Uber Driver Quotes

Uber drivers, summoned by phone, awaited them and drove them to the restaurant. This 'sleight of hand' was Father Jon's idea. Jennifer felt like an actress in a James Bond movie, but she appreciated the subterfuge.

Imagine the uproar when Uber’s cars start arriving without drivers.

They tell you to get a guy friend to walk you home, not realizing that guy friends can rape you. Take a cab! But the cab driver can rape you. Take an uber, but they're even more rapey. Take the metro -- rapists ride free. What if everyone was like me, I wondered, and hunted down their respective Will's? Would the economy collapse?

A 2018 study at MIT found that fully three-quarters of Uber drivers earned less than the minimum hourly wage in the states where they were driving. Almost a third of them lost money in the deal. In effect, they were paying Uber to drive. It was a pretty good deal for Uber. The company’s thirty-nine-year-old founder had a personal net worth of $5 billion.

How you treat: -the mailman -the cashier -the garbage man -the usher -the custodian -the receptionist -the uber driver says A LOT about you.

The Uber driver cranks up the volume knob before waiting for my answer. It’s Ariana Grande’s hit single “Focus on Me.

to make old things work better, to make new things possible, and to do old things in fundamentally new ways. For instance, the invention of the Uber taxi service did all three: it didn’t just create a new competitive taxi fleet; it created a fundamentally new and better way to summon a taxi, to gather data on riders’ needs and desires, to pay for a taxi, and to rate the behavior of the driver and the passenger. These sorts of transformations are now happening in every business, thanks to the energy release of the supernova.

Most people believed, correctly, that most normal North Africans tended to be relatively poor and therefore unlikely to be able to afford a new car, and on the basis of that statistical association their presumption was that the individual North African driver of a nice car was a criminal. Now they assume he is an Uber driver, which is clear progress.

Uber’s drivers are the R&D for Uber’s driverless future. They are spending their labor and capital investments (cars) on their own future unemployment.

she hated the concept of Uber. In her eyes, it was barely a step above hitchhiking. At least taxi drivers had to go through rigorous background checks.

In real life, the value capture process is sometimes deliberately managed by elites to manipulate and control others with game design-like tactics. Gig economy platforms like Uber and Lyft use "badges" and rating systems to manage the decision-making environment of their driver employees. Even outside of work, social media features such as likes, shares, and retweets play the role of points in games. Over time, these simple metrics threaten to distort or take the place of values (say, the wish to meaningfully contribute to discussion or to take pride in the quality of one's work) that might otherwise have inflected our behavior on these platforms.

That memory is commercially valuable. A technologist who neglects history ensures their users will get exploited. Proof? Consider reputation systems. Any scaled marketplace has them. The history of an Uber driver or rider’s on-platform behavior partially predicts their future behavior. Without years of star ratings, without memories of past actions of millions of people, these platforms would be wrecked by fraud. Macrohistory makes money. This is just one example. There are huge short and long-term incentives to record all this data, all this microhistory and macrohistory. And future historians24 will study our digital log to understand what we were like as a civilization.

McCullough points out that early treatment does not just prevent hospitalization; it quickly starves pandemics to death by stopping their spread. “Early treatment reduces the infectivity period from 14 days to about four days,” he explains. “It also allows someone to stay in the home so they don’t contaminate people outside the home. And then it has this remarkable effect in reducing the intensity and duration of symptoms so patients don’t get so short of breath, they don’t get into this panic where they feel they have to break containment and go to the hospital.” McCullough says that those hospital trips are tinder for pandemics, especially since, at that point, the patient is at the height of infectivity, with teeming viral loads. “Every hospitalization in America—and there’s been millions of them—has been a super-spreader event. Sick patients contaminate their loved ones, paramedics, Uber drivers, people in the clinic and offices. It becomes a total mess.” McCullough says that by treating COVID-19 at home, doctors actually can extinguish the pandemic.

You're certainly not dressed like you're running a business." Eyes blazing, she glared. "What's wrong with how I'm dressed?" "An apron and a pink tracksuit with Juicy written across the ass are hardly serious business attire and they certainly don't scream swipe right on desi Tinder." Sam didn't know if there was such a thing as Tinder for people of South Asian descent living abroad, but if it did exist, he and Layla would definitely not have been a match. Layla gave a growl of frustration. "You may be surprised to hear that I don't live my life seeking male approval. I'm just getting over a breakup so I'm a little bit fragile. Last night, I went out with Daisy and drank too much, smoked something I thought was a cigarette, danced on a speaker, and fell onto some loser named Jimbo, whose girlfriend just happened to be an MMA fighter and didn't like to see me sprawled on top of her man. We had a minor physical altercation and I was kicked out of the bar. Then I got dumped on the street by my Uber driver because I threw up in his cab. So today, I just couldn't manage office wear. It's called self-care, and we all need it sometimes. Danny certainly wouldn't mind." "Who's Danny?" The question came out before he could stop it. "Someone who appreciates all I've got going here-" she ran a hand around her generous curves- "and isn't hung up on trivial things like clothes." She tugged off the apron and dropped it on the reception desk. "I'm not hung up on clothes, either," Sam teased. "When I'm with a woman I prefer to have no clothes at all." Her nose wrinkled. "You're disgusting." "Go home, sweetheart." Sam waved a dismissive hand. "Put your feet up. Watch some rom-coms. Eat a few tubs of ice cream. Have a good cry. Some of us have real work to do.

But unlike naïve Marxians, we do not believe that economic interests alone drive change. Change is often affected by the evolution of ideas, and particularly of overarching beliefs.54 Once the Enlightenment notion that “all men are created equal” was accepted (however that idea came to be accepted, whatever the drivers), it was no surprise that it evolved in directions that brought within its ambit women and slaves. Given these beliefs, it would be hard to preserve the slavery system, in spite of the economic interests in preserving slavery—and even though motivated interests may have played a role in the creation and spread of the racial “construct” in the first place.55 The uber-ideology of the Enlightenment—the questioning of authority and the belief in meritocracy, the notion that change is possible and desirable, the respect extended to science and technology—have created preconditions that are favorable to the creation of a learning society and to learning institutions (firms)

The bill, AB2293, addresses the insurance coverage during the period when drivers log in to a smartphone app but have not yet been matched with riders. In a well-publicized incident, an UberX driver struck and killed a young girl in San Francisco on New Year's Eve, reportedly while waiting for a ride request. Bill author Assemblywoman Susan Bonilla, D-Concord, initially wanted the companies to provide $1 million of commercial coverage during this period. In its final form, the bill requires them to provide $200,000 of coverage, on top of insurance either from the companies or drivers providing $50,000 per person, $100,000 per accident, and $30,000 for property damage. An earlier version required $300,000 per accident.

Uber is already one of the most valuable startups in the world, even while giving around 75 percent of the money earned from each ride to the driver. To that end, how valuable would Uber become if in the span of a couple of years, the company was able to replace every single human driver with an AI-powered self-driving car? Or

By contrast, one company that clearly understands the stakes is Uber. In the last several years, few companies have captured the media’s attention like Uber. In my opinion, Uber has been successful because it’s perfectly nailed a Job to Be Done. Yes, Uber can often offer a nice car to take you from point A to point B, but that’s not where it’s built its competitive advantage. The experiences that come with hiring Uber to solve customers’ Jobs to Be Done are better than the existing alternatives. That’s the secret to its success. Everything about the experience of being a customer—including the emotional and social dimensions—has been thought through. Who wants to have to outmaneuver other poor schlubs on the same street corner who are trying to hail a cab? You don’t want to either pay for a car service to wait outside your meeting or be at its mercy when you’re finally ready to call it to come back and get you. With Uber, you simply push a few buttons on your mobile phone and you know that in three minutes or seven minutes a specific driver will arrive to pick you up. Now you can relax and just wait. You don’t have to worry if you have enough cash in your wallet or fear that if you swipe your credit card in that taxi machine, you’ll get a call from your bank wondering if you’ve recently made purchases in some state you’ve never even been to. Calling an Uber has even more potential to ease your anxieties about getting into a cab alone. With Uber there’s a record of your request, you know specifically who is picking you up, and you know from the driver’s ratings that he or she is reliable.

To paraphrase the very quotable Silicon Valley venture capitalist Marc Andreessen, in the future there will be two types of jobs: people who tell computers what to do, and people who are told by computers what to do. Wall Street was merely the first inkling. The next place where this shift would be seen at whopping scale in terms of both money and technology (though I didn’t realize at the time) was in Internet advertising. And after that, it would hit transportation (Uber), hostelry (Airbnb), food delivery (Instacart), and so on. To take the theory further, computation would no longer fill some hard gap in a human workflow process, such as the calculators used by accountants. Humans would fill the hard gaps in a purely computer workflow process, like Uber’s drivers. But we’re getting ahead of ourselves. There’s an additional lesson here. This shift from humans to computers took place predominantly on the equity side of things. The debt side of the financial world, for various reasons, still traded in what amounted to open-outcry markets with humans talking to one another, whether through phones or instant messaging systems. It was capitalism at the speed a tongue can wag or hands can type. This was mostly because a company’s debt is complex and multifarious, and entities like General Motors have hundreds if not thousands of different types of debt floating around the world’s trading floors. Briefly, they are not what economists call “fungible,” meaning interchangeable the way quarter-inch screws or bottle caps are.

Under Grossman’s Regulation 2.0 scheme, government regulatory agencies would operate quite differently from the way they do today. Rather than establishing rules of market access, their primary job would be to establish and enforce requirements for after-the-fact transparency. Grossman imagines a city government responding to the arrival of Uber by passing an ordinance that states: “Anyone offering for-hire vehicle services may opt out of existing regulations as long as they implement mobile dispatch, e-hailing, and e-payments, 360-degree peer-review of drivers and passengers, and provide an open data API for public auditing of system performance with regards to equity, access, performance, and safety.”54

To begin the discussion of the Tipping Point, I’ll start with a prominent strategy, “Invite-Only,” that is often used to suck in a large network through viral growth. Another method to tip over a market is with a “Come for the Tool, Stay for the Network” strategy. Take Dropbox, for instance, which is initially adopted by many people for file backup and keeping files synced up between work and home computers—this is the tool. But eventually, a more advanced and stickier use case emerges to share folders with colleagues—this is the network. And if that doesn’t work, some products can always just spend money to build out their network, with a strategy of just “Paying Up for Launch.” For many networked products that touch transactions like marketplaces, teams can just subsidize demand and spend millions to stimulate activity, whether that’s in paying content creators for your social network, or subsidizing driver earnings in rideshare. If the hard side of the network isn’t yet activated, a team can just fill in their gaps themselves, using the technique of “Flintstoning”—as Reddit did, submitting links and content until eventually adding automation and community features for scale. In the end, all of these strategies require enormous creativity. And to close out the Tipping Point section of the book, I introduce Uber’s core ethos of “Always Be Hustlin’”—describing the creativity and decentralized set of teams, all with its own strategies that were localized to each region. Sometimes adding the fifth or one hundredth network requires creativity, product engagements, and tactical changes. In the goal of reaching the Tipping Point, teams must be fluid to build out a broad network of networks.

The Internet put us on this disintermediating path some time ago, well before the blockchain came along. But it’s worth noting that at the heart of each new Internet application that cuts out some incumbent middleman there has typically been a technology that helps humans deal with their perennial mistrust issues. Who would have thought a decade ago that people would feel comfortable riding in the car of some stranger they’d just discovered on their phones? Well, Uber and Lyft got us over that trust barrier by incorporating a reputation scoring system for both drivers and passengers, one that was only made possible because of the expansion of social networks and communication. Their model showed that if we can resolve our trust issues with technology and give people confidence to transact, those people are willing and able to go into direct exchanges with complete strangers. These ideas are setting us on a path to a peer-to-peer economy.

After all, what’s another word for data storage in a computer? Memory. Memory, as in the sense of human memory, and as in the sense of history. That memory is commercially valuable. A technologist who neglects history ensures their users will get exploited. Proof? Consider reputation systems. Any scaled marketplace has them. The history of an Uber driver or rider’s on-platform behavior partially predicts their future behavior. Without years of star ratings, without memories of past actions of millions of people, these platforms would be wrecked by fraud. Macrohistory makes money.

Uber said it would go out of business if it had to reclassify drivers as employees, pleading unprofitability even as it doled out millions to BLM.

The commission proposed that Uber and its drivers obtain licenses to operate in the city, which would require background checks and regular inspections. Private drivers such as for black cars or limousines would have to charge a minimum of $50 — well above Uber’s $7 base fee. The regulations would also ban the practice used by Uber called “demand response booking,’’ where drivers pick up passengers without knowing their destination in advance. After a huge outcry, the licensing board backed away from its recommendations and said it will hold more meetings before deciding on new rules.

As a result, the motto in Silicon Valley today is: everything that is analog is now being digitized, everything that is being digitized is now being stored, everything that is being stored is now being analyzed by software on these more powerful computing systems, and all the learning is being immediately applied to make old things work better, to make new things possible, and to do old things in fundamentally new ways. For instance, the invention of the Uber taxi service did all three: it didn’t just create a new competitive taxi fleet; it created a fundamentally new and better way to summon a taxi, to gather data on riders’ needs and desires, to pay for a taxi, and to rate the behavior of the driver and the passenger. These

Uber’s algorithm (which it has been refining since 2011) is the company’s greatest asset and most significant innovation, allowing it to find the price that will attract drivers—whom, as independent contractors, it can’t order onto the road—without alienating customers.

Rather than taking supply and demand as a given, the new breed of microeconomist helps nudge the two into line. In the early days of Airbnb, an online market for home rentals, its economists pored over customer data to spot market weaknesses. Costly enhancements, including professional photographs of every listing, are rigorously tested to make sure they work before being rolled out. The company also guides users uncertain about the right rate to charge for a listing. At Uber, a taxi service, prices surge during peak hours, pulling more drivers onto the road. At Poynt, a Silicon Valley startup offering a new type of cashless

The “transaction cost” of using an outsider to fix something (as opposed to keeping that function within your company) is falling. Rather than controlling fixed resources, on-demand companies are middle-men, arranging connections and overseeing quality. They don’t employ full-time lawyers and accountants with guaranteed pay and benefits. Uber drivers get paid only when they work and are responsible for their own pensions and health care. Risks borne by companies are being pushed back on to individuals—and that has consequences for everybody.

The logistics of getting them around were just completely insurmountable,” said Hanson-Press. “I was really stressed every single day about getting them around.” Cue HopSkipDrive, a Los Angeles start-up that has been described as ride-hailing for children. Founded by three Angelenos who are also moms, the service chauffeurs only children ages 7 to 17. In many ways, it's similar to transport network companies such as Uber, Lyft and SideCar (Uber requires customers to be over 18). Drivers are contractors who use their own vehicles to transport passengers. All drivers undergo third-party background checks and vehicle inspections. Parents can book rides for their kids through a mobile app and pay through a cashless transaction. But there are also significant differences. Unlike Uber, whose drivers simply need to have experience behind the wheel, HopSkipDrive drivers are required to have at least five years of experience caring for children (this can mean people who are themselves parents, nannies, teachers, camp counselors, etc.). And like Shuddle, a similar service that operates in the San Francisco Bay Area, all drivers are vetted in person. HopSkipDrive checks drivers' references and will even go for a ride with each driver it signs up. All rides are covered by insurance specific to transporting minors.

A San Francisco couple who said their family was destroyed when an Uber driver struck and killed their daughter urged lawmakers Wednesday to increase auto insurance requirements for ride-sharing companies. Ang Jiang Liu and Huan Hua Kuang of San Francisco spoke at a legislative hearing for AB2293 by Assemblywoman Susan Bonilla, D-Concord, which would require ride-sharing companies to cover drivers with commercial insurance policies from the time they turn on the app to the time it's turned off.

Ofer Sharone, a professor at MIT’s Sloan School of Management, says some of these new services create wonderful opportunities for the underemployed and long-term unemployed. “If you’re looking for a way to survive, they can be helpful.’’ But, he acknowledges, they are “threatening to people who are doing OK with the status quo, like a taxi driver or bed-and-breakfast owner who has invested a lot and suddenly is competing with Uber or Airbnb.

Over the last generation, journalism has slowly been swallowed. The ascendant media companies of our era don’t think of themselves as heirs to a great ink-stained tradition. Some prefer to call themselves technology firms. This redefinition isn’t just a bit of fashionable branding. Silicon Valley has infiltrated the profession, from both within and without. Over the past decade, journalism has come to depend unhealthily on Facebook and Google. The big tech companies supply journalism with an enormous percentage of its audience—and therefore a big chunk of revenue. This gives Silicon Valley influence over the entire profession, and it has made the most of its power. Dependence generates desperation—a mad, shameless chase to gain clicks through Facebook, a relentless effort to game Google’s algorithms. It leads media to ink terrible deals, which look like self-preserving necessities, but really just allow Facebook and Google to hold them even tighter. Media will grant Facebook the right to sell advertising or give Google permission to publish articles directly on its fast-loading server. What makes these deals so terrible is the capriciousness of the tech companies. They like to shift quickly in a radically different direction, which is great for their bottom line, but terrible for all the media companies dependent on the platforms. Facebook will decide that its users prefer video to words, or that its users prefer ideologically pleasing propaganda to hard news. When Facebook shifts direction like this or when Google tweaks its algorithm, they instantly crash Web traffic flowing to media, with all the rippling revenue ramifications that follow. Media know they should flee the grasp of Facebook, but dependence also breeds cowardice. The prisoner lies on the cot dreaming of escape plans that will never hatch. Dependence on the big tech companies is increasingly the plight of the worker and the entrepreneur. Drivers maintain erratic patterns of sleep because of Uber’s shifting whims. Companies that manufacture tchotchkes sold on Amazon watch their businesses collapse when Amazon’s algorithms detect the profitability of their item, leading the giant to manufacture the goods itself at a lower price. The problem isn’t just financial vulnerability. It’s the way in which the tech companies dictate the patterns of work, the way in which their influence can shift the ethos of an entire profession to suit their needs—lowering standards of quality, eroding ethical protections. I saw this up close during my time at the New Republic. I watched how dependence on the tech companies undermined the very integrity of journalism. At the very beginning of that chapter in my career, I never imagined that we would go down that path.

you never knew what lurked beneath the surface of a pretty face. That charming man at the coffee shop who struck up a conversation could be the bullet that got you. Every day, we spun the chamber, went out into the world, and pulled the trigger. A chat with your Uber driver. Ordering lunch in a small café. Picking up dry cleaning. Every interaction bore the potential to be catastrophic. Thankfully, the barrel was usually empty because most people, no matter how seemingly odd, were harmless. If that weren’t the case, we’d all be agoraphobics hiding in our homes. Instead, we greeted new acquaintances with a smile and hope in our hearts—even those of us who’d played the game and lost.

Uber Driving In Los Angeles Is Random And Very Unpredictable. Expect The Unexpected.

Uber drivers, 60 percent of whom have other jobs, have become prime examples for what became known as the “gig economy.” Both Uber and Lyft also rolled out modern versions of carpooling services that match up a rider with another rider in close proximity headed to nearby destinations.

Technology innovation is a key factor in retaining the gains produced by business model innovation. After all, if one technology innovation can create a new market, another technology innovation can render it obsolete, seemingly overnight. While Uber has achieved massive scale, the greatest threat to its future doesn’t come in the form of direct competitors like Didi Chuxing, though these are formidable threats. The greatest threat to Uber’s business is the technology innovation of autonomous vehicles, which could make obsolete one of Uber’s biggest competitive advantages—its carefully cultivated network of drivers—essentially overnight.

A well-organized revolt by the major members of its hard side can kill a product entirely. Twitter once bought an app called Vine for a reported $30 million. It let users create and view six-second looping video clips—it was ahead of its time, and not dissimilar from the insights behind TikTok. Like many social apps, the most popular content creators became very successful, and they were important to attract an audience. Unfortunately, a few years in, more than a dozen of the top content creators organized a revolt: Led by creators Marcus Johns and Piques, the group pitched an idea: If Vine paid each star $1.2 million and changed certain features of the app, each creator would post 12 Vines per month. Otherwise, all 18 would leave the platform. “We were driving billions of views—billions—before we left,” DeStorm Power explained of the monetary request.69 Vine turned down the plan, and a few years later, the service was shuttered. The hard side is worth the effort to cultivate. The most successful and prolific members of this side of the network also provide the highest level of service, are willing to make the investments to scale their impact, and ultimately become the defensible backbone of the network—assuming they can be retained. In Uber’s case, the power drivers represented the top 15 percent of drivers but constituted over 40 percent of our trips. They were also among the safest and most highly rated drivers—after all, it was their primary source of income.

Up-front investment to try to professionalize the supply side early on in a network’s development inevitably comes with risk. In a well-publicized misstep for Uber, the company sought to expand its supply side by financing vehicles to provide cars to potential drivers who didn’t own vehicles, a program called XChange Leasing. The hypothesis was that this should push these drivers into power-driver territory quickly. Payments could be automatically deducted from their Uber earnings, and their driver ratings and trip data could be used to underwrite the loans. XChange Leasing unfortunately lost $525 million and failed to professionalize the driver side of the market. The problem was, it attracted drivers highly motivated by money—usually a positive—but who didn’t have high credit scores for good reason. They often failed to make payments, using their Uber-provided car to drive for competitors and avoid the automatic deductions. They would steal the cars and sell them for, say, half price. They would drive for Lyft instead of Uber, as a way to avoid the automatic payment deductions—they would try to have their cake and eat it, too. Uber needed to organize a massive repossession effort to get the cars back, but it was too late—many had been sold illegally, some finding themselves as far away as Iraq and Afghanistan, GPS devices still attached and running. This is a colorful example of how scaling the supply side, when a lot of capital is involved, can be tricky.

Webmonde provides Uber/Lyft Taxi clone application and website development. Our Clone is outstanding amongst scripts that suit well for the ride-hailing business. Our taxi clone app comes with important features like a user-friendly interface, customized admin panel, and interactive solution for both customer and driver. Please speak with our expert at +91 9990 492 467

Every hospitalization in America—and there’s been millions of them—has been a super-spreader event. Sick patients contaminate their loved ones, paramedics, Uber drivers, people in the clinic and offices. It becomes a total mess.

In today’s era of digital transformation, every organization and every industry are potential partners. Consider the taxi and entertainment industries. Ninety percent of Uber riders wait less than ten minutes for a driver, compared with 37 percent of taxi riders. Netflix costs its viewers $0.21 per hour of entertainment compared with $1.61 per hour with the old Blockbuster video-rental model.

Every hospitalization in America—and there’s been millions of them—has been a super-spreader event. Sick patients contaminate their loved ones, paramedics, Uber drivers, people in the clinic and offices. It becomes a total mess.” McCullough says that by treating COVID-19 at home, doctors actually can extinguish the pandemic. “So

Uber had to get creative to unlock the hard side of their network, the drivers. Initially, Uber’s focus was on black car and limo services, which were licensed and relatively uncontroversial. However, a seismic shift occurred when rival app Sidecar innovated in recruiting unlicensed, normal people as drivers on their platform. This was the “peer-to-peer” model that created millions of new rideshare drivers, and was quickly copied and popularized by Lyft and then Uber. Jahan Khanna, cofounder/chief technology officer of Sidecar, spoke of its origin: It was obvious that letting anyone sign up to be a driver would be a big deal. With more drivers, rides would get cheaper and the wait times would get shorter. This came up in many brainstorms at Sidecar, but the question was always, what was the regulatory framework that allows this to operate? What were the prior examples that weren’t immediately shut down? After doing a ton of research, we came onto a model that had been active for years in San Francisco run by someone named Lynn Breedlove called Homobiles that answered our question.22 It’s a surprising fact, but the earliest version of the rideshare idea came not from an investor-backed startup, but rather from a nonprofit called Homobiles, run by a prominent member of the LGBTQ community in the Bay Area named Lynn Breedlove. The service was aimed at protecting and serving the LGBTQ community while providing them transportation—to conferences, bars and entertainment, and also to get health care—while emphasizing safety and community. Homobiles had built its own niche, and had figured out the basics: Breedlove had recruited, over time, 100 volunteer drivers, who would respond to text messages. Money would be exchanged, but in the form of donations, so that drivers could be compensated for their time. The company had operated for several years, starting in 2010—several years before Uber X—and provided the template for what would become a $100 billion+ gross revenue industry. Sidecar learned from Homobiles, implementing their offering nearly verbatim, albeit in digital form: donations based, where the rider and driver would sit together in the front, like a friend giving you a ride. With that, the rideshare market was kicked off.

Finding the Competitive Levers When there’s a battle between two networks, there are competitive levers that shift users from one into the other—what are they? The best place to focus in the rideshare market was the hard side of the network: drivers. More drivers meant that prices would be lower, attracting valuable high-frequency riders that often comparison shop for fares. Attract more riders, and it more efficiently fills the time of drivers, and vice versa. There was a double benefit to moving drivers from a competitor’s network to yours—it would push their network into surging prices while yours would lower in price. Uber’s competitive levers would combine financial incentives—paying up for more sign-ups, more hours—with product improvements to improve Acquisition, Engagement, and Economic forces. Drawing in more drivers through product improvements is straightforward—the better the experience of picking up riders and routing the car to their destination, the more the app would be used. Building a better product is one of the classic levers in the tech industry, but Uber focused much of its effort on targeted bonuses for drivers. Why bonuses? Because for drivers, that was their primary motivation for using the app, and improving their earnings would make them sticky. But these bonuses weren’t just any bonuses—they were targeted at quickly flipping over the most valuable drivers in the networks of Uber’s rivals, targeting so-called dual apping drivers that were active on multiple networks. They were given large, special bonuses that compelled them to stick to Uber, and every hour they drove was an hour that the other networks couldn’t utilize. There was a sophisticated effort to tag drivers as dual appers. Some of these efforts were just manual—Uber employees who took trips would just ask if the drivers drove for other services, and they could mark them manually in a special UI within the app. There were also behavioral signals when drivers were running two apps—they would often pause their Uber session for a few minutes while they drove for another company, then unpause it. On Android, there were direct APIs that could tell if someone was running Uber and Lyft at the same time. Eventually a large number of these signals were fed into a machine learning model where each driver would receive a score based on how likely they were to be a dual apper. It didn’t have to be perfect, just good enough to aid the targeting.

To make these loops actionable for product teams, you can break them down into more granular steps, and A/B test them. For example, Uber’s viral loop for drivers involved a referral program that was exposed during the onboarding process. There were a dozen or so screens on the app that a driver moved through during the sign-up process—entering their phone number creating a password, uploading their driver’s license, etc. Each of these steps could be optimized so that more users would pass through. Then, drivers would be presented with an explanation on how to refer their friends, and what type of bonus they’d get for doing so. This could be improved as well—should the message offer $100 to sign up, or $300? If you invite five people should you get a bonus? Should an invite mention the name of the inviter, or just focus on Uber, as an app? On the sign-up page, should you ask for a driver’s email or their phone number, or both? A product team can brainstorm hundreds of these ideas and systematically try them, measuring for conversion rates and the number of invites sent. Optimizing each of these steps with A/B tests might only boost each step’s conversion by 5 percent here or 10 percent there, but it’s a compounding effect. Hundreds of A/B tests later, the millions of dollars you might be spending on acquiring customers is made substantially more efficient.

What England didn’t know was that Uber’s general managers, engineers, and security professionals had developed a sophisticated system, perfected over months, designed to help every city strike team—including the one in Portland—identify would-be regulators, surveil them, and secretly prohibit them from ordering and catching Ubers by deploying a line of code in the app. The effect: Uber’s drivers would evade capture as they carried out their duties. Officers like England could not “see” the shady activity, and could never prove it was happening. England

You know nothing about him? What did he used to do? Where did he go to school? Nothing? Nothing about his family? Nothing?” “No. Like, why are you acting like that’s a huge deal? You once fucked our Uber driver. Did you ask about his family history?

If you do not change direction, you will end up where you are heading. ~Lao Tzu

I’m sorry you were catfished by a sixty-year-old Uber driver.

Jenn notes that in California, the number of Chevrolet Bolt vehicles rented by Uber and Lyft drivers skyrocketed under GM’s business model that leases the cars to drivers who save on ownership and fuel costs.

Our drivers, I thought, are almost all immigrants and minorities looking to make more money than they could driving a cab or working another job. Our customers numbered plenty of millennials, but also a lot of working people who lived in the boroughs and used UberX because it was cheaper and more convenient than taking a taxi, and for black and Latino customers (much of de Blasio’s base), the experience of being passed over by an empty taxi once the driver saw the color of their skin had created decades of deep-seated resentment. No one knows the color of your finger when you summon an Uber, so to many New Yorkers, taxis were the bad guys and Uber represented real, positive change. By the time my flight reached cruising altitude, it hit me that the fight to kill de Blasio’s proposal of capping Uber’s growth at 1 percent a year would work a lot better if we ran the campaign from his left. He’d never faced that before. (No one had ever thought they could question his progressive bona fides.)

Of course, cross-side effects are not necessarily symmetrical. On OkCupid, women attract men more than men attract women. On Uber, a single driver is more critical to growth than a single rider. On Android, a single developer’s app attracts users more than a single user attracts developer apps. On Twitter, the vast majority of people read, while a minority tweet. On question-and-answer networks like Quora, the vast majority asks questions, while a minority answers them.15

Nobody wants to work as an adventurer. There are no benefits and only drawbacks. It’s like working as an Uber Eats driver.

As I sat there on the tarmac waiting for takeoff, I thought hard about the man standing between us and Uber’s future. Bill de Blasio became mayor of New York City in 2013 by portraying himself as a champion of the left, as the antagonist of income inequality, as the hero of people of color. He structured every fight, every policy, every issue as “de Blasio, champion of the oppressed versus big, bad corporation.” The politics worked well for him, since it forced virtually every union, newspaper, pundit, political influencer, and everyone else in the system to take his side or risk being thrown out of the progressive mafia. His play was clearly going to be “de Blasio defending poor taxi drivers against the big, bad, multibillion-dollar Uber.” And that play had a very good chance of success. We had to come up with a different story.

This is the key to its advantage over traditional business models when it comes to data, since a platform positions itself (1) between users, and (2) as the ground upon which their activities occur, which thus gives it privileged access to record them. Google, as the platform for searching, draws on vast amounts of search activity (which express the fluctuating desires of individuals). Uber, as the platform for taxis, draws on traffic data and the activities of drivers and riders. Facebook, as the platform for social networking, brings in a variety of intimate social interactions that can then be recorded.

Everything is impossible; until its not! ~ J.L. Picard

Metromile, which offers per-mile insurance. The company gives drivers a device that plugs into their cars to track how far they drive. The more they drive, the more they pay. Even better, Metromile can track the driving and match up trips with Uber rides, so the insurance company can see which of miles are personal miles and which are commercial. Metromile charges users only for the personal miles, since Uber covers the car when drivers are with or en route to passengers. “The existing model for insurance hasn’t been able to adapt [to Uber],” Metromile CEO Dan Preston said.3 “We have a technology that drives the insurance product.” More mainstream insurance companies, such as Geico and Progressive, have followed Metromile’s lead by offering ride-share insurance that caters to Uber and Lyft drivers.

Uber was spending $40 million to $50 million on subsidies in China every single week, an enormous sum just to convince riders and drivers to use Uber over DiDi.

My Uber driver in Sacramento was not like my San Franciso Uber from earlier that day at SFO. My SAC Uber driver’s first presdential election was JFK-Nixon (or Eisenhower in 1956) and he was already drawing a Social Security check. "Father Time" overshot my fixed location (twice) and then didn’t listen to the navigation instructions. This guy’s signature move (and totem animal) is a U-Turn, a mile past the original juncture.

The judges believed Uber and Lyft to be more powerful than they were willing to admit, but they also conceded that the companies did not have the same power over employees as an old-economy employer like Walmart. “The jury in this case will be handed a square peg and asked to choose between two round holes,” Judge Chhabria wrote. Judge Chen, meanwhile, wondered whether Uber, despite a claim of impotence at the center of the network, exerted a kind of invisible power over drivers that might give them a case. In order to define this new power, he decided to turn where few judges do: the late French philosopher Michel Foucault. In a remarkable passage, Judge Chen compared Uber’s power to that of the guards at the center of the Panopticon, which Foucault famously analyzed in Discipline and Punish. The Panopticon was a design for a circular prison building dreamed up in the eighteenth century by the philosopher Jeremy Bentham. The idea was to empower a solitary guard in the center of the building to watch over a large number of inmates, not because he was actually able to see them all at once, but because the design kept any prisoner from knowing who was being observed at any given moment. Foucault analyzed the nature and working of power in the Panopticon, and the judge found it analogous to Uber’s. He quoted a line about the “state of conscious and permanent visibility that assures the automatic functioning of power.” The judge was suggesting that the various ways in which Uber monitored, tracked, controlled, and gave feedback on the service of its drivers amounted to the “functioning of power,” even if the familiar trappings of power—ownership of assets, control over an employee’s time—were missing. The drivers weren’t like factory workers employed and regimented by a plant, yet they weren’t independent contractors who could do whatever they pleased. They could be fired for small infractions. That is power. It can be disturbing that the most influential emerging power center of our age is in the habit of denying its power, and therefore of promoting a vision of change that changes nothing meaningful while enriching itself. Its posture is not entirely cynical, though. The technology world has long maintained that the tools it creates are inherently leveling and will serve to collapse power divides rather than widen them.

Shervin Pishevar’s other star investment, Uber, was embroiled in its own case about whether it was as humble and powerless as it claimed. A group of drivers had sued Uber, as well as its rival Lyft, in federal court, seeking to be treated as employees under California’s labor laws. Their case was weakened by the fact that they had signed agreements to be contractors not subject to those laws. They had accepted the terms and conditions that cast each driver as an entrepreneur—a free agent choosing her hours, needing none of the regulatory infrastructure that others depended on. They had bought into one of the reigning fantasies of MarketWorld: that people were their own miniature corporations. Then some of the drivers realized that in fact they were simply working people who wanted the same protections that so many others did from power, exploitation, and the vicissitudes of circumstance. Because the drivers had signed that agreement, they had blocked the easy path to being employees. But under the law, if they could prove that a company had pervasive, ongoing power over them as they did their work, they could still qualify as employees. To be a contractor is to give up certain protections and benefits in exchange for independence, and thus that independence must be genuine. The case inspired the judges in the two cases, Edward Chen and Vince Chhabria, to grapple thoughtfully with the question of where power lurks in a new networked age. It was no surprise that Uber and Lyft took the rebel position. Like Airbnb, Uber and Lyft claimed not to be powerful. Uber argued that it was just a technology firm facilitating links between passengers and drivers, not a car service. The drivers who had signed contracts were robust agents of their own destiny. Judge Chen derided this argument. “Uber is no more a ‘technology company,’ ” he wrote, “than Yellow Cab is a ‘technology company’ because it uses CB radios to dispatch taxi cabs, John Deere is a ‘technology company’ because it uses computers and robots to manufacture lawn mowers, or Domino Sugar is a ‘technology company’ because it uses modern irrigation techniques to grow its sugar cane.” Judge Chhabria similarly cited and tore down Lyft’s claim to be “an uninterested bystander of sorts, merely furnishing a platform that allows drivers and riders to connect.” He wrote: Lyft concerns itself with far more than simply connecting random users of its platform. It markets itself to customers as an on-demand ride service, and it actively seeks out those customers. It gives drivers detailed instructions about how to conduct themselves. Notably, Lyft’s own drivers’ guide and FAQs state that drivers are “driving for Lyft.” Therefore, the argument that Lyft is merely a platform, and that drivers perform no service for Lyft, is not a serious one.

blitzscaling. It is an idea that applies to many different industries, as he and Chris explain in the last section of this book. But prioritizing speed over efficiency—even in the face of uncertainty—is especially important when your business model depends on having lots of members and getting feedback from them. If you get in early and start getting that feedback and your competitors don’t, then you’re on the path to success. In any business where scale really matters, getting in early and doing it fast can make the difference. This is especially true for two-sided business models, where you have two user groups that create positive network effects for each other. For example, LinkedIn wants to attract people who are looking for work as well as employers who want to hire them. Airbnb wants guests looking for a place to stay as well as hosts with space to rent. Uber wants to attract drivers as well as riders.

There are additional social and cultural factors that come into play which have nothing to do with computer parts, highway infrastructure, and laws. For example, the failure or success of driving-related public health initiatives, such as those regarding texting while driving, will influence our attitudes about driverless cars. If the youngest Millennials and Generation Alphas increasingly rely on the present-day Uber car service to get around, they may not value driver’s licenses in the future, which could increase social pressure for driverless cars.

Why do Uber drivers get rated on customer satisfaction but corporate executives get a pass?

The Uber driver is unassuming and blank and I wouldn’t be surprised if he kills us all.

If you think of General Motors as a manufacturer that produces cars, then in a simplistic sense, Uber is a manufacturer that produces transactions between drivers and riders. Uber doesn’t actually deliver the ride, but it facilitates the connection and exchange of value between drivers and passengers.

What is the core transaction? The core transaction is the set of actions consumers and producers must complete in order to exchange value. Every platform has a core transaction. On Uber, drivers make themselves available and consumers submit requests for rides. On YouTube, producers upload videos and consumers watch, rate, and share them. On Lending Club people or small businesses request loans and others fund them. These examples of the core transaction highlight its purpose: to construct a set of simple, repeatable actions that producers and consumers take to create and consume value through a platform.

The trainers at Uberversity, where new employees underwent a three-day initiation, began schooling everyone on this scenario: a rival company is launching a carpooling service in four weeks. It’s impossible for Uber to beat them to market with a reliable carpool service of its own. What should the company do? The correct answer at Uberversity—and what Uber actually did when it learned about Lyft Line—was “Rig up a makeshift solution that we pretend is totally ready to go so we can beat the competitor to market.” (Andreessen Horowitz, the venture capital firm where I work, invested in Lyft and I am on its board, so I was keenly aware of the dynamic between the companies—and I am decidedly biased.) Those, including the company’s legal team, who proposed taking the time to come up with a workable product, one far better than Uber Pool 1.0, were told “That’s not the Uber way.” The underlying message was clear: if the choice is integrity or winning, at Uber we do whatever we have to do to win. This competitiveness issue also came up when Uber began to challenge Didi Chuxing, the Chinese market leader in ride-sharing. To counter Uber, Didi employed very aggressive techniques including hacking Uber’s app to send it fake riders. The Chinese law on the tactic wasn’t entirely clear. The Chinese branch of Uber countered by hacking Didi right back. Uber then brought those techniques home to the United States by hacking Lyft with a program known as Hell, which inserted fake riders into Lyft’s system while simultaneously funneling Uber the information it needed to recruit Lyft drivers. Did Kalanick instruct his subordinates to employ these measures, which were at best anticompetitive and at worst arguably illegal? It’s difficult to say, but the point is that he didn’t have to—he had already programmed the culture that engendered those measures.

The way that Berardi describes labor will sound as familiar to anyone concerned with their personal brand as it will to any Uber driver, content moderator, hard-up freelancer, aspiring YouTube star, or adjunct professor who drives to three campuses in one week: In the global digital network, labor is transformed into small parcels of nervous energy picked up by the recombining machine…The workers are deprived of every individual consistency. Strictly speaking, the workers no longer exist. Their time exists, their time is there, permanently available to connect, to produce in exchange for a temporary salary.15 (emphasis mine)

For example, Twist is “call-ahead” software that sees where you are and knows where you are heading, as well as knowing the driving conditions en route. It sends a text message to your next appointment while you keep your hands and your mind on the road. Glympse, as we mentioned, is similar and lets you share your location with others—who just might rat you out when you speed. GasBuddy.com lets you find the cheapest gas near your location. Nooly Micro Weather reports uber-localized weather, within .4 miles of where you are and just 15 minutes into the future, preparing you for the fog bank around the next curve on a mountain road. As we write this, it is available as a phone app and the developer is working with Ford and Toyota for the app to be included in cars as they ship. The integrated, automotive Nooly will signal the car to turn on fog lights or the defroster a moment before the weather changes. Waze is a mobile app that lets drivers share updates on road conditions in near realtime. With a community of nearly 50 million members as of May 2013, it is perhaps the most robust source of user-generated road data in the world. Google acquired Waze in the summer of 2013 for just under $1 billion.