Hollywood put us in a driverless cab in 1990 and made it a joke. Thirty-six years later the joke is a $126-billion company. This is the full breakdown: how the taxi lost the curb, how rideshare swallowed dinner, what we traded away in the back seat — and whether Waymo is about to do to Uber exactly what Uber did to the cab.
When Total Recall hit theaters in 1990, it did something most science fiction fails at: it built a future that felt plausible. Not a distant galaxy — a version of next Tuesday. And the smartest, funniest piece of set dressing in the whole picture was the Johnny Cab: a driverless taxi with an animatronic mannequin bolted behind the wheel, wearing a peaked cap, cheerfully asking where you'd like to go.
Brilliant name. Brilliant gag. And for two hours it plays as pure comedy — until Douglas Quaid, Arnold Schwarzenegger's construction worker with a stolen past, is sprinting for his life with armed men closing in. He throws himself into a Johnny Cab and screams at it to drive. Anywhere. Just go.
The machine wants a street and a number. The man wants to live. Quaid solves the impasse the way action heroes do: he rips the robot out of the mount, finds the manual control underneath, and drives himself out of it.
That scene is the whole argument of this article, filmed thirty-six years early. Verhoeven's joke was that automation is flawless right up until the moment reality goes off-script — and that when it does, a human hand on a stick beats a perfect algorithm with no imagination. The film even doubles down on the point: the automated cabs are Earth's technology. When Quaid gets to the Martian slums, his driver is a person. The future was automated where it was rich and human where it was poor.
We are now living in the middle of that scene. The driverless cab is real, it's in six American cities, and — this is the part Verhoeven got backwards — it is measurably safer than the human it replaced. But there is still no joystick under the dash.
To understand where the machine is taking us, you have to understand what it's replacing — and that story starts a long way from Mars.
Stand on 42nd Street with your arm up in the rain, negotiating with strangers for the yellow chariot that will save you from the subway. Stand in Wan Chai watching for the illuminated red "For Hire" flag on the dash of a Hong Kong cab, bracing because the driver may throw the rear door open before you've finished stepping toward it. Grip the rail of an auto-rickshaw in Delhi as it threads a gap between two buses that did not appear to leave one. Different continents, different vehicles, identical transaction.
Taxis are load-bearing infrastructure. They are how a city moves its business, feeds its restaurants, empties its bars at 2 a.m., and gets its night-shift nurses home. And the deal they run on is the oldest commercial arrangement humans have: I have something to get done, you have the means, name your price. Plow my field, take two cows. Build my wall, take the gold. Carry me across town, drop the flag. Every civilization has invented a version of the taxi because every civilization needs one.
Which is why the modern version is enormous. Global ride-hailing is now roughly a $200-billion-plus market, with forecasts pushing it past $250 billion by 2030. It is not one market so much as three regional empires that rarely invade each other.
North America is Uber-and-Lyft country. Asia-Pacific — the largest and fastest-growing region — belongs to China's DiDi (around 30 million rides a day at home), Southeast Asia's Grab (about 9 million daily), and India's Ola. Europe, Africa and the Middle East are a scrum of Uber, Estonia's Bolt, and local specialists. Globally, Uber sits on top at roughly half the market, and the five biggest platforms — Uber, DiDi, Grab, Lyft and Bolt — together control the lion's share of it.
The pattern to hold in your head: the U.S. is only about a third of global ride-hailing revenue, but it is where every act of the story you're about to read premiered first — and where the next act, the driverless one, is being written now.
The business evolved in slow, orderly steps for most of a century. First came the big fleets — you clocked in, you drove the company's car, you turned in the sheet. Then came the owner-operators: smaller outfits and individual drivers who owned their own cab but still ran under the same municipal rulebook, the same meters, the same inspections, the same insurance minimums. Different ownership, same universe of law.
Then the universe changed. The disruption has a birth year: 2009, when Travis Kalanick and Garrett Camp founded Uber after a snowbound, cab-less night in Paris. The black-car app launched in San Francisco in 2010 and reached New York in 2011. But the real detonation was 2012 — the year UberX opened the platform to ordinary drivers in ordinary cars, and the year Lyft launched with its fist-bumps and fuzzy pink mustache. Suddenly anyone with a sedan and a smartphone was a taxi, and none of the old rulebook applied.
For a century, the taxi's scarcity had been artificial and profitable. New York created the medallion in 1937 to cap the number of cabs, and that cap turned a strip of metal into a blue-chip asset. By 2014, a single NYC medallion changed hands for more than $1 million — some near $1.3M — sold to mostly immigrant drivers on borrowed money, on the promise that the city would protect their monopoly on the street hail.
The city didn't. As app-hailed cars flooded in — NYC's for-hire fleet roughly tripled from about 40,000 vehicles in 2010 to over 120,000 by 2019 — that promise evaporated, and the medallion followed it down.
It was not quiet. Cabbies staged rolling protests and horn-blaring blockades from New York to London, Paris and beyond. The taxi industry sued Uber and Lyft for skirting the rules everyone else had to follow — and sued regulators for letting them. New York's Taxi & Limousine Commission was buried in litigation after its first ride-hail rules landed in 2015. And the human cost turned tragic: as earnings cratered and loans came due, more than 950 medallion owners filed for bankruptcy, and at least nine NYC drivers died by suicide, one on the steps of City Hall.
(An uncomfortable footnote history has since added: a 2019 New York Times investigation found the medallion bubble was inflated for years by predatory lending and the city's own revenue-hungry practices. Uber lit the match — but the powder had been packed long before.)
They fought on three fronts, and mostly lost all three. They built their own apps — Curb, Arro, Flywheel, Hailo — bolting e-hailing onto the yellow cab, but always a step behind Uber's scale and subsidies. They lobbied for caps and rules, and here they scored a partial win: in 2018 New York capped new ride-hail licenses and set a driver minimum-pay floor (about $17.22/hour), the first big city to make Uber and Lyft blink. And they competed on price and turf they still owned — the spontaneous arm-out street hail and the airport queue, the last redoubts where an app wasn't already faster.
Here is the loss nobody put on a balance sheet. Driving a cab used to be a job — with everything that word carries. You came to the garage. You picked up your car from the same bay every morning. There was a shift, which meant there was a start and an end. There was a dispatcher who yelled at you, which meant there was someone who knew your name. And when you clocked out, you clocked out with the other people who had just done the same thing, and you went and got a drink and complained about your day — exactly like a stockbroker, a framer, a paralegal, or a cop.
That is not sentimentality; it's structure. The cab garage was a workplace, and workplaces manufacture something beyond their product: they make colleagues.
The culture noticed. Taxi — the sitcom that ran on ABC and NBC from 1978 to 1983 — was not set in a cab. It was set in the Sunshine Cab Company's Manhattan fleet garage, and the show worked because the garage was where the drivers actually lived, needled each other, and got berated by Danny DeVito's dispatcher from inside his cage. It won 18 Emmy Awards, including three straight for Outstanding Comedy Series, and it was built from a 1975 New York magazine piece about the night shift at a real Greenwich Village garage. Whole films took the front seat as their subject: Scorsese's Taxi Driver (1976), Michael Mann's Collateral (2004). The cab was a place where American stories happened.
And then there's the one that proves the other half of this article's argument almost too neatly.
Taxicab Confessions premiered in 1995 and ran, on and off, for over a decade. The entire premise was that under the cover of a city night, in a vehicle with a stranger who would never see you again, people will say anything. That show is a documentary record of a psychological condition that has since been engineered out of existence — and we'll come back to it.
To be fair — and this matters — the trade was not one-sided. Rideshare handed drivers something the garage never did: total autonomy. You set your own hours. You work Tuesday and skip Wednesday. Nobody assigns you a weekend, refuses your overtime, or holds a shift over your head. For a parent, a student, a retiree, or someone bridging between careers, that flexibility is not a consolation prize — it's the entire appeal, and it is why millions of people took the work.
What they gave up was everything on the other side of the ledger: no coworkers, no employer, no benefits, no bargaining power, no floor under the fare, and — for the first decade — no legal path to organize at all, because independent contractors sit outside the federal labor law that gives employees the right to unionize.
That last part has started to change, and it's worth being precise about it, because the picture is genuinely mixed.
So the arc runs: the cab driver had colleagues and a union and a boss. The rideshare driver traded all three for a schedule of their own and is now, city by city, slowly clawing back a fraction of what was traded. And the robotaxi resolves the whole labor question by deleting its subject. Waymo's car doesn't negotiate, doesn't organize, doesn't clock out and doesn't go for a drink. It works until the battery needs charging, and then it works again.
Killing the taxi didn't create a free-for-all; it created a duopoly. Lyft mounted the only real challenge, clawing from about 22% of the U.S. market in 2016 to 39% by the end of 2018, cresting near a third of all rides during the pandemic reshuffle of 2021. Then Uber's deeper pockets and global footprint reasserted themselves. By 2024 Lyft had settled back to roughly 24%, leaving Uber with about three-quarters of American rideshare and — for the first time, in 2023 — an actual operating profit.
Once the two-horse race stabilized, the competition stopped being about which app and started being about which car. The single undifferentiated cab ride splintered into a menu: economy, XL, SUV, black, comfort, electric. Closer and cheaper, or nicer and pricier — your call, priced accordingly, quoted upfront. A yellow cab could never have offered that, because a yellow cab was a yellow cab. Riders stopped caring which company's logo was on the windshield and started caring only whether the car showed up. That indifference is a crucial detail, and it will matter enormously when the car that shows up has nobody in it.
Having conquered the passenger, the platforms noticed the empty seat and the idle driver between fares — and pivoted to moving food instead of people. Uber launched what became Uber Eats in 2014; DoorDash, founded in 2013, out-hustled everyone on the suburbs. Then COVID-19 hit in 2020 and turned a convenience into infrastructure overnight.
The same playbook that gutted the taxi got run on the restaurant. Where a diner once phoned the pizzeria or the restaurant paid its own delivery kid, an app now sat in the middle — taking a commission of roughly 15–30% per order and dispatching a gig courier who belonged to no restaurant at all. Menus quietly inflated 15–25% to cover the cut. The delivery driver, like the rideshare driver before them, became a contractor floating between apps.
Today three players — DoorDash out front, Uber Eats second, Grubhub (now owned by Wonder) a distant third — control roughly 96% of U.S. meal delivery, a market worth well over $100 billion. Notice the through-line: Uber didn't just win rides, it became a logistics company that happens to also carry people. That shift is the hinge for everything the robots are about to do.
There's a casualty in this era that rarely makes the analyst decks. Delivering food used to be a teenager's job — arguably the great American starter job. It taught you the things nothing else teaches at sixteen: show up on time, handle money, read a map, talk to adults, take responsibility for something that gets cold. Plus the occasional wrong order you got to eat in the parking lot.
That job now largely belongs to an adult contractor with a car payment. The restaurant no longer employs the driver; the platform dispatches one.
Honest framing matters here: the delivery apps did not single-handedly kill the teenage job — that decline started around 2000 and has many authors. But the apps did convert a specific, formative, locally-employed role into a nationally-dispatched gig, and in April 2026 roughly 5.19 million American 16-to-19-year-olds were employed, down from 5.48 million a year earlier. Whatever else the delivery economy built, it did not build a place for a sixteen-year-old to learn to work.
Now the obvious question, and the one that gives this piece its charge: is Waymo about to do to Uber and Lyft exactly what Uber and Lyft did to the taxi? Remove the human, undercut the incumbent, flip the market?
The raw numbers say a revolution is underway. Waymo's paid rides went from about 10,000 a week in 2023 to 100,000 by August 2024, past 200,000 by early 2025, and — by analyst counts in early 2026 — roughly 400,000+ a week across six cities. It logged around 15 million rides in 2025 alone, tripling year over year. In San Francisco it has reportedly climbed to 25–27% market share, surpassing Lyft inside its service area. In February 2026 it raised $16 billion at a $126-billion valuation, with expansion planned to 20-plus cities including Tokyo and London.
So far, robotaxis are not cannibalizing rideshare the way rideshare cannibalized cabs. The counterintuitive data point of 2025: Uber and Lyft have been growing roughly five times faster in cities with robotaxi fleets than in cities without them. Lyft's CEO calls autonomy a "massive TAM expander" — driverless cars are pulling people out of their own cars and into on-demand rides generally, and Uber is smart enough to be partnering with Waymo rather than fighting it, dispatching Waymos through the Uber app in Austin and Atlanta.
Why the difference from the taxi bloodbath? Because Waymo's constraint isn't demand — it's supply. Each car costs a fortune, the fleets are small, and the service still skips airports and highways. Uber didn't have to build a car; Waymo has to build every single one. For now, the pie is growing faster than the robots can eat it.
Which is exactly why Tesla matters to this story, and why it deserves more than a footnote. Tesla is running the opposite wager, and the two approaches disagree about the most fundamental question in the industry: what a self-driving car needs in order to see.
Waymo's answer is everything — LiDAR, radar, cameras, and centimeter-accurate maps of every street it operates on, scanned block by block before a single paying passenger gets in. That's why each car is expensive and each new city takes months. Tesla's answer is cameras only. No LiDAR, no pre-built map. If it works, the economics invert completely: expanding a service area becomes close to a software toggle, the hardware is a Model Y instead of a sensor-crowned research vehicle, and the potential fleet is the millions of FSD-capable Teslas already sitting in driveways waiting for their owners to opt in. Waymo has to manufacture its supply. Tesla, in theory, already sold it.
That is a genuinely enormous "if," and as of mid-2026 it remains unresolved.
Tesla launched its robotaxi service in Austin in June 2025 with roughly ten to twenty Model Ys and a safety monitor riding in the passenger seat. The regulatory door opened on May 28, 2026, when a new Texas driverless-vehicle law took effect and Tesla self-certified at Level 4 the same day. On June 3 it removed the monitors and expanded unsupervised coverage to the entire Austin metro — roughly 245 square miles, airport included. On the map, Tesla had just out-covered Waymo in a major American city.
Then you count the cars. Independent trackers put Tesla's active unsupervised Austin fleet at around 20 vehicles serving all 245 of those square miles. State filings tell the same story from the regulator's side: 42 Tesla robotaxis registered in Texas against Waymo's 577 — the same state, the same paperwork, a 13-to-1 gap. Nationally the asymmetry is starker still. Waymo told NHTSA in December 2025 that it operates 3,067 robotaxis, and it now runs over half a million paid rides a week across ten U.S. cities.
The safety picture is thinner and harder to read. Tesla's Austin operation logged 17 reported incidents with NHTSA between July 2025 and April 2026 — two involving minor injuries, one requiring hospitalization. Electrek, which has tracked the program since launch, calculated a crash rate roughly nine times the human benchmark; with a fleet this small the error bars on any such rate are wide, and Tesla disputes the framing. But note the asymmetry that matters: Waymo's safety case rests on a peer-reviewed study of 56.7 million driverless miles. Tesla's rests on a pilot. Musk has tied real scaling to FSD v15, an architectural rewrite expanding the driving model from roughly one billion parameters to ten, targeted for late 2026 or early 2027.
One more detail belongs here, because it closes a circle this article opened in 1990. Tesla's purpose-built robotaxi, the Cybercab, is a two-seater designed with no steering wheel and no pedals at all. Not a car with the driver removed — a car in which the driver's position was never designed in the first place.
Musk unveiled it in October 2024 and said it would sell for under $30,000 — roughly $31,500 in 2026 money. Two seats, on the argument that 90% of miles are driven with one or two people aboard. No steering wheel, no pedals, nothing to adjust. Production began at Giga Texas in April 2026, slowly, on what Musk called a stretched-out S-curve. The first production cars carried paying passengers in Austin on September 4, 2026.
The interesting part isn't the car. It's the paperwork. A vehicle with no steering wheel does not obviously satisfy federal safety standards written on the assumption that somebody is steering. Zoox, Amazon's robotaxi arm, went the formal route — it petitioned for a Part 555 exemption, was granted a temporary waiver from eight standards, and launched commercially in July 2026, bound by the rule capping exempted vehicles at 2,500 units. Tesla didn't petition. Tesla self-certified the Cybercab as compliant with every existing standard, the same process Toyota uses for a Camry, and in doing so stepped around the cap entirely.
The regulator noticed. On the same day the first Cybercabs took passengers, NHTSA opened an investigation into "the process and technical data on which Tesla relied when certifying the Cybercab," noting that existing standards remain in force until that work is finished. Tesla has, in effect, declared its own car legal, and is now being asked to show its working.
Which brings us to the thing that should interest anybody reading this who has a driveway.
Musk's pitch was never that Tesla builds and runs a fleet the way Waymo does. It's that you do. "I think it would end up being some kind of combination of like Airbnb and Uber," he said — you buy the car, and when you aren't using it, it goes out and works. The arithmetic attached to it is genuinely seductive. A private car sits idle almost all of its life, in use maybe 12 hours a week. On the network, 60. "The interesting thing," Musk noted, "is the car still costs the same." At Tesla's 2019 Autonomy Day he put a number on the upside: around $30,000 a year in gross profit per vehicle, roughly $38,700 in today's money.
On September 3, 2026 — the day before those first Cybercabs took passengers — Tesla published a form asking who wanted in. The options: Cybercab fleet vehicle purchasing, mobility hubs and infrastructure, event collaboration, other.
Read that list again, because the word that matters is the one that isn't on it. The form is addressed to businesses. Not to you.
The city caps the number of cabs, and a strip of tin becomes an annuity. By 2014 one changes hands for more than $1 million — about $1.4 million in today's money — mostly to immigrant drivers buying on borrowed money. Then the cap stopped meaning anything, and the asset took its owners down with it.
Be your own boss. Bring your own car, set your own hours, keep what you earn. The car, the fuel, the insurance, the maintenance and the depreciation stayed with the driver. The commission stayed with the platform, and it went up.
Same offer, minus the driver. Buy the car, let the network rent it out, collect while you sleep. Ownership of the asset sits with you. So, as ever, does the risk on it.
And there's a harder question underneath the pitch, which Electrek's Fred Lambert has put about as bluntly as it can be put: if a Cybercab on that network genuinely printed $30,000 a year, why would Tesla hand that money to a stranger instead of keeping every car for itself?
That isn't a rhetorical flourish. It's the test. A company that has built a machine which prints money does not sell you the machine. It buys more of them. Waymo — which has the working autonomy and the operating proof — sells nobody a car and operates every one of the 3,067 it told NHTSA it owns. The moment a robotaxi business becomes willing to sell you the vehicle is the moment worth asking what the seller knows about the margin that the buyer doesn't.
The precedent isn't encouraging, because Tesla has made this exact offer before. Owners who bought Full Self-Driving — at up to $15,000, about $16,900 today — were told they would be able to add their cars to something called the Tesla Network and earn taxi income from them. That promise dates to 2016, and was restated in 2019. It has never shipped. Tesla runs the service itself, with its own cars, and the people who paid for FSD on the strength of that revenue are, a decade on, still unable to collect it. The September 2026 form did not change that: individual FSD owners remain left out.
Then there's the asset itself. MisterGreen, a Dutch leasing company, bought more than 4,000 Teslas on precisely this reasoning and lost $40 million when the residuals went against it — used Teslas depreciating at roughly three times the rate of the broader used-car market. A fleet owner isn't only betting on ride demand. They're betting on resale values, on software arriving when it was promised, and on a regulator that is at this moment asking the manufacturer to justify the car's legality.
Strip the technology out and the offer is the oldest one in this story. In 1937 a city sold a man a piece of tin and called it an annuity. In 2012 a platform sold him be your own boss and took a cut that grew every year after. In 2026 the pitch is unchanged — buy the asset, let it earn while you sleep — and the genuinely new part is only that nobody has to sit in the car. Whether the person holding the keys keeps the money has never once been settled by the machine. It has been settled by whoever wrote the terms.
Market share is the easy part. The harder and more important question is whether any of this made people safer — and here the analysis has to start with an admission, because the honest finding is a hole in the data.
Uber has published three U.S. Safety Reports, and the trend within them is downward: 5,981 reports of sexual assault in 2017–2018, 3,824 in 2019–2020, and 2,717 in 2021–2022. Lyft's first report disclosed 4,158 assault reports across 2017–2019, followed by a 2020–2022 report covering 1.41 billion rides.
Two findings inside that data complicate the easy narrative. First, harm runs in both directions: across 2021–2022, drivers were the accused party in roughly 68% of reported sexual assaults — and in fatal physical assaults over the same period, 61% of the victims were drivers, not riders, with a third party responsible in nearly half of fatalities. Second, Lyft reported assaults against drivers rising from 714 in 2021 to 1,038 in 2022. The person most likely to be hurt in a for-hire vehicle is often the one being paid to be there.
Which brings us to the statistic that reframes the entire taxi era. Driving a cab was, for decades, one of the most dangerous jobs in America — not because of crashes, but because of people. BLS data put the annual homicide rate for taxi drivers and chauffeurs between 9 and 19 per 100,000 workers from 1998 to 2007, against a national all-worker rate at or below 0.5. That is 20 to 30 times the average, higher than police officers. Between 1994 and 2013, an average of 34 U.S. cab drivers were murdered on the job every year.
And here is the detail that should govern how we think about robotaxis: the thing that fixed it was surveillance. A NIOSH study across 26 U.S. cities found that cities mandating in-cab security cameras saw a roughly threefold reduction in driver homicides. Bullet-resistant partitions showed no significant effect. Cameras did. Being recorded was the intervention that saved drivers' lives — thirty years before anyone described total trip logging as a robotaxi feature.
The mechanism behind most of that violence was simple: cab drivers carried cash, worked alone, and went wherever a stranger told them to at 3 a.m. Rideshare removed the first variable almost entirely. There is nothing in the car worth robbing, the fare is quoted before you get in, the route is on a map both parties can see, and every trip carries a name, a timestamp, a GPS trace and a payment record. The classic taxi frauds — the scenic route, the "broken" meter, the disputed fare — became structurally difficult. That is a genuine and underrated safety gain, and the robotaxi is its endpoint: no cash, no driver, no negotiation, no discretion.
The draft version of this argument said robotaxis have "no prejudice," and the research broadly supports it — but not in the flattering way you'd expect, because the comparison is ugly on both sides. A landmark 2016 field study by MIT Sloan, Stanford and the University of Washington ran nearly 1,500 controlled rides in Seattle and Boston. Black passengers waited up to 35% longer; riders with Black-sounding names had UberX trips canceled more than twice as often, rising to roughly three times for men in low-density areas. Crucially, the same researchers also documented racial discrimination among conventional taxis in Seattle and explicitly declined to say which system was worse.
So the honest version is this: the app didn't invent the problem, and it didn't fix it either. It digitized it, and in digitizing it made it measurable for the first time. A driverless car is the first vehicle in this history that cannot see your name, your face, or your neighborhood before deciding whether to accept you. That is not a small thing for the people who have spent fifty years failing to get a cab to stop.
On collisions the evidence is strong and peer-reviewed. Across 56.7 million rider-only miles, published research found Waymo's vehicles involved in dramatically fewer injury crashes than human benchmarks on the same roads: roughly 92% fewer involving pedestrians, 82% fewer involving cyclists and motorcyclists, and about an 80% reduction in any-injury crashes overall. By late 2025 the fleet had cleared 127 million autonomous miles.
That third number is the one a good article doesn't leave out. In December 2025 Waymo filed a voluntary software recall after its cars illegally passed stopped school buses — Austin's school district documented at least 19 such incidents in a single school year, several after Waymo said it had already patched the problem, prompting an NHTSA investigation that began with a separate case in Atlanta. Two further recalls followed, covering roughly 3,900 vehicles for driving into closed freeway construction zones and about 3,800 for entering standing water. No injuries were reported in the school-bus incidents. The NTSB opened its own probe.
None of that erases an 80% crash reduction. But it defines the shape of the risk, and the shape is genuinely new: human error is retail — one distracted driver, one bad night, one intersection. Machine error is wholesale. When the software gets a school bus wrong, it gets every school bus wrong, in every city, simultaneously, until someone ships a patch. That is the trade the public is actually being offered: dramatically fewer bad outcomes, arriving in correlated batches instead of one at a time.
It is the question every reader arrives with, and it deserves a direct answer rather than a shrug. The direct answer is that it depends entirely on which harm you mean, and for two of the four categories nobody can honestly say.
No comparison exists at the level of an individual trip. But there is decent evidence that rideshare's presence in a city reduces sexual assault: a peer-reviewed study in Information Systems Research tracked Uber's city-by-city rollout from 2005–2017 plus precinct-hour data in New York, and found entry negatively associated with rape incidents — strongest exactly where taxi service was worst. Contested by later work arguing the opposite.
The strongest case for rideshare. Cash was the motive; the app removed it. A 2025 study found significant declines in DUI and motor vehicle theft following ride-sharing entry — though it called results for assault and robbery "less conclusive." The catch: a new crime replaced the old one. The car became the target instead of the cash box.
There is no dataset. Congress ordered this exact comparison in Sami's Law; the GAO reported back in 2024 that available data "cannot fully describe the extent of assaults in these industries." Taxi operators told investigators they'd had few or no assaults — self-reported, unpublished, unverifiable.
Advocacy researchers documented 50+ app workers killed on the job between 2017 and January 2022 — then at least 31 in 2022 alone, 77% of them people of color. They estimate app work would rank among the five deadliest U.S. sectors if federal statistics tracked it separately, which they don't.
Then there is the structural difference, which the numbers alone miss. In survey research, 57% of app drivers — and 62% of drivers of color — said they did not cancel a ride despite feeling unsafe, because they feared losing the income or being deactivated from the platform. A salaried cab driver could refuse a fare and still have a job at the end of the shift. That is not a statistic about crime; it's a statistic about leverage, and it shapes who ends up in a dangerous car.
Which is the finding worth taking away. Uber publishes its numbers; the taxi industry never had to. Nobody counted what happened in the back of a cab for eighty years, so the moment somebody started counting, the totals looked catastrophic by comparison — against a baseline of zero, because no baseline was ever built.
But the missing baseline cuts both ways, and honesty requires saying so plainly: it also means nobody can prove taxis were worse. Uber cannot claim victory on a comparison that was never possible. What genuinely changed is that harm inside a for-hire vehicle became visible — an achievement Uber gets too little credit for, and one that simultaneously destroyed its ability to say it made you safer.
The robotaxi is where that argument finally resolves, and not by being more transparent. It resolves because the category of harm this whole section is about requires a second person in the car.
Here is where the analytics stop being about money, and where the whole story turns on something no spreadsheet has a column for: what it feels like to be a passenger.
The old taxi was an anonymous confessional. There was a partition. The driver didn't know you, didn't rate you, often didn't share a language with you — and in that indifference, you could vanish. You could take a call you'd never take at the office. You could stare out the window and decompress. You could be nobody for fifteen blocks. The separation was the product. The driver was functionally unseen, and so, for a moment, were you.
Rideshare ended that quietly and completely. Now there's a named human up front who greets you by your first name, whose five-star rating you hold and who holds yours. You can see them on their phone; they can see your history. The ride became a small social performance — polite, pleasant, mutually surveilled. It is nearly impossible to let go of reality while being reviewed.
And be clear that it was a trade, not a theft — the security is real and it is worth something. No more standing in freezing rain fighting a stranger for the same cab. No more empty taxi line at midnight. No more meter anxiety, no scenic route, no "card machine's broken." The price is quoted before you commit. The trip is tracked end to end — route, stops, duration, all of it on the record — and the interior is often recorded too. If your driver cancels mid-journey, another car is already coming. It is a well-oiled machine, and it removed a genuine category of misery from urban life.
It just also removed the room. Ask yourself why Taxicab Confessions could never be remade today. The show didn't work because cabs had cameras — it worked because passengers believed the person in front of them was nobody, going nowhere, keeping nothing. Strip that belief out and people stop confessing. The app didn't just change how you book a ride; it changed what you're willing to say inside one.
Which makes the robotaxi the strangest resolution imaginable. The front seat is empty again. Nobody greets you, nobody rates you, nobody is owed a tip, nobody misunderstands your address, and nobody decides — consciously or not — whether you look like a fare worth taking. The solitude of the old cab is handed back to you intact.
And yet nothing is anonymous, because the machine logs everything: every route, every stop, every second, in perfect fidelity, forever. It is the privacy of an empty room inside a building full of cameras. Freer than a rideshare, safer than either, and more comprehensively recorded than a taxi ever dreamed of being. Whether that reads as liberation or as a subtler kind of company is going to depend entirely on who's in the back seat — and that, not market share, is the thing worth watching.
The honest scorecard — where each model wins, and where it costs you something.
| The Taxi | Rideshare | Robotaxi | |
|---|---|---|---|
| Crash safety | – Uneven; no telemetry | Rated drivers; background checks | + ~80–92% fewer injury crashes |
| Failure mode | Individual, one-off | Individual, one-off | – Fleet-wide; fixed by recall |
| Risk to the driver | – 20–30× average homicide rate | – Majority of fatal-assault victims | + No driver to endanger |
| Payment | – Cash on board; disputes | + Cashless, quoted upfront | + Cashless, no tip, fully automated |
| Discrimination | – Documented refusals | – 2× cancellations, 35% longer waits | + Can't see name, face or race |
| Privacy / anonymity | + Truly anonymous; you can vanish | – Named, rated, social | Nobody present — everything logged |
| Availability | Street hail & airports | + On-demand, near-universal | – Few cities; no airports/highways yet |
| Price | Metered, often higher | Dynamic / surge | Competitive, falling as fleets scale |
| The human factor | + Local knowledge, improvisation | Conversation — for better or worse | – None; can't handle the odd situation |
| Worker's deal | Shift, colleagues, union, a boss | Total flexibility, no floor, no colleagues | – No worker at all |
| Who bears the risk | Driver (medallion debt) | Gig driver (no benefits) | The platform (capital cost) |
Three questions, three honest answers, no crystal ball required — just the direction the data is already pointing.
The cab won't vanish — it retreats to the corners apps never fully took: the arm-out street hail, the airport queue, the cash economy, the rider who won't or can't use an app, and cities that legislate its survival. A permanent niche, a fraction of its former self.
Uber and Lyft aren't the next taxi. They're becoming the demand layer — the app you open that dispatches a human today and a Waymo tomorrow. Uber already resells Waymo rides. Owning the customer may matter more than owning the driver.
Waymo is winning on operating proof rather than promises — but scaling is slow, expensive and recall-prone. Tesla holds the cheaper architecture and the bigger theoretical ceiling, and has yet to convert either into fleet or evidence. Whoever solves the other's problem first takes the decade.
The tidy narrative — taxi killed by rideshare, rideshare killed by robot — is too neat. What's actually happening is stranger and more interesting: each layer absorbs the last rather than simply burying it. The medallion became an app; the app is becoming a dispatcher for machines; the machine still runs on the network the app built. The driver is disappearing from the front seat — but the ride, in every era, only gets more essential.
Which returns us, finally, to 2084.
Verhoeven's Johnny Cab was a warning dressed as a gag: the machine will be polite, efficient, and catastrophically literal, and one day you will need it to understand something it cannot. What he could not have predicted is that we'd run the numbers and find the machine crashing 80% less than we do, refusing nobody, robbing nobody, and never once taking the long way. The joke aged into an argument.
But hold onto the last frame anyway. Quaid got out of that cab because he could tear the driver out and put his own hand on the control. There is no joystick under the dash of a Waymo — and the Cybercab is being built without a steering wheel at all. What's left instead is a support line, a fleet-wide software patch, and a company deciding what your car does next. We are not choosing between a human driver and no driver. We are choosing between a driver we can argue with and one we can only file a complaint about.
The meter's still running. It just doesn't need a hand to start it anymore — and it no longer has one to take.
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