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SPEAKER_11: Radiolab is supported by Apple Card. Apple Card has a cash-back rewards program unlike other credit cards. You earn unlimited daily cash on every purchase, receive it daily, and can grow it at 4.15% annual percentage yield when you open a savings account. Apply for Apple Card in the Wallet app on iPhone. Apple Card subject to credit approval. Savings is available to Apple Card owners subject to eligibility requirements. Savings accounts provided by Goldman Sachs Bank USA. Member FDIC terms apply. SPEAKER_09: Listener supported. WNYC Studios. This week on The New Yorker Radio Hour, the SPEAKER_14: novelist Jennifer Egan on how we could end the enormous problem of homelessness if we had the will to do it. That's The New Yorker Radio Hour. Listen wherever you get your podcasts. SPEAKER_11: Quick heads up. This episode does contain some profanity, which is not bleeped. SPEAKER_04: Oh, wait, you're listening. Okay. Alright. Okay. Alright. You're listening to Radiolab. SPEAKER_06: Radiolab. From WNYC. I'm Leto Panaser. I'm Lula Miller. This is Radiolab. And should SPEAKER_10: we just start? Yes. Yeah. Okay, so I have a story about a guy. His name's Adam, Adam Payton, grew up in Kansas, lived in New York City for a while after college, eventually came back to Kansas. Cool. And decided he wanted to start his own business. Wasn't sure exactly what. But then he realized, wait a second, maybe I can bring to Kansas the thing I love most about New York, which was an authentic New York slice. Pizza. That was one of the SPEAKER_08: first things I missed. I kept asking myself, why does this not exist here? Why does this not exist here? And I mean, you know, there's there are a couple places in Kansas City, but it's not widespread. And so he's like, I'm gonna start a pizzeria. Okay. It's just SPEAKER_08: called AJ's NY Pizzeria. And Manhattan, Kansas is where I opened my first one. It's actually where I live now. Manhattan, Kansas? Yeah, Manhattan pizza to Manhattan, Kansas. Our SPEAKER_08: motto at the beginning was from the Big Apple to the Little Apple. That's cute. Is it actually SPEAKER_10: called the Little Apple or you made that up? Yes, no, it's called the Little Apple. Amazing. And he loves it. And his customers love it. And he's like serving up great pizza and they are all enjoying it. Yeah. Okay. Okay. So now cut to Yeah, this is about three years ago now. It's Friday night. And he gets a call from a customer saying that the pizza SPEAKER_08: that they got was wrong. They were delivered different pizzas and they ordered. But the SPEAKER_10: thing is, his restaurant doesn't do delivery. It's dine in and take out only he decided not to do delivery for this very reason to preserve the quality of his pizza. So it's SPEAKER_08: a busy Friday night. I'm trying to figure out what's going on. We're slammed. I can't figure out a who they got it delivered from the I don't know how to fix it because I mean, we can't just deliver a pizza. So later that night, I got their number, call them back and then figured out exactly what happened. What he finds out is that this person ordered SPEAKER_10: the pizza through DoorDash. Now, Adam didn't have any deal with DoorDash. He hadn't even heard of them at that point. But he discovered that if you went to the DoorDash app or even just Googled the restaurant, there's our logo, there's our menu, you can order from us. And SPEAKER_10: at the time, DoorDash would call in the order, have someone go get it. No DoorDash jacket, nothing like that. So Adam had no clue. But then the customer would get the wrong pizza and think it was Adam's fault. And when he, you know, saw all the pieces when he put it all together, he was pissed. When you're building a brand, when you're the new restaurant, you're SPEAKER_08: the new pizza restaurant, you want to present your pizza in the best possible way. Did you SPEAKER_10: feel like like it was almost like you're like your pizzas are being hijacked or something? It's something's like it's being stolen. So first, he tries to just get his business off SPEAKER_08: of the app. That was the first thing. And there's no easy way to do that. And when that SPEAKER_10: didn't work, he basically just is like, okay, let me let me order a pizza myself and just see what exactly is happening. Okay. So he goes on to DoorDash to order a specialty pizza. But when he's there, he notices something weird, which is that the pizzas don't make SPEAKER_08: 23.99 and they're charging 15.99. What the customer's paying less than what we're actually charging. So that's really weird, right? So he's like, wait a second, they're charging SPEAKER_10: less $8 less for a pizza. So then he was like, wait a second, are they ripping us off? Are they paying us less? But then he looked in his, you know, his account books, and he was like, no, no, they're not shorting us. They're just paying more than they're charging, which does not make sense. So I didn't understand what was going on at all. And then that's SPEAKER_08: when I was chatting with Ron Jon. And so we'd kind of banter back and forth on Gchat because SPEAKER_09: he's completely confused at first. He starts chatting with his friend Ron Jon. Ron Jon SPEAKER_10: Roy was actually a roommate of Adam's when he was in New York. So I used to work in trading SPEAKER_09: 2002 to 2009. Went to the Financial Times, was working on the business side for a couple of years, went out, started a startup. He's also an expert in all things business. I actually SPEAKER_10: found this story in his newsletter, super fun newsletter about business technology called Margins. So anyway, so Adam reaches out to Ron Jon on Gchat to see if he understood what was going on here. SPEAKER_09: Again, the business model is scrape a bunch of menus, put them on your platform. And Ron Jon was like, they probably just have an algorithm that scrapes menus and prices SPEAKER_10: off the internet. SPEAKER_09: You're not going to invest the time to have someone actually validating every single price there. SPEAKER_10: I bet it just scraped the menu wrong. It was just literally misread. SPEAKER_11: Really a misread thing. But because this company is so enormous, DoorDash, they haven't SPEAKER_10: even noticed. It doesn't even matter. It doesn't even matter to them. It's like not even a rounding error, you know? OK. Wow. Yeah. But whatever the reason for the pricing error, the bigger thing that Ron Jon thought was SPEAKER_10: this is where the arbitrage comes in. SPEAKER_08: All of a sudden I get on a Gchat of the arbitrage, which I didn't even know. I don't even know what arbitrage is. Yeah. Say it again what the definition is. SPEAKER_09: So arbitrage is buying and selling an asset at the exact same time and achieving a profit with no risk. SPEAKER_10: It's a dealer trade that's just instant free money. And finance is kind of this magical goal that people are always aspiring to. SPEAKER_10: So Ron Jon is like, oh, my God, this is like it's like we found this perfect glitch in the matrix. When I saw buy for 16, sell for 24 at the exact same time, it seems like a no brainer, SPEAKER_09: right? SPEAKER_10: So you're like, jump on this. OK. SPEAKER_09: Here's what you do. You order 10 pizzas, pay DoorDash $160, and then DoorDash goes to your restaurant and pays you $240. And then those pizzas you can just take, eat. SPEAKER_10: Eat them, throw them out. Doesn't matter. As long as you keep buying them, you keep making money. Ron Jon came up with that and we just started doing that. You started sending pizzas to his wife, his friends. Then Ron Jon has this kind of he's like, wait a second, wait a second, wait a second. We can't even take this to another level. SPEAKER_09: What if we just have a box with dough? Do we even need a pizza? Because dough at that point is effectively costless. The driver will still hold something. And you know, the driver doesn't really care either way. So his cost now is even going down. SPEAKER_10: Sweet, this is so funny. He's basically just ordering dough balls. And he's like minting money, right? Yeah. Yeah. And then the driver is like, OK, here's what we do now. I sitting here in New York, I'm joking with him. SPEAKER_09: I'm like, fire all your employees. SPEAKER_10: Oh my God. Just basically become a dough ball factory. Wow. Like there's no need to do anything else. SPEAKER_09: Your top line revenue is just going to explode. And then you go to Domino's and say, look at this business. It's incredible. You know, like that is the Silicon Valley way of doing business. SPEAKER_10: I mean, this is basically the game that Dornash is playing. Like so many of these Silicon Valley startups, it doesn't matter if you're actually making anything as long as it looks like you're growing and you're a good investment. So let's just beat them at their own game. I mean, it is easy to like just see Dornash as the bad guy. SPEAKER_11: Yeah. Is that how you see it? SPEAKER_10: Well, to me, it's not it's not a bad guy necessarily. It's just like it like the emperor has no clothes. It's a skyscraper built on, you know, sand basically. Like and it's just it's just it's the the financial logic of it. Like it doesn't make sense and it's unclear whether it'll ever make sense. SPEAKER_11: But aren't they does it truly not make sense? Are they not making like so few of these giant companies like Uber and like so few of them SPEAKER_10: actually make any profit? And according to Ron Jon, like this is how the system is designed to work. SPEAKER_09: That is actually the business model that we're going to lose money per transaction in order to grow our overall usage and get people used to it. That's it. SPEAKER_10: And to hear Ron Jon tell it like even a glitch like the one at Adam's Pizza Place, even that sort of feeds the system. SPEAKER_09: Yeah. Yeah. Like a regional sales manager of the Midwest could go to his boss and be like, look, I am killing it in Kansas right now. We're growing, you know, like 40 percent year over year. And they are going to go back to their investors. They're going to go back to their investors. And it could actually weirdly work out for everyone. SPEAKER_10: But how could like like how could this be so ridiculous? Like all these towering, colossus companies around us are actually all throwing stacks of money out the window, it feels like. But the idea, the unspoken part of the strategy is its monopoly kind of ingrained the customer SPEAKER_09: behavior where everyone is just used to taking an Uber ordering on DoorDash. And then once you own that entire value chain, the customer, the supplier, which would be the restaurant or the Uber driver, you get to set the price. SPEAKER_10: I mean, this way of doing business is everywhere, right? I mean, and it's a relatively recent thing. But now rides, food delivery apps where you get your groceries or whatever you want delivered to your door. Millions of people use these apps every day. Millions of people work for them. But the rules of the road for these businesses and these workers are just all sort of up in the air. So today in Radiolab, we're getting into the gig game. We've got several different stories from different perspectives about what exactly as customers or business owners or drivers we're getting sucked into. And who's really playing who? Well, before we get going, I mean, how does Adam's story end once he found that dough SPEAKER_11: ball vulnerability? Is he just exploiting it and rolling in the dough? SPEAKER_10: Well, no. OK, so Adam is basically like, look, like I'm I don't care about any of that. I mean, Ron Jon loved it. SPEAKER_08: He was all in this. It's like this is soft baked money. And I just kind of like, all right, Ron Jon, calm down. We're not we're not running a major arbitrage out of this little pizza shop. I've got pizza places to run, man. So cool. He jets. I'm not going to send 500 pizzas to my house. SPEAKER_10: He decided he just wanted to actually run his actual business that sends actual pizzas to actual people with actual mouths. You know, even if it wasn't easy money. SPEAKER_11: Go Adam. Resist utter greed. SPEAKER_10: But what he does do is like, so if I had to spend 30 minutes on the phone dealing with SPEAKER_08: an issue with this, then that is when I would say, OK, I'm sending myself 10 boxes. It was kind of a justification. SPEAKER_10: Got it. Every time he gets a call from a customer being like, Doordash screwed up my order. He's like, OK, doing one dough ball delivery. Like just as a kind of as a kind of like he's like make retribution. SPEAKER_11: Yeah. SPEAKER_08: It was one of those kind of if they're going to use strong arm tactics on me, I feel like I should be able to use strong arm tactics on them. SPEAKER_10: Have they fixed it all now or it's still it's still there. So it went away after two months. SPEAKER_08: We found out after the fact that this is a demand test. So what they say is we we put your restaurant on our website. You are ordered X amount of times. This is why you should partner with us. So that's what that's what it was. It was a kind of like they they wanted to prove how good they are before they approach SPEAKER_10: you to actually partner with you. Yeah. We should say Doordash told us that they do not do this anymore. That as of 2020, everyone on the platform is there with consent, including. SPEAKER_08: No, it's what we're we're partnering with them. Adam. Oh, yeah. SPEAKER_11: Wait, really? Yeah. SPEAKER_10: He gave it. I mean, it seems like these days if you're going to run a restaurant, it's almost impossible not to. But when we come back, we'll meet some people from the other side of the app who are pushing back. SPEAKER_11: Lulu here. If you ever heard the classic Radiolab episode sometimes behave so strangely, you know that speech can suddenly leap into music and really how strange and magic sound itself can be. We at Radiolab take sound seriously and use it to make our journalism as impactful as it can be. And we need your help to keep doing it. 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Savings is available to Apple Card owners subject to eligibility requirements. Savings accounts provided by Goldman Sachs Bank USA. Member FDIC terms apply. SPEAKER_17: But her emails became shorthand in 2016 for the media's deep focus on Hillary Clinton's server hygiene at the expense of policy issues. Is history repeating itself? SPEAKER_13: You can almost see an equation again, I would say, led by the times in Biden being old with Donald Trump being under dozens of felony indictments. SPEAKER_17: Listen to On the Media from WNYC. Find On the Media wherever you get your podcasts. SPEAKER_06: I should just start by how I kind of got it. Lulu. Lutiff. Radiolab. SPEAKER_10: Okay, let me take a sip of water. And now a story from producer, Becca Bressler. Okay. SPEAKER_06: I mean, I guess it kind of starts with you, Lutiff, with your pizza story. You were the sort of original DoorDash ambassador at the show. SPEAKER_10: I'm the door to door dash, you might say. And you dashed through it. SPEAKER_06: Yeah. So your story, I think in general, it got me thinking, I've always kind of thought about DoorDash a little bit because I actually use DoorDash quite a bit. And like the fact that all you have to do is pull out your phone and press like three buttons to have food show up at your door is pretty amazing. And on the one hand, it feels kind of like magic. On the other, obviously, this incredible thing happens because there are people on the other side of the app and they're out there busting their asses doing this work. And I, you know, realize I don't actually know anything about what it's like to do that work. But there's actually the street corner near my apartment. Ba ba ba. Okay. Where a bunch of delivery guys hang out. I'm gonna put my headphones on. And so a couple months back, I grabbed a mic and walked over there. Could I ask you a few questions? Yes. Is that okay? To see what they had to say about what it's like to do this job. How long have you been doing pickup orders for DoorDash? SPEAKER_17: Like a year. SPEAKER_06: Like is this your hotspot sort of? You can say like that. SPEAKER_10: So I was standing there talking to this guy, Jewel, and he was just staring down at his SPEAKER_06: phone the whole time. And every 10 seconds or so he would get these pings. SPEAKER_12: Like this one? SPEAKER_06: And when it would ping, it was like this order that popped up on his phone. It had, you know, the restaurant, where it was going, and how much it would pay. Okay, so you're gonna take this one? SPEAKER_10: No, no, I don't accept this order because it's small. SPEAKER_06: And he's like, nah, too small. Probably not gonna be a good tip. Ooh, are you gonna, do you want to take this one? No, no. SPEAKER_01: It's going like too far. Oh, too far. Yeah. SPEAKER_06: And I don't know, I was like standing there and it almost looked like he was using a dating app. Like he was using Tinder and just like going like, no, no, no. And it's his job. Like he's doing his job. But it did feel like he was playing a game. SPEAKER_06: And there were dozens of people just doing the same thing. I see a guy with a green backpack, which I think maybe means Instacart. There was Grubhub. And also it's an Uber Eats bag. And I started, like when you see the scale of it, I just started thinking about this whole system where whenever any of us presses a couple buttons on our phone, there are millions of people all around getting these pings and then doing these calculations on the fly, deciding whether they're going to take it. No, yeah, I do this one. SPEAKER_10: Oh, you'll accept it. SPEAKER_06: How much is it for? It's $9.25. SPEAKER_08: And I just started to wonder what it's like to have this constant pinging in a sense like SPEAKER_06: it be your boss and to really like have to play a game for your job. And as I was talking to drivers and honestly just reading everything that I could find, I came across this story about a guy that answered these questions in a pretty shocking way. SPEAKER_04: I hate driving. I hate driving, period. I did not want to learn how to drive. So his name's Jeffrey Fung and he is a former gig driver. SPEAKER_06: So where should we start this? SPEAKER_04: The year probably, I would say 2012. That would probably be a good point. So 2012, Jeffrey was a student at City College of San Francisco studying philosophy. SPEAKER_06: He didn't have good grades. And so we ended up dropping out. And at that point, I did not have an answer to what's next or what else. SPEAKER_06: He didn't have a job lined up. And so he decided to fly home to visit his parents. SPEAKER_04: I took a trip back to Beijing where my dad, mom and dad was. To regroup and figure out what's next for him. SPEAKER_06: But also while he was out there. I met my now wife there in Beijing. SPEAKER_04: He fell in love. So we decided to get married. SPEAKER_06: So he gets married, comes back to San Francisco. And does he come back? He comes back with his wife? No, he doesn't come back with his wife. So that's the thing. He needs to get a... His wife would need a visa to be able to come over to the United States. And for reasons I don't totally understand, he needed around $50,000 to make that happen. SPEAKER_04: And I was sort of like, shit, I was down to like maybe a few thousand dollars in my name. SPEAKER_06: And he just had no idea what kind of job he should even be looking for. SPEAKER_04: But just on one random morning, I was at one straight corner of the Union Square in San Francisco. And I saw a car with this giant pink mustache. I'm like, huh, what is Susan G. Komen Breast Cancer Foundation up to? This is something new. SPEAKER_06: But he does Google pink mustache. I was like, oh. And he learns about Lyft. SPEAKER_04: It's driving people for money. I was like, well, I know how to drive. And I live in San Francisco for at least over 10 years now. And maybe I could do this to make a little money. SPEAKER_06: Seemed like it could be an easy temporary fix to his money problems. And one of the great things about this job for Jeffrey in particular is that it's super flexible. So if he wants to work like a ton of hours for a few months and then take a couple of weeks off to go visit his wife in China, he can do that. I'm my own boss. SPEAKER_06: So he just downloaded the app, signed up. He doesn't have to do any interviews or anything like that. But this job would end up becoming like a defining part of who he was and sort of take over his life. SPEAKER_06: Do you remember like your first day on the job? SPEAKER_04: I do. I do. I remember I was having cold sweats picking up people because I was very, very messed up on the app. But within a few days, I'm like, okay, I could do this. I could do this. SPEAKER_06: And he started doing it pretty much every day. Like a day job. And so every morning he'd hop in his car, turn on the phone, the app would ping him with a ride. And in the beginning he figured, okay, best way to make money is just accept every ride. Only problem was... SPEAKER_04: Sometimes it really pays really well. Sometimes it doesn't. SPEAKER_06: The UK on any given day was all over the place. Because when a ride shows up on the app, you have 15 seconds to accept it, but it doesn't SPEAKER_06: tell you where the person is going until after you accept it. Like it could take you downtown. It could take you somewhere totally outside the city where there's no other rides for SPEAKER_04: you to have to be had for the next 20 minutes or maybe 30 minutes, even an hour. SPEAKER_06: You also don't know how much money you're going to make until after you drop them off. So each time Jeffrey hits accept, it was like a slot machine, like pulls push up. What do you do with it? Pull a slot? Yeah, you pull. These hidden little like slot machine pulls where you don't know what's going to come out of it until you finish it. SPEAKER_04: You're playing your luck. Right. SPEAKER_06: So after doing this for a while... I was sort of like, shit. SPEAKER_06: He's like, who knows how long this could take to get my wife over here. Oh man. But then his fortune kind of changes when he finds out about this crew. SPEAKER_07: Jeffrey found out that there is a parking lot in San Francisco at a shopping center where Lyft drivers kind of meet up on their, you know, lighter hours of the day or... So this Lawrence Miley, she wrote about Jeffrey for Wired and she says this motley crew of SPEAKER_06: guys... The gym rats, the vapors, the DJs, there were a couple of people who would spin tunes SPEAKER_07: out of the back hatch of their car. And a lot of these guys had been driving since the early days of Lyft. SPEAKER_06: And when Jeffrey showed up and was talking to these guys, they were like, dude, you can't just accept every ride. You got to learn how to play the game. What does that mean? It means a couple of things. One, pay attention to the incentives that the app gives you. So if you know, if you do a certain number of rides, you can get a bonus. Okay. Also, they told him like, you have to go out and get the good rides. So early morning, head to the airport because those are the moneymakers. Pro tip, 2 a.m., go to Club Booty. There's a club called Booty. Yeah, there is. I've been there. It's awesome. But the main thing that people are talking about in this parking lot is... SPEAKER_04: The big magic dollar called the prime time. SPEAKER_06: What's prime time? So if you're a driver and you open up your app, you'll see some part of the city highlighted in pink. And that just basically means a bunch of people are requesting rides over there. And so the Lyft app is just saying like, hello, we need you. A lot of people over here come and grab a ride. And if you do, you could double your money. SPEAKER_04: Boom. 200% prime time. SPEAKER_06: Oh, cool. Yeah. So Jeffrey starts chasing the prime times. SPEAKER_04: So say there's a game. The Giants got the win last night. SPEAKER_06: A baseball game. SPEAKER_04: Giants. SPEAKER_09: Ready to go tonight to try and take a three game for two leads. SPEAKER_04: That's a money making bet. People will be there. SPEAKER_06: Jeffrey would be in the car looking on his phone. He's looking at road closures. And what are the police going to start setting up barricades, like setting up in terms of SPEAKER_04: where we can't get to? Maybe he's got a map at the stadium looking at where the exits are. SPEAKER_04: Where naturally people will congregate trying to score right. And then he'd go check on the game. SPEAKER_06: He's like, all right, okay, seventh inning. SPEAKER_04: Okay, all right, let's start positioning ourselves. Put himself in exactly the right spot. SPEAKER_06: The curve ball puts him away. SPEAKER_17: And the Giants have won it. SPEAKER_06: And then a ride comes in. Tap to accept. Pick up the passenger. Jeffrey. Drop them off. Oh, fuck yeah. If you can double back, you can get another one. Boom. SPEAKER_04: I feel like I just unlocked like the secret vault level where I get the big load of cash. Yeah. SPEAKER_04: The rewards is instant. It makes you feel really good. SPEAKER_06: And he's raking it in. Oh yeah, yeah. Over and over again. Games, concerts. Boom. He started making $1,000 a week. SPEAKER_06: Boom. Then $2,000 a week. Boom. Then $2,500 a week. Boom. That'd be like $130K a year, by the way. Wow. SPEAKER_04: Not to be braggy about it, but there's a bit of a satisfaction in knowing that I am capable of doing something just out of driving and making that money at the end of the day. SPEAKER_06: So Jeffrey's feeling pretty good. He takes a little time off and flies home to China. SPEAKER_04: Chinese New Year, the Christmas of Asia. SPEAKER_06: You know, to spend time with his family, his parents, his wife, and their new baby. SPEAKER_04: Son. SPEAKER_06: And while he was there, he heard from some friends that Lyft was starting to make some changes. SPEAKER_04: They lowered the per mile pay as well as per minute pay. SPEAKER_04: We were all looking at the number like, oh, that's bad. They were dropping a bomb on us and letting basically just say, well, here you go, guys, go fuck yourself. This is Jeffrey on a podcast he did with some driver friends in January 2016. SPEAKER_06: It was just $5 ride after $5 ride. SPEAKER_04: And if I got anything above $5, it involved a trip across the entire city. Essentially, it made it unprofitable to drive people, to drive Lyft at all. I mean, at this point, I'm just looking for my exit strategy from ride share because... SPEAKER_06: A bunch of Jeffrey's driver friends got out of the Lyft game, but Jeffrey decides to keep driving. Even though he's figuring it's unprofitable now? Yeah. Well, he sort of didn't know what else to do, but it was also like a new puzzle. You know, a new game to beat. SPEAKER_04: That's kind of like the drug that kept me in too. SPEAKER_06: It was just like he leveled up. SPEAKER_04: Your brain starts thinking, your pattern of thinking started to become like, okay, you want to go out and grab that money. SPEAKER_11: So how do you do that? Well... SPEAKER_04: For lack of a better word, be kind of a bastard driver. For example, like... SPEAKER_06: He'd accept a ride. And I would go to the pickup spot, tap that arrive. SPEAKER_04: See the destination. If I don't like where I'm going, I just drive off. Leave the passenger hanging. And then go chase a better ride. Exactly. If he can get the passenger to cancel the ride, it doesn't hurt your acceptance rating. Okay, so by this time he's driving with Uber too, and with Uber, there was this hack that SPEAKER_06: he did with the app. SPEAKER_07: If you put your phone into airplane mode and dropped off the network, dropped off the app. Again, Lauren Smiley. You could accept the ride and then it would show to you where that ride was going. And then if it was a bad ride, you could just cancel the ride and then hop back onto the network. And it was like it never happened. SPEAKER_06: Clever. Mm-hmm. And Jeffrey's new set of moves were paying off. Oh yeah. SPEAKER_04: Oh yeah, yeah. It's like, I'm making more money than before. Holy cow. Damn. SPEAKER_06: Yeah, probably not more than his peak back in the day, but he was able to keep making it work even after the fair cuts. And for Jeffrey, it felt like he had beaten the next level of the game. SPEAKER_04: To be able to figure out these hacks, you're a maverick. SPEAKER_06: And there were times that this was all he could think about. Like he would be at dinner with his friends. I will have my app on. He's just constantly looking down on his phone. SPEAKER_04: You would check what's the incentive, what's the bonus, is there a prime time? He'd become obsessed. So they're like, damn it, Jeff, freaking like fucking turn your phones off, dude. Just turn it off. It's like, there's, there are rides, man. Yeah. SPEAKER_06: There are rides. Okay, so we're going to fast forward a bit. It's 2020. Okay. He saved a bunch of money and with a little help from his parents, his family comes over from China, his wife and now one, two more kids. So family of five. The house was not exactly ready. SPEAKER_04: It has sort of a, still had a kind of a bachelor pet kind of thing. But they moved in. They came over and said, I'm always like, what? You lived like this? You're not like me. SPEAKER_06: But anyway, this dream that he's had for years has finally come together. Now it wasn't long after they came over that the pandemic hit. So at this point, nobody's taking rides, but now he's got a family to support. So he hops over to food delivery. SPEAKER_04: You have Uber Eats, you have DoorDash, Postmates, you have Grubhub. SPEAKER_06: Which for Jeffrey felt like a new game. Your criteria for taking order, where am I going to end up? SPEAKER_04: Is there going to be restaurant there? I can take order back. Second, the restaurant, is their food usually ready? Are they on time? SPEAKER_06: He figured this one out pretty quickly. But about a year into the pandemic, something happened that for Jeffrey sort of turned the whole game job, like his whole life upside down. SPEAKER_07: Yep. It was a Saturday in February of 2021. SPEAKER_04: It was a sunny day. SPEAKER_06: Jeffrey's at home with his family in the late afternoon. SPEAKER_07: And his wife wanted to stay home and tutor their eldest son. SPEAKER_04: Online Zoom lesson for schoolwork. SPEAKER_06: So he had to figure out something to do with the other two kids and he checks his phone. SPEAKER_04: That's when I said, you know what? I'm going to go do dinner. Go for the dinner run. SPEAKER_06: So he grabbed the two kids, got them strapped in. Turned on Shrek 2. And turns on his DoorDash app and heads out there. It was a kind of a cold weekend. SPEAKER_07: Good night for takeout. SPEAKER_06: He's doing pretty well. Lots of orders. It's getting pretty late. Dark out. And this order comes in from a pizza place. SPEAKER_04: Tap to accept. SPEAKER_06: He heads over, hops out of the car, grabs the pizza. SPEAKER_04: Hop back in and then I go to the destination. To an apartment building. And I deliver. So he pulled up to the building. SPEAKER_04: Put the car in the driveway of the apartment building. That's my strategy for not getting ticketed or getting honked at. He's going to be super quick. No more than five minutes, right? So I knew super quick I kept the engine running instead of turning the car off. Because in that way, I don't disrupt the DVD playing in the background for the kids. SPEAKER_06: So he goes into the apartment building, drops off the food, comes out. SPEAKER_04: I see a man in my car. He's in the driver's seat. He was sitting in my seat. So I'm like, what the fuck? This guy's trying to jack my car. Shit, my kid's inside. So I ran up to the car, opened my car door. I yelled at him, get out, get the fuck out. Jeffrey grabs the guy's arm and tries to drag him out of the car. SPEAKER_06: We struggled, but man, I couldn't move him. SPEAKER_04: The guy cuts his losses. SPEAKER_07: Jumps out of the car. Over Jeffrey and... SPEAKER_04: Grabbed my phone. SPEAKER_06: He's seeing this guy running off with his phone. His everything. The thing that has ruled his life for the last seven years, the thing that had given him a job, had allowed him to bring his family over and set up this life for himself that he'd wanted for years. And he thinks to himself... SPEAKER_04: He doesn't swim too fast. SPEAKER_06: He checked on his kids in the backseat, made sure they were okay. And... SPEAKER_04: I just ran. I ran after him from my phone. SPEAKER_06: So... There is a getaway car. The guy he's chasing jumps into the car and Jeffrey, he catches up to the car. SPEAKER_07: Grabs the passenger door handle. SPEAKER_04: I held onto it, ran with it for a little bit. Opens the door. And hops into the passenger seat to actually ride shotgun. SPEAKER_07: And he just started screaming at them. SPEAKER_03: Oh yeah. SPEAKER_07: I mean, what do you do when someone's literally in your car screaming at you? SPEAKER_04: They gave me my phone back and they let me out of the car. So now he's about two blocks away from his car and he starts hustling back. SPEAKER_06: I ran and walked, ran and walked, with as much strength as I could muster. SPEAKER_04: I got back. It was gone. The car was gone. They were gone. SPEAKER_11: Oh my God. SPEAKER_04: I scream as loud as I can into the night, say, help. And at the same time dialing that one what. Right away breaking news coming out of San Francisco tonight. SPEAKER_01: An Amber Alert has just been issued for two small children. So the police showed up and a news crew showed up. SPEAKER_06: Beyond absolute nightmare situation out here for that father and his two children who he says... SPEAKER_10: And Jeffrey stood in front of the camera and... SPEAKER_06: I pleaded, I tried to plead it to the car thief. SPEAKER_04: I just want my kids back. I know times are hard if you're going to resort to stealing. That's one thing. But please don't hurt my kids. SPEAKER_03: Let them return safely back to me and my wife. Please. SPEAKER_06: Jeffrey just waited there on that sidewalk in front of that apartment building. Calling everyone. Calling family, calling friends. Looking at his phone, reading alerts. SPEAKER_04: I was there for four and a half hours. SPEAKER_06: Oh my God. And then... SPEAKER_04: It was near 1 a.m. He gets a call from the police. SPEAKER_04: They found them. His car was abandoned in someone's driveway. SPEAKER_06: It was in a random house and his kids were safe in the backseat. When they informed me, it was relief. SPEAKER_04: I would feel relief and finally they were found and at least they're safe. And I can just start dealing with it. I can allow myself to feel from that point forward and deal with the aftermath. By the time I got home, they were sleeping at home. I didn't get home until morning. I was exhausted. SPEAKER_06: What was that next day like for you and your family? How did you talk about it with them? SPEAKER_04: That I prefer not to address. SPEAKER_06: Okay. He did at least tell me about this call he got from a friend. He made me promise him to really take a break from my family. SPEAKER_04: Mm-hmm. Just stop for a while and just recuperate. SPEAKER_06: But later that day, you know, the day after this whole disaster, he opened up his phone and he looked at the DoorDash app. SPEAKER_04: I did. I did because the bonus was super high. I mean... What was it? It was like $4 extra per order. SPEAKER_06: Did you go out there? SPEAKER_04: No, I didn't go. I just, out of habit, I checked. Out of addiction, I checked. I didn't do anything. SPEAKER_11: So after hearing this whole story and talking to Jeffrey about what happened, what does it leave you thinking? Yeah. SPEAKER_06: I mean, I think about Jeffrey pretty much every time I use DoorDash, which I do a lot. I still use DoorDash a lot. And like with Jeffrey, I think about that moment when he checked the app the day after his kids were taken. Yeah. And I see him doing a thing that he's done for seven years, which is picking up his phone and checking an app at any time of day. If he's sitting with friends at dinner or if, you know, it's a Saturday but there's a big event going on. And, you know, one of the benefits of this job is like the flexibility. You get to do this whenever you want. But with Jeffrey, that notion of flexibility is so complicated. I mean, one, he really needs the money, okay? Two, there are all these incentives built into the app that make it really hard to not drive when the company wants you to drive. There's the thrill of it, the gaminess of it that like keeps you going back to that app. So yes, there's flexibility. But when you like look at Jeffrey and you look at all of these factors, for him, and I'm sure plenty of other drivers who really need the money, the fact that you can do it anytime means that you end up doing it all the time. Even when you'd be maybe better off not. SPEAKER_11: Thank you, Becca. Yeah, thanks, Becca. SPEAKER_10: Sure. SPEAKER_06: And big thanks to Lauren Smiley. Her Wired piece on Jeffrey was totally amazing and that's actually where I learned about Jeffrey's story. SPEAKER_10: We'll be back in a second with another look at the Gigaverse. SPEAKER_11: Radiolab is supported by Apple Card. Apple Card has a cashback rewards program unlike other credit cards. You earn unlimited daily cash on every purchase, receive it daily, and can grow it at 4.15 annual percentage yield when you open a savings account. Apply for Apple Card in the Wallet app on iPhone. Apple Card subject to credit approval. Savings is available to Apple Card owners subject to eligibility requirements. Savings accounts provided by Goldman Sachs Bank USA. Member FDIC terms apply. SPEAKER_10: Lulu. Lutthuf. Radiolab. Okay, so we just heard a story about a guy who figured out how to play this gig economy game really well, decoded the rules, found loopholes, exploited them, and how that sort of ran them into the ground. Next up. Oh my God, Barry Lamb. SPEAKER_11: Who's Miller? SPEAKER_10: We have a story from philosophy professor and fellow podcaster Barry Lamb alongside once again producer Becca Bressler. And this one's about a group of people SPEAKER_06: at one of these companies in a moment when the rug, in this case, the rules, was sort of pulled out from under them. Ooh, okay. And it starts, have you ever had someone stick a mic in your face before? With this one guy. I've had a camera in my face, but not a microphone. SPEAKER_19: Named Willie. My name is Willie Solis and I am a gig worker based in Denton, Texas, which is a suburb of Dallas. So what brought you to the gig economy to begin with? SPEAKER_06: Basically what ended up happening was- SPEAKER_19: Willie had a job as a construction worker, SPEAKER_06: but when he was trying to get himself a new roofers license, he found himself without work. SPEAKER_19: I ended up having to figure out a way to make money, make ends meet here, and gate work provided a very low bar of entry for me, and so I decided to enter the gig economy. He first tried shopping with Instacart. But I quickly, probably within the month, gravitated towards Shipt. Hi, we're Shipt. SPEAKER_06: Then moved to this newer app called Shipt. We're a grocery delivery service, SPEAKER_00: but actually with the service part. It's a delivery service owned by Target SPEAKER_06: where customers place an order on the Shipt app and a shopper like Willie will go to the store, grab the items, and deliver them. I'm helping someone with the service that they really need. SPEAKER_17: I think Shipt just delivered our dog food. SPEAKER_06: And what Willie loved about Shipt, compared to Uber, Instacart, Doordash, or any of the other delivery service apps, is that instead of having a complicated algorithm deciding how much he'd get paid, Shipt paid its workers this one simple flat percentage fee. Yeah, at the time it was 7.5% plus $5. SPEAKER_19: 7.5% of the total order cost plus a $5 base fare. SPEAKER_06: So initially I was really happy. SPEAKER_19: I was making roughly between $18 to $25 an hour depending on the day. Like I really enjoyed it and the pay was equally as good. Okay, so this sounds good. This sounds great. SPEAKER_10: Shipt sounds kind of cool. Everybody's happy. Right. SPEAKER_18: But then a few months into using the app, so now we're at January 2020, Willie's scrolling through Facebook and he sees that a bunch of Shipt shoppers are posting on the official Shipt shopper page. They were just kind of rumblings of SPEAKER_19: this pay change isn't good or this pay change has just happened overnight and we weren't expecting it. And those complaints were coming from two cities in particular, SPEAKER_18: Kalamazoo, Michigan and San Antonio, Texas. Shipt shoppers in those cities weren't getting paid that flat fee anymore. In fact, they couldn't tell why they were getting paid what they were getting paid. We were all like, what is going on? SPEAKER_05: Like, why is this paying this and this is paying this? And I mean, there's no rhyme or reason to it anymore. This is a shopper we'll call Heidi SPEAKER_18: because she doesn't want to use her real name. I mean, you could sit there and rack your brain SPEAKER_05: for hours, days, weeks, and you're not going to make sense of it. SPEAKER_18: So Heidi was an insurance agent full time and when she had her third kid, she wanted more flexibility in her life so she started shopping for Shipt. And she loved Shipt for the same reason Willie did. It was simple. SPEAKER_05: It was very transparent. But then it changed. SPEAKER_18: I mean, in my head, I've still got that old pay model SPEAKER_05: and I'm thinking this would have paid X amount of dollars and now it's paying, wait, hold on, let me do the math. Are there days I'm like, how am I going to get milk and dog food and dinner for my family? Yep, absolutely. And so I was really concerned. SPEAKER_19: Is that pay change going to happen here in Dallas as well or is it going to not affect me at all or what's going to happen because it's coming here? So Willie's sitting in Texas trying to figure out SPEAKER_18: if the pay change is going to affect him. But as he talks to more and more people on Facebook. I talked to over 650 people. SPEAKER_19: You're talking to 650 people? Hearing all these stories. She has three children and she didn't know how she was going to be able to feed them. Eventually he's like, SPEAKER_19: Somebody has to do something. Somebody has to speak out. SPEAKER_18: But first he had to figure out what actually changed. Like how much less were people making in this new pay model? So what did you call it? SPEAKER_19: We called it the shipless. We made a Facebook group. SPEAKER_06: Is that a pun? It is. It's a pun. SPEAKER_19: And then I used that Facebook group as a way to communicate with other shoppers that we needed information. We needed data. SPEAKER_18: Asked people in the group to share the data from each of their orders. People were putting screenshots of what the order pay was like SPEAKER_19: and how much they were making. Then he'd take that data SPEAKER_18: I would put it into an Excel spreadsheet on my phone. SPEAKER_19: So that he could use those numbers to compare how much people were paid SPEAKER_18: in the new model, call it V2, versus in the old one, V1. But SPEAKER_19: I was spending very little time working. I was basically consumed by just gathering all the data. SPEAKER_18: Eventually he just got overwhelmed. So SPEAKER_19: That's when I decided to reach out to Dan from MIT. I study the relationship between labor, the labor movement, and data and algorithms. SPEAKER_18: He brings in Dan Colacci, who's a PhD student at MIT's Media Lab and formerly a gig worker himself. I biked around Boston delivering ice cream in the middle of the summer. SPEAKER_16: Someone wanted a single pint of ice cream. And Dan gets right to work. SPEAKER_18: I was looking at the spreadsheet and immediately I was like, SPEAKER_16: oh, we could do this automatically. Automates the data entry process SPEAKER_18: with a handful of code that I could write in an afternoon. SPEAKER_16: Wow, rip the numbers from a photo. SPEAKER_18: That's exactly right. He then makes this chatbot that shoppers can text their screenshots to and that leads to a lot more entries. Now we're talking about thousands and thousands of data points that you can do rather than a few hundred that you have to enter by hand. So after eight months of running the chatbot, Dan and Willy finally had enough data to figure out how was version two paying workers compared to version one. You want to know the results? I'm like, oh my God. SPEAKER_11: Okay. So from about 200 people who had submitted orders, SPEAKER_16: 41% of people were getting paid less under V2 than they were under V1. Okay. SPEAKER_06: So then that means that 59% of people were getting paid more with V2 than V1, yes? SPEAKER_16: Yep. V2 pays out more. Really? SPEAKER_10: That is so surprising. Yeah. SPEAKER_06: And this checks out with what Shipt said in a statement. While some orders may pay more and others pay less in the updated model, we have seen average base pay levels remain consistent overall and slightly higher in some markets. Okay, wait. Huh. SPEAKER_11: But averages can hide nefarious truths. Ding, ding, ding, ding, ding. SPEAKER_18: That's exactly right, Lily. Oh, I was ready to leave. SPEAKER_10: I was ready to be done with the story and I'm like, oh, so great. I'm going to download Shipt. SPEAKER_06: I'm going to start ordering stuff. SPEAKER_11: Stock up on turkey and lotion, pleather, purses, let's go. Overpriced earrings, bring it. Clatter, clatter, clatter. Okay. No caviar. SPEAKER_18: No, no, no. You got it exactly right. The average has hid so much. When you disaggregate and you look at by person how much a person is getting paid for the same work, SPEAKER_16: then you see that there's this whole group of people who are getting paid less. And not just like on average across weeks of shops. It's week to week to week they're getting paid less under this new algorithm. Basically when you look at each individual person, SPEAKER_18: they're typically either consistently making more money or they're consistently making less. And when the new pay model came to Texas where our guy Willie works, SPEAKER_06: are you able to provide for your family right now? Not through the gig economy. I had to actually take on another job. SPEAKER_19: He ended up making a lot less. SPEAKER_06: A regular W2 job. And so I'm basically working between the gig economy and my regular W2 job. SPEAKER_19: Is that W2 job, is it like full time or is it part time? SPEAKER_06: It's full time. So I'm working two full time jobs basically. SPEAKER_19: When do you sleep? So like actually when do you sleep? SPEAKER_06: I have to find time. SPEAKER_06: So meanwhile Dan, he's looking around and he's like, what is going on here? Why are some people consistently making more and others less? SPEAKER_16: We just don't know why. SPEAKER_06: Because of course the algorithm is proprietary. It could be biased based on your location. It could be something about your demographic. SPEAKER_16: It could be that you're just a fast walker or a fast driver. SPEAKER_06: And then one day he stumbled across this blog post from Shipp's engineering team about this new tool that they were developing called a shopping time estimator. It basically used all sorts of data. The square footage of a store, people's walking speed, you know, number of items, SPEAKER_16: how they're distributed physically across the store. To estimate the length of time a specific job should take an average worker. SPEAKER_06: And then he thought, wait a second, what if I calculate the hourly wage each shopper is making? And when he did that, he saw basically the same number popping up over and over. Somewhere south of $15 an hour. SPEAKER_16: I think that the V2 algorithm was attempting to pay people an hourly wage. That's my guess. Wait, that's so weird. Why don't they just pay people $15 an hour then? SPEAKER_10: That's a great question. Like this is such a roundabout way to do that. Right, right. But being roundabout, according to Dan, might actually be an advantage for a company like Shipt. SPEAKER_06: I think companies like Shipt are willing to pay a premium, a kind of premium, SPEAKER_16: in order to reduce transparency so that they have more autonomy. And I think a big reason for that is that it allows you as a company to adjust and change pay completely opaquely. Like they had one change, right? This was the big shift for them from V1 to V2. But now it's V something. It's been two years since we did that campaign. Their algorithm could have changed dramatically in that time. SPEAKER_06: According to Shipt, what the current algorithm is trying to do is make pay based on quote unquote effort, which honestly might result in it being more fair overall, but we still don't know exactly how they calculate effort. And so for an individual worker trying to work harder to make more, there's no way for them to know how to do that. And the rules keep changing. And as soon as you think you've figured it out, they change again. And then you spend a bazillion more hours trying to figure it out, trying to figure out how to play the game, trying to make as much money as you possibly can. And then, oh, look, they change again. And it seems like for most of these gig workers, that that just is the job day in, day out. SPEAKER_11: This episode was reported by Lachif Nasser, Becca Bressler and Barry Lamb, and was produced by Becca Bressler, Sindhu Namasanbandhan and Eli Cohen. Original music and sound design contributed by Becca Bressler and Jeremy Blum, with mixing help from Arianne Wack. SPEAKER_10: Special thanks to Julie Warnow, Drew Ambrogi, David Condos, David Pickerel, Cory Doctorow, and Katherine Mangu-Ward. SPEAKER_11: You can find links to Barry Lamb's podcast, HiFi Nation, from Slate and Ron Jon Roy's newsletter, Margins, on our website, radiolab.org. SPEAKER_10: Thanks for listening. Be careful out there, in the gigaverse. SPEAKER_12: Radiolab was created by Jad Abourad and is edited by Soren Wheeler. Lulu Miller and Lachif Nasser are our co-hosts. Suzy Lechtenberg is our executive producer. Dylan Keith is our director of sound design. Our staff includes Simon Adler, Jeremy Blum, Becca Bressler, Rachel Cusick, W. Harry Fortuna, David Gable, Maria Paz Gutierrez, Sindhu Namasanbandhan, Matt Kielty, Annie McEwen, Alex Neeson, Sara Khare, Ana Raskawit Paz, Sarah Sambak, Arianne Wack, Pat Walters, and Molly Webster. Our fact checkers are Diane Kelly, Emily Krieger, and Natalie Middleton. Hi, I'm Erica Inyampers. Leadership support for Radiolab science programming is provided by the Gordon and Betty Moore Foundation, Science Sandbox, a Simons Foundation initiative, and the John Templeton Foundation. SPEAKER_15: Foundational support for Radiolab was provided by the Alfred P. Sloan Foundation. SPEAKER_00: I'm Krista Tippett of On Being, where we take up the big questions of meaning for this world now. In our new podcast season, we're going to have a different human conversation about AI and also the intelligence of our bodies, grief and joy, social creativity and poetry, and so much more. joy, social creativity and poetry, and so much more. A conversation to live by every Thursday.