Tesla has finally moved its robotaxi vision from the stage into public service. But the bigger story is not simply that another driverless taxi has appeared on American roads. Tesla’s Cybercab represents a different bet on how autonomous transportation should work, one built around a purpose-designed, steering-wheel-free vehicle, Tesla’s camera-led artificial-intelligence approach and the possibility of eventually turning millions of existing cars into part of a giant autonomous network.
Technology & Mobility | WorldAtNet | September 2026
Facts at a Glance
| Issue | What matters in 2026 |
|---|---|
| Tesla vehicle | Cybercab, a purpose-built two-seat autonomous vehicle without a conventional steering wheel or pedals. |
| Current launch | Public Cybercab rides have begun in selected areas of Austin, Texas. |
| Tesla's wider robotaxi fleet | Tesla is also using Model Y-based robotaxis in its U.S. service. |
| Waymo | Waymo remains the more mature large-scale American commercial robotaxi operator, with fully autonomous service expanding across 14 cities. |
| Core Tesla approach | Tesla emphasizes camera vision, neural-network software and a vertically integrated vehicle-and-AI strategy. |
| Core Waymo approach | Waymo combines autonomous-driving software with a multi-sensor perception system and carefully mapped operational areas. |
| Biggest promise | Lower-cost, on-demand transportation that could operate for long periods without a human driver. |
| Biggest uncertainty | Safety, regulation, reliability, public trust and the speed at which Tesla can scale beyond limited operating zones. |
The Robotaxi Era Has Entered a New Phase
For years, autonomous vehicles were discussed as though they belonged to a distant future. Demonstration cars appeared at technology conferences. Engineers talked about neural networks, lidar, computer vision and high-definition maps. Companies promised that one day passengers would enter a vehicle, name a destination and simply sit back while a machine handled the road.
That future is no longer theoretical in the United States.
Waymo has already built a substantial commercial robotaxi business. In September 2026, the company said it was beginning to welcome public riders in Denver, San Diego and Tampa, bringing its fully autonomous service to 14 cities. Tesla has now moved its own purpose-built Cybercab into public service in Austin, Texas. The two developments are important because they show that autonomous driving is shifting from an experimental technology toward an actual transportation industry.
Tesla’s launch is especially significant because Cybercab is not simply another conventional electric car with autonomous software added to it. Tesla describes it as a vehicle designed for full autonomy, without a steering wheel or pedals. The company says the vehicle uses camera vision and sensors to navigate roads, intersections and parking areas.
That creates a fundamental question: if Waymo has already been offering driverless rides, what is actually new about Tesla?
The answer is that Tesla is attempting to change the economics and architecture of the robotaxi business at the same time. Instead of treating autonomy as a specialized fleet technology that operates inside carefully prepared service areas, Tesla is trying to build an autonomous transportation network around a mass-market automotive manufacturing system and a common AI platform.
If Tesla succeeds, the consequences could extend far beyond taxis. The company could help change how people commute, how families own cars, how cities allocate parking space, how elderly people travel, how disabled passengers access services and how businesses move workers and goods.
But there is a catch. The same strategy that could make Tesla’s system extraordinarily scalable also places enormous pressure on the company to prove that its autonomous software is reliable enough to remove the human fallback entirely.
That is why the Cybercab launch should be viewed neither as the final victory of autonomous driving nor as another technology demonstration. It is the beginning of a much bigger contest.
What Tesla Has Actually Launched
Tesla’s latest robotaxi is called Cybercab. It is a compact, two-seat vehicle designed specifically around autonomous operation. Tesla’s own rider documentation describes a vehicle without a steering wheel and with a central touchscreen, passenger-focused cabin and storage capacity for luggage.
The distinction matters. A conventional self-driving test car can still be driven manually if the autonomous system disengages. A vehicle without traditional controls is making a much stronger statement: the machine, rather than the passenger, is expected to remain responsible for driving.
Tesla has also not abandoned conventional Tesla vehicles as part of its robotaxi strategy. Its Robotaxi service includes Model Y-based autonomous vehicles alongside Cybercab. Tesla’s official service page currently lists Austin, Dallas, Houston, Miami, Orlando and Tampa among its U.S. operating markets.
The rollout remains much smaller than the grand vision suggests. Tesla is beginning with restricted operational areas rather than immediately opening every road in every city. That is normal for autonomous transportation. A robotaxi company has to understand local road layouts, traffic patterns, pickup and drop-off behavior, construction zones, weather conditions and unusual intersections before it can responsibly expand.
What makes this launch different is the physical vehicle. The Cybercab is a purpose-built autonomous machine rather than a regular passenger car that happens to have autonomous capabilities.
That design opens the door to another important idea: once a vehicle does not need a human driver, the cabin can be designed around passengers instead of drivers.
How Tesla’s Robotaxi Is Different From Earlier American Driverless Taxis
The simplest way to understand the difference is to separate the robotaxi industry into two layers: autonomy and transportation economics.
Earlier American robotaxis, especially Waymo’s, proved that a vehicle could navigate urban roads without a human behind the wheel. Tesla is trying to prove that the same basic concept can become a mass-market transportation network built at automotive scale.
Waymo has followed a relatively cautious model. It develops the autonomous driving system, equips vehicles with a sophisticated sensor suite and gradually opens carefully validated service areas. Its current commercial fleet is supported by a large operational infrastructure designed around autonomous ride-hailing.
Tesla is pursuing a different architecture. Its strategy places much greater emphasis on computer vision, neural networks, onboard computing and the company’s ability to manufacture vehicles in large numbers. Tesla also has an enormous installed base of consumer vehicles that can serve as a potential source of real-world driving data.
There is another dramatic difference: Cybercab does not have conventional driver controls. That is more than a styling decision. It signals that Tesla wants autonomy to be the primary function of the vehicle rather than an optional driving mode.
There is also a difference in business ambition. Waymo is primarily a robotaxi operator and technology company. Tesla is simultaneously an automaker, battery company, AI company and energy business. Its long-term vision is therefore potentially much larger: manufacture autonomous vehicles, operate them as a fleet, sell autonomous technology and potentially allow Tesla owners to participate in an autonomous ride network.
This could create a powerful network effect. More cars could generate more driving data. More data could improve the software. Better software could support more vehicles. More vehicles could make the service more available. Higher utilization could lower the cost per ride.
That is the theory.
The practical test will be whether Tesla can achieve the safety and reliability required for that flywheel to operate in the real world.
Tesla vs Waymo: Two Very Different Philosophies
The emerging Tesla-Waymo competition is one of the most fascinating technology contests in America because the companies are not simply selling two versions of the same product. They represent two different philosophies of autonomy.
Waymo has spent years developing a highly specialized autonomous driving system. Its sixth-generation Waymo Driver is designed to operate across multiple vehicle platforms, and the company says it has completed more than 20 million fully autonomous trips. In September 2026, Waymo announced public expansion into Denver, San Diego and Tampa, taking its service footprint to 14 cities.
Waymo’s approach is built around redundancy and detailed environmental understanding. Its vehicles use multiple sensor technologies and sophisticated mapping. The company has emphasized a phased process in which a new city is manually driven and mapped before autonomous operations are expanded.
Tesla’s strategy is more radical. It wants a system that can learn from a huge number of vehicles and function using a simpler hardware philosophy. Tesla argues that human beings drive using vision and intelligence rather than lidar scanners, and it has therefore invested heavily in camera-based perception and neural-network training.
There is a major economic attraction to Tesla’s approach. If a camera-led system can deliver the required safety without expensive specialized sensor arrays, autonomous vehicles could eventually become cheaper to manufacture.
But the trade-off is obvious. A simpler hardware strategy places greater pressure on software. The system has to interpret rain, glare, darkness, unusual road markings, emergency scenes, debris, pedestrians and countless rare events with extraordinary reliability.
Waymo’s strategy is therefore closer to controlled expansion with extensive redundancy. Tesla’s strategy is closer to mass deployment through generalized AI.
Neither model has conclusively won.
And that is precisely why the robotaxi race matters.
The Technology Behind the Cybercab
At the heart of every robotaxi is a deceptively difficult problem: converting the chaotic physical world into decisions a computer can make safely.
A human driver looks at a road and immediately recognizes a school zone, a cyclist, a police officer directing traffic, a temporary lane closure or a pedestrian about to cross. Human brains combine visual information with memory, context, common sense and social expectations.
An autonomous vehicle has to reproduce those abilities computationally.
Tesla's system relies heavily on cameras and neural-network processing. Cameras provide continuous visual information. Neural networks interpret that information. Planning software determines what the vehicle should do next. Control systems translate the decision into steering, acceleration and braking commands.
The difficulty is not handling an ordinary road. The difficulty is handling the one-in-a-million situation that was not represented perfectly in training data.
This is why autonomous driving is fundamentally an AI problem rather than simply a car problem.
A robotaxi also needs a communication layer. Passengers need to know where the vehicle is going, whether a door is locked, what to do in an emergency and how to contact assistance. Fleet operators need remote support systems, maintenance systems, charging infrastructure and monitoring tools.
Cybercab therefore represents only the visible part of a much larger technological stack.
Behind the passenger is a network of servers, maps, software updates, vehicle diagnostics, charging operations, customer support and regulatory reporting.
In other words, a robotaxi company is not merely building a car. It is building a transportation system.
Why the Economics Could Be Revolutionary
The economic argument for robotaxis is brutally simple.
In a conventional taxi or rideshare vehicle, the driver can represent a substantial portion of the cost of every trip. The vehicle also spends much of its day parked, while its owner pays for depreciation, insurance, maintenance and financing.
A driverless fleet changes the utilization equation.
A robotaxi could potentially operate for far more hours each day than a privately owned vehicle. Instead of sitting outside an office for eight hours while its owner works, it could transport other passengers. Instead of being used for a short morning commute and a short evening commute, it could continuously circulate through a city.
That creates an unusual possibility: the same physical vehicle could provide transportation to dozens of people during the day.
Once the driver cost is removed and vehicle utilization rises, the price of a ride could theoretically fall.
That does not mean every robotaxi ride will immediately become cheap. Autonomous fleets still require expensive sensors, computing hardware, charging, insurance, cleaning, maintenance, remote assistance, fleet management and infrastructure. Early services may also command premium prices because demand exceeds supply.
But if the technology scales, transportation economics could shift dramatically.
A family might decide that buying a second car is unnecessary. A young professional might postpone car ownership. A university student could travel independently without owning a vehicle. A hotel could send robotaxis to airports. A business could provide autonomous commuting services to employees.
The car could gradually move from being a privately owned asset toward being a service.
That would be one of the biggest changes in transportation since the mass adoption of the automobile itself.
How Robotaxis Could Change Everyday Life
The most important impact of robotaxis may not be technological at all. It may be psychological.
For more than a century, mobility in many developed countries has been tied to the ability to drive. A driver's license became a symbol of independence. A family car became a symbol of adulthood. Teenagers waited for the day they could drive alone.
Autonomous transportation challenges that relationship.
Imagine waking up on a winter morning and ordering a vehicle without searching for keys. Imagine sending children to an approved destination in a monitored autonomous vehicle. Imagine leaving a stadium after midnight and entering a car that drives itself home.
For commuters, the journey itself could become productive time.
People could read, work, study, watch educational content, make calls or simply sleep. The traditional distinction between travel time and personal time would begin to disappear.
This could have enormous economic consequences. A worker who spends an hour commuting each way currently loses two hours of potential personal or productive time. Autonomous travel could convert part of that time into usable time.
There is also a major social benefit for people who cannot drive.
A New Mobility Revolution for Older and Disabled People
Autonomous transportation could be transformative for elderly people.
Driving becomes more difficult as vision, reaction time and physical ability change. Families often face a painful dilemma when an older relative can no longer drive safely. Taking away the car can also mean taking away independence.
A reliable robotaxi could separate mobility from driving ability.
An older person could travel to a medical appointment, grocery store, community center or family home without needing a relative to provide transportation.
For people with disabilities, the potential is even broader.
Accessible autonomous vehicles could reduce dependence on specialized transportation systems that often require advance booking. A passenger could theoretically request a vehicle adapted to their needs and travel whenever required.
However, accessibility will not happen automatically. Autonomous vehicles must be designed with wheelchair access, visual and hearing assistance, emergency communication and secure boarding procedures in mind.
Tesla and its competitors will therefore be judged not only by whether the cars can drive themselves, but by whether the transportation system serves people who have historically faced mobility barriers.
What Happens to American Cities?
The biggest long-term question may be what robotaxis do to the physical shape of cities.
American cities devote enormous amounts of land to parking. Office buildings have garages. Shopping centers have huge parking lots. Apartment buildings require parking spaces. Streets are designed around the assumption that vehicles will spend most of their time parked.
If shared autonomous transportation becomes widespread, parking demand could fall.
That could free valuable urban land for housing, parks, offices, schools and public spaces.
But there is a paradox.
If robotaxis become extremely cheap, people may travel more frequently and over longer distances. Vehicles that previously stayed parked could spend more time moving. That could increase congestion rather than reduce it.
The outcome will depend on policy.
Cities could encourage shared rides, dynamic road pricing and efficient pickup zones. Or they could allow empty autonomous vehicles to circulate endlessly while searching for passengers.
The same technology could either reduce congestion or make it worse.
This is why autonomous driving cannot be considered merely a private-sector innovation. It is also an urban-planning challenge.
The Jobs Question
Every transportation revolution creates winners and losers.
Truck drivers, taxi drivers, rideshare drivers, delivery drivers and other professional motorists could face significant disruption if autonomous systems become reliable and affordable.
The scale of the impact is difficult to predict. Autonomous vehicles will not eliminate every driving job overnight. Regulation, weather, complex routes, union agreements, customer preferences and technological limitations could slow adoption.
But the direction of travel is clear: if a machine can perform a driving task more cheaply and safely than a human, businesses will have an economic incentive to use it.
This is part of a much broader automation trend. As discussed in WorldAtNet's analysis of AI and the changing workforce, automation is no longer confined to factories. It is moving into professional services, logistics, transportation and everyday consumer activities.
The answer cannot simply be to stop automation. Instead, governments and businesses will have to prepare workers for the occupations that emerge around autonomous systems: fleet operations, AI supervision, robotics maintenance, cybersecurity, vehicle servicing, data management and advanced logistics.
The robotaxi may remove the driver from the front seat while creating new jobs elsewhere in the transportation ecosystem.
Safety: The Argument That Will Decide Everything
No robotaxi story can avoid the safety question.
A human driver makes mistakes. People become tired, distracted, angry or intoxicated. Humans also have limited reaction times and imperfect vision.
Autonomous vehicles have different weaknesses. They can misunderstand unusual situations, encounter sensor limitations, misclassify objects or make unexpected decisions when road conditions fall outside their training and operational assumptions.
The comparison therefore should not be “humans make mistakes, robots do not.” Robots make mistakes differently.
The real question is whether autonomous systems can make substantially fewer dangerous mistakes than human drivers across the conditions in which they are allowed to operate.
Waymo has reported a large reduction in serious injury crashes across its fully autonomous operating history. The company said in 2026 that its system had accumulated 127 million fully autonomous miles and recorded a 90 percent reduction in serious-injury crash rates compared with its human-driver comparison benchmark. These are company-reported figures and should be interpreted alongside independent regulatory and safety analysis.
Tesla faces a different burden because its autonomous strategy is being deployed at the intersection of a huge consumer vehicle population and a more generalized AI approach.
The regulatory scrutiny arrived quickly. On September 4, 2026, the U.S. National Highway Traffic Safety Administration opened an audit query into Tesla's certification that Cybercab complies with applicable Federal Motor Vehicle Safety Standards.
The investigation does not itself establish that Cybercab is unsafe. It demonstrates something more important: once a company puts a production autonomous vehicle without conventional driving controls onto public roads, regulators have to determine whether the existing safety framework adequately fits the machine.
That regulatory debate will shape the future of the entire industry.
Washington Has Entered the Robotaxi Debate
The timing of Tesla's launch is politically significant because Washington has just announced a national strategy for automated vehicles.
The U.S. Department of Transportation unveiled an Automated Vehicles National Strategy on September 3, 2026. The strategy emphasizes American leadership, safety, regulatory modernization and reducing unnecessary barriers to autonomous vehicle deployment.
That creates a delicate balancing act.
The United States wants to remain the world's leading center for artificial intelligence, robotics and advanced transportation. Excessive regulation could slow innovation and push investment elsewhere. But inadequate regulation could undermine public confidence after a serious crash.
The Cybercab is particularly important because it removes the traditional fallback controls. Federal regulators have historically designed vehicle standards around the assumption that a human occupies the driver's position. Purpose-built autonomous vehicles challenge that assumption.
Washington therefore has to answer a series of questions.
How should a vehicle without a steering wheel be certified? Who is legally responsible when an autonomous vehicle causes a crash? What data must manufacturers share after an incident? How should cybersecurity be regulated? What standards should apply to remote assistance? How should states and the federal government divide authority?
The answers will influence not only Tesla but Waymo, Zoox, automakers, technology companies and foreign competitors.
The United States is effectively writing the regulatory architecture for a new category of transportation while the technology is already arriving on city streets.
The Energy and Climate Dimension
Robotaxis are likely to be electric because electric drivetrains are well suited to fleet operations. They have fewer moving parts than combustion engines and can be efficiently managed through centralized charging systems.
If robotaxi fleets replace a significant share of gasoline-powered urban trips, petroleum demand could eventually decline.
But autonomous driving alone does not guarantee lower emissions.
If robotaxis create millions of additional vehicle miles, some of the environmental benefit of electrification could be offset by increased electricity demand and traffic.
The cleanest outcome would be a combination of electric autonomous vehicles, high fleet utilization, shared rides and increasingly low-carbon electricity.
That is why the robotaxi revolution belongs in the wider discussion about the future of electric mobility, battery technology and smart cities.
For more context, WorldAtNet's coverage of future cities and smart technologies examines how AI, sensors and connected infrastructure are changing urban life. Robotaxis could become one of the most visible parts of that transformation.
Why the Tesla-Waymo Race Matters Beyond America
The American robotaxi contest is already part of a global race. China has developed major autonomous ride-hailing programs, including Baidu's Apollo Go, while companies such as Pony.ai and WeRide are expanding autonomous mobility. Japan and Europe are also moving toward regulated automated-driving deployments.
The competitive issue is not simply who builds the best car. It is who develops the best combination of artificial intelligence, batteries, manufacturing, mapping, regulation and fleet economics.
This is another chapter in the wider global artificial-intelligence competition. As WorldAtNet has explored in its analysis of the global AI race, the next phase of technological competition is increasingly about physical systems rather than software alone.
A successful robotaxi network could become strategic infrastructure. Countries that master autonomous mobility could gain advantages in logistics, urban productivity, manufacturing and AI development. Countries that fall behind may eventually depend on foreign autonomous-driving platforms.
That makes the robotaxi race part of industrial policy as well as consumer technology.
There is also an important geopolitical dimension. Autonomous vehicles require advanced chips, computing infrastructure, batteries, sensors, telecommunications and cloud or edge-computing capacity. In other words, the robotaxi is a rolling demonstration of an entire technology ecosystem.
That is why governments are increasingly interested in autonomous driving. The technology sits at the intersection of transportation policy, artificial intelligence, industrial strategy, energy security and national competitiveness.
What Could Go Wrong?
The excitement surrounding robotaxis should not hide the risks.
First is technology risk. Autonomous driving must handle edge cases that humans encounter only occasionally but which can have catastrophic consequences. A system can perform brilliantly for millions of miles and still fail in a rare situation.
Second is cybersecurity. A connected fleet creates an enormous attack surface. A compromised vehicle is no longer simply a stolen car; in a large network, cyberattacks could potentially affect transportation infrastructure at scale.
Third is economic concentration. If a small number of technology companies control large shares of urban transportation, they could gain enormous influence over pricing, mobility data and access.
Fourth is congestion. Cheap autonomous rides could increase travel demand and empty vehicle movements.
Fifth is employment disruption. Driving-related livelihoods could eventually be affected as autonomous systems become capable of handling more routes and operating conditions.
Sixth is privacy. Robotaxis will operate in public spaces while collecting enormous amounts of visual, location and operational data. Governments will need clear rules about what is collected, why it is collected and who can access it.
Seventh is public trust. A single dramatic crash can have an outsized effect on public perception. Autonomous transportation therefore has to be not only statistically safer but visibly accountable.
There is one additional risk that receives less attention: unequal access. If autonomous transportation initially becomes concentrated in wealthy neighborhoods, it could deepen existing mobility inequalities. The long-term social value of robotaxis will be much greater if they are available across a broad range of communities rather than functioning primarily as a premium service.
What the Next Five Years Could Look Like
The next phase will probably not be a sudden moment when every American car becomes autonomous. The transition is more likely to occur city by city and use case by use case.
Robotaxis will first become common in dense urban areas with predictable road networks and strong demand. Airports, downtown districts, technology campuses and tourist zones are natural early markets. As reliability improves, service areas will expand.
Eventually, suburban routes and highways will become more important. Long-distance autonomous travel could create new competition with trains, buses and traditional car ownership.
The automotive business could also change. Today, manufacturers compete by selling consumers cars. In an autonomous future, they could compete by selling transportation capacity.
A vehicle could be owned by an individual, leased to a fleet operator, shared by a family or deployed commercially as a robotaxi. The distinction between personal vehicle and commercial vehicle could begin to disappear.
Tesla's most ambitious possibility is that its software becomes the platform connecting those vehicles into one network. If that happens, the company would no longer be simply an automaker. It would be operating a global mobility platform.
But Waymo's advantage should not be underestimated. It already has millions of real autonomous trips behind it and is expanding to more cities. If it continues to demonstrate strong safety and reliable service, it could become the benchmark against which every other autonomous company is measured.
The winner may ultimately be determined not by which company has the most impressive prototype, but by which company can deliver the safest ride at the lowest cost with the fewest restrictions.
There is another possibility: the market may not have one winner. Tesla could dominate mass-market autonomous vehicle production while Waymo specializes in operating fleets. Automakers could license autonomy from technology companies. Ride-hailing platforms could integrate several autonomous fleets. Public transit agencies could use robotaxis as feeder services.
The future could therefore be an ecosystem rather than a single dominant network.
The World After the Driver
Tesla's Cybercab launch is important because it changes the question.
The question is no longer whether autonomous taxis will exist. They already do.
The question is how quickly they can scale, how safe they can become and how profoundly they can change the economics of movement.
Waymo has already demonstrated that fully autonomous commercial ride-hailing can operate in major American cities. Tesla is now attempting to push the concept into a different phase with a purpose-built vehicle that removes the steering wheel and pedals and is designed from the beginning around autonomous operation.
That distinction could become enormously important.
If Tesla succeeds, the robotaxi may become less like a futuristic taxi and more like a mobile utility. People may stop thinking about owning a car and start thinking about access to transportation.
A teenager may not need to wait for a driver's license to visit friends. An elderly person may remain independent longer. A disabled passenger may gain new freedom. A commuter may turn travel time into work or rest. A family may decide that one car is enough — or no car at all.
Cities could reclaim parking land. Businesses could rethink office locations. Airports could redesign curb space. Hotels could integrate autonomous transportation. Public transit could use robotaxis to connect neighborhoods to rail stations.
But the opposite future is also possible.
If autonomous vehicles are cheap but mostly empty, roads could become more crowded. If companies collect excessive mobility data, privacy could suffer. If regulators move too quickly, public trust could be damaged. If automation outpaces worker transition programs, communities dependent on driving jobs could face severe economic disruption.
The technology therefore does not determine the future by itself. Policy, urban planning, economics and public trust will determine what society does with it.
That is why Tesla's Cybercab matters far beyond Tesla.
It is an early physical expression of a much bigger shift: artificial intelligence moving from the screen into the street.
For more than a century, the automobile gave humans control over movement. The next era may reverse that relationship. The passenger may simply state where they want to go, and the machine will handle everything between here and there.
The most important revolution may therefore not be the disappearance of the driver. It may be the disappearance of the assumption that transportation requires one.
And if that assumption finally breaks, everyday life could change in ways that are difficult to see from the driver's seat of today's world.
Sources and Further Reading
This article uses current company and government information alongside independent reporting. Readers should consult primary sources for regulatory updates and service availability.
- Tesla Robotaxi — official service information
- Tesla Cybercab FAQ
- Tesla Cybercab Rider Guide
- Waymo — official autonomous ride-hailing information
- Waymo's September 2026 expansion to Denver, San Diego and Tampa
- NHTSA investigation into Tesla Cybercab certification
- U.S. Department of Transportation — National Strategy for Automated Vehicles
- Reuters — Tesla Cybercab public launch and regulatory context
- Associated Press — Cybercab launch and autonomous-vehicle competition
Editorial Note
This article is intended for general informational purposes. Robotaxi availability, fleet sizes, regulations, safety investigations and operating areas can change rapidly. Statements attributed to companies should be understood as company-reported information unless independently verified. Safety statistics should be interpreted carefully because different operators may use different definitions, operating environments and comparison groups.
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