On the road with Uber: an ethnography

Abstract

The article aims to investigate the work management strategies undertaken by Uber in relation to its drivers. Using the observant participation method, the researcher drove a car performing races mediated by the platform for a period of four months in the Metropolitan Region of Salvador, Bahia. The company operates with a management strategy that encourages false entrepreneurship and, at the same time, hides an employment relationship: dissimulation. To do so, it makes use of tactics such as encouragement, task management, pedagogism, fraud, risk-sharing and obscurantism, as ethnography has managed to identify.

Keywords:
Uberization of work; Employment relationship; Ethnography

Resumo

O artigo tem por finalidade investigar as estratégias de gestão do trabalho empreendidas pela Uber em relação aos seus motoristas. Fazendo uso do método da participação observante, o pesquisador conduziu um automóvel realizando corridas mediadas pela plataforma por um intervalo de tempo de quatro meses na Região Metropolitana de Salvador, Bahia. A empresa atua com uma estratégia de gestão que estimula um falso empreendedorismo e, ao mesmo tempo, esconde uma relação de emprego: a ocultação. Para tanto, faz uso de táticas como incentivismo, tarefismo, pedagogismo, estelionato, compartilhamento de riscos e obscurantismo, como a etnografia conseguiu identificar.

Palavras-chave:
Uberização do trabalho; Relação de emprego; Etnografia

Introduction

Initially, the digital network was celebrated as a medium of unlimited freedom. In this sense, Microsoft's first slogan in 1994 asked "Where do you want to go today?", suggesting freedom and mobility without borders on the Internet (HAN, 2020, p. 18). Freedom, innovation, and technology went hand in hand, and the internet evolved with these concepts. In Web 1.0, corresponding to the early days of the Internet, content was distributed through the World Wide Web; in the era of Web 2.0, called the people's Internet, this content is now hosted on a single computer network owned by a single organization, administered by the organization that owns a piece of software, called a "software platform" (SLEE, 2020, p. 223). Finally, Web 3.0 corresponds to the Internet of Things and makes a total record of life possible (HAN, 2020).

Innovations in digital technologies and big data - the ability to quickly and cheaply exchange large amounts of data and information between individuals, companies, and devices - have laid the foundations for the rise of the digital economy (ILO, 2021) and have also made it possible to make predictions about human behavior (HAN, 2020).

Globalization has grown exponentially with datafication/big data, for example, allowing the Uber platform in the United States to recruit and direct drivers work in many countries in a broader system of on-demand work through apps (STEFANO, 2016).

Uberization is part of the context of a new capitalism. Shoshana Zuboff (2020) sees a scenario called surveillance capitalism, consisting of the extraction of behavioral superavit: human behavior in its entirety is quantified and categorized to allow predictions and prognoses as a saleable commodity to corporations which, in turn, aim not only to promote highly effective advertisements but also to market products and even modify human conduct for profit.

This article aims to investigate the management strategies Uber uses in relation to its drivers, in this process called the uberization of work. It presents an ethnographic study that empirically explores how the current mechanisms for disciplining the workforce through the platform work. The analysis results from four months fieldwork as a driver and 350 hours of using the app. Through observant participation, this approach sought the subjective and concrete experience of providing service to the Uber company as a car driver from December 2021 to March 2022 in the Metropolitan Region of Salvador, Bahia, Brazil.

In addition to observational participation, we used the walkthrough method (step-by-step interaction with the app), analysis of company documents, messages and videos from the platform, screenshots, social networks, messages from app interlocutors, a literature review, and, finally, netnography, due to joining a WhatsApp group made up of app drivers.

1. FEAR AND RISKS IN APP-BASED WORK

I pull the door handle and head for the garage, where old paint cans are mixed with the beach umbrella. I see the red Honda with the Uber sign barely centered on the windshield. I take a look at the car's bodywork; there's cat hair and bird poop on the roof, as well as a lot of dust - the passengers will complain. It's only been seven days without a ride; why is it like this? I press the button on the key that unlocks the alarm and opens the car. I take the yellow flannel in the door pocket, on top of the sunglasses I usually wear during races, as the sunlight is very intense, and use it to remove dirt and stains from the car's body. I only do this on the passenger side; I can't afford to do it on the whole car, and in the end, I just need a good note from the passenger. The fenders will still be dirty because if I went to the car wash, I'd lose half an hour without driving. I look inside the vehicle for something my children might have forgotten. I remove the dust from the carpet by knocking it against the wall and rubbing it carelessly with the same dirty flannel. I throw away the gum wrappers I had left for the passengers the week before, which only one child had ventured into. Everything else is fine, but I still think I will get a bad review because the black film on the glass only highlights the dirt on the car. I'm going to start work with a bad feeling. I fill my bottle with water from my home filter and apply sunscreen that leaves my arms greasy. Now I understand why app drivers wear those colorful sleeves on their arms; it's much better than getting sustained, as has happened to me. I place the cell phone in the central holder. I'm ready.

The change of language in this section to the first person is necessary due to the assumptions of ethnography itself. Their writing, without the appropriate language, is not only difficult but also unproductive from a scientific point of view. In this sense, it also reflects the impossibility of this report being detached from my life trajectory and social place. Recognizing my condition as a historical being was the way I found to take an approach that dialectically associates the realization of this research with my existence.

I experience a lot of downtime, with the car switched off, waiting for races in January. At this time of year, although some tourists are going to laboratories and pharmacies to get tested for COVID-19, and teenagers are going to friends' houses, traffic is very weak, with few drivers in the square and few passengers requesting rides, because school and professional vacations are hurting demand, so I spend a lot of time alone and idle.

Staying put is a way of saving money and having fewer expenses; it's not an exercise in autonomy. I've been on standby increasingly, waiting for the platform to call me at work when I stay in the car. You can't say I'm resting either because, in addition to the attention I need to avoid muggings, I always have to be on the lookout for places with dynamic fares or new requests. Without support points, there is a feeling of discomfort and insecurity, as the driver needs to be vigilant not to become a victim of theft or robbery of the cell phone or the vehicle: - You need to catch the view! - they teach me. Fear is a very present feeling in this profession.

My first experience racing in a dangerous place was in the neighborhood of Portão, in Lauro de Freitas, a municipality adjacent to Salvador, in the morning, when the passenger asked me to lower the windows so the local drug dealers could see me. He sat next to me - and not in the back seat, as required by the platform - so they wouldn't know I was an app driver. Two teenagers were sitting on the sidewalk who, according to him, was armed and acting as “olheiros” (observers) for the faction leaders: "Don't ever take passengers after Malibu Warehouse", where I left him, because after there, the drug trade dominates, in the face of a war between rival factions. I knew I shouldn't wear Uber stickers for this reason, and I was aware of the high crime rates in Bahia, but it's scarier when you experience it for real. Gradually, more reports from passengers began to refer to bar fights and shots fired upwards at paredões (popular parties that take place in the streets, with a large contingent of people and loud, mobile stereos fitted to cars).

When I start driving around the city for many hours, I see a lot of traffic accidents, such as people hanging from buses that fall over, motorcyclists or cyclists with bodies lying in the street, or accidents that result in corpses covered in black plastic. Brutality is being trivialized.

Another risky situation occurred in the neighborhood of Cosme de Farias, on the outskirts of Salvador, known for its statistics on violence, when the passenger disembarked on a narrow slope - which had a samba circle at the top, like in a scene from a brazilian soap opera - and could only exit backward, one car at a time. Still, the passenger helped me maneuver the exit, asking me twice if everything was all right (I wondered if it was an ambush). In the end, he gave me a tip of R$10.00 in cash.

The streets on the outskirts of the capital of Bahia are a festival of means of transport and characters: bicycles, pedestrians, motorcycles, vans, topics, buses, carts, garbage trucks, and cars; all mixed up with children returning from school, ladies buying cacetinho (a small bread), workers returning home, teenagers playing ball in the middle of the street, street sweepers and street vendors, with their multiple colors, making a point of affirming the blackness of the capital of Bahia.

The previous Friday, an app driver was murdered in Salvador, in the Itapuã neighborhood, where I have boarded and disembarked passengers several times, which left me very shaken by the news (CORREIO24HORAS, 2022), whose video from a security camera of the exact moment of the crime, ran freely on the social networks of app drivers. They had been set up to steal his car and, when the driver tried to escape, one of the gang shot him in the head. In previous years, at least seven app drivers were murdered in the city (SOCIEDADE ONLINE, 2019, IBAHIA, 2020, BAIANO, 2021, UOL, 2019). Still, there doesn't seem to be an official statistic for this category of workers.

A group went to the driver's funeral on Sunday at Campo Santo Cemetery, and there were two protests to put pressure on the authorities, one at the police station where the bandits were being held and the other at the Nina Rodrigues Legal Medical Institute (LMI) in the capital, where the accused were due to undergo a forensic examination. I participated in the protest at the LMI and spoke to motorists, all of whom were outraged at the depravity of the crime and without hope for justice since it was likely that, after the custody hearing, some of the primary defendants would go free. Slogans such as "murderers" were uttered when the police car disembarked the suspects, and some drivers wrote "mourning" on the rear windows of their cars that day. Some also questioned whether the right thing for the victim to do was to try to run away. There were comments about the small number of colleagues participating in the protest, indicating a lack of solidarity. There was discussion about the direction of the category, given the emergence of new leaders (competing cooperatives) who were "playing one against the other" and undermining the current Union of App Drivers, Cooperative Drivers and Outsourced Workers in General (SIMACTTER), which was leading the protest.

The protest and mobilization, however, should be seen as an act of solidarity that needs to be weighed against the daily struggle for survival that the platform imposes through payment exclusively for races: standing still for an hour without receiving requests to participate in a political movement, harms the drivers' financial lives and Uber doesn't seem concerned about the routine of robberies, kidnappings and murders that is witnessed daily.

In a day, the average commuter travels 200 km or more. The shortest trip I made during my fieldwork was 500 meters, while the longest was 48.4 km, lasting 51 minutes and costing R$69.01 (approximately 14 US$). Because they are extremely rare, it is practically impossible for a driver to make ten runs of this type in a working day, with an imaginary projection of a turnover of R$700.00/day. Each run had an average distance of 7.48 km throughout the study.

My maximum time behind the wheel in a single day was 12 hours, and my longest time online was 16h 42m. Each race lasted an average of 13 minutes. Considering that there is also waiting time and travel time until the passenger boards (this is not hours in itinere under paragraph 2 of article 58 of the CLT (Consolidated Labor Laws, the main Brazilian labor law), as the driver is already working when he gets into the vehicle), it is very difficult to make more than three journeys in an hour. Earning more than R$30 per hour is an income for the privileged.

Of all the 350 races held, there were only two compliments: "Comfortable, clean car, super polite guy," was one of them. On only three occasions, I asked why I was taking Uber. There were 218 5-star reviews and only one 1-star, the minimum grade. In the experiment, which lasted four months, only four users requested rides not mediated by the app, which suggests that users' trust lies in the relationship with the Uber company and not with its drivers, which prevents the formation, in practice, of any stable fixed clientele.

After meeting around 400 passengers during the ethnographic experience, I didn't make friends with any of them. The platform's advertising that this work allows you to meet new people proved misleading. Since my deactivation after the field research, Uber has continued to send messages, like the one I received in June 2022, asking me to drive again, offering promotions that pay R$100.00 for ten trips.

2. FINDINGS OF RESEARCH

The observant participation method sought to update the concept of subordination for digital platform workers from the perspective of the employer (employer power).

Uber works with two basic axes of labor management. The first axis is called dissimulation, while the second axis is called despotism, subdivided into a cycle of command, monitoring, and punishment. This article aims to discuss mainly the axis of dissimulation.

Combined with the need to earn an income, which is inherent to the labor market (you work to eat, and you eat to work) and which prevents any work from being truly free, Uber's management strategy encourages false entrepreneurship that hides an employment relationship - dissimulation - which, in turn, is subdivided into six other tactics: encouragement, task management, pedagogism, fraud, risk sharing and obscurantism.

These management methods have a dual purpose: to camouflage the employment relationship and, at the same time, to promote a simulacrum of autonomy in the figure of the worker. As by-products: it seeks to instill a competitive "more work, more profit" mentality in the driver; it encourages adherence to a wage model that pays exclusively for the task performed; it promotes the apprenticeship of workers to the molds desired by the company; it encourages the radicalization of profit at every possible opportunity, even if it uses illicit means to do so; it encourages the sharing of workers' goods and property for the benefit of the platform and; it omits information to prevent any shred of autonomy or collective resistance to the platform's corporate interests. All this against a backdrop of neoliberal rationality proactively stimulated by the state whose parameters are interpersonal competitiveness and the corporate form as the predominant one (DARDOT; LAVAL, 2016).

The despotism axis, in turn, creates a normative framework within the platform's regulatory power that promotes a flurry of commands and employer imperatives aimed at exercising the power of command under the euphemisms of guidelines, instructions, tips, and the improvement of conduct that the platform considers advantageous; it exercises intense monitoring of all drivers' attitudes - including dialogues with passengers - to finally act surgically to punish deviant conduct.

Uber promotes this ideological persuasion all the time, on a daily and insistent basis, and this tactic begins even before registration with the offer of large and misleading salaries to recruited drivers. It is essential to understand these management techniques.

2.1. Encouragement

The incentive forged by Uber aims to generate ideological commitment on a large scale among its drivers. This conceptual category does not derive from an incentive perpetrated by an independent and disinterested agent in the driver's conduct. It's a deterrence-persuasion whose financial benefits will be extracted directly by the platform. This engagement is part of a larger backdrop stimulated by the company, consisting of the prior purchase of vehicles, a declaration to the family about the intention to be an app driver, registration in the app, and the assumption of links to other commercial contracts, such as telephone plans, toll devices or digital banks, which transcend the direct relationship with this worker.

Within the idea of merging the producer with the consumer (prosumer), the registration of an approved Uber driver opens the door to soft debt bondage since the screening carried out by the platform acts as a credit guarantee for other consumer and worker exploitation companies, all of which want a slice of this market¹.

In addition to this double exploitation, this tactic also compromises the worker with the platform, preventing them from exercising their full freedom. Partner companies capture this target audience, absorbing drivers as purchasers of other products and services. According to Zuboff (2020), since it is possible to anticipate the behavior of this social group - their entire behavioral history is cached - these users are seen as sources of raw material for a digital age production process that targets a new business client in the operations of surveillance capitalists.

As for the aspect of the driver as a profit producer, the platform encourages rewards through gamification in the style of sticks and carrots². According to Schmidt (2017), gamification is a technique that allows platform providers to protect favorable user behavior by awarding virtual credit and points and ranking users' performance in public leadership. The points awarded often serve as a pseudo-occurrence within a platform's reputation economy but cannot be transferred to others. Gamification turns paid work into a game, often in a manipulative and behavioral way.

The Uber app uses words and symbols (emojis) that stimulate positive emotions (good humor, joy, and satisfaction with human diversity and gains) or negative emotions (fear of being disconnected). Its features, colors, and sounds are similar to games that can be played on mobile devices, using images and graphics reminiscent of children's cartoons. However, this does not dispense with issuing orders that are communicated in a variety of ways; after all, man is a machine that obeys voice commands (WEIL, 1996, p. 171)³, but stimulating maximum work through the promise of earnings is an integral part of encouragement and gamification.

The digital platform sells the idea that your pay depends only on you (CASTRO, 2019, p. 60), representing a radical approach to the myth of meritocracy.

In this sense, devices of rewards and punishments, encouragement and discouragement systems, replace and complement sanctions to guide the choices and conduct of individuals when punitive situations are not entirely feasible or desirable. These coercions force individuals to adapt, placing them in situations that force them into the "freedom to choose", that is, to manifest in practice their ability to calculate and govern themselves as "responsible" individuals, as required by the model (DARDOT; LAVAL, 2016, p. 217-218). For app drivers, there is this obligation to choose within the prior regulatory framework so that the flow of services offered by Uber is not interrupted.

Encouragement operates as follows: while the platform invites drivers to become partners, offering them prizes for missions, agreements with accredited companies, and creating playful career promotion categories, it also threatens them with warnings, blockages, pay cuts, and deactivations. These are crude means, using both subjection and the "lure" of gratification as a stimulant through a method of domestication (WEIL, 1996, p. 152).

If, on the one hand, the missions that are accomplished represent rewards of a salaried nature in kind, the missions that can't be achieved - there's always a new mission - push the app driver to constantly accept rides, resulting in a job with remuneration that is lowered by the ordinary prices they charge, but which are left in favor of the platform when not achieved: they are promises of salaries that are not paid in proportion to the goals achieved.

The payment of supposed prizes materialized in missions makes it clear that the company's claim that it only connects passengers to drivers is untrue. As Uber pays the worker directly, regardless of the route or the specific ride, the wage nature of the consideration is evident, given that this remuneration is not being paid to the driver (supply) by the passenger (demand), but by the company.

In this game, in any scenario, the platform has the advantage. In fact, for the company, it's just as good as seeing that the drivers are fulfilling their missions as it is to see that these workers haven't managed to meet their targets because, in this way, trips made without the payment of any bonus act as a "war booty" for defeated drivers who have worked hard but haven't managed to complete their objectives and targets.

These missions not only aim to reward drivers who complete the specified number of runs but also to break the resistance of drivers who are refusing too many calls and force them to work constantly, with successive acceptances, set times, and a large number of runs, to undermine this autonomous style of worker.

As the ethnography showed, there is no equal and impartial basis for offering these incentives. Dynamic pricing depends on each driver, how much they have earned in recent weeks, how much they have earned that day, and their historical acceptance/cancellation rates. As the platform knows the employee's entire behavioral experience, it can offer the right incentive, in the right measure and at the right time, as it can predict with a good margin of certainty what their "free" behavior will be. For Uber to extract this data from the driver's habitus, the driver doesn't need to enter any information on the app's screen, as their entire work history, behavioral tendencies, earnings, and debts are available for datafication.

To a large extent, Uber requests drivers to work at certain times or locations through positive and negative financial incentives that force workers to stay online or move to locations with dynamic prices. All this added to the fact that the prospect of reasonable earnings, necessary for subsistence and paying off the debts resulting from the initial investment to enter the business, is the result of the pricing inherent in the platform's regulatory power, which also requires long hours of daily work from the drivers (OLIVEIRA, 2021).

These aspects of behavioral conditioning become addictive, as I was able to experience in my fieldwork. Natasha Schüll (2012, p. 507) studied the relationship between addicted gamblers and slot machines typical of casinos in the United States. The author calls this moment the "machine zone", which is nothing more than a state of self-forgetfulness in which the person is dragged along by an irresistible impulse in which they seem to be "being played by the machine" and not the other way around. This "machine zone" achieves a complete immersion associated with a loss of self-awareness, automatic behavior, and a total rhythmic absorption that occurs alongside a wave of compulsion. For app drivers, the location of the cell phone in the holder, the comfort of their car seat, their hands firmly on the wheel, the alternating visual landscapes of the city, and the rotation of passengers project a very well-fitted device, whose architecture is very stimulating and generates a pleasurable sensation, similar to the consumption of a drug.

This encouragement, therefore, extends to other moments and dimensions beyond the moment when the contract is executed: it is present in how workers are recruited, in the system of practical and quick registration on the app, in the exciting advertising to recruit drivers and even in the technological strategies to make workers more productive (promises of advantages and pyramid schemes). It tries to completely capture the subjectivity of the worker and turn him into the ideal driver, the one who works on Sundays, at dynamic prices, with very clean cars, who offers courteous service, accepts crazy rides, and who also convinces other colleagues to do the same.

2.2. Task management

The term task management is used as a synonym for the Uber platform's management tactic to obtain greater ideological consent from workers in constructing its goal through the imposition of the traditional piece-rate wage.

Uber's salary does not consider the month, week, or days worked by the driver. The salary is not paid for the hours the driver is online, nor from the moment he accepts the ride. Nor is there any remuneration according to the number of runs made. It is paid exclusively for the mileage traveled with passengers in the vehicle's cabin, representing the complete freeze-drying of wages (ANTUNES, 2018). This method pressures workers to accept rides so that more users are in the car on the move.

Initially, it should be said that the change from the classic form of remuneration (time-based pay) to piece-rate or task-based pay generally confuses legal hermeneutics. By opting for remuneration that does not consider working time but exclusively the task, the platforms strategically pave the way for the seductive discourse of the self-made entrepreneur (ABÍLIO, 2019).

In the case of uberization, the conceptual confusion between autonomy and piece-rate pay is deliberate and encouraged by Uber: "When he wants to drive, all he has to do is turn on the app. There is no minimum daily, weekly or monthly time for the partner driver to use the platform" (UBER, 2020b).

Remember that "partner" refers to someone no different from the other, an equal or similar. Still, the relationship between an app driver and the platform can be anything but a partnership.

The ILO itself (2020) has taken up the uberian premise: "Working on digital platforms offers workers the opportunity to work anywhere, at any time, and to take on the tasks that suit them," as if this were a golden opportunity and not a business demand, and without noting that any place, any time and any task, in practice, means anywhere, at any time, and for any task.

Payment for production is not a new practice of work intensification (CANT, 2020). In Brazil, piecework wages are legally stipulated in Art. 78 of the Consolidated Labor Laws (CLT) since 1943, stipulating that when wages are set for this type of task or piece, the worker must be guaranteed a daily wage that is not less than the minimum wage, a rule that the platform has not even observed.

Given the piece-rate wage, it is natural that the worker's interest is to employ his labor power as intensely as possible, which makes it easier for the capitalist to raise the normal degree of intensity: "The piece-rate wage is the form of wage best suited to the capitalist mode of production" (MARX, 2015, p. 762-764). Friedrick Taylor himself announced at the beginning of the 20th century that the scientific organization of work combined with piece-rate wages would put an end to the class struggle because their systems are based on the common interest of the boss and the worker, as well as the consumer public itself (WEIL, 1996, p. 148).

Productivity pay is often associated with the sticks and carrots system, as this wage system pushes workers to work when the pay per task/run is too low and unable to meet their survival needs. Another inconspicuous effect of salary is its use as an instrument of managerial power when it performs that little bit of magic, speeding up the pace, agitating the body, increasing attention, and almost always producing stress. For the employer, although salary seems to be just a cost, it can also be an income (VIANA, 1997).

Wages also become an instrument of managerial power when it comes to piecework wages or wages that promise prizes and bonuses. In this case, even the employer's service can include a new service from the employee or, more precisely, an implicit command to intensify their work.

The way piecework wages are defined consists of a) individualized remuneration per task/product determining the wage to be received; b) a controlled/limited transfer of work demand, with the establishment of productivity targets; and c) a maximum amount of physically possible for each worker defining the working day limit (COLLI, 1998). These requirements will consequently engender the employee's limited autonomy regarding the time and manner of performing the service.

Productivity pay is imposed exclusively by the employer within its regulatory powers. When the employer defines the remuneration system this way, it results in a false desire on the part of the employee, who is forced to produce more to earn more.

Obeying the control rules imposed by this system of task management and encouragement takes a heavy toll on app drivers. The drivers interviewed show hopelessness and annoyance at the constant changes in the dynamics of piece-rate wages. "The new work is imposed suddenly, without preparation, in the form of an order which must be obeyed immediately and without reply" (WEIL, 1996, p. 159). Unhappy, Uber's digital workers complain and reminisce about a time - "right at the beginning" - when they made a lot of money.

The work of the app driver requires three systems to be put in place simultaneously: a pay-as-you-go system, an evaluation or ranking system, and a system of bonuses and incentives. It's a salary for productivity that depends on the passenger's evaluation, which can have repercussions in terms of higher or lower future earnings (higher categories or promotion levels, in the prizes paid for missions, or even directly, through tips), which is also a variable of meeting incentive targets openly offered by the platform. In turn, such systems always refer to an individualized evaluation of results linked to the worker's production (DARDOT; LAVAL, 2016, p. 227).

In addition to the individualization of the social value of the worker, there is an exacerbated individualization of his salary. The specificity of the type of salaried employment that exclusively considers payment for productivity, rather than the traditional monthly unit of time, implies greater competition between workers and a greater transfer of management powers to the app's algorithms, managed by the employer. And where there is directive power, there is employee subordination. App drivers only have an illusion of this independence due to task management because they always and necessarily have to sell their labor to some platform, be it Uber, 99 Pop, or Indriver.

Wages are only paid to employees. If the platform were free, without the abusive discount on Uber's fee, there would be no question of the existence of an employment relationship. Still, in addition to subordination, there is also onerousness, which is not exclusively associated with task management. The fact that Uber pays its drivers remuneration for missions completed reinforces the salaried nature of its payments to its workers.

2.3. Pedagogism

Mixed in with the encouragement and task management, the platform also promotes a lot of pedagogism through professional training materialized in digital content with instructions on all the characteristics of the app driver's activity. In platform capitalism, in part, workers are trained for these professions beforehand. The employer gauges the prior qualification by contractually demanding documents proving skills such as driving, delivering food, and dealing with mobile technology. However, as the empirical research has shown, much more is learned after joining these companies.

These messages and communications are like professional learning, as they set guidelines on what the app's features are, what behavior is expected of the driver, provide advice and tips from other co-workers, prevent damage to the company such as possible compensation for harassment, discrimination or criminal conduct by drivers, and also educate on how to handle the platform to obtain better results. Pedagogism prepares the ground for the implementation of hierarchical directive power.

Subordination is a control of behavior, so whoever controls behavior subordinates. It's no coincidence that this pedagogism encourages subordination, just as it's no coincidence that the word discipline means both a body of knowledge to be passed on and also represents disciplinary power.

In its educational content, Uber is selective and does not address or qualify drivers on the real costs of the driver's activity, much less on the legal possibility of recognizing the employment relationship of this professional, which constitutes a deliberate practice of preventing relevant information from becoming known and the fruit of future union agendas. Selective pedagogism works hand in hand with obscurantism.

In addition to these messages, communications, and instructions, there are videos available on the app, and many others posted on YouTube, as well as the succession of screens and an exploratory menu that are part of these teaching techniques.

Duarte and Guerra (2019, p. 44) point out that even "the successive chronology of screens in the app", the dynamic pricing, the acceptance and cancellation fees, and the reputation system are part of an architecture deliberated by human intervention to generate direct engagement and an attempt to guide and encourage drivers and users. An example of this is heat maps in places with dynamic prices. The app's screen acts as a full-time educational coach for drivers still unsure about what to do.

Part of learning the job of an app driver is done through the "trial and error" method that running the app imposes daily, as the fieldwork showed. The very form of communication used by the platform also includes this despotic pedagogism, with automated messages that serve as a response when contacting "User Support" and with the "Help" feature that only reinforces the conduct desired by Uber when answering drivers' questions. With communication aimed at workers with a standardized, unilateral, and authoritarian pattern - typical of robotic call centers - it ends up infantilizing workers, considering them mere consumers who don't know exactly what their real demands are since all the dimensions of complaints have supposedly already been effectively predicted by the algorithm: if there isn't a button with an automatic response, it's because it's not a significant demand.

2.4. Fraud

With the logic of radical profit extraction, the platform uses dishonesty to increase its profits to the detriment of workers and consumers. The practice of fraud in the legal sphere consists of obtaining an undue advantage for oneself to the detriment of others by misleading or keeping someone in error through deception, trickery, or any other fraudulent means. It is typified in Article 171 of the Brazilian Penal Code.

Promoting this illusion contributes to the dissimulation axis, which generates more driver engagement. One wonders whether the illegal advantages that the platform obtains for itself to the detriment of drivers are being obtained maliciously or are motivated by the app's technical flaws, as many pointed out during the ethnography. However, the total secrecy imposed on the operation of the algorithm's source code prevents absolute certainty about this conduct.

What is not questioned is that Uber formalizes contracts with drivers (without signatures or printed versions) but grants itself the power to change them unilaterally. In addition, as a business strategy, it promises advantages it does not fulfill and does not compensate those harmed by this unlawful conduct.

I was able to observe this strategy during my observation when the platform promised to pay dynamic fares that were not passed on in full, when it maintained different dynamic price indicators for drivers in the same region, or when it advertised dynamic prices in certain locations just to promote the driver's commute, but without the real intention of paying them.

The dynamic tariff has the appearance of being beneficial, representing a plus arbitrarily set by the platform on top of the salary, but it has disadvantages in the long term. The more drivers organize themselves to work at peak times, the more this supply of services increases, and with this, there is a tendency for dynamic prices to decrease over time, so this cannot be a consistent policy. What's more, the riskier and more dangerous the service, the more benefits the platforms offer (CANT, 2021), as the company is not obliged to replace a vehicle that has broken down due to rain or accidents that are common during rush hour, or a car that has been stolen in dangerous neighborhoods.

The episodes of dishonesty, confirmed by all the drivers in the ethnographic experiment, also consist of changing the amount of fees charged for each ride, granting discounts to passengers that end up being paid for by the drivers, not passing on amounts due for toll reimbursements, as well as simply not paying for certain rides in cash using the "pay next time" feature. These attitudes weaken the app driver, who feels vulnerable and powerless to challenge such decisions, strengthening the platform's power. Drivers need to work harder to make up for these small daily shortcomings.

The incidents of fraud look like bugs in the app and force drivers to accept rides for cash or outside the regions indicated in the app, not to mention the "Defined Destination" feature, which allows drivers to receive requests from a specific area, but which in practice doesn't allow them to reach the planned destination, as sometimes the routing doesn't work very well (CASTRO, 2019, p. 96).

This cunning aspect manifests itself in the attempt to reinvent words and concepts the platform intends to disseminate. This cheating consists of giving a new grammar to traditional legal relationships and concepts dear to the law. There is a strong ideological charge contained in the expressions used by the platform in its documents and messages because it is not a question of a partner driver, outsourcing of work, or supply chain management. It should be considered that Uber keeps drivers working as its employees: this is a real fraud in the employment relationship and not a partnership, outsourcing, or supply chain.

This directive power is peculiar to other traditional capitalist enterprises: it tries not to be recognizable, always concealing its apparent form, trying a priori, and intentionally not to be identified or identifiable. To this end, it replaces the nomenclature of order with instructions, dismissal with blocking, a task with the request, and working day with online time. The company doesn't talk about salary in its regulations, but about income and earnings; it doesn't talk about work but about fun activities; it talks about revolution and innovation with flexible working hours when we're dealing with a traditional service that replaces the fleet of taxi drivers through exhausting working hours. Hierarchical commands related to how people work behind the wheel are euphemistically called "safer driving practices" reports, and their employment contracts are called "terms of use". Uberization thus tries to subordinate language and, consequently, the thinking of workers, in a tactic similar to George Orwell's doublethink in his book "1984".

2.5. Risk-sharing

One aspect considered genuine in the so-called sharing economy is the idea of capitalist companies sharing risks with their workers.

The fifth aspect that underpins Uber's business model about its personnel management is this transfer of business risks, another factor responsible for interfering with the dissimulation axis. Unlike the classic employment relationship, in which the risks of the business activity belong to the employer, in platform capitalism, the sharing of risks with app drivers is a factor that increases the disguise of the employment contract and makes workers believe that they are the owners of their enterprise.

As is well known, the ownership of the car and the work tools of the activity carried out by app drivers belong to them, which implies transferring the business risks to the workers, but this management mechanism requires some consideration. If the concept of self-employment were true, this type of work would never require the presence of a third party, which presents itself as an app (and not a company) mediating the relationship between passenger and driver. A self-employed relationship does not need intermediaries; even less does it need this intermediary platform to be plenipotentiary, with abuse of rights being recognized as a valid prerogative. From the moment federal and municipal laws in Brazil allow this costly intermediation of app driver activity, the lack of autonomy of these workers becomes more evident.

Furthermore, the individual ownership of cars transferred to the platform is not an indication of autonomy since, in the overall business activity, the free transfer of the 3.5 million vehicles used by Uber around the world (UBER, 2020b) is solely the factor that effectively allows it to carry out its operations. Although the driver, from an atomized perspective, really is the owner of his car, from a holistic perspective, this single automobile ends up looking much more like an instrument of labor, given the ownership of all the means of production that the platform holds. Owning a car allows you to make a particular trip, but it does not authorize Uber to carry out its final activity from a global perspective.

The crowd that lives of work serves as a lever for the regular operation of Uber's business, which can, if it sees fit, change the price of the ride to the limit of what is necessary to satisfy the consumer and its business interests. Still, it is essential to relativize the importance of car ownership because if setting the price of the ride is not up to the driver, this indicates that the merchandise offered (transport service) does not belong to the worker but to the platform.

In this way, only the driver's labor power is being commercialized because if the driver were self-employed, he would own the result of his work (the race) and not just his car, and as such, would freely sell it for whatever price he wanted. Therefore, focusing on autonomy in the ownership of the worker's car is a short-sighted discussion, even though it is deeply ingrained in the mentality of Brazilian society and the workers themselves, as the empirical research found.

Only the unemployment experienced in recent decades worldwide provides such levels of ideological acceptance and government policies that endorse the free market at all costs. For those who invest in acquiring a car with financing, the debt pressures the driver to work and stay working for Uber.

The requirements for establishing an employment relationship for app drivers are set out in ILO Recommendation 198. The international recommendation draws attention to the fact that the supply of tools, materials, and machines should be made by those who require the work and not the worker (OIT, 2006)⁴. Reversing this logic does not authorize the characterization of legitimate employees as self-employed, as it remains the employer's duty to provide these means of production or at least pay for them, something Uber does not even do.

Similarly, the Brazilian Superior Labor Court believes (TST) that workers who own the vehicles they drive are not prevented by this condition alone from being recognized as employees as long as the other requirements, such as non-eventuality and subordination, are present (TST, 2008).

In short, when a driver pays an installment on the financing of his car, he is doing so for the benefit of the platform, the main beneficiary of a car that is at his disposal for an average of 12 hours a day. The ethnography showed that the driver is a factor of production for the platform not only because of the extraction of his labor force or because he is a potential consumer for other partner companies but also because he is a supplier of basic and essential inputs for the operation of Uber's business, such as cars, telephone handsets, fuel, or the payment of property taxes. This tactic further promotes cheapening platform costs close to the zero limit.

There is still a lot of misunderstanding about the scope of business risk-taking. Nowadays, if the worker is always paid for the value of the race, then he doesn't have to assume the business risks. This risk of Uber as a whole can never be confused with the risk of each passenger and each ride (DE BURUAGA AZCARGORTA, 2019). If the freelancer can't advertise his brand but only the company, and if the only way for the partner to expand his business is to work more hours for Uber, there is no real autonomy.

2.6. Obscurantism

The lack of information is the platform's strategy for deceiving drivers and forcing them to work harder and accept all kinds of requests. This generates more engagement and also contributes to the dissimulation axis. Knowledge must be omitted to make it easier for the driver to adhere to business logic and reduce the chances of the employment relationship being recognized.

Within surveillance capitalism, Zuboff (2020, p. 109) names such a strategy a "culture of secrecy" since it is institutionalized in the policies and practices that govern all aspects of surveillance capitalists' behavior. Why doesn't someone who knows everything about you tell you anything about them?

It's not just a question of an asymmetry of information between bona fide contracting parties on equal terms, where one has more information about the whole business to be carried out, which is a common and expected practice in civil law. The platform's management technique consists of true obscurantism because it is a deliberate strategy to prevent facts or information from becoming known to the category of app drivers.

Data on drivers, users, races, and routes from the Uber platform in Brazil is transferred to the American headquarters, which will process and analyze it. This is a "cross-border data transfer", a true digital extraction that is not subject to restrictions and cannot be repatriated (SCASSERRA, 2021, p. 53); however, even with such comprehensive data, little or nothing about how the platform and its algorithm work is known.

Uber omits essential information for drivers when it refuses to indicate, during a brief request, the value of the ride, the fee or discount applied, and, above all, the exact destination. It also doesn't state how many passengers will be boarding or whether the journey will be made on behalf of a third party, which puts the driver's physical integrity at risk.

There is no certain clarification as to which rule applies to the prioritization of races. Uber's legal representative, in a deposition, provided information that the distribution of rides is done by proximity and automatically (MPT, 2021). However, ethnography has shown that, in many cases, this rule is relativized, such as requests made at airports or directed at highly-rated drivers. The proximity criterion is also relativized for various other reasons, such as the driver's gender identity with the passenger, priority for those who speak the passenger's language, choice of travel preferences (Comfort/X or card/cash payment), lane direction or sense, and, above all, by cars in disembarkation operation. There are so many possible relativizations that the criterion ceases to be a rule and becomes a suggestion.

On the other hand, this spatial proximity generates competition between drivers who vie for the best races according to the algorithm's rules. Obscurantism serves perfectly to increase competition between workers. Punishments, such as roadblocks or shutdowns, are also applied without drivers knowing why.

The driver knows little about the passenger (and vice versa), can't communicate with them to get information after the ride, can't interact with other colleagues through the app to organize their work collectively, and, finally, doesn't know almost all the rules of how the algorithm works. Self-employment doesn't go hand in hand with an almost total lack of information about the service to be performed, revealing a binary autonomy that doesn't allow for gradations, in a "take it or leave it" style with a precarious aspect.

Uber acts with intense information asymmetry and visible bad faith since the most basic information is withheld from drivers, aiming to keep the passenger transportation system running. Given the deliberate refusal and the fundamental nature of the omission of data by the platform, the concept of obscurantism seems more appropriate.

Conclusion

When I joined the platform as a researcher to carry out this work, I tried to prevent Uber from hiding what it wanted to hide from the public eye. The idea of ethnography has always been that of an anthropology of subordinate work - and not an anthropology of autonomous work - even though the renaming and classifications in companies seek to affect the identity and public face of workers (LOPES, 2013).

The dissimulation axis discussed here thus concerns all the strategies to hide the employment contract and generate driver engagement and commitment. This strategy succeeds when the driver incorporates the need to set individualized salary targets and, unthinkingly, begins to reproduce the platform's ideology, assuming himself to be a partner driver.

These characteristics of Uber's labor management (encouragement, task management, pedagogism, fraud, risk-sharing, and obscurantism) are essential for allowing the employment relationship to be defrauded and also have repercussions on the low rate of judicialization in labor claims that seek recognition of this relationship.

The characteristics of the platform's directive power, analyzed here, correspond to spheres of influence and conditioning on driver behavior. However, we did not intend to deal with the subject exhaustively, so further research can be undertaken to uncover how the direct hierarchy imposes itself on these digital workers.

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• 1
  Uber recommends to drivers, for example, via messages in the app or via email, that they frequently sanitize the vehicle's main contact points with Lysoform disinfectants. Filling up at Ipiranga service stations guarantees a 4% cash back. The car suggested for rental is from Zarp Localiza. For vehicle purchases, the company has partnerships with JAC Motors and Renault. Discounts are offered on the purchase of special beers, wines, toiletries, beauty products, chocolate and flowers from Grupo Pão de Açúcar/Extra or BIG, as well as on the purchase of products in general at Sams Clube, or medicines at Drogasil and Droga Raia. Uber suggests opening a digital account to transfer earnings to Digio. Discounts of 20% through coupons are provided when buying at restaurants registered with Uber Eats, and the best health plan is with Vale Saúde Sempre, which has quality and low prices. All of them, brazilian brands.
• 2
  Carrot and stick metaphorically meaning a form of conditioned stimulus in which rewards and punishments are used to get someone to perform a desired behavior.
• 3
  The French author uses the expression "man" to represent both men and women, since her field diaries recount, as a woman, her observational participation research at the Renault factory in 1930s Paris. The ethnographic research carried out here also analyzed the gender issue and found that the difficulties faced by female app drivers are much more pronounced in the face of urban violence, lack of toilets, or episodes of sexual harassment.
• 4
  The document recently produced by the ILO (2020), cited above, seems to conflict with the content of the aforementioned Recommendation. This discrepancy possibly stems from the fact that these instruments were drawn up at different times (before and after the emergence of digital platforms), have a different normative character (report versus rule) and, in a way, do not go into the central point of the discussion, which is the express recognition of the employment relationship of app workers, but only point out guidelines. In other words, the ILO's position also seems to be in dispute.

Publication Dates

• Publication in this collection
  18 Mar 2024
• Date of issue
  Apr-Jun 2024

History

• Received
  22 Aug 2022
• Accepted
  23 Nov 2022