Episode Transcript

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Morgan Sung, Host:  Hello, Tabbies. We’ve been workshopping games. What do you think of Tab Hive? Could also go with Tab Closers? Maybe Tabdom, like Tab fandom, but I don’t know, that sounds kind of ominous. Anyway, if you’re a Close All Tabs listener and you like our deep dives, then please rate and review the show on Spotify, Apple Podcasts, or wherever you’re listening to this. It would be a huge help to get the word out. Okay, let’s get to the show.

So online, there’s this kind of urban legend when it comes to booking flights. Basically, as the myth goes, if you’ve been looking up flights between certain destinations and you’re finally ready to book, you should always clear your cookies or book the flight from an incognito tab so you get a better price. For years, this travel hack was based on anecdotal experience, not actual evidence that airlines were using personal data to determine prices. But we do know that our personal data is kind of up for grabs anyway. We talk about this all the time on the show. It’s not wild to believe that corporations are tracking you and price gouging you based on your specific habits. But if you brought it up on travel forums or comment threads, you might get written off as a tinfoil hat conspiracy theorist. And then in April, JetBlue just tweeted it out.

Lindsay Owens, Guest: This is just a really incredible story, one of those ‘truth is stranger than fiction’ moments.

Morgan Sung: Lindsay Owens is an economic sociologist who runs the affordability think tank Groundwork Collective. She keeps a pretty close eye on this kind of thing.

Lindsay Owens: If you’re feeling it in your wallet, we are studying it.

Morgan Sung: So back in April, a customer took to X, the site formerly known as Twitter…

Lindsay Owens: To kind of complain, vent, gripe about the fact that his flight had increased by more than $200 overnight, and he was just trying to get to a funeral. And he tweeted sort of, JetBlue, what gives here? Why are you doing this? And incredibly, JetBlue’s corporate Twitter account replied.

Morgan Sung: Here’s the real travel hack. If your flight is delayed or canceled or you’re stuck in customer service hotline hell, complain about it on Twitter. There’s a chance that the airline will see it and give you a discount or at worst a snack voucher. At least that’s how they usually respond. But this time JetBlue took a different approach.

Lindsay Owens: They said ‘try clearing your cash and cookies or booking with an incognito window.’ And then they did say, ‘we’re sorry for your loss. ‘

Morgan Sung: In other words, JetBlue’s official corporate social account told the customer that if he didn’t want to be overcharged, he should just trick the company’s booking software into not identifying him.

Lindsay Owens: And this was a pretty stunning thing to see on Twitter. JetBlue’s HQ immediately weighed in and said the tweet was mistaken, that they don’t use personal information to set prices.

Morgan Sung: A spokesperson for the company told multiple news outlets that the airline fares are determined by supply and demand, not by customer data. JetBlue very quickly deleted the response, but it’s the internet, screenshots live on. This exchange went super viral.

Lindsay Owens: It was a real confession of sorts, but it was a window into the ways in which pricing is changing right under our feet.

Morgan Sung: An airline surreptitiously gleaning personal information to maximize how much money they can make off of each individual customer, it’s not out of the realm of possibility. In fact, Lindsay said that just last year, she listened in on a Delta earnings call and the company told investors about this new strategy they were piloting, a partnership with an Israel-based AI company called Fetcherr, which specialized in personalized pricing. Lindsay went on Fetcherr’s website and found a white paper.

Lindsay Owens: Phase two was called ‘the exploitation phase’ —really not hiding the ball with this one. That’s when they’ve learned everything they can about Delta’s competitors, about their customers, and when they start going for broke and they start increasing those prices and getting better revenues for Delta. They were guaranteeing increases in revenue of near 10% in some cases. So we’ve had quite a few of these examples with the airlines now revealing some of their plans, experiments, and things that they’re working on.

Morgan Sung: Lindsay wasn’t the only one paying attention. Journalists did too. News of the earnings call spread. This set off a PR firestorm for the company with Delta’s competitors saying that they’d never do this to their valued customers, and Delta announcing that they didn’t actually plan to go through with it. But this practice is becoming the norm across industries. We’ve gotten used to dynamic pricing: price fluctuating based on supply and demand, like, how concert tickets get more expensive as seats fill up. What we’re talking about today goes further. Economists call it personalized pricing. This idea that companies charge you based on their assessment of how much you’re willing to pay for a good or service. It’s a practice more commonly known as surveillance pricing.

Lindsay Owens: They’re doing anything they can to learn about you, including sometimes spying on you, which is why I do think the term surveillance pricing is so apt and accurate. Companies gather a lot of data about us. Some of it we offer up willingly, our browsing history, we accept the cookies, we agree to let them sell our data, and all of that can be used to set a price for you specifically — ideally, if you’re a company, a price that gets pretty close to the maximum that you’d be willing to pay before you might walk away or start looking elsewhere.

Morgan Sung: Today, we’re diving into surveillance pricing. Where it came from, how it works, and what we’re supposed to do to save ourselves from it. And no, clearing cookies isn’t always the answer. Ready?

This is Close All Tabs. I’m Morgan Sung, tech journalist and your chronically online friend, here to open as many browser tabs as it takes to help you understand how the digital world affects our real lives. Let’s get into it.

Here’s the funny thing. A set price is a fairly new concept compared to the entirety of human history. Let’s talk about it. Kicking this off as always, let’s open a new tab: History of the price tag.

[Audio from Jessie J singing “Price Tag” live]
Ain’t about the, uh, cha-chang-cha-chung
Ain’t bout the, b-bling-b-bling
Wanna make the world dance
Forget about the beep beep beep boop boop boop

Morgan Sung:  …price tag. To quote the iconic Jessie J, we need to take it back in time. We don’t even have to go that far back. The price tag dates back to 1861, when Wanamakers opened its stores in Philadelphia. It was one of the first American department stores, and also invented the.

[Audio from Jessie J singing “Price Tag” live]
Priiiiiiiiiicetaaaaaagggg!

Morgan Sung: The price tag.

Lindsay Owens: Prior to Wanamaker, you really had thousands of years where we haggled. You went to the market, you picked out what you wanted, and then you started a process of bartering or haggling to set the price. The merchant at the souk or the market maybe sized you up a little and said, oh, you look like someone who could pay more. Maybe he knows a little bit about you, knows you’re wealthy, charges you more. Maybe you know a little bit about him, you have a little dirt on him, he charges you less, right? Those were the kind of rules of the bizarre economy.

That started to shift in the U.S. context really with the Quakers and they felt like bartering and haggling was really unfair. They felt a sort of moral conviction about this; you and I are created equal under God, they thought. Why would we be charged different amounts for the same item? So they instituted a fixed price, and everyone would pay the same amount for items at a Quaker market.

Morgan Sung: John Wanamaker wasn’t a Quaker, but he was a devout Christian, and he had this brilliant idea. What if he took this Quaker concept further? Not just standardized prices, but print them on a little tag attached to each item, and then call it.

[Audio from Jessie J singing “Price Tag” live]
…the priiiiiice taaag!

Lindsay Owens: But of course, Wanamaker wasn’t just doing this for religious reasons, he was also doing it because he was a good businessman and haggling takes a lot of time. The price tag is pretty efficient, right? It makes it pretty easy to tally up what you owe and get on with the purchase. But look, the price tag, I think, did a number of really important things. The first thing it did is it offered transparency. And transparency is really key to fair and honest markets, and that’s really key to a healthy economy. We knew how much something cost. As part of that transparency, we could comparison shop. We could look at how much anything cost in one store, we could look at how much something cost in another store, and we could take the offering that we thought provided the best value. Actually, that mechanism of bargain hunting and comparison shopping is also an important function in a healthy competitive economy.

Morgan Sung: And the price tag also offers some stability and predictability. Of course, things like inflation and seasonal availability and wars that shut down access to major waterways can affect prices. But overall, you’d probably have an idea of how much your weekly groceries will cost.

Lindsay Owens: And predictability is bedrock to home economics, to budgeting in the household. If you don’t know how much something is gonna cost from one week to the next, it is hard to know if you’re gonna clear at the end of the week.

Morgan Sung: Dynamic pricing has gotten out of hand and Lindsay said this wasn’t always the case.

Lindsay Owens: I do think while we have gotten very used to dynamic pricing in a whole host of settings, it is actually the case that in the not too distant past, there were other ways that companies allocated scarce resources. It has really shifted over time and I also think dynamic pricing is increasingly happening in places where resources aren’t scarce at all. You know, you see dynamic pricing in the grocery store, Target isn’t running out of wheat thins. Kroger’s not running out of Barilla pasta, right? This isn’t about managing scarcity. It’s just about charging what they can at any given time. So I think there has been a, kind of, increase in the prevalence of dynamic pricing and the types of goods that are subject to it.

Morgan Sung: When did this use of personal data specifically to set prices become such a common practice?

Lindsay Owens: I think the way to think about the advent of surveillance pricing is to start with the advent of surveillance advertising, which really takes you to the internet. I mean, that’s when this starts getting really creepy, and it’s when it starts to become big business. You may have heard about a company called DoubleClick. They really pioneered and built the infrastructure for surveillance advertising on the internet. They tracked what you looked at online. And then they built an advertising system to serve it back to you. So if you’ve ever looked at an item, you didn’t buy it, and then the next day it started popping up in your feed over and over and again, and you finally relented and purchased the item, that’s just the latest iteration of surveillance advertising.

DoubleClick was eventually purchased by Google, and Google is advertising king in the early digital era. In some ways, the logical next step for many of these companies was as they get better and better at knowing what you want, predicting what you want, maybe persuading you to want something, they might as well also think about getting better and better, figuring out how much you might be willing to pay for it. And so marrying sort of dynamic pricing with surveillance advertising is how we get to the modern form of surveillance pricing that we’re starting to see today.

Morgan Sung: Why does the idea of dynamic pricing and surveillance pricing, why does that upset people so much?

Lindsay Owens: By and large, Americans hate the idea of companies charging different amounts to different people for the same item at the exact same time from the exact same store. I think the answer is really simple. I think when you see sort of a ubiquitous response to something in culture, it’s because you’ve tapped into a core human value. And in this case, I think that value is fairness.

Morgan Sung: So how does surveillance pricing work in practice? That’s a new tab, which we’ll open after a quick break. But first, we wanted to remind you that close all tabs depends on listeners like you to keep us going. You can support us by becoming a member at donate.kqed.org slash podcasts. Okay, after the break, big data and your wallet. Stick around.

We’re back! So how does surveillance pricing work exactly? Time for a new tab: Big Data and Your Wallet. Let’s talk about some examples of surveillance pricing and how mass data collection determines those prices.

Lindsay Owens: So this one was uncovered in an analysis by ProPublica, which showed that the prices for online SAT tutoring packages at the Princeton Review, the test prep company, were varying quite substantially depending on where customers lived. So if you went online to book an online test prep package and you typed in your zip code, Some people were offered the course for $6,600. That’s, by the way, a good price, apparently, for a test prep package in 2015. I’m sure it’s more today, it’s a little staggering. But for others, the same package would be almost $2,000 more. And what they determined is that folks in zip codes with a larger percentage of Asian Americans were almost twice as likely to be offered that higher price than others.

Morgan Sung: They called this the “tiger mom tax.” Yeah, and even in lower income neighborhoods, Asian Americans were quoted the highest prices by the Princeton Review.

Lindsay Owens: I think it is a good example of how companies were using zip codes and demographic information to try to estimate the likely willingness to pay for a service like test prep. We have seen similarly during that period, a study from the Wall Street Journal in 2012, which showed that the online office retailer Staples was varying prices by zip code. This one was actually a little more nefarious in some respects. If you lived in a zip code where there were other office stores nearby, like an Office Depot, you were getting better pricing. If there was not an OfficeMax or an Office Depot within 20 miles or so, you were charged more because they knew you didn’t really have any ability to go to a competitor or go anywhere else. You were probably gonna go with the Staples offering. So those are some of the early examples of companies starting to toy around with gaging your desperation, gaging your willingness to pay. Gaging how likely your exit options were, how much choice you have in a market, and then using that to put you over a barrel and charge you as much as they possibly can.

Morgan Sung: You know, it’s so funny that you say that because my friends and I joke that with Pride right around the corner, Target is probably jacking up prices for plain white tank tops for queer people because they know we’ll probably buy them for all the lesbian events in June. And obviously, that’s purely speculative and it’s mostly us kind of joking among ourselves like, ‘oh, this $5 tank top is going to be $12 next week.’ But it seems like this theory isn’t that far-fetched after all.

Lindsay Owens: It is not far-fetched at all. That is exactly the kind of thing to expect. When Walmart announced that they were installing electronic shelf labels in every Walmart store throughout the country. The first thing that many consumers thought is they are going to start jacking up the of coke and ice cream and cool items on a hot summer day. When there’s a snowstorm, they are gonna charge more for soup. These are all the things that are possible when you have the ability to do dynamic pricing at scale, either online or in brick and mortar stores, which you can do with electronic shelf labels. Pricing algorithms can be controlled remotely. It is very easy to have them respond to things like the weather and other data inputs. And it starts to present, I think, a real sort of dystopian view of what shopping could look like in the future.

Morgan Sung: So what are some of the pieces of personal information that could be used to set the price that you pay, which people probably aren’t thinking about?

Lindsay Owens: It is a long list. So you give up a lot of your information in a lot settings. Those terms and conditions when you get on a website that you click on without reading, often what you’ve done is just sort of pulled back the curtain and let the company ransack all of your data. Loyalty programs can be great, but often are sophisticated data harvesting operations. Okay, kinds of things they might know: they might be connected to your bank account and know when it’s payday. They might have information about your location. They might your purchase history, what you buy weekly, what you haven’t bought in a while that you usually buy and so you’re due for. They track your movements online, your mouse movements, what you hover over, how long you hover it, what you click on, what you put in your cart and don’t buy.

Morgan Sung: Lindsay pointed to this report from former Washington Post tech columnist, Geoffrey Fowler. He requested his data from Starbucks and got a detailed dossier of everything he ever bought there.

Lindsay Owens: He was a reporter, so he had purchased a lot of coffee.

[Geoffrey Fowler in Washington Post story]
The more coffee I ordered, the fewer discounts I got. Sure, I was still collecting stars, but the average price I paid per cup of coffee was going up. My loyalty was working against me.

Lindsay Owens: You know, in this case, they are collecting all the information about your caffeine habits. When you have your morning cup of copy, when you have you afternoon cup of cofee, if you have a sweet tooth and like to have a cookie with your afternoon coffee, right? All of those things they can collect. They can buy information about you from third parties. So, you know, this breadcrumb trail of data you leave when you participate in e-commerce provides a really robust set of data that companies can use to predict how much you’re willing to pay for any given item.

Morgan Sung: More and more consumers are using chatbots and AI agents to do the price comparisons for them. You know, kind of taking off the drudge work of like sifting through all these websites. Are AI agents shopping for you, the new haggling?

Lindsay Owens: Shopping and e-commerce and chat bots combined is really scary for folks who worry about privacy and for the potential for surveillance pricing at scale. We may be just in the first inning of our journey through the big bad world of surveillance pricing. A lot of the data that companies collect about you is behavioral and a lot of it is inferences. We think you must like this because you hovered over it for a while. So they’re guessing and using those guesses to decide what to advertise to you and how much to charge you.

But now with conversational LLMs, often the guesswork can be eliminated because you might just tell them, right? You might say to your chat bot, hey, I have a wedding on Friday. I’m totally screwed. I need a dress. What are some options? Show me some options. Well, you’ve really just given away the store. Right? They know you’re desperate, they know you are in a rush, they know you need it now, and they’re gonna charge you top dollar for it. They’re gonna return results that cost you a lot of money. So the types of data that you offer Chopbots is pretty helpful in commerce. And so then the question is, how will the sort of move from AI into commerce make use of that data? And I think there are real questions about what’s likely to transpire.

But we got a very recent hint and it was not great: a couple of researchers, one at Princeton University, one at the University of Washington, tested some LLMs and they put in some different scenarios and tried to measure how the advertising and pricing would work. You know, the results were pretty alarming. All of the current LLM’s, they tested all of them, exhibited risky behaviors, that was the researcher’s word, that favored the company over the user; steering users towards more expensive sponsored products; concealing that the products were sponsored and therefore impacted their recommendations; recommending predatory products like bad loans with high interest rates.

In practice, users were also nudged to spend more. That one we didn’t need a study to confirm, we already have data from Walmart, where the CEO has been quite candid with their investors about the fact that Sparky, the Walmart chat bot, is doing a great job of nudging consumers to spend more. And folks who use Sparky are spending 35% more than folks who don’t, in part because Sparky is bidding up their cart total very effectively.

We also learned in the study that when asked to recommend between two otherwise equivalent products, The vast majority of the models in the study chose the sponsored option more than half the time, despite it being twice as expensive. I think this is really the next big frontier in surveillance pricing. It’s the next place for people like me who research this stuff and who think through and help craft policy solutions to protect consumers from this stuff.

The good news is people aren’t overwhelmingly shopping in AI right now, although, as I mentioned, companies like Walmart are building this into their apps and into their e-commerce offerings. But it would be great to get this one fixed before the horse is out of the barn because the future doesn’t look great.

Morgan Sung: Yikes, right? I mean, how is any of this even allowed? Is there anything we could do to stop it? Okay, let’s open one last tab: Is surveillance pricing even legal? I’ve googled this question many times, and the answer is never satisfying. Long story short, yes, surveillance pricing is legal. At the federal level, the U.S. is not great about comprehensive data privacy laws. And you may be asking, but what about the FTC? The Federal Trade Commission. They’re supposed to protect consumers and promote business competition. Well, under Lina Khan’s leadership, the FTC conducted a preliminary study on AI-driven pricing tools. It was released in January 2025, right before the Trump administration took over. And since then…

Lindsay Owens: I mean, look, the federal government is not really leading the charge right now. We’re seeing much more action in the states.

Morgan Sung: To understand what’s going on there, we need to talk about the flip side of surveillance pricing:  surveillance wages.

Lindsay Owens: Companies learning about you to figure out the maximum you’re willing to pay can use the exact same tools to learn about their workers and figure out the minimum they’re willing to charge in the form of wages. So it’s great news for companies who can deploy both at the same time because they can bring in more revenue from consumers and they can spend less on their workers. The processes and the systems are really similar and we’ve started to see some, oh really I think, concerning examples of this type of algorithmic wage discrimination starting to pop up in a whole host of sectors.

There are some examples of day nurses being subjected to auctions where they bid against each other for a shift. But instead of an auction where the highest bidder wins, whoever will take the minimum to show up for work would win. We have examples of Uber offering different drivers different fares for the same trip, right? So we are starting to see some examples of algorithmic wage discrimination in parallel to these examples of surveillance pricing.

Morgan Sung: So why might this whole practice of algorithmic wage discrimination actually lead to more legal action against these companies that are using surveillance pricing?

Lindsay Owens: To crack down on surveillance pricing, arguably we’re gonna need new laws. We’ve now seen in 40 states and localities just this year in 2026, people cracking down on surveillance pricing, introducing bans in state legislatures to eliminate this practice. Some of those bills also include prohibitions on algorithmic wage discrimination.

Morgan Sung: Just last month, Colorado actually passed a bill that would do both. It bans corporations from using personal data to set individual prices and wages.

Lindsay Owens: But there are some cases in which algorithmic wage discrimination will already be illegal. So we have fair labor laws and we have employment discrimination laws and it is illegal to pay men and women different amounts for the same job. And so where algorithmic discrimination falls afoul of existing employment discrimination and labor laws, there may be opportunities for enforcement agencies to go ahead and crack down on those practices even without updating the law.

Morgan Sung: Do you think that this kind of legislation will be effective in combating surveillance pricing? How does it compare to other policy pushes that you’ve seen?

Lindsay Owens: So far, we have seen a couple of different types of laws. We’ve seen disclosure laws, which would require companies to tell you they’re spying on you in order to overcharge you, which New York put into effect this year. If you are the victim of surveillance pricing in New York, you will know it, because you will see a disclosure that says this price was set by an algorithm using your data. So disclosure laws are interesting. They’re interesting to people like me, because it gives me a nice population of companies to study. They’re interesting to consumers because sometimes you can say, okay, I’d rather not purchase from this company anymore. But, you know, I would prefer that companies not be able to do this.

Morgan Sung: At the beginning of the year, California Attorney General Rob Bonta opened a sweeping investigation into surveillance pricing. California lawmakers have also proposed an outright ban on the practice. A similar bill failed to reach the governor’s desk last year, but this one just cleared a major milestone in the state legislature this month. If it does pass, Lindsay said it could be a really strong law.

Lindsay Owens: I think it would be a game changer for a state as large as California with as many tech companies located in California as there are to pass a bill like this and it would great to see that happen as soon as possible.

Morgan Sung: It seems like we’re finally at a kind of inflection point for surveillance pricing with consumers, especially after the JetBlue tweet, kind of waking up to it and starting to push back. How are retailers responding to the policy pushbacks and also the consumer outrage?

Lindsay Owens: Retailers have to make some tough choices about the costs and benefits of deploying technologies like this. The benefits are clear. You can make a lot of money charging your consumer the absolute maximum they are willing to pay for every item in their cart. There is revenue to be won. But the risk is that when consumers find out about this, they are really, really ticked and you risk boycott and losing some market share. And throughout history, we have seen companies touch the stove when they, you know, went too far.

In the 90s, the CEO of Coke let slip that they were piloting, installing thermometers in Coke vending machines so that they could charge you more for Coke on a hot summer day. That was in 1999, it was before TikTok, but it was viral. It was on the front page of every major newspaper in the country. The Honolulu paper, the Philadelphia paper, the Wall Street Journal, hardly a bastion of consumer sentiment, weighed in on how outrageous that proposal was. Pepsi, of course, seized on the gaff. Coke immediately backtracked, said they wouldn’t be piloting it. They would never do it.

You know, I think the best way, absent the law, to keep companies from pursuing some of the most egregious forms of this practice, the spying on you, the overcharging you, is actually consumer pressure. There are, of course, retailers who use slightly different business models who say, you know, I’m not in the business of charging consumers the maximum they will pay. The canonical example is Costco, who uses a cost plus model. They charge between 14 and 15 percent on top of the wholesale price. It’s cost plus 14 or 15 percent, that’s the margin. They could go higher, they don’t, they pass the savings along. But, you know, generally speaking, companies are moving in the direction of getting more sophisticated with pricing and of taking their pricing to a place that’s much higher tech.

Morgan Sung: I’m sure you are asked this question constantly, but what could the average consumer do to limit surveillance pricing in their lives?

Lindsay Owens: I really do not believe it should be every consumer’s job to bob and weave and try to beat the machine. Shopping against the robot is not a future anybody wants to have, and it should be lawmakers’ job and policymakers’ job to make sure markets are fair and honest because that’s good for everyone. It’s good for our economy, it’s good for society. The second thing I’ll say is I do really believe in the power of consumer boycotts. And I think when you see something, say something. Take to Reddit, take to TikTok, take to Twitter like our friend experiencing the JetBlue price hike did. Those are great ways to sound the alarm and sometimes to get companies’ attention. Consumer boycotts can be effective.

But finally, there are a few things to think about as a modern consumer. It’s probably time to update how you think about comparison shopping. So it used to be that you would look at the same item at two different stores, see which store offered you the better price, go with that one. Now you probably need to comparison shop within stores. Look at the price in the app, look at the place on the website, look at price in the brick and mortar store, compare those three, go with the lower price. You could do some comparison shopping with your spouse, sit on the couch, both of you log in, see if one of you gets a better price. Go with that price. So I think there are some ways to sort of update how you think about comparison shopping. And then of course, all of the standard advice around browsers that offer more robust privacy protections, all of that can be useful as well.

Morgan Sung: Let’s close the loop on the JetBlue saga. They now face a class action. Everyone’s still really mad at them. It’s been weeks and they’re still getting like, comments being like, remember when you said this? Like, we’re not letting that go. How do you think the saga will end for JetBlue?

Lindsay Owens: Uh, hard for me to know what the result of that class action lawsuit will be. And of course, those can take a long time to unwind. So it may be a minute before we get to read the final chapter of that book. But, you know, I do think JetBlue will face some pretty substantial damage in the interim. I think they have lost faith with a lot of consumers when consumers may look elsewhere for their travel. That being said, we’ve got a problem in the airlines, which is they’re not very competitive. We don’t have that many carriers and we actually just lost one of the main competitors to JetBlue— Spirit. So they have a lot of pricing power right now. They have a of dominance as a low cost carrier, but they certainly, I think, have lost the faith of a lot consumers and they may have lost a lot their customers.

Morgan Sung: Never underestimate the power of a rage tweet. That’s it for today’s deep dive, but stick around after the credits for a surveillance pricing fun fact. Actually, it’s less fun and more terrifying, but hey, it’s good trivia. Okay, let’s close all these tabs.

Close All Tabs is a production of KQED Studios and is reported and hosted by me, Morgan Sung. This episode was produced by Chris Egusa, who also composed our theme song and credits music, Production help from Francesca Fenzi. It was edited by Chris Hambrick. The Close All Tabs team also includes producer Maya Cueva and audio engineer, Brendan Willard. Additional music by APM. Audience engagement support from Maha Sanad. Jen Chien is our director of podcasts and Ethan Toven Lindsey is our editor-in-chief.

Some members of the KQED podcast team are represented by the Screen Actors Guild, American Federation of Television and Radio Artists, San Francisco Northern California Local. This episode’s keyboard sounds were submitted by Alex Tran Alex Tran, and recorded on his white Epomaker Hi75 keyboard with Fogruaden red samurai keycaps and gateron milky yellow pro v2 switches.  Thanks for listening.

Lindsay Owens: There was a really interesting study in 2023 that got quite a bit of attention. And it looked at how Uber was charging customers more if their phone battery was sunk. Like, you got to get in that Uber before your phone dies. As someone who is always on low battery mode.

Morgan Sung: I would never remember to charge my phone.

Lindsay Owens: Me neither. It’s like really scary to think about that one.