A Rebel’s Guide to the Gig Economy: All 11 episodes & transcript

A Rebel’s Guide to the Gig Economy is a series of podcasts by journalist Ben Wray and researcher Marini Thorne which gets behind the tech jargon and the CEO propaganda to examine the reality of work in the gig economy and look at how gig workers can challenge the power of their algorithmic bosses.

All 11 episodes of the series are below, as is a full transcript of the episodes.

The Gig Economy Project is a BRAVE NEW EUROPE media network for gig workers in Europe. ⁠Click here⁠ to find out more and ⁠click here⁠ to get the weekly newsletter.

Episode 1: What is the gig economy?

Episode 2: Why are gig workers paid per task?

Episode 3: What is the algorithm?

Episode 4: Are gig workers their ‘own boss’?

Episode 5: Is gig work really ‘flexible’?

Episode 6: Is the gig economy really a “godsend” for women?

Episode 7: Is the gig economy good for migrants and ethnic minorities?

Episode 8: What makes platforms powerful?

Episode 9: Why do gig platforms struggle to turn a profit?

Episode 10: Why should gig workers join a union?

Episode 11: How do gig workers take control of their data?

Episode 1: What is the gig economy?

Everyone’s heard of ‘the gig economy’, right? But what actually is it?

If you listen to Uber CEO Dara Khosrowshahi, he’ll tell you that the gig economy is a force for individual empowerment and enrichment, where companies like Uber just act as intermediaries connecting customers and workers together. 

[Uber CEO Dara Khosrowshahi speaks]: “The singular theme that I hear from our driver-partners, what they love about Uber, is they tell me ‘Uber lets me be my own boss’.”

Many journalists and researchers have fallen for this story. 

[Journalist to Uber CEO Dara Khosrowshahi]: “The gig economy has really benefited – mutually benefited – both you as a company and many of the drivers.”

Some academics, including ones who have been bought and paid for by the company, have even published research defending Uber’s narrative.

As critical journalists and researchers on the gig economy, we are here to tell you that Uber’s story is a fairytale. 

Uber drivers and food delivery couriers are not their own boss. They are very much subordinates, just like an employee in any other capitalist enterprise. The only difference is that they are told what to do by an algorithm, rather than a human-being. 

And the work is very hard. Workers work very long hours for very low-pay, in working conditions which are opaque, insecure, sometimes unsafe, and devoid of workers’ rights. 

These are ights that workers have fought for centuries to win, and are now being undermined in the name of digital progress.

In this Rebel’s Guide to the Gig Economy we will sort fact from fiction, getting behind the rhetoric of what it means to be a gig worker to the reality.

Our Rebel’s Guide is split into three parts. 

First, is about the labour process: why are gig workers paid-per-task? What is the algorithm and how does it function?

Secondly, we are going to bust the myths of the gig economy. Is it true that gig workers are their own boss? Is gig work really so flexible, as the platforms like to say. And is it good for women and ethnic minorities, as they also claim?

Finally, we are going to look at power in the gig economy. Why is it that platforms are powerful? Why is it they struggle so much to turn a profit? And how can gig workers become powerful? How can they harness the power of unions, and can they use data for their own benefit?

But firstly, let’s answer the question: what actually is the gig economy? There’s three elements that are necessary to understand what the gig economy is. 

First, the gig economy involves digital technology. As the academic Juliet Schor writes in her book, ‘After the Gig’, “When the financial system crashed in 2008, a powerful idea emerged from the rubble: digital technology could solve the problem of work.”

Specifically, around the mid-2000s, the increasing presence of wifi and data services, and the widespread use of smartphones, created the conditions for on-demand services which could link consumer orders to the allocation of gigs. The tool which ultimately facilitated this process on an instantaneous basis is known as an algorithm. So that’s the first key part of what it means to be a gig worker: you are a data worker managed algorithmically.

The second key part is the companies themselves. The algorithm which allocates your work is not like Wikipedia, they are not open source technology, nor are they collectively owned. Rather, for 99% of gig workers, the algorithm is controlled and owned by for-profit companies, like Uber, Deliveroo, freelancer.com or care.com. These companies are termed ‘digital labour platforms’, because like Facebook or Ebay, when you make an account you agree to share your data with them. But, unlike Facebook and Ebay, these platforms are specifically for you to register in order to sell your labour. 

Digital labour platform is another term that can give a misleading impression. When we think of a platform we think of the place where people stand together to wait for a train, all on the same level. While a company like Uber might feel like a digital version of a train platform for the customer, it certainly doesn’t feel like that for the worker, for whom a ‘platform’ can feel like running up an escalator the wrong way: you make lots of effort, but you don’t get very far, and you have the feeling that the platform is rigged against you. 

The third, and perhaps most important aspect of gig work is that rather than being paid for your whole time at work, you are paid only for the time spent executing a task, whether that is delivering food or cleaning a house. 

This model of payment isn’t new, it has been around for centuries actually, but it has been given a new lease of life through the gig economy. 

And for most gig workers, they have to provide all the means that they need to do the work: whether that’s the equipment; a bike, a car or a mobile phone. The only thing the platform provides is the app. 

So, that’s it. A gig worker is someone who’s work is managed algorithmically by a digital labour platform and is paid per task completed. This is our working definition of a gig worker, that we’ll use throughout these podcasts. Other people will have different ways of defining this. But what you will find from our Rebel’s Guide series is that we want to emphasise the commonalities that exist between gig workers and other forms of precarious work. 

Whether it’s a retail worker on a zero-hours contract, a hospitality worker that is hired through an agency, or a construction worker employed through a subcontractor. None of these are gig workers but what they have in common with the gig economy is that their work has been specifically organised to undermine labour rights and to weaken their ability to organise collectively as workers. In the final analysis, gig workers are just one part of a working class that has common collective interests. 

What we want to do with this series is to shine a light on the reality of the gig economy so that gig workers now, and those who are threatened by ‘gigification’ in the future,  can understand their exploitation, get prepared and get organised. Ultimately, the aim should not be to modify or to tame the gig economy, but to eradicate it. Because work will not be dignified, secure or democratic as long as it remains gig work.

Episode 2: Why are gig workers paid-per-task?

When most of us go to work, we are paid for our whole time on the job, regardless of how productive you are during that time. But not if you are a worker in the gig economy.

Gig workers are typically paid only when they complete a task, whether that is cleaning a house, dropping off a passenger, or delivering food. 

Platforms say that gig workers prefer to be paid-per-task, rather than per hour, because it gives them motivation to work efficiently and thus earn more money. 

Here is a clip of a US cleaning company, MasterCorp, promoting their pay-per-task policy:

“Basically the more units you clean, the more money you make. You control how much money you make and how fast you make it.”

But while the upsides of this for the platform are obvious, for the gig worker pay-per-task comes with a lot of costs.

Most importantly, the waiting time and time between tasks goes entirely unremunerated. One study of New York Uber drivers found that the time spent waiting for a ride actually takes up 58% of all of their working time. As drivers aren’t paid during this time, they are actually losing money, because they are paying for parking, driving around looking for work and increasing their fuel and car repair costs.

The platforms argue that pay-per-task is the future of work, because now we can use data to time exactly how long it takes to do something, and thus workers can be paid precisely, based on their exertion. 

But if we look at history, we find that the gig economy model of pay is not as new as the platforms want you to believe. 

In fact, the 19th century philosopher, Karl Marx, wrote extensively about the problems of payment per task completed, or what at that time was known as “piece wages”, which simply meant payment for every ‘piece’ of material produced, rather than payment for the worker’s time. 

Marx said that “piece wages” were “a lever for the lengthening of the working-day, and the lowering of wages”, even describing it as “capitalistic cheating.”

Why was Marx so against piece-wages? He argued that by linking the worker’s wage directly to their output, the piece-wage worker is motivated to work faster, as the more pieces she produces in the same amount of time, the more money she earns.

But, as Marx noted, the piece-wage worker does not reap all of the profits of their increased productivity, because it is the capitalist who takes the value of the worker’s labour – what Marx called “the price of labour-power” – and in return for that value, the capitalist gives the worker a wage for each piece they produce. 

Because the capitalist wants to extract as much value as possible out of the worker, the payment  per piece that the capitalist offers must be high enough to motivate the worker to come back to work the next day, but not so high as to convince them that they can reduce the intensity of their labour or reduce the amount of hours they work per day. Which actually is no different to a worker who is paid per hour.

Marx wrote that: “Wages by the piece are nothing else than a converted form of wages by time, just as wages by time are a converted form of the value or price of labour-power.”

To explain this in another way, think about the gig worker who delivers food for restaurants, such as at Deliveroo, at Uber Eats or at DoorDash. These workers are paid per delivery completed. We can see the impact of this by looking at an early shift in Deliveroo’s payment practices. 

In 2016, the company shifted wages from an hourly rate to pay-per-task. While workers had once received £7 an hour – which wasn’t exactly great – they would now receive only £3.75 per ride. One worker described how recently they had received only one order in a period of four hours, this would have cut their take home pay from £28 to just £3.75. 

Once Deliveroo workers were forced to accept such piece rate payments, workers were forced to spend more time on the streets looking for work, and many more of them found that they were being paid less than the minimum wage for the time worked. 

The piece wage, i.e. payment per task, then encourages the worker to make up this lost value, by intensifying their work, taking shorter breaks, by accepting more trips that are lower value, or by working longer, increasing their working day. And it increases the amount the company earns on every ride.

Plus, it has important health and safety implications. Piece work means workers are encouraged to drive, when tired, or even sick.  In the case of drivers and delivery workers, this can mean risking one’s own health, and even subjecting urban areas to a higher number of vehicle accidents. The worker risks life and limb, and it is platform companies that benefit. 

Here is Dr Callum Cant, author of ‘Riding for Deliveroo’, on the health risks of piece work in the food delivery sector:

“Platform workers are usually paid-per-delivery, and over the last few years wages have been driven down to poverty levels. Now that means if you want to make a decent wage you’ve got to go faster and faster. If you want to make a living, you’ve got to risk your life.”

Marx also noted that piece work shapes how workers think. He argued piece-wages create the illusion that your wage is determined by your own effort as a singular worker. This, Marx explained, leads to an individualistic attitude towards work, driving workers to compete against one another to be the most efficient, rather than seeing that they have a collective interest as workers in organising with one another to demand that the platform pays them more.

In the 20th century, after Marx’s death, piece work became less and less common because of the growing strength of the trade union movement internationally, which demanded time-based wages, including limits to the length of the working day and working week. 

It is with the dawn of the digital age, where algorithmic management tools can be used to organise work, that piece-wages have started to become more common again in the form of the gig economy.  And, just as Marx described, this modern form of piece-wages has been associated with the lengthening of the working day and the lowering of wages. 

 As a gig worker you may feel like being paid-per-task on a self-employed basis rather than per-hour as an employee means that you are rewarded for working faster and longer, but in reality it means that the platform gets to absolve itself of the responsibility of paying for basic obligations. 

This could be the basic obligation to provide you with the tools you need to undertake your work, e.g. a bike or a car. Instead, with Uber or delivery work, workers have to pay upfront for the costs of these tools – and they have to cover the cost of maintaining the tools themselves. This transfers costs from the employer to the worker. 

Often workers need to borrow money in order to pay for these tools – for example, taking out a loan on a bike or car. The need to meet the repayments on these tools can make workers work more consistently and for a longer time – and that’s just what the platform wants, as it helps produce a more exhausted and more compliant workforce. It also allows them to hire more workers than they need at no extra cost – creating more competition among workers and pushing wages down even further.

More important still, the per-task system enables companies to evade rights that were won by previous generations of workers, such as sick pay and paid holiday leave. So despite the ‘freedom’ that workers supposedly enjoy, the need to get enough money to pay for food, rent (or the loan on your vehicle) forces them to work even harder. At the end of the day, the platform gets to decide unilaterally how much you are paid and the way in which you work, just like if you were an employee. 

The illusion of independence is why Marx described piece wages as “capitalistic cheating”, which is as true today as it ever was. While some call the gig economy “the future of work”, it’s origins are firmly in the past. Just as workers in the past organised to change these conditions, workers in the gig economy can do the same today.

Episode 3: What is the ‘algorithm’?

Everyone knows what an app is these days. But what is less known is the mechanisms behind the app: how is information sorted and prioritised? How are prices calculated? In other words, how are decisions within the app made? 

The answer of course is: through an algorithm. But what actually is an algorithm? The Cambridge Dictionary defines an algorithm as “a set of mathematical instructions or rules that, especially if given to a computer, will help to calculate an answer to a problem”. 

The algorithm in an app, like Uber Eats’ or Just Eat, is programmed to make complex data calculations very quickly, so that if an order for food comes in from one location it can be allocated to a worker based on their proximity, availability and other data points, with a pay rate offered based on a whole variety of factors, which we will explain more later.

The crucial point to keep in mind is that the algorithm isn’t neutral. Because the instructions to a worker come from an app, rather than a human-being, it can sometimes feel like the algorithm is based on a set of abstract mathematical principles which are unchallengeable, which are based on a set of rules which we can’t possibly get our heads around. But the “mathematical instructions or rules” which the Cambridge Dictionary definition referred to are based on decisions made by people, usually web-designers and platform management, to achieve its objectives. So the maths and the algorithm are simply the means by which management decisions are processed through an app. 

So, if algorithms simply carry out management instructions to the worker through an app, what’s the problem?

The problem is that algorithmic management accentuates the power imbalance between managers and workers, in three ways. Firstly, algorithms allow managers to change their instructions, including the price they are willing to pay, in an instant. Secondly, the data which algorithms generate gives managers greater control and surveillance over the work process.And thirdly, algorithms make it harder for workers to identify who is making the decision and on what basis. This leaves management with loads of buttons at its finger-tips to control workers, while the workers are left in the dark about how the decisions are made and who makes the decisions.

For example, it is not uncommon for gig workers to be ‘robo-fired’: de-activated from the app through an automated or semi-automated process without any opportunity to challenge or review this decision. These workers have often been working for years to build up their five-star ratings from customers, all of which can be destroyed in an instant. Often these robo-firings are based on mistakes, such as claims of ‘fraudulent activity’ from the driver or food delivery courier which have no basis in reality. 

But the problem is not only that the algorithm makes mistakes, it is that they are designed to deliberately discriminate against workers to maximise the platforms’ revenue. 

For example, Uber has recently introduced its ‘dynamic pricing’ policy for setting pay rates for its drivers and prices for its customers. Dynamic pricing means that there is no standard formula for calculating pay, for instance $10 for every 2 kilometres distance travelled. Instead, a whole variety of data inputs go into setting the pay rate for each trip, including the personal data history of the driver. 

Uber has denied that they do this, but the platform stated in their own 2021 privacy policy that: “Users can be matched based on availability, proximity, and other factors such as likelihood to accept a trip based on their past behaviour or preferences.” 

Here is Dara Khosrowshahi, Uber CEO, explaining the benefits of the dynamic pricing policy in a call with investors:

“So I think what we can do better is in actually targeting different trips to different drivers based on their preferences or based on the behavioural patterns that they are showing us. That is really the focus going forward, offering the right trip, at the right price, to the right driver.”

What this means is that if there are two drivers side by side and Uber thinks driver A will accept a lower pay rate for a trip than driver B based on driver A’s history of accepting lower pay rates, they can offer the trip to driver A at £10 then driver B at £12.

To prove this, many drivers have now conducted this exact experiment, sitting side-by-side with one another and getting very different pay rates on the same trip. Here’s a demonstration on the youtube channel The Rideshare Guy of two drivers sitting side-by-side in Chicago:

“Driver A is a Tesla owner with an acceptance rate of 9% and a CR, or ‘Cancellation Rate’, of 14%. And Driver B is a hybrid renter with an acceptance rate of 15% and a Cancellation Rate of 23%. They’re sitting on the couch together and they’ve got the trip radar coming in…the same trip: $6.25 to $4.55. The same exact trip.”

Gig economy scholar Veena Dubal has called dynamic pricing “algorithmic wage discrimination”:

“So algorithmic wage discrimination borrows from the idea of consumer price discrimination and attempts to help us to think about how the same thing is happening to how people are being paid. So one worker is being paid differently for the same amount of work, at the same skill level and done at the same time based on what a company might know about that individual worker, and these determinations are done algorithmically.”

What can be done about these various forms of algorithmic discrimination? 

The algorithmic control exercised by the platforms is not just a problem for workers due to their lack of control over how and why they work and the pay rates they are receiving. Workers also have no transparency over the data that is being held on them and how it is used. The starting point for workers, therefore, is to access their own data to better understand how it is being inputed into the app.

Because the data is the property of the platforms, they keep it away from prying eyes, but in many parts of the world there are laws which, in theory, permit workers to access the data which is held on them.

Unfortunately, it doesn’t end up being that straight forward. First of all, there’s lots of loopholes which platforms can apply to restrict what data they release, including ‘commercial confidentiality’ and ‘trade secrets’. Also, the data which workers get is often in an almost unreadable format, and requires the help of data science specialists to make sense of it. 

Nevertheless, there are examples of workers accessing their data and using it to good effect. For example, in Geneva, a court ruled that Uber drivers were employees and Uber must pay them on that basis, back-dated to 2017. But only Uber could access the data going back to 2017, so how could the Uber drivers know if what Uber was offering them as back-dated pay was fair or not? The drivers worked with data specialists to uncover their data and decide whether to accept Uber’s offer or to challenge it in court. 

Worker Info Exchange, a gig worker advocacy organisation, also won a major court case in Amsterdam in April 2023. This required Uber and Ola Cabs to provide information to workers on automated-decision making, including how personal data is used in ‘dynamic pricing’.

What this shows is that gig workers potentially can have access to the data that is held on them by the platforms, but they have to fight for it collectively. The prize is to bring the hidden management instructions which direct the algorithm out into the open, enabling workers to identify and challenge the ways in which they are being exploited. 

Episode 4: Can gig workers really be their ‘own boss’?

One of the attractions of the gig economy is the freedom this work promises compared to working, for example, in a call centre, where a boss is always on top of you, watching and controlling your every move.

Indeed, platforms like Uber and Deliveroo, go as far as to argue that in the gig economy you can ‘be your own boss’. That you are able to make your own decisions about when to work, how to work, and for who you want to work. 

Here’s Uber’s CEO Dara Khosrowshahi:

“The singular theme I hear from my driver-partners, what they love about Uber is, they tell me ‘Uber let’s me be my own boss’.”

It is true that working as, for example, a food delivery courier, offers certain freedoms that you don’t get from working in a call centre or in an Amazon logistics factory. You get to work outside. There’s no human supervisor on top of you all the time. You can wear what clothes you want. And yes, you can even work when you want, although in practice your working hours are highly constrained by times of peak demand for food deliveries. 

But how does all of this amount to being your own boss? The reality is that these limited freedoms have to be set against the various ways in which gig workers are subordinated to the platform. This level of subordination is not necessarily true for workers who are genuinely ‘self-employed’. 

Here are three ways in which gig workers are typically subordinated.

Number 1: The worker doesn’t own or control the app that they work through. This app is proprietary software, meaning all of the data is owned by the platform. The worker does not collect any information of her own on the clients or the customers, so she does not acquire the means to work independently of the app as a rider or a driver, for example. This is an essential requirement to running a genuinely independent business. 

Secondly, the worker has to execute the work in the way that the platform wants. When a food delivery courier accepts an order on the app, they can’t decide when and how to deliver it. They have to go the most direct possible and as fast as possible. As they carry out the delivery, they are constantly being surveilled and timed by the platform, and if they are deemed to go too slow or not to give the food to the client in the right way, they can be deactivated from the app. This level of authority which the platform exercises over the worker is much greater than for the vast majority of employees. 

Thirdly, the worker doesn’t have any control over how much they are going to be paid. They either accept the pay rate offered to them, or they don’t get the work. This is very different from a carpenter or a plumber, who will give the customer a quote for how much they would charge to do the work before it begins. In the gig economy, the price is set neither by the client nor the worker, but by the platform. The worker doesn’t even know how much the client has been charged, nor does the client know how much the worker has been paid. The fact that the pay rate set by the platform is frequently below the minimum wage is another reason why employment protections are so necessary in these jobs.

But if that hasn’t convinced you that gig workers are not their own boss, there has been years worth of court cases over the employment classification of gig workers which we can look at and analyse. Do judges think food delivery couriers and Uber drivers are their own boss?

The answer, in Europe at least, is: no. The Eurofound database on platform economy court cases lists court verdicts from 2016 to 2024. In the case of food delivery couriers, only one country – the UK – has found that they are not eligible for collective bargaining because they are not employees. In every other case identified – in Spain, in Portugal, in France, Italy, the Netherlands and Belgium – the most recent court verdicts have found that riders are employees, including the Dutch and Spanish Supreme Courts. 

The Dutch Supreme Court verdict in 2023 in relation to Deliveroo riders is illustrative of why judges usually consider food delivery couriers to be employees even when they don’t have employment contracts. 

First of all, what is written on the terms and conditions that couriers sign with platforms when they register on the app was irrelevant to the Dutch judges, since what they were interested in was the facts of the working relationship in practise, not what the platforms write in their T&C’s, which are determined unilaterally by the platform and very few riders even read.

Secondly, the judges found that all circumstances must be considered when evaluating whether a worker is in an employment relationship. While Deliveroo riders showed some evidence of a certain freedom at work, like being able to work when they want and being able to substitute their work for another worker, the judges found that this substitution right was rarely used, and therefore of little significance. 

More importantly, those factors had to be weighed against a whole load of other criteria that goes into determining employment status. These include:

  • How pay is determined and paid
  • Whether the worker can act as an entrepreneur while conducting the work, for example building up their own client list and taking on commercial risk
  • The level of authority exercised over the worker while conducting the work, including surveillance and control over the work process,
  • And the nature and duration of the work. 

In all of these cases and more, the Supreme Court judges found that the worker was acting as an employee. 

And if you still don’t believe us, it’s worth listening to the words of Mark McGann, Uber’s former chief lobbyist in Europe. McGann became a whistleblower in 2022, exposing many of the platform’s darkest secrets in the ‘Uber Files’ scandal. 

Here’s MacGann speaking to the European Parliament last year about whether Uber workers are employees:

“From early 2014, we faced class-action lawsuits from drivers who were already challenging their self-employed status. Those lawsuits forced us into exhausting linguistic and semantic gymnastics. 

“‘On no account should anyone use the word ‘job’. On no account should anyone use the word ‘employment’.

“Uber didn’t create a new type of worker, as much as find new ways to avoid the costs and responsibilities that employers have towards their workers. If it walked like a duck, if it quacked like a duck, our instinct was to say ‘it’s a duck’. But no, the management in San Francisco said “it’s not a duck, it’s a hamster, call it a hamster!’.”

So there you have it. The platforms want to convince us that their workers are self-employed because they want to avoid the additional costs which come with employment contracts and they want gig workers to believe that the gig economy means freedom for them. 

But a food delivery courier with a bike and an app is not an entrepreneur, they are workers with an algorithmic boss and a common set of interests with one another. This common set of interests enables them to fight together for better pay and conditions, just like any other employee. 

Episode 5: Is gig work really ‘flexible’?

One of the major selling points of the gig economy is flexible working. If you listen to the CEO of Uber or Bolt or Deliveroo make the case for working in the gig economy, it won’t take too long before you hear “flexibility”.

Have a listen to this Uber advert targeted at drivers:

“Everybody says they want more flexibility, but what does that mean? Flexibility is working a 40 hour week or a 4 hour week, if that’s what you need. It’s a cancelled class, creating an opportunity to earn. It’s having dinner with the family on Wednesday and delivering during dinner rush on Friday. Flexibility is taking the afternoon-off, the week-off, and then picking right-up where you left off. 

So it’s no wonder 85% of drivers say they need flexibility. Because flexibility works.

Indeed, ‘flexibility’ is the platforms’ primary argument against employing their workers, on the basis that this form of freedom is what gig workers really want but wouldn’t get if they were employed in any other job. 

But is gig work really as ‘flexible’ as the platforms’ make out? Moreover, is it true that having an employment contract and flexible working are totally incompatible?

Before we get on to that, it’s worth considering ideas around work, freedom and flexibility in a broader historical context.

Before capitalism, feudalism was the dominant mode of production, where economies were divided between peasants and lords. A peasant usually had no choice about who they worked for: they had to work for the lord or face imprisonment or even death. 

Capitalism changed that. With the arrival of businesses not tied to a particular landed estate, workers could choose who they worked for. At the dawn of the industrial revolution, when capitalism really took off as the dominant mode of production, liberals like the Scottish economist Adam Smith celebrated capitalism as a new dawn of freedom for workers.

Like every powerful argument, Smith’s case had an element of truth to it. Workers could choose who they work for, but whichever capitalist they chose, they had to sell their labour in return for a wage. In this, there was basically no option: if they didn’t work for a capitalist, they would end up in a doss-house struggling to survive, or even worse.

In the 21st century, very few people argue that the right to sell your labour brings great freedom, because we have now been doing it for hundreds of years and we know the limitations of that freedom. 

Instead, when people talk of freedom and work today, we talk about things that are not the normal wage-labour relationship we have grown accustomed to. We talk about the right to time-off, the right to work from home, the right to a sabbatical, the right to a short working week, and – yes – the right to flexibility: over when to work, how to work, power over the thing we spend a lot of our lives doing.

That’s why the flexibility argument of the platforms is so powerful, because it is something that many of us want in our working lives but don’t have. But just like the argument of the liberals at the start of the industrial revolution about wage-labour, the argument of the gig economy advocates about flexibility only contains an element of truth.

It is usually true that if you work on a digital labour platform you can choose when you want to work. I say ‘usually’ because there are platforms that still require drivers or food delivery couriers to commit to specific shift times, but mostly you can start and stop work whenever you want.

However, in practice this freedom comes with the major limitation that you can earn more money at specific hours and you can earn very little at other hours. For ridehail and food delivery, the evenings and weekends are usually the peak times for demand. The platforms incentivise you to work at these peak times to meet that demand, through ‘surge pricing’ and other pricing policies which mean you can earn significantly more money at peak hours than the rest of the day. So as an Uber Eats food delivery courier, you are free to only work from 6 in the morning to 12 in the afternoon, but don’t expect to make even the minimum wage across those hours.

In practice, this highly constrains the freedom you have to choose when to work. In fact, gig workers tend to work hours which are more anti-social than employees in 9 to 5 jobs, due to the higher salaries on offer in the weekends and evenigns. Research shows that women tend to earn less per hour than men in the food delivery sector partly because they are more constrained by familial responsibilities in the hours they can work. So it’s ultimately not very flexible at all!

Also, it is possible to work flexibly while having an employment contract. Gig economy researcher Juliet Schor has analysed a package-delivery platform which hires some workers as independent contractors and some on employment contracts, finding that workers on employment contracts still had flexibility in terms of work schedules, concluding that “employment status can coexist with the platform model”. 

The reality is there are many employees in the global economy today who work flexible hours and are given project, rather than time-based, tasks by their manager or are evaluated based on their productivity over a week or a month. 

The platforms argue that if they had to employ their workers it would be necessary to set a fixed schedule of hours for workers to make it financially viable. Just Eat, the largest food delivery platform in Europe, does employ some of its food delivery couriers and they do work a fixed schedule of hours. But let’s be clear – that is an operational choice, it’s not a necessity.

Also, choosing your working hours is just one form of flexibility that a worker has to take in to account. Another is, ‘do I have the flexibility to take a holiday?’ If you are self-employed, you don’t get paid holidays, so time on holiday comes at a significant financial cost. 

Or, ‘do I have the flexibility to rest while I am sick?’ Many gig workers continued to work during the pandemic despite getting sick with Covid-19 because they felt they couldn’t afford not to because they didn’t get paid sick leave. 

One final question is, ‘do I have enough hours in the day and enough money to have the flexibility to do what I want in my time when I’m not at work?’ For those who work full-time in the gig economy, it is not untypical to work more than 10 hours a day, which means that once you include time for sleep, cooking and cleaning the house, maybe caring for kids, and any other social activities, the time for leisure really doesn’t exist.

Even Adam Smith, a pioneer of capitalist economics, wrote in his most famous book ‘The Wealth of Nations’ that “Workmen…when they are liberally paid by the piece…” – or as we would say today, paid-per-task – “…are very apt to overwork themselves and to ruin their health and constitution in a few years.”

Looked at as a whole, the ‘flexibility’ that exists in the gig economy is far greater for the platform than it is for the worker. It’s the platform that has the flexibility to not pay you at times of low-demand, or if you are sick, or if you have a family emergency. The platform has the flexibility to increase or decrease the wage they offer, depending on for example the time of day. Or to delete you from the app without a moment’s notice if they decide you aren’t following their instructions properly, or if you are trying to organise a union. That’s great flexibility for the platform, not so much for the worker.

The lesson is that there is no true flexibility for the worker without workers’ rights.

Episode 6: Is the gig economy really a “godsend” for women?

One of the arguments in defence of the gig economy is that it benefits historically undervalued groups of workers, especially women.

Cloud platforms like Upwork promote themselves as being “for a new generation of women” who can build “careers that lead to both financial and personal freedom”. 

Here’s Anne Marie Slaughter, head of think-tank New America, calling the gig economy a “godsend” for women:

“I would say the on-demand economy, for those of you who want to keep your hand in as lawyers, it’s a godsend, because you’ll be able to care for your child and work on a project basis. 

“That’s the high-end, at the low-end, every time I have an Uber I ask the driver why they are driving, and particularly if it’s women, they say ‘this is the way I can make money and also care for my kids’.”

Supposed benefits of remote platform work include the claim that working online offers greater anonymity, thereby eliminating traditional gender biases. Also, that unlike a typical office set-up, there is no macho work environment where male bosses privilege other men. Finally, that the flexibility of the gig economy makes it easier to combine personal goals, like having a child for example, with career development.

Do these arguments hold up to scrutiny? Is gig work really a great opportunity for women?

The answer is no. But, it’s important to recognise that there are genuine criticisms to be had of traditional labour markets, where discrimination against women is far too prevalent. But just because traditional employers have big problems, that does not mean that the gig economy is offering a good alternative. In fact, in some ways the gig economy takes many of the discriminatory practices of offline jobs and makes them even worse. 

Gig work like food delivery and ridehail does nothing to redress traditional gender divisions in ‘masculine’ jobs. Problems for women – such as lacking a bathroom or toilet, and no responsibility on the platforms to address cases of sexual harassment or assault – are obvious. 

In traditionally female-dominated services – domestic work, home care and cleaning – platforms claim to have improved what has historically been an industry notorious for abuse. However, the use of a ratings system for clients to judge the performance of domestic workers means that they are often pressured to do things that they don’t want to, or are not being paid to do, for fear of a bad rating. This will affect their future job prospects. 

Studies have shown that in some countries gig platforms have made this sector even more informal as they attract care workers who were previously in the public sector. These workers report being paid late or not in full. 

This kind of informalisation can make workers extremely vulnerable to poor treatment on the job. Workers at Urban Company, a platform which offers domestic cleaning and beauty services in India, widely report customers arbitrarily leaving bad reviews, sexual harrassment, and caste-based discrimination in the privacy of customers’ own homes. 

But even when working in the gig economy remotely, what is often termed ‘cloudwork’ or ‘remote platform work’, the supposed flexibility benefits for women are often elusive. Rather than being family-friendly, many clients on platforms like freelancer.com demand workers to work anti-social hours, respond rapidly to messages and do more work than was initially advertised, undermining the predictability many women need to manage care responsibilities. 

These demands also ensure that women still face gendered disadvantages on online platforms. Research suggests that on these platforms, women make less money than men, because male cloudworkers are more likely to have the time to meet the needs of demanding clients, therefore getting a higher rating, and they are more available to take-on longer, higher paying tasks. 

The idea that women can combine this sort of work with childcare, if anything reinforces the traditional sexist ‘double-burden’ on women of waged labour and domestic unpaid labour, when what is needed is gender-equality in care responsibilities and affordable childcare provision.

Here’s Professor Al James, author of a study on women in the online gig economy:

“So actually what you are finding is these platforms that pitch themselves as inclusive – gender inclusive, female inclusive, socially inclusive – it says nothing about the terms on which you are being included. Essentially if you are a women with kids, your ability to compete on these platforms is constrained, relative to other workers who don’t have extensive childcare commitments and other workers who don’t have a female identity.

James asked over 100 female gig workers if they agreed with Anne Marie Slaughter that the on-demand gig economy was a “godsend” for professional women, and just a fraction agreed with her.

In fact a range of studies have shown that the ‘gender pay gap’, the difference between what men and women earn in an average year, is even worse in the gig economy than in other sectors. For example, amongst women who work on the cloud work site, Amazon Mechanical Turk, women tend to earn 10% less than men. Where women have to negotiate their own pay, for example on the platform Upwork, the disparities are even greater: women tend to earn 48% less than men. 

The supposed ‘flexibility’ of the gig economy therefore does nothing to address the costs of women’s caring responsibilities, the constraints upon their time, nor does it place them in a stronger position to bargain for better wages. 

It seems that only those women who have the disposable income to pay for services from platform companies – like cheap taxis, cheap spa treatments and on-demand food – are liable to benefit. 

That’s why, women workers in this sector must organise and fight back, to challenge the double burden of paid and unpaid labour, and to push for better wages, working conditions and the public services necessary to reproduce society over the long term. 

It’s only through strategies of collective action that women can reorganise this unfair load of paid and unpaid work, to win a more equitable world in which the distinction of supposedly male and supposedly female work ceases to have the same meaning. 

Episode 7: Is the gig economy good for migrants and ethnic minorities?

Black and minority ethnic workers are disproportionately represented in the gig economy. Why might this be? Is it because this work is particularly good for historically marginalised groups? This is the argument that the platform companies want you to believe. 

In 2020, during the Black Lives Matter protests, Uber declared themselves “an anti-racist company”. Similarly, Uber has described themselves as advancing employment opportunities for minority ethnic workers. 

Politicians, like the French President Emmanuel Macron, have followed this line. Macron defended Uber’s presence in the country on the basis that it has provided work for the banlieus, the housing estates on the outskirts of Paris which have high-levels of unemployment and large first and second generation migrant populations. Macron said banning Uber would be like sending young people back to the banlieus “to sell drugs”. 

But can we really believe Uber’s claim to be anti-racist? And is Macron right that the company is providing good quality work to those who might otherwise be selling drugs? 

Not only is Macron’s claim obviously racist, but as we’ve discussed before it’s not clear that Uber offers good quality work to migrant workers. 

To understand this, we have to put it into its proper context. Migrants and ethnic minorities tend to be disproportionately represented in the most marginal and least well-paid jobs. 

This is where racism and the organisation of labour markets has to be factored in. Race and migration has long been fundamental to how labour markets are organised. For example, European colonialism tended to force the indigenous populations over whom they ruled to undertake waged and unwaged labour, often through brutal strategies, such as debt bondage, and even enslavement. This racist schema tended to be premised on the separation of workers from one another, with each part of the labour process attributed to a specific ethnicity or race. This approach made it harder for workers to organise collectively. 

In the second half of the twentieth century patterns of labour migration increasingly shifted, however. With many more migrants from the global south encouraged to  migrate to undertake work in nations which once colonised their lands. While this might offer the promise of more stable wages to migrants, in the eyes of the capitalists in the global north, it offered a supply of low cost workers for European labour markets. Often migrants have been forced to work in the most poorly paid and least secure professions in these economies, as well as facing discrimination in housing, education and civil rights.  

The structural disadvantage which migrant workers then and now have tended to face – in terms of employment history, access to education and access to capital – changes the kinds of work that they can access: pushing minority ethnic workers towards jobs with ‘low barriers to entry’. 

For example, to be a food delivery courier in the UK, you don’t need a qualification or a degree, you don’t need a high-level of English, and you don’t need to do a job interview. You just log-on to the app and go. 

For a group of workers that face discrimination and marginalisation, the easy access that the gig economy offers can be appealing. But that doesn’t mean ethnic minorities stop being marginalised when they enter the gig economy. 

The low wages and precarious conditions make it very hard to dig yourself out of poverty doing that type of work. In a job like food delivery or ridehail there’s no prospects for career advancement. The work can be dangerous and you aren’t contributing to a pension for when you get old. So it might be easy to access, but that doesn’t mean the work is good, or even dignified.

Plus, migrants who arrive from the global south tend to find it harder to enforce their rights than  workers born here in the global north. If you are a migrant on a student-visa, your residency will often be tied to your work status, meaning that getting sacked from a job for union organising, for instance, can affect your residency. It can also be harder to access your rights as a migrant worker because you don’t know what they are, you can’t speak the language well or don’t have connections to people who can help you. 

And then there are the migrant workers’ who have been excluded from the right to work. These undocumented workers, who lack even the most basic legal protections, are the most vulnerable to exploitation by their employers. 

Platforms seem to almost be designed to take advantage of this racialised section of the labour market. In food delivery, riders are hired on a self-employed basis and their boss is an algorithm, the platforms never really knows who is actually delivering the food on their behalf. This means platforms give riders the right to provide a ‘substitute’ for their work, meaning they are allowed to let someone else use their account.

Often, undocumented workers rent the account, with the account holder keeping up to 50% of the wage and the undocumented worker taking the rest. Thus, these workers are doubly exploited, first by the platform, and second by the account holder, and they need to work twice as many hours to make an income they can live on, sometimes working 12-15 hours a day. 

In some large cities in Europe, like Paris and Madrid, undocumented workers are thought to make up more than 50% of all food deliveries in the city, although there are no official figures. 

The point is that these riders are fundamental to the operations of food delivery platforms in Europe, precisely because they are in a situation of complete legal and economic marginalisation.

There has been a growing realisation about this form of exploitation by the media and the government. But rather than the state clamping down on platforms for being unaware of who is working for them, they have instead targeted riders through immigration raids. 

Here’s a journalist at GB News undercover with immigration police in the UK:

“We are with immigration and enforcement officers in Brighton city centre. A joint operation with Sussex police as they target the delivery drivers they suspect of working illegally.

“Police have just stopped this driver on the sea front. As they carry out checks, immigration enforcement teams hang-back, out of sight so as not to alert other drivers that they are around.

“Just round the corner, other immigration officers have stopped an Indonesian delivery driver: ‘He is currently under arrest, first of all I need to take a photograph of him.’

“Checks on him indicate he is working here illegally and likely faces deportation.”

The platforms also have racially-charged authoritarian policies of their own, such as Uber Eats which uses Microsoft’s facial recognition technology which Microsoft itself has admitted does not work properly on ethnic minorities.

Here’s platform work researcher Dalia Gebrial, speaking about her research on facial recognition technology software in the platform economy:

“I was speaking to a driver of Bangladeshi descent, at a time he had a flare-up of eczema on his face which caused his skin to darken, which tends to happen for darker skin tones, and he failed a spot-check of this facial recognition software.

“So he was essentially immediately locked-out of his livelihood, of his only source of income, and for three months he was struggling to even get a response from Uber, just facing automated message after automated message. Because as far as they were concerned, there were a hundred riders behind him who would be able to take on the jobs that he wasn’t able to take on.

“It was only when his MP got involved that Uber had enough pressure put on them and actually re-instated him, but he wasn’t compensated. I’ve spoken to countless other drivers who have been in the same position and were never re-activated.”

This is part of the de-humanisation of riders which is characteristic of racially-discriminative labour abuses. It’s for this reason that in an academic paper on ‘racial platform capitalism’, Gebrial has argued that racialisation is an “organising principle” of platform capitalism. 

Gebrial finds that the the UK immigration regime combined with the misclassification of drivers as self-employed and the use of punitive forms of discipline through algorithmic management are the “processes of racialisation” which “have been crucial at every stage of the platform economy’s rise”. 

To the extent that platforms are simply a digital version of traditional labour markets, they re-produce the same forms of discrimination that ethnic minorities experience in standard jobs. But it’s worse than that, because the gig economy also undermines workers’ rights– the very tool with which oppressed and exploited workers can use to defend themselves. 

This produces a vicious cycle in which already marginalised workers are subject to further marginalisation by the inability to enforce their labour rights. That’s why building workers’ collective power in the gig economy is the best means to tackle the structural racism which keeps marginalised workers on the margins.

Episode 8: What makes platforms powerful?

There is no doubt about it, the largest digital labour platforms in the world today have significant power over consumers, workers, and even politicians. 

Let’s look at the biggest one, Uber. The company claims to have more than 131 million active users worldwide, that’s the equivalent of the whole population of Germany and Spain combined. They say they’ve got 5.4 million drivers, roughly the population of where I’m from: Scotland.

Uber’s not just big, it’s also influential. Here’s Mark MacGann, the company’s former chief lobbyist in Europe turned whistleblower, being asked about how easy it was for Uber to access political power:

Journalist: ‘When you are meeting with presidents, prime ministers, chancellors, city mayors, how easy was it for you to get those meetings for Uber?’

MacGann: ‘It was unprecedented in my career to have such easy access to senior members of government, heads of government, heads of state…’

Uber used this access to change laws, over-ride regulations and fundamentally transform the shape of the taxi sector internationally. Before, the sector was dominated by small, local taxi firms, but thousands of those have been put out of business by Uber. 

Uber’s influence goes well beyond the taxi industry: the company has inspired copy-cat platforms using a similar gig model, so that we now have ‘Uber-for-pets’, ‘Uber-for-flats’, ‘Uber-for-beauty’, and so on. Academics all over the world talk of the ‘Uberisation’ of industry sectors.

How did Uber become so powerful? And what is the method that platforms use in general to gain power? 

Technology is of course one part of the answer. Platforms have strong ‘network effects’ which tend towards users all gravitating towards one big platform. But technology is just a very small part of how platforms like Uber become powerful. 

There are three keys to understanding the power of digital labour platforms: Finance, labour and politics. Let’s look at each in turn.

We begin with finance. The story of Uber is not one of the plucky small-time entrepreneur who built up their business over time before becoming a giant. Uber started life as a giant. Why? Because it was funded by venture capital. 

Venture capital is money which investors provide to start-up firms, in return for a stake in the company. It’s been around for a long time, but the difference with Uber is the amount of venture capital it has raised has been off-the-scale, an unprecedented $23.9 billion from some of the world’s biggest companies, including Goldman Sachs, Microsoft, Saudi Arabia’s public investment fund and Blackrock.

These investors did not expect immediate returns on their money. Instead, Uber pursued what is known as a ‘growth-before-profits’ strategy. All that investor money was used to fund massive massive marketing campaigns and to subsidise Uber fares so that the company was cheaper than traditional taxis. Fares were not only discounted to customers, drivers were also ‘incentivised’ to join the app using high fares which would enable drivers to earn more than they usually would. This meant that Uber could build its customer base and its worker base, first in almost all of US cities and then across the world.

This external finance meant that Uber was able to run at a loss for the first 13 years of its life. As one venture capitalist and Uber investor, Shervin Pishevar, said in 2013, Uber was “in the empire-building phase”. Traditional taxi firms, which do not have access to this sort of finance, simply couldn’t compete. 

Once the empire is built and the competition eradicated, the idea goes, Uber could then raise its prices and its investors can reap the rewards of monopolising the taxi sector. It has not exactly turned out like that, as we will explain more in our next podcast, but the point here is that this huge venture capital funding made Uber very powerful overnight, a power it has used to game the market, cities and even its own drivers. 

Uber is just the tip of the spear in the gig economy – all of the major digital labour platforms in the world today are financed in this way.

The second factor in the power of platforms is their labour model. Platforms gain huge advantages by contracting workers on a self-employed basis for many reasons. One of the reasons is that it costs them nothing to register a worker on the app, as they only pay a wage for the time the worker spends executing a task. This allows the platform to have an over-supply of labour on its app, meaning there are more workers than there is work to do. 

This over-supply of labour weakens the power of workers and strengthens the power of the platform, because the worker faces more competition from other workers for tasks, and therefore is willing to accept lower pay rates to access the work. 

This problem also exists on an economy-wide scale. Ever since the 2008 financial crisis, wages have stagnated and there has been a rise in precarious work, not just in the gig economy but also in things like agency work and zero-hour contracts. This general precariousness is good for platforms like Uber because they offer low-paying, precarious jobs too. If wages were rising and there was greater job security outside the gig economy, workers would have less incentive to work for Uber. 

We have seen this dynamic play out in the last few years. During the pandemic, many Uber drivers stopped driving because of the health risks and low consumer-demand. As a result, Uber had a labour shortage, rather than their usual over-supply. In response, they had to increase the wages of drivers to attract more workers to Uber.

In the wake of the pandemic, the cost of living crisis kicked-in, which pushed more workers to drive for Uber to earn additional income. This rise in poverty was good for Uber, as the company’s CEO Dara Khosrowshahi was happy to boast about.

Khosrowshahi: “72% of drivers in the U.S. are saying that one of the considerations of their signing up to drive on Uber was actually inflation, life is getting more expensive, they need to pay extra for their groceries, so on the supply side we may be actually benefiting from the inflationary environment.”

Not only does Uber benefit directly from fake self-employment, it also benefits indirectly from poverty wages across the economy.

The final part we need to look at is politics. Uber being flush with venture capital money has also allowed it to buy influence in the corridors of power. Uber, Lyft and other gig platforms spent $224.3 million to convince Californians to vote against employment rights for gig workers, a record-sum for a state-wide referendum. 

In Brussels, digital labour platforms have a small army of lobbyists to lobby the European Union against any reforms which it doesn’t like. After a European Parliament vote on the EU Platform Work Directive, the rapporteur for the Parliament, Elisabetta Gualmini, said she had never seen such an intense campaign to pressure politicians as the one waged by the platforms over the Directive.

But these platforms do not just stick to legal routes to apply pressure. As the Uber Files scandal revealed, Uber’s power grew through the systematic breaching of laws. 

First, the company knowingly broke local and national regulations when entering markets, in an attempt to force governments to change the laws or negotiate. MacGann described the strategy as “basically Uber launches, and then there is a regulatory and legal sh*itstorm.”

Secondly, if governments and regulators sought to bring the company to heel, Uber had a range of illegal tactics to deploy, including a ‘kill switch’. This kill switch destroyed all of the company’s documentation whenever investigators were about to enter their offices.

Third, Uber buys powerful people. Neelie Kroes, ex EU Vice-President for the digital agenda, breached EU rules when lobbying the Dutch Prime Minister and EU Commissioners on behalf of Uber. 

The Uber Files also revealed that academics and newspapers were on the Uber payroll, but they never made that public when publishing research and writing opinion pieces helpful to the company. 

Uber’s money has corrupted not just politics but also civil society. Is it any wonder that Uber has been able to avoid having to give its workers’ social security benefits and pay them for waiting time when money talks in politics? 

Uber has huge financial muscle and it has translated that into political power to defend an illegitimate and exploitative business model. 

So that’s what makes platforms powerful, but it’s important to know that they are not omnipotent. In the final three episodes of A Rebel’s Guide to the Gig Economy, we will explain where their weaknesses are and how gig workers can take advantage of them.

Episode 9: Why do platforms struggle to turn a profit?

There is a strange paradox in the gig economy. Platforms can, at one and the same time, have huge resources, be very powerful institutions politically and economically, and yet still struggle to be profitable. 

Uber is the most well known example. The company was not profitable for the first 13 years of its existence, burning through $31.5 billion in that time, before finally turning a small profit in the second quarter of 2023. 

But there are many other cases of digital labour platforms struggling to make money. Indeed, it is difficult to find a major food delivery platform that has actually made a profit. Some of these platforms have been so far in the red that they’ve gone bust.

Why, despite huge customer bases and very limited government regulation, do these platforms find it so difficult to earn more money than they spend?

At first, these platform companies weren’t looking to be profitable. As we explained in the last episode, they were funded by huge sums of venture capital to prioritise growth before becoming profitable, in order to defeat competitors and build a dedicated customer base.

But despite the huge growth of these platforms, the profits still haven’t come. Many investors have lost patience. The share prices of all big food delivery platforms are now well below their value when they first floated on the stock market. What went wrong?

First of all, we need to understand the financial context in which these platforms operate within, which has changed dramatically in recent years. 

After the 2008 financial crisis, governments propped up the banks with huge bailouts, including through a money creation policy known euphemistically as Quantitative Easing. 

This policy of socialism for the banks meant that there was huge amounts of money in the financial sector looking for a home. And because interest rates were low, for a time even at 0%, financial investors were incentivised to spend since they would not earn much interest from saving.

This was the context for a huge surge in investments in tech start-ups, which were seen by the money men as ‘the future’ in light of the success of firms like Facebook and Apple. All of the big gig economy platforms today were born in this environment where, as the bankers like to say, money was cheap.

However, the days of cheap money are over. The pandemic and the Ukraine war has led to inflation surging around the world, leading Central Banks to sharply raise interest rates, meaning the cost of debt has become more expensive. That has led venture capitalists to pull-back on subsidising loss-making operations like the gig economy platforms. In the financial world, this has been dubbed ‘the tech downturn’. 

Suddenly, platforms like Uber have had to change strategy. Instead of growth-before-profits, the new buzzphrase is ‘pathways to profitability’: all of the big platforms are cutting spending and wages, and for a time they raised customer prices, in a bid to try to become financially self-sustaining. Uber CEO Dara Khosrowshahi sent a memo out to staff in 2022 saying: “Channeling Jerry Maguire, we need to show them the money”. 

For their drivers and couriers, Uber’s bid for sustainability has been devastating. As one courier in London who has worked for Uber Eats for seven years told the Guardian, when he started as a courier he could earn £1000 a week, now he doesn’t even make half of that. 

For customers, Uber has also got a lot more expensive, with prices higher now than they ever were under the traditional taxis which Uber had been under-cutting for years.

Here’s journalist Steven Levy talking about the response of Khosrowshahi when he was told the price of Levy’s Uber to get to the interview:

“That was one of the first questions I asked him, ‘do you know how much it cost me to go 2.9 miles to where we are now in an Uber?’ And he guessed $20, and I said ‘no it was about $52, and he said ‘oh my god, wow!’”

But it gets worse, because, as Transport Economist Hubert Horan has pointed out, Uber is still struggling to make any money on its core operations, and in Q1 2024 the company was back in the red again. Despite all the belt-tightening, Khosrowshahi is still struggling to show investors the money.

The reason for this can be found in an important insight of Horan’s into the fundamentals of the taxi industry since its origins. That is, that taxis have always been a low-margin industry. 

85% of the cost of a taxi is the fuel, the cost of the vehicle and the wage of the driver. The price to the customer has to cover all of this without being so expensive that they are put-off getting a taxi at all. There is a reason there was no big global taxi corporations before Uber: there’s just not a huge amount of money to be made out of it.

Uber told its investors that its use of an app would transform the economics of the taxi industry, but the 85% cost of the taxi – the fuel, the vehicle and the driver – still exists with an Uber. Only Uber has to pay an additional cost to service the app as well as the huge salaries of its top executives, making a ridiculous €24 million a year salary for the CEO, wages which no small taxi boss ever made. 

Here is tech critic Paris Marx talking about how Uber’s promises of a more efficient taxi sector haven’t come to fruition:

“By using these technologies to upend the taxi system, they were going to make public transportation a lot more efficient in cities. What independent researchers have found is that basically all the promises they made about the improvements they were going to deliver were not followed through on.

“The Uber model is actually a lot less efficient because you don’t have the fleet to manage but you do have these really expensive headquarters, the tech engineers who are paid a lot of money, instead of the lower cost taxi model.”

The point is that while Uber may have made it easier to book a taxi, it has done nothing to improve the productivity of the taxi itself. 

As for food delivery, that’s another low-margin industry. After the restaurant and the food delivery courier have been paid, there’s not a lot left over. One study by the Open University of Barcelona found that the economics only works at scale, in big cities, because it takes 8,000 deliveries to break even, and 19,000 to continue expanding. Moreover, if the restaurant fee for each delivery was to be 20% rather than the 30% that most platforms charge, then twice as many deliveries would be necessary just to break even. 

Some Uber investors were convinced that future tech advances would make taxis and food delivery more productive and therefore more profitable. For years, Uber was funding research on driverless and even flying cars, and they’ve spent huge amounts of money on using robots for food deliveries. But during the pandemic, as Uber began to make cutbacks, it sold its driverless car section. Uber has given up on what used to be one of its big selling points: a driverless future for taxis.

However, Uber does still have some tricks up its sleeve. Because the company gathers huge amounts of proprietary data on its drivers and customers, it can use this data to manipulate wages and prices. Secondly, it can sell this data on to third parties. Finally, this data can be used to advertise other Uber services to customers, with the company keen to build a transport ‘super-app’ where customers can meet all their transport needs – taxis, trains, buses, flights, cruises – through just one app. 

To become a super-app, Uber is trying to use its huge lobbying machine, which doesn’t seem to have faced the same belt-tightening as its drivers and riders have, to convince politicians that it should be trusted with public services and with the decarbonisation of public transport. That way, it can also profit from government subsidies. There are signs that some local governments around the world are being convinced by this. 

Whether all of these additions to Uber’s core operations will make the company profitable over the long-term is difficult to say. But the fact that a combination of monopolising whole industry sectors and driving small competitors out of business, manipulating workers’ data, government subsidies and a labour model of precarious piece wages is all needed to get Uber even close to profitability should be a good indication that something stinks here. 

The reality is that, whether platforms like Uber are profitable or not, they don’t serve the public good when it comes to the need for high-quality, sustainable, worker-friendly public transport services.

Episode 10: Why should gig workers join a union? 

In these podcasts we have been talking about some of the problems faced by workers in the gig economy. We’ve talked about: the shortcomings of ‘algorithmic management’, the lack of real flexibility gig workers have, the ways in which platforms manipulate politics and the functioning of the economy, and the way that the platforms can entrench, rather than do away with, problems for women and people of colour. But we haven’t actually talked about what you can do about all of this.

The starting point is rather simple: join a  union. 

Sometimes people think that it isn’t possible to build a union amongst gig workers. They point out that gig workers rarely work together on a single ‘shop’ floor, or they say that platform companies’ use of algorithms mean they are too strong, while gig workers have too little attachment to the company to want to organise collectively. This has led some to consider gig workers as ‘unorganisable’.

But the reality begs to differ! With the growth of the gig economy over the last decade, there’s been thousands of new worker associations emerging all over the world. A recent academic study identified news reporting of 1721 cases of gig worker unrest worldwide between 2017 and 2020, with 38% of those cases involving workers’ taking strike action.

Some of these strikes are organised informally through whatsapp groups, some of them are organised by grassroots worker associations and some through traditional unions, but whichever way gig workers choose to organise, the important part of any type of union organisation is that gig workers act collectively, using their collective power as workers to disrupt the operations of the company and demand that the platforms negotiate with them to improve their working conditions.

The most common type of strike in the gig economy is for higher pay, but disputes have also taken place over the benefits they receive, like holiday and sickness pay, as well as protections that they need on the job, like equipment and accident insurance. It’s possible to organise a strike over any issue that affects the lives of gig workers. 

Indeed, in the gig economy, because the traditional Human Resources manager doesn’t exist, workers have no other way to make a complaint other than to strike. Also, because they are usually self-employed, there’s fewer strike laws, so workers can organise strikes informally without jumping through the same regulatory hoops. 

Gig economy researcher Jamie Woodcock has said that in the gig economy the “common form of voicing problems at work becomes the wildcat strike.”

One of the most successful strikes in the gig economy took place in Greece in September 2021. E-Food, which is owned by German multinational Delivery Hero, decided to sack all of the workers that were hired as employees and re-hire them on an independent contractor basis.

In response, the workers held mass meetings and decided to organise a huge strike across Greece, with between 1000 to 1500 riders driving and cycling through the centre of Athens in a massive march. Alongside the strike, they organised a #Cancel_EFood campaign, which got a massive response on social media, with thousands of E-Food consumers tweeting that they had deleted the app, while Google users downgraded the apps performance from 4.5 to just 1 star.

Ahead of another day of strike action, the E-Food bosses decided not only to reverse its decision, but to give the riders permanent contracts, having previously been on three-month fixed term contracts. The riders went ahead with the second day of strike action anyway to celebrate their victory.

This example shows the potential for gig workers to win, but workers can only win in this way when they organise collectively. As individuals, gig workers are easily ignored by the platform and they are easy to replace. Platforms are also commonly known to de-activate workers from the app who they consider to be ‘troublemakers’. But what’s really important to remember is that when the troublemakers are organised together, they have power to cause real trouble for the platforms and transform their working conditions.

You may still doubt the potential power of unions in the gig economy, but platforms like Uber don’t. They see real unions as a real threat, which is why they spend significant amounts of time and money strike-breaking, or  funding so-called “yellow unions”, which repeat the narratives of the company and help to confuse and divide the workers. Uber wouldn’t bother funding yellow unions if they weren’t scared about what real unions could do.

There are lots of tactics that can be used by gig workers to maximise the effectiveness of their action. For example, the Stuart Delivery strike in 2021 and 2022 in the north of England was the longest in the history of the gig economy. While the strike did not win all of its demands, it did win some of them, and the reason they were able to sustain the pressure on the French company for so long was because they had a very targeted approach to the strike.

Rather than striking all the time, the strike focused on picketing the most popular restaurants at the peak times for food delivery. This way, the couriers could still make money the rest of the day, necessary for workers in precarious circumstances, while putting maximum pressure on the company’s relationships with its most important restaurants. The pickets were also vital in recruiting more riders to join the strike, increasing its size and strength.

The grassroots union which organised the strike, the IWGB, managed to raise a lot of money for the workers in a hardship fund it promoted on social media, with donations coming in from members of the public and other unions. That money was used to reduce the financial burden on the riders from participating in such a long strike.

Here is Khalil Lange, one of the leaders of the strike in Sheffield, on the 21st day of the strike talking about the confidence their approach was breeding among the workers:

“At first they were a bit hesitant about whether or not it was possible to do. So they were doing it but they were wondering, ‘are we going to be able to sustain, is it going to work, is it going to get the results we want?’

“And then, we started getting these little moments, when [management] get in touch and are reaching out. And we put the word out that the only reason they are doing this is because of what we are doing, they are scared. When you force a company to respond it shows they are worried about you not the other way around, so hold it.

“And as we’ve held for longer and the strike has become easier, and as other workers, who maybe are not in the strike and on the picket, they see us and they know what we’re doing, and they go ‘we will live and go somewhere else’. And we here the effect from the McDonalds managers who are having ‘issues’, they are saying ‘we are losing money’, and that gives the guys that confidence to say ‘you are actually succeeding, keep it up’.

“So when Stuart finally come out and have a face-to-face meeting, that’s just left everybody feeling like, yeah as long as we hold out we will get the win.”

These are just some of the creative strategies gig workers have used to fight for their rights. Unions also play a crucial role in other ways: communicating with the media to get the workers’ message across, lobbying governments for changes to regulation, and taking specific concerns of their members to the platforms, such as if a worker has been wrongly deactivated from the app. 

In some European cities, such as Brussels and Paris, gig worker unions have organised a space for food delivery couriers to meet, rest, wash, fix their bike and get help with any problems they have. This is called ‘The House of Couriers’ and provides the sort of collective infrastructure for gig workers which the platforms refuse to provide as they prefer to keep them atomised and isolated while working. 

Of course, it’s not easy. Gig workers’ strikes often don’t succeed, as the platforms have numerous ways to defeat them. Most importantly, it costs the platforms nothing to just register more workers on their app when a strike happens, making it extremely difficult for gig workers to achieve a critical mass which can seriously disrupt the company’s operations. 

Because gig work has very low barriers to entry, there are usually unemployed or underemployed workers looking for more work, and the platforms often make the pay higher when you first sign-up to draw you in and then progressively reduce the pay over time. In response to a major food delivery strike in London in February 2024, the platforms raised pay rates significantly during the hours the workers were on strike, sometimes offer pay rates that the workers had never seen before, in order to incentivise workers to work those hours and thus break the effectiveness of the strike. 

So as we’ve talked, it’s not easy for unions in the gig economy to win, but just because it isn’t easy, that doesn’t mean it’s not possible. 

In the 18th and 19th century, as the labour movement was just getting started, many workers lacked fundamental rights on the job and it was extremely difficult for workers to strike and to win. But with persistence, unity, and careful strategy, they eventually did win, and secured workers’ rights which most workers today take for granted.

But with the emergence of the gig economy, app-based workers have to fight and win workers’ rights all over again. And it can’t be done without strong unions.

Episode 11: How do gig workers take control of their data?

A digital labour platform, like any capitalist enterprise, is based on a division of labour. The CEO and the investors own and control the digital application, the data and the algorithm which makes it all function. They decide everything about how the platform works.

The workers, on the otherhand, do all of the execution of the work. They are the ones who pick up the passenger and drop them off. Without them, there is no business. Yet, not only do workers not own or control the platform, they aren’t even given key information about how the boss makes decisions, or what is done with all of the data the company has collected from their labour. 

But what if that was different? What if this division of labour was abolished? What if the workers were the ones who executed the work and owned and controlled the platform? 

If this seems like a utopia, you should know that it already exists in miniature, in the form of platform co-operatives. In the food delivery sector, Co-op Cycle is an association of more than 70 bike delivery co-ops internationally, all using the Co-op Cycle software for their apps. A % of the revenue from each co-op goes towards maintaining and improving the software, a digital commons, and all decisions are made democratically between the co-op members.

Here is Trebor Scholz of the Platform Co-operative Consortium talking about the benefits of ‘Up & Go’, a home cleaning platform in New York, for its workers:

“Here is Esmeralda Flores, she is a home cleaner in New York City. And like so many home cleaners, she is using a tech platform, an app, to connect to clients. But unlike other home cleaners, she is making $25 an hour, which is twice as much as she used to make at her previous company, and she makes the living wage. There is no algorithmic boss at her company which changes the pay and hours from under her feet, so she has some stability for her family. And every week the workers at this company are meeting to decide how to run this company. They decide on the operations.”

Many platform cooperatives are very successful at local level, but the difficulty that platform co-operatives have is one of scale: they are usually not competing directly with the big platforms like Uber because they are not big enough, and so for most workers they are not a realistic alternative to working for the platforms.

This problem of scale is primarily about finance. Platforms become powerful because they have received huge sums in up-front investment, long before they make a profit. A large part of this investment goes towards a marketing budget, so that citizens know about what the platform offers and therefore can become customers. Co-ops can’t access these financial markets because they are not for-profit business models, so without big marketing budgets they are largely reliant on word of mouth to grow their customer base. 

That’s why, if you really want to change the gig economy, you can’t ignore politics. It is the state which sets the framework in which economic actors – workers, platforms, financial investors – all operate within, and therefore to change the gig economy requires changing the rules of the game. 

How could the platform economy be re-wired differently? At the most basic level, the state could regulate platforms in such a way that workers can easily access legible information about their own data. That wouldn’t change the fundamentals of the division of labour between worker and capitalist, but at least it would ameliorate the information asymmetry which currently exists between workers and platforms, information that could be used by workers to make collective bargaining claims and much else besides.

More ambitiously, the state could play an active role in supporting democratic platform models. National and local government could favour co-operatives over for-profit models through use of grants and tax policies. Or, the public-sector could establish its own platforms as alternatives to Uberisation.

An example of this is the Barcelona Metropolitan Area which has established a public-sector app that makes it easy for local citizens to access Barcelona’s yellow & black taxis. This has been combined with strict regulations which effectively bar ridehail platforms like Uber from operating in Barcelona, on the basis that the taxi industry is considered a public service in the Catalan capital, and should be protected in the same way as the bus or train service.

This public platform model has increased the efficiency of taxis, which spend less time driving around looking for passengers. It also has ecological benefits, as less fuel is consumed. A public taxi model also reduces the problem of needing to spend a fortune on marketing, as government has direct means of providing information to citizens about the app. 

Another big idea is to make workers, and indeed all citizens, the owners of their own data by default. One way of doing this would be on an individual basis, where companies have to pay people for access to and usage of their data. Workers could club together and establish data collectives, with the sum of the data collectively being of greater value than its individual parts. 

Here is Parminder Jeet Singh, Executive Director of IT for Change, imagining how a data collective of Uber drivers in New Delhi could work:

“Community data, and community ownership of data, from that we are also able to derive other forms of collective ownerships of data. For example, Uber drivers can collectively own the data which they contribute, which alone makes Uber such a big corporation. The New Delhi drivers own the data which the drivers give to Uber, and the Uber operation in New Delhi is based on that data.

“This kind of right to that data, should be able to claim some sort of co-ownership of Uber’s operations. They can insist that they sit on the board of Uber.”

Alternatively, some consider a “data commons” to be the answer. By making data a collective good in shared stewardship and based on open source licensing and protocols, it can be used by anyone, eliminating the private ownership of data which allows for the creation of enormous IP monopolies in the digital age. 

Whether it be co-operatives, greater regulation, public-sector apps, data collectives or a data commons, all of these would be steps towards greater democratisation of data and empowerment of platform workers. 

The starting point to move in this direction is an awareness that data is power, and data workers – which is really what gig workers are – will always be the weaker party as long as their own data is owned and controlled not by them, but by a class of people who call themselves entrepreneurs and innovators, but are simply their data bosses.

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