughts, and people have asked me that over and over, and I've told them various of my thoughts. I was shocked and I was sad at the same Point that a line has been breached that had never been breached before. I mean, presidents have tried to manipulate BLS data, but they've always been stopped. The closest case, certainly in modern times of that kind of effect was when President Nixon decided that the bad numbers coming out of the BLS were due to a Jewish cabal and tried to fire the Jewish leadership in the bls. Two of them lost their jobs, although not the commissioner.

[D]

Whoa. So this is not entirely unprecedented in a certain way.

[E]

It's not entirely unprecedented, but the actual firing of the commissioner has never happened before.

[C]

All right, Erica, I wanted to ask why this data at the center of all this sort of political controversy, like why it matters. Correct me if I'm wrong, like you have basically employment statistics and inflation statistics. Those are the main things that come out of the bls. And so some of this is obviously useful to government like the Social Security Administration, I think, uses, you know, the inflation numbers, figure out how much it needs to increase the benefits, but also lots of businesses, like, if you're trying to price a good, this is data that you can use. If you're trying to figure out if you're a software company that, that makes like human resources, softw employment statistics are going to be helpful in figuring out like what your next quarters look like. Can you just talk about what's at stake with this infrastructure if we start messing with it?

[E]

Our country's philosophy all the way down is to push decision making down to the most local levels. Right. Families should make as many decisions as possible for themselves. Businesses should make decisions as much as possible for themselves. So the BLS has a very deep, broad website. The very busiest part of their website is actually the Occupational Outlook Handbook where people who are looking for jobs, people who are advising people who are looking for jobs, can see what wages and employment trends are likely to be for over 300 occupations.

[D]

They're looking to see if, like, what about my profession? Is like, is my profession hiring? Is it firing? Is like, what's what about the healthcare sector?

[C]

Or like I'm trying to, I'm trying to plan compensation costs for my company for the next year. Like, what raise am I going to have to give my employees to keep them from quitting?

[E]

What qualifications should I look for for people in that Occupation? What are 10 year prospects? Where are those jobs geographically? What are adjacent occupations that maybe I might be able to transition to? Things like that? So there's that. When BLS was founded, it was during a time, 1884, there was a lot of industrial unrest because of immigration, trade.

[D]

Nascent unionism, technology changing.

[E]

Technology changing, right. And the policymakers at the time seeing all this unrest, I mean, people were killing each other in the streets over this, said, well, we'd be one step closer to industrial peace if both sides had the benefit of truth that they can trust about the labor market conditions, about pay, and about the cost of living. And so the BLS was founded to provide that information to move negotiators and people in conflict close to resolution faster.

[D]

So I wanted to talk about the actual data in question. It's a couple of surveys. The big one, I think, that people tend to really look at and trust is the current employment statistics. That is where we get the jobs added, if I'm correct. So, you know, they'll say 73,000 jobs added this month. Can you talk about, like, how do you get that information and why the revisions? Like, what is the process of getting this information? Walk us through the data.

[E]

Sure. So this is a survey of employers, right. Every month, 120,000 employers are asked about all of the work units that they have.

[D]

Work units being people?

[E]

No, no, no, not people, but the establishments, the places of work that they have. So that covers about over 600,000 places.

[D]

Of work, like offices and offices.

[E]

That's right. Stores, manufacturing facilities, things like that. So you take these. 120,000 employers have been recruited in advance, and they know they're going to be tapped for the next X number of years to provide this information on a monthly basis. So the biggest companies are sending this stuff electronically. An automatic feed out it goes. Right. The smallest ones may be emailing it, they may be faxing it, they may be calling someone on the phone. There are many modes because our businesses are quite varied. So we're talking all the way from Microsoft and Amazon all the way down to your local dentist, mom and pop store, the, you know the.

[D]

The feed store in the middle of Iowa.

[E]

Right. The car repair shop.

[D]

So basically, you're just getting this information by any means you can. And then are there people at the Bureau of Labor Statistics, like, counting this stuff, tallying it up, like, what happens to this data?

[E]

Frankly, the people aren't doing the adding. The computers are doing the adding. Right. This is feeding into a data collection facility. And the reporting is fairly simple. It's how many people did you have on your payrolls during the pay period? That contains the 12th of the month. Oh, and for that pay period, how much did you pay? All of them. How many hours on average did they work? Then there's some basic Information about the company that's already there, what's your location, what's your industry? And that's pretty much it. And it's more like a form, as I say. There's no opinion in there. Right.

[D]

So why the revisions then?

[E]

They have like a week to get this information in. And some companies, if they're paying monthly, they haven't paid yet for the pay period that contains the 12th of the month. They don't know the answer yet. Or they may be in the midst of changing their IT system or they may be really busy with something else. Hiring people or firing people. Sally may be sick that day, that week. Right. So they can't all get it in on time. Only about 60 to 70% of them actually get it in in time for the first deadline.

[D]

Oh. So like 30 to 40% of the responses are not in on time. They kind of extrapolate them out.

[E]

Right. So the BLS then has divided all of their sample into cells. Industry location, workplace size cells. And if you don't report during that time, then you're missing data and they're going to calculate the average without you.

[D]

Okay.

[E]

And so that implicitly imputes to you the average percentage change of everybody who did report.

[C]

So I guess one thing I'm wondering is, and I think probably what a lot of people are wondering is sort of like, how bad is this going to be? Other countries, there's some examples, I think Greece, Argentina, where they've sort of mucked with economic statistics.

[D]

China and south is a big one.

[C]

Yeah, yeah. And where there have been like real ramifications where like people are paying more and more in interest rates on mortgages or to borrow money than they otherwise would because investors like just don't really know what is going on in the country and demand a risk premium. And the people who pay that risk premium are basically us like Right, right. Regular people who are just trying to like transact in the economy. My understanding, Erica, is that the head of the Bureau of Labor Statistics doesn't actually like. It would be pretty tricky to like get in there and muck with the survey in any given month. Like it's, it's not like just doing this firing is going to instantly change the survey. On the other hand, you could imagine an erosion of trust. You could also imagine a long term scenario where processes are changed and where these statistics.

[D]

Shortcuts.

[C]

Yeah. That are really seen as like sort of gold standard. Everybody trusts them. We trust them more than like the numbers that LinkedIn puts out or something because like private Companies put out numbers as well, but, but I don't think they're seeing as quite as reliable as these numbers. And like, what's at stake right now and what does the future look like over the next few years? Are we in danger of crossing over to a point where basically like our statistics are like Greece's statistics or are we kind of a long way from there?

[E]

Well, we're still a long way from there, but we have crossed a line that's never been crossed before. Right. So in the next month or two, I think there's going to be no change in the reliability of BLS statistics because all of these processes are still in place. The Deputy Commissioner is now the acting Commissioner. His name is Bill Wiatrowski. I appointed him to the job.

[D]

So you feel good about him?

[E]

I feel good about him. He has been acting Commissioner twice already. That said, BLS is down about 20% of its staff. Its leadership is down by almost by a third. Its advisory committees have been eliminated. Its contracts that it relied on have been terminated willy nilly. So they're not on a particularly sustainable path generally because of those policy changes. Also, their funding had been lousy for years and is still problematic. So it has continued to produce gold standard statistics in spite of all of this. But some of those chickens are coming home to roost because of that. But it's not because of manipulation.

[D]

So there's a lot of stuff going on in the government right now. And I think you could make the fair point of like, well, so what if the data's not as trustworthy? Like what is the big deal? Yeah.

[E]

So think about Social Security benefits which are adjusted every year to the cpi.

[D]

The CPI being inflation numbers.

[E]

That's right, the Consumer Price index. If the CPI is wrong by a tenth of 1% of one basis point, the federal government will overpay or underpay recipients by about a billion dollars. Oh, and that's just one example. Right. The Federal Reserve. Now remember that the Federal Reserve follows modern monetary policy and it has this dual mandate of maximum sustainable employment and stable prices. Right. Well, what does it rely on for that? It's BLS data that was originally created to quell industrial peace, but has turned out to be useful for this other really important decision.

[D]

Do you think trust is eroded in the data?

[E]

Well, I think that for the people who are listening to what the President said, it erodes their trust in the data. For people who are not swayed by his opinion, then the fear that his policies will inject politics. It also makes people fear the data and fear that the data is going to be manipulated and the knowledge that there are these real funding and operational issues is problematic. And then there is the actual degradation of data that has happened because of falling survey response rates and the resource issues. So right now that's showing up in BLS in eliminating some of the granularity of the data. So the CPI is still being produced.

[D]

These inflation numbers used.

[E]

Right. And really the standard error on the top line, the national number hasn't changed very much. So that will, you know, that's about as reliable as it was. But the granularities, so the city and the state estimates of inflation, the product estimates of inflation, some of that's just been eliminated entirely. And the margin of error, the ability to say, okay, the big, the headline number went up, but you know, why and how does that impact this group of people or that industry or something like that? That's what we're losing.

[C]

All right, well, we're gonna have to leave it there. Eric, thank you for joining us.

[D]

Yes, thank you so much.

[E]

Oh, it's my pleasure. Glad to be here.

[A]

Every business has an ambition. PayPal open is the platform designed to help you grow into yours with business loans so you can expand and access to hundreds of millions of PayPal customers worldwide. And your customers, customers can pay all the ways they want with PayPal, Venmo, pay later and all major cards so you can focus on scaling up when it's time to get growing. There's one platform for all business PayPal Open grow today at PayPalOpen.com loans subject to approval in available locations. On September 25th, Bloomberg Green returns to New York to bring together leaders from business, finance and government during Climate Week nyc. Join us for a half day of timely insights and high impact networking backed by Bloomberg's global journalism and data expertise. Together we'll explore strategies for future proofing business and communities from the planet's most pressing climate challenges. Supporting sponsor Susano. Learn more at BloombergLive.com Greenny Stacey Vanek.

[C]

Smith, you are the biggest fan of artificial intelligence that I know.

[D]

Use it sometimes.

[C]

Okay, but, but when you think about, when you think about like the advances in this field, like AGI superintelligence, like what, what kind of springs to mind, what is the future that, that this technology evokes for you?

[D]

I mean I think of AI as kind of a, a personal assistant in a way. What are the movie times tonight? Or can you help me write this.

[C]

Email, write this script for, for Bloomberg?

[D]

Write this script? Yes, write me a shopping list Kind of, I don't know, like a helper. That's how I think of it. Like a helper.

[C]

Right? Like some kind of amazing humanoid creation. Maybe one day it'll even be our friends. We've talked about that. There's also, like, people, these futurists, like the, the CEO of OpenAI, Sam Altman, talks about, you know, super intelligence, curing cancer, or solving global warming.

[D]

Mark Zuckerberg saying, it's going to be our main friends.

[C]

Exactly. You're not going to need a romantic partner anymore because you can just hanging.

[D]

On Facebook all day never forgets anniversaries. AI.

[C]

Exactly. But you know what? Here's the thing, Stacey. I actually don't think any of that really reflects where this technology is going. I think what all of these data centers that are going up everywhere around the country, what all of this technology, these, these coders who are being offered hundreds of millions of dollars a year to jump from, like, anthropic to open AI to Facebook, they're all just going to basically make our airline tickets more expensive.

[D]

Explain.

[C]

Okay, so for this week in BusinessWeek, I looked into a sort of controversy around AI pricing. So this is the idea that instead of, you know how like, you go on the website for an airline and you try to buy a plane ticket and one day it costs $150, and the next day you go back and it costs $200, and the day after that it maybe costs $125, the price is always changing. This is called dynamic pricing. But there's this idea in the airline industry that they're going to use AI to make it even better. Last year, during a Delta Airlines investor event, the president of the company said they were going to like, maybe we could raise the price $20. Maybe we could raise it $40, sort of suggesting that essentially what the AI is going to do is look at you and figure out what you, Stacey Vanek Smith, are willing to pay to fly to Idaho to today and get set the price at the exact highest point that they could possibly set it.

[D]

Okay. But this has been, I know this has been going on for a long time in certain iterations with cookies and stuff. I know this because I, my family lives in Idaho, and every time I try to book a ticket to Idaho that I have to go into, I try to, like, incognito mode and all this stuff because they, all the cookies and data they've mined of mine over the years mean that they're serving me up expensive ticket prices. So how is this here's the thing.

[C]

It'S going to get worse because I looked into one of the companies that is working with airlines, this company called Fetcher, and basically found this sales document that they put out. And this is a sales document not aimed at consumers, but aimed at businesses who of course, just want to raise prices, want to raise revenue. And it talks about the idea of applying what they call alien superintelligence to the problem of figuring out how much money they can charge you. And the idea is to take the technologies that were used by high frequency traders, you know, these, these crazy strategies that are too complex to even conceptualize, but to bring that to domains with consumers. So when you're buying an airplane ticket, there's some like, crazy algorithm working behind the scenes that is, is figuring out how much you're going to pay. And I should say this idea of AI pricing is everywhere now. It's not just in airlines and this sense that you have of, of the frustration of buying airline tickets, Stacy, it is going, it's going to be everywhere very soon. And it in fact is everywhere. We've seen landlords using it to figure out rents using AI software. And pretty much every online retailer in the planet has used AI to price to some extent. You know about rideshare fares, I assume, because like Uber, when, you know, depending on, when you, when you do it, that that affects the price. It also affects rideshare wages. So, so how much the driver is going to get paid. And we've, we've seen drivers complain, credibly complain that it's not necessarily the same thing. It's like your surge price may be different than the driver surge price, meatpacking prices. There, there were allegations of AI being used to raise those. So let me just lay out the nightmare scenario which, which you alluded to, which is like you need to fly somewhere for a funeral or for a medical procedure. You cannot delay your trip. And an AI figures that out and, and jacks it up like five times the normal price. Or like you're driving for Uber and you have $0 in your bank account and Uber figures out, oh, like this guy is desperate. Like, I'm just going to pay him $5 for this ride instead of 15, which is what I would have paid. He's going to do it because he's that desperate. That is the scary situation. I think that that is not quite there yet. And in the course of this story and amid the outcry over Delta and the use of AI, the company has come out and said, essentially, we are not Using personal data to, to, to set AI prices. They did not say yet, but I do think that yet is there that like many companies are going to use personal data.

[D]

Well, Amazon does well. Yeah, yeah, very openly.

[C]

Yeah. So and the thing is, the thing about AI is that you don't really know like what data is being used because it's a black box. You're just putting a bunch of information into a large language model and telling a large language model or this model to which the company that works with Delta calls a large market model. But basically the same thing to sort of figure it out. And we've seen with large language models that personal data sometimes leaks into these data sets. They don't mean to put your Social Security number or your phone number into OpenAI. But because OpenAI is crawling something with some personal information, it could find its way in there. So like that is a possibility. The other thing is there are ways to learn about you without actually accessing your bank account or knowing consumer portfolio.

[D]

Or looking at your.

[C]

Or more right. Like, like really complicated behavioral targeting. And I think the truth is that we are just more predictable than we realize and they're able to figure out your own personal interests just by your behavior. I think what we're leading towards is, is these companies are going to have so many. Even if they don't say it's personal data, they're going to be so many different fair classes. Instead of having like 10 different fare classes, there'll be like 300 fair classes. And if you have 300 fair classes, you could imagine one of those is like desperate bereaved traveler. One is like broke Uber driver. You know, like you could get really granular, granular to the point where like it doesn't really matter if they know you, Stacy Vanek Smith, but they know what your exact situation is and are able to use that to their advantage.

[D]

Is that different than like data mining and, and consumer profiles and stuff like that? Is it like it's just a supercharged thing, steroids?

[C]

It's concerning that they could be using these like alien super intelligence to like squeeze a few bucks out of you. But there's also this, this concern over AI collusion. So this is the idea that I have an AI to set prices and one of my competitors has an AI to set prices and the two AIs work together to just raise prices for price fixing. Indeed, yes. And the thing is this has already happened so at least according to a complaint against Amazon. So Amazon tried out this AI according to this FTC complaint which Amazon disputed that would essentially raise prices briefly and then see whether competitors would raise prices in turn, and if they did, keep the prices up, but if not, drop them down. And then this led to a bunch of research by academics. There's a paper by some Carnegie Mellon professors were basically showing how if you had two companies using these AI pricing algorithms, the two algorithms would start colluding with one another to raise prices.

[D]

Is there a way to avoid this, or is this just our. Like, is this just the future we need to prepare for?

[C]

The cynical tech reporter me says this.

[D]

Is the future we need to prepare for. Okay.

[C]

Just because this stuff is basically unregulated right now, the only thing that is stopping companies from doing more of this, essentially, I think, is embarrassment. There was a point where you had a very active FTC under Lina Khan, where a lot of those examples I rattled off, yeah, we know about those because the FTC uncovered them and put them in complaints. Trump has, you know, obviously made clear that he doesn't want to regulate businesses the way they were regulated under the Biden administration. Also, there is this really powerful force within the Trump administration led by all these guys who gave Trump, you know, hundreds of millions of dollars, who donated his inauguration, who basically want to have zero regulation in AI. So I'm not really holding my breath. There are ways that you can kind of protect yourself. And you alluded to some of them, right? You know, clearing your cookies, you know, looking at fares or any kind of price on different web browsers, just like being more cognizant of the ways that your own behavior and how you are purchasing a given item can affect the ultimate price you get. And using that knowledge to basically shop around, even if there's only one airline for one route, like, just try. Try to buy it in a few different ways and see what happens. The last thing, and this is maybe this is the optimistic tech reporter in me, I do think we're going to see companies that attempt to apply these same algorithms on our own behalf. So, like, there's an alien intelligence working for Delta to try, or any airline to try to maximize revenue. We're going to have our own algorithms. I hope to try to overcome those. Like, we'll be. We'll have to act like our own.

[D]

Hackers, finders and stuff like online coupons.

[C]

Kayak already does this, but I'm confident that as this stuff becomes bigger, there will be incentives for basically middlemen to come along and try to help make our prices lower. So I guess what I'm saying is that Silicon Valley will save us this time.

[D]

Save us from it.

[C]

From it. Yeah. All right, Stacy, I know you've got a really important story to share with me. That story that has not gotten enough attention from the lamestream media and I'm ready to hear it.

[D]

This is my favorite story of 2025. So I don't know how much you know about cattle ranching.

[C]

I know there are cows and cowboys.

[D]

There's a big problem on cattle ranches in the west, which is wolves. So wolves got reintroduced. They were in danger. They were reintroduced into a lot of the American West. The problem is the wolves come onto cattle ranches and it's like a buffet. It's like a golden corral. Literally. It is like they walk into a buffet and they are like picking off these cows. And the ranchers, because the wolves are endangered, cannot kill the wolves.

[C]

This has got to be a big issue where you're from.

[D]

It is, yeah. My parents had a cattle ranch. They didn't have wolves. But this is a. I mean, if.

[C]

The wolves came, they wouldn't be like, look at these majestic beasts.

[D]

Yes, they would be. It's so wonderful to see them.

[C]

They would be afraid.

[D]

Yes. And so this is a big issue and ranchers are trying to figure out it is illegal to kill the wolves, but you have to. But wolves are really smart and they're really strong. How do you keep them away from the cattle? Cows are not fast.

[C]

Okay.

[D]

So they're trying all kinds of interesting things. And one of the things that they are trying to do is they fly drones around, heat seeking drones that can spot wolves. And then they play sounds for the wolves to scare them away.

[C]

Like what kind of sounds? Like a dog whistle type. Like a sound that's so high pitched that human ears can't hear it. But it sends the wolves into a tizzy.

[D]

Yeah. What is going to scare a wolf? Right. These are apex predators. So as it turns out, there are a couple things that they are using to scare the wolves. One, I mean, they use like thunder sounds and gunshot sounds. Also AC dc the song Thunderstruck by.

[C]

Acdc, which is a great song. So I don't know what the wolves are thinking.

[D]

Maybe they're thinking that it's actually an overrated song. But it gets better.

[C]

Do you think it's the name they're like, oh, the song is called Thunderstruck. So.

[D]

Well, it's not just thunderstruck. All acds, they also play a scene from a movie. The movie Marriage Story. This movie with Adam Driver and Scarlett Johansson. Right there Is a scene where they get into a big fight and the.

[C]

Wolves don't like that.

[D]

They play that fight scene to scare off wolves. Here is the clip that they play. Yeah, here's the clip that they play.

[C]

I'm gonna try to connect with my lupine brain.

[D]

People used to tell me that you were too selfish to be a great artist. And I used to defend you. They were absolutely right.

[C]

All your best acting is behind you. You're back to being a hack.

[E]

You gaslighted me.

[D]

You're a villain.

[C]

Oh, you want to present yourself as a victim because it's a good legal strategy, fine. But you and I both know you chose this life. I've never seen the movie marriage story.

[D]

Can you imagine? Like this is what they're you doing to scare off wolves, but wow.

[C]

I just.

[D]

About a couple fighting.

[C]

Yeah.

[D]

And like splitting up.

[C]

You just lost your appetite, right?

[D]

Like toxic relationship.

[C]

I don't really want to go to the golden corral. I just. I just want to go and cry a little bit. Yeah.

[D]

Wolves are like, it's time for some self care. I just, I can't even eat right now. I just lost my appetite.

[C]

Okay. So the heat seeking drones, like fly around. Like there's some software that's like wolf and then it blasts AC DC and.

[D]

From a marriage story.

[C]

Yeah.

[D]

To scare off the wolves. Apparently it's working.

[C]

Yeah. If you and your significant other are hiking together and you see a mountain lion, just start fighting.

[D]

Just fighting. It's time to go into like all the resentment that you have tamped down in the back of your brain and use that.

[C]

Stay safe out there, everybody. And everybody who is listening to this show, first of all, definitely want to know what's going on, what songs you use to scare large predators. But also if you have a pricing story, like we're talking about our own personal experiences around AI and pricing. If you have experienced this in some way or you have thoughts on it, definitely send us an email. Everybody'[e-mail] everybody with an [e-mail] or if.

[D]

You have an idea of what else could scare off the wolves. Maybe, you know, markets, news.

[C]

You know, actually this podcast, this could.

[D]

Be useful to scare off wolves.

[C]

Who's the head of the department of Interior under Trump now? Anyway, if you're listening, just give it a shot.

[D]

Yeah.

[C]

Could send us right to the top of the.

[D]

Could send us to the top. Yeah, we're big with wolves.

[C]

I mean, for now though, we could use your reviews to send us further up in those rankings and also to let other people know about the show.

[D]

Yes, it helps them find the show. You can do that wherever you get your podcasts.

[C]

This show is produced by Stacey Wong. Magnus Hendrickson is our supervising producer. Amy Keen is our editor. We get engineering support from Blake Maples. Dave Purcell Fact Checks Sage Bauman heads Bloomberg Podcast and special thanks to Jeff Muskus, Julia Rubin and Maria Ling. If you have a minute, if you are a wolf or a human, please rate and review this show.

[D]

Or a drone.

[C]

Or a drone. It'll mean a lot to us. And if you have a story that should be our business or email us@everybody's bloomberg.net, that's everybody with an S at the end bloomberg.net thanks for listening. We will see you next week.

[A]

On September 25th, Bloomberg Green returns to New York to bring together leaders from business, finance and government during Climate Week nyc. Join us for a half day of timely insights and high impact networking back to by Bloomberg's global journalism and data expertise. Together we'll explore strategies for future proofing business and communities from the planet's most pressing climate challenges. Supporting sponsor Susano learn [e-mail] greenny.