Literary Insights

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Here are the key points from the introduction:

The “gig economy” refers to online platforms and apps that connect consumers, businesses, and workers for very short-term jobs, often just a few minutes long. Major players include Uber, Lyft, Deliveroo, TaskRabbit, etc.
These platforms promise convenience and flexibility but often leave workers without security or protection, essentially treating labor as a commodity to be bought and sold.
Amazon Mechanical Turk pioneered the idea of “humans as a service” - renting out small units of human labor like any other IT service.
While laws have long tried to prevent the commodification of labor, gig platforms found ways around these protections by rebranding their workers as independent contractors rather than employees.
There is intense public debate around the gig economy, with some seeing it as exploitative while others argue it increases efficiency and flexibility. The reality is complex.
This book will explore the promise and perils of work in the gig economy, looking at its innovation but also its disruption of traditional labor protections.

The gig economy relies on technology and algorithms to match workers with tasks, presenting itself as simply facilitating connections between independent workers and clients. But in reality, platforms exert significant control over transactions, resembling traditional employers more than passive intermediaries.

Despite this, platforms classify workers as independent contractors beyond the reach of employment regulation. They portray themselves as innovative technology companies ushering in a new era of flexible entrepreneurship. But for many workers, gig jobs replace traditional employment and come with insecurity and lack of protections.

The book explores the reality of work and life in the gig economy, seeking solutions to problems like low pay and instability while recognizing platforms’ potential benefits. The goal is a sustainable model where all can enjoy innovation without reducing humans to a disposable service.

Regulation is key to ensure platforms bear costs of their business model, establishing equal conditions for all. Rather than humans as a service, platforms should be. The gig economy holds promise but must work for everyone involved.

Here is a summary of the key points about the gig economy from the introduction:

The gig economy refers to the increasing prevalence of short-term, independent work assignments (“gigs”) facilitated by digital platforms that connect workers with customers.
Key examples of gig economy platforms include Uber, Lyft, TaskRabbit, Amazon Mechanical Turk, Deliveroo, and many others. These platforms act as intermediaries between workers and customers.
Platforms rely on sophisticated algorithms to match workers with customers and exercise ongoing control over these relationships.
The variety and number of gig economy platforms is growing rapidly around the world. Their business model centers on taking a commission from each transaction they facilitate.
Advantages of gig work include flexibility in choosing when and where to work, and the ability for platforms to offer innovative, affordable services.
Downsides of gig work include economic insecurity from intermittent work, and a lack of traditional employment protections like minimum wage, benefits, and job security.
The rise of the gig economy represents a major shift in how work is organized and regulated, raising complex questions around employment status, workers’ rights, and the role of digital platforms.

Here is a summary of the key points about the size and scope of the gig economy:

There is debate about how big the gig economy really is. Some claim it is reshaping work, while others argue it is still a small fraction of labor markets.
Estimates of participation vary widely, from 0.5% to over 30% of the workforce, depending on how gig work is defined and measured.
Surveys find between 1-5% of adults actively participate in gig work as a main job, with more doing it occasionally or supplementary.
The gig economy concentrates in certain sectors like transportation, delivery, home services, remote digital work.
Geographic concentration is high, with most activity in major urban centers.
The number of gig economy workers is growing steadily, though the pace is debated. The flexibility and supplementary income appeal to many.
Challenges measuring the scope include definitional issues and underreporting by survey respondents. Self-reporting surveys may underestimate.
The gig economy intersects with broader trends in non-standard and independent work. Traditional freelancing is also growing.
While the scale is uncertain and evolving, the gig economy is likely to remain a small but significant portion of the labor market. Its influence may be disproportionate to its size.

Here is a summary of the key points about the economics of the gig economy and the growth of sanction costs on traditional businesses:

The gig economy has seen explosive growth in recent years, fueled by large amounts of venture capital investment. Platforms like Uber and Handy have expanded rapidly across cities and countries.
One economic rationale given for the success of gig platforms is that they greatly reduce search and transaction costs through better matching of supply and demand via algorithms and rating systems. This unlocks new value by enabling transactions that otherwise would not occur due to high friction.
However, some argue this does not fully explain the high valuations of many platforms. An alternative view is that much of platforms’ value comes from regulatory arbitrage - avoiding the regulations and costs faced by traditional businesses in the same sector.
For example, ride-hailing platforms classify drivers as independent contractors rather than employees. This avoids costs like minimum wage, benefits, payroll taxes, and more. Critics argue this creates an uneven playing field.
More broadly, platforms can disrupt regulated industries by using apps and Internet platforms to connect supply and demand in ways not envisioned in current regulations. While providing benefits, this also imposes costs on incumbents required to follow legacy rules.
As the gig economy grows, regulatory gaps create tension and highlight the need to modernize legal frameworks. Resolving this is crucial for a fair playing field between platforms and traditional businesses.
Tomassetti argues that Uber does not live up to its claimed “disruption” when analyzed under Coasian theory. Platforms like Uber lower transaction costs compared to incumbents, but their production processes mostly follow traditional models (Uber operates like a taxi firm).
The key to platforms’ business models is regulatory arbitrage - evading employment regulations by classifying workers as independent contractors. This allows them to avoid responsibilities and costs associated with employing a large workforce.
Most gig economy platforms are sustaining major losses, propped up by venture capital. This raises questions about whether they will ever be profitable on their own.
Investors may be willing to burn so much cash because platforms are trying to establish monopoly power, not just harness network effects. Massive subsidies allow them to flood the market and undercut competitors.
If platforms achieve monopoly status, investors expect they will then be able to recoup losses through monopoly rents in the future.
There are contrasting views on the gig economy. Some see it as increasing competition and benefiting consumers and workers through flexible work and extra income. Others see it as exploitative and harming workers through low pay and poor conditions.
Supporters argue the gig economy provides flexible work opportunities, helps excluded groups access work, allows people to pursue dreams/passions, and benefits consumers through cheaper, easier services.
Critics argue it offers illusory flexibility, isolates workers, fosters competition, involves invasive data collection, provides low unpredictable wages, and harms worker resilience.
There are also concerns about the quality of gig economy services and algorithmic price increases.
While increased economic activity brings gains, questions remain around how equitable they are across society. The gig economy embodies long-standing debates about technology’s impact on labor markets and inequality.

Here are the key points regarding industry narratives and regulation of the gig economy:

Industry narratives aim to shape public understanding and regulation of the gig economy. The stakes are high, as favorable regulation gives companies advantages.
Firms employ public relations advisers and form industry groups to promote positive narratives about the gig economy. Some claim to represent workers while lobbying for industry interests.
A common narrative is that regulation hinders innovation. More sophisticated versions propose “participatory” models of regulation without state involvement.
Attempts to rebrand gig work as non-economic activity or fundamentally different from traditional work aim to avoid regulation. But the commercial focus and employment-like aspects of much gig work undermine this.
Claims that gig work represents genuine entrepreneurship and innovation pose a significant challenge. If true, traditional employment regulation may not apply. The validity of these claims requires careful scrutiny.
Overall, industry narratives aim to shape information asymmetries between regulators and firms. Scrutinizing the doublespeak and recognizing the diversity of gig work is key to balanced regulation.

Here are the key points from the summarized passage:

Many on-demand platforms argue that existing regulations are harmful to consumers and workers, and entrench established competitors against disruptive start-ups. They advocate for minimal or no regulation.
This “ask forgiveness, not permission” approach allowed some platforms, especially in transportation, to expand rapidly. However, it also led to clashes with regulators and incumbents around the world.
Some acknowledge that regulation is necessary, but argue for an “innovation first, regulation later” approach that allows experimentation. Others say platforms themselves should take on more regulatory responsibility.
However, past regulation shapes today’s choices, so care is needed. Letting platforms self-regulate raises issues around accountability and effectiveness. Overall, the anti-regulation narrative seems designed to shield platforms from oversight, rather than benefit consumers and workers.
Many calls for deregulation of the sharing/gig economy are premised on fostering innovation by small startups. However, many key players have quickly become large companies themselves.
The notion of platforms as “disruptive innovators” is also questionable. Their business models are often not that innovative or disruptive in the original sense meant by Clayton Christensen. Rather, “disruption” has come to mean breaking laws and regulations.
Ignoring regulations is portrayed as virtuous innovation, likened to resistance heroes like Gandhi or Rosa Parks. But some argue it is more akin to “corporate nullification” and establishing services before regulators can act.
Complete deregulation is advocated by some as fostering “crowd-based capitalism”, with regulation seen as a constraint on innovation. But this often just maximizes platforms’ profits at the expense of competitors, consumers, and society.
While increased competition has merits, the broader push for complete deregulation relies on misleading narratives, misapplying disruption theory, and excuses for breaking the law.
The real prize for platforms has been selling gig work as innovative entrepreneurship, avoiding employment laws. This involves doublespeak around the nature of gig work.

Here are the key points about the language used to rebrand work in the gig economy:

Platforms use communal language like “sharing”, “peers”, and “neighbors” to portray their services as informal community assistance rather than businesses. This framing aims to avoid regulatory obligations.
In reality, most gig economy platforms are profit-driven businesses, not altruistic community endeavors.
Workers are rebranded as “freelancers” and “entrepreneurs” rather than employees. This recasting aims to avoid providing protections like minimum wage and anti-discrimination standards.
Platforms present themselves as passive matchmakers rather than powerful labor intermediaries. But they exert significant control over workers through contracts, guidelines, and oversight.
Euphemistic language is used for aspects of the work experience, like being “onboarded” instead of hired, and “terminating supplier agreements” instead of firing workers.
The language aims to obscure the business model and employment relationship to avoid regulatory scrutiny and obligations. But it contrasts sharply with the reality of profit-driven platforms and precarious work.

This passage discusses how gig economy platforms use narratives of entrepreneurship and innovation to argue against the applicability of existing employment regulations.

The key points are:

Platforms portray gig work as empowering micro-entrepreneurship that unlocks new economic opportunities. They claim it allows workers flexibility and independence to be their own bosses.
Based on this narrative of transformational innovation, platforms argue employment regulations are outdated and a hindrance. They lobby for exemptions and new laws classifying workers as independent contractors.
Proposals range from denying employee status entirely to creating intermediate “third category” laws with reduced protections compared to employment. The common thread is using tales of innovation to justify deregulation.
Examples are given such as ride-sharing laws in some US states that codify contractor status and carve out exemptions, as well as EU guidance echoing industry views on classification.

In summary, by rebranding gig work as entrepreneurial innovation, platforms aim to avoid employment regulations through contractual reclassification and shaping more favorable laws. The language suggests empowerment while often reducing protections.

Here is a summary of the key points regarding the claims of entrepreneurship and autonomy in gig economy work:

Platforms portray gig workers as “micro-entrepreneurs” who have freedom and autonomy. This supports their narrative that workers are independent contractors, not employees.
In reality, there is a spectrum of experiences. Some workers do have genuine autonomy and entrepreneurial opportunities. But many face tight control by platforms, low pay, insecurity, and lack of legal protections - more reminiscent of precarious Victorian-era work than Silicon Valley glamour.
Platforms exert control through Ratings systems, algorithms that govern access to jobs, and detailed service requirements. This undermines claims of independence.
Earnings are often low and unpredictable, without employment benefits like minimum wage, paid leave, insurance. The rhetoric of high median incomes obscures the precarity many face.
Gig work is presented as flexible, but workers can face unpredictable hours, risk of deactivation, and pressure to constantly work to get jobs. Autonomy is limited.
While some workers successfully operate independent businesses through platforms, many lack capital and market access to be true micro-entrepreneurs. Platforms provide the underlying infrastructure.
The entrepreneurship narrative is overstated for a large proportion of gig workers, contradicting the premises underlying claims that employment regulation shouldn’t apply.
Scientific management, or Taylorism, aimed to improve business efficiency through close monitoring and control of workers and frequent adjustment of pay based on output. In practice, it was exploitative and dehumanizing.
The on-demand economy has resurrected Taylorism under the guise of technology and algorithms that enable an unprecedented degree of oversight and control.
Rather than just ‘matching’ workers and customers, platforms use rating algorithms to tightly manage a large, invisible workforce.
Algorithmic control is exercised in myriad ways, from vetting workers, assigning tasks, and directing how work is done, to sanctioning unsatisfactory performance.
Rating systems serve as a substitute for traditional management, enabling ‘soft control’ over workers’ routines. Ratings have little value in signaling quality but are powerful in controlling workers.
Algorithmic management limits workers’ autonomy regarding what tasks to accept, their working hours, and their actual pay. Platforms use various strategies to ensure quick acceptance of jobs, maximum work hours, and prevention of focusing only on profitable tasks.
Through a combination of technology and ratings, platforms exercise firm control over how work is done and the standard expected, despite the promise of autonomy.

Here are the key points from the passage:

On-demand platforms exercise significant control over how workers perform tasks, through stipulations like dress codes, scripts, and monitoring via technology. Workers have little ability to contest dangerous, unethical, or emotionally difficult tasks.
Platforms also control workers’ pay, by setting wages, controlling fees and payouts, and manipulating labor supply to depress wages. Many workers are paid below minimum wage.
Wage rates are kept artificially low through oversupply of labor and platforms taking an increasing percentage of earnings as commission.
This level of control over work and pay undermines the notion of worker autonomy and entrepreneurship frequently claimed by platforms. The realities of gig work differ starkly from the happy experiences described by some workers, who may not be representative or may feel pressure to give positive accounts.
On-demand platforms exercise tight control over workers through algorithms that assign jobs, set pay rates, monitor performance, and impose sanctions. This undermines the promise of autonomy for workers.
Platforms frequently change commission rates and fees in order to maximize revenue. This makes it difficult for workers to control their income levels.
Platforms often offer generous rates when entering a new market to attract workers, then later reduce pay. This ‘bait and switch’ tactic locks in workers then lowers their income.
Rating systems impose harsh and arbitrary sanctions on workers, with little transparency or opportunity to improve. Discrimination is a concern.
The ability to choose hours flexibly is constrained by platforms’ need to have enough workers available at all times. This pushes workers to work long hours for low pay.
Overall, on-demand platforms exercise pervasive control over workers through algorithms, making the promise of autonomy and self-determination largely illusory. Workers have little control over their work and income.
On-demand platforms initially offer good pay and conditions to attract workers, but then start to tighten conditions once they have an established workforce. For example, Uber forced drivers with older cars out of its premium UberBlack service.
Platforms frequently change pay structures and conditions, nearly always to the financial disadvantage of workers. These changes are presented cynically as boosting worker earnings through increased demand, even when workers contend they now have to work longer hours for the same pay.
On-demand workers face major obstacles to organizing and asserting their rights, with platforms actively discouraging unionization. Workers are isolated, often considered independent contractors unprotected by labor laws, and risk deactivation for speaking out.
Platforms prohibit basic freedoms like sending substitutes, soliciting own clients, or taking disputes to court. Contracts often ban workers from claiming employee status or suing the platform. Mandatory individual arbitration clauses are used to avoid class actions.
Rating systems, commission structures and threat of deactivation lock workers into platforms. Rather than diversifying their work, workers are incentivized to concentrate their activity on one platform, becoming dependent on its algorithms.

Here is a summary of the key points in this chapter:

The innovation claim is central to sharing economy doublespeak - it is used to argue against regulation and treating platforms like other businesses.
There is a fundamental paradox: the technology platforms used by the sharing economy are undoubtedly innovative, but the business models and work organization are not new.
There is historical precedent for many aspects of gig work, including:
- The model of matching fluctuating labor supply with variable demand for work - this can be traced back centuries in places like Japan, Europe, England, and major cities.
- Low pay, harsh working conditions, lack of bargaining power for workers.
- Shifting economic and legal risk from companies to workers/consumers.
So while the technology is new, many aspects of gig work have existed before. The innovation claim is overstated when it comes to labor practices.
This suggests we should be cautious about buying the rhetoric that existing regulations cannot apply due to the supposed novelty. There is precedent that can inform regulation of gig work.
The chapter argues that gig economy platforms are not as innovative as claimed in terms of how they organize work.
Features like breaking jobs into tasks, crowdsourcing work, and powerful intermediaries have existed for centuries, such as in the putting-out system of home production common in the 19th century.
Just as gig platforms do today, historical systems also involved decentralizing production into small units that could be easily standardized, controlled, and measured.
Highly skilled work that requires training can also be broken down into discrete tasks and distributed, challenging the notion that this is a novel feature of digital platforms.
The resulting competition for routine, often low-paid work has a long history and is not unique to the gig economy.
In these ways, despite the digital infrastructure, the underlying business model shares many similarities with historical forms of organizing labour and production.
The central claim is that gig economy platforms have overstated their innovation when it comes to how they structure work, since many key elements replicating long-standing practices.
Task economies involve breaking down large data samples into small tasks that can be distributed to individual workers online. This allows companies to tap into a large, on-demand workforce.
There are historical precedents for this kind of commodified work, such as the outwork system of the 19th century. Outworkers performed small production tasks at home and were subject to aggressive competition and fluctuating demand.
Task economies unlock new labor markets by allowing participation from traditionally excluded groups like women, immigrants, and rural workers. However, this can lead to an oversupply of labor and heightened competition.
Intermediaries play an important role in managing dispersed workforces in both historical and modern task economies. They identify workers, allocate tasks, monitor quality, and take a cut of earnings.
Technologies like algorithms and geolocation may be new, but the underlying logic of intermediation has changed little over time. Control is exercised through economic pressures and job insecurity rather than direct supervision.
There are historical precedents for many aspects of gig economy work models, including putting-out systems and use of labor brokers in the 19th century.
These historical systems involved work being put out to individuals in their homes, with intermediaries coordinating and profiting from the work. Wages were low and work was irregular.
Similar narratives were used to justify poor conditions, portraying the work as “supplementary income” not subject to normal standards.
While not an exact replica of the past, gig work shows strong parallels in terms of undermining worker bargaining power through irregular work and intermediaries.
The innovation claims of the gig economy mask continuities with more recent trends like outsourcing and temporary work agencies. These models have also fragmented work and undermined standards.
Portraying gig work as radically new and innovative shields it from scrutiny and regulation aimed at precarious work. But there are clear historical and contemporary parallels. The gig economy combines longstanding models rather than reinventing work.
The gig economy claims to be innovative and disruptive, but in reality it is resurrecting old models of casual and fragmented work like outworkers, dock labourers, and temp agencies.
There is nothing new about decentralizing production and exploiting cheap labor. What is new is that technology allows even greater control over workers and matching of supply and demand.
The language of innovation conceals two problems with the gig economy model:

It shifts business risk onto individual workers without giving them the potential rewards of entrepreneurship. Platforms avoid putting their own capital at risk.
It may actually disincentivize innovation by entrenching incumbent platforms and discouraging investment in R&D and better working conditions.

Ratings algorithms serve to lock in both workers and consumers rather than facilitate genuine competition. The gig economy is focused on cornering the market, not fostering innovation.
Overall, the innovation claims ring hollow. The gig economy divorces entrepreneurial risk from reward and may hamper wider productivity growth. We should be skeptical of the rhetoric around innovation.
The heterogeneity of gig work means that any solution must balance flexibility and insecurity. The key is to recognize gig work as work, and regulate it as such under employment law.
The first step is to tackle the ‘personal scope question’ - are gig workers employees or independent contractors? Who is their employer? We can draw on existing legal frameworks to correctly characterize gig work and assign responsibility.
The second step is updating protective standards to suit the gig context. Key issues include minimum wages, social security, collective bargaining, and non-discrimination. Novel solutions like portable benefits can help provide security.
Overall, the aim should be symbiotic innovation - harnessing technology’s potential whilst protecting workers. Smart regulation can nurture innovation and flexibility while tackling insecurity.
Achieving this requires coordinated action - by platforms, policymakers, courts, and gig workers themselves. But creative solutions are feasible if we recognize that technology need not entail a race to the bottom on labor standards.

Here is a summary of the key points from the excerpt:

Legal regulation of the labor market is based on a divide between protected employees working under contracts of employment, and unprotected independent contractors.
Some gig economy platforms try to avoid regulation by misclassifying workers as independent contractors rather than employees, even when they exercise significant control over the work.
Platforms use contractual terms to assert workers are independent contractors, but courts look beyond the labels to the reality of the relationship.
Courts have developed doctrines like “sham self-employment” to reclassify workers as employees based on the level of control, even when contracts claim otherwise.
Platforms cannot avoid regulation simply by asserting in their terms that workers are independent contractors - the law looks at the facts of the relationship.
Bringing gig workers properly under employment law requires looking beyond contractual labels to the reality of the business model and level of control.
There has been a wave of litigation by gig workers against on-demand platforms seeking recognition as employees rather than independent contractors. Courts and regulators are beginning to look behind the contractual labels used by platforms.
Early case law suggests judges are willing to find employment relationships exist despite platforms’ protestations. Uber lost several key cases in the UK, with judges criticizing the “remarkable lengths” Uber went to in order to avoid legal obligations.
Results have varied across jurisdictions due to different legal tests and business models. But the overall trend seems to be towards recognizing employment status for many gig workers.
Platforms’ dispersal of control across workers, customers, and algorithms can make identifying the responsible employer more complex. A functional approach that examines who exercises key employer functions like hiring, firing, and controlling work can help determine legal responsibility.
The complexity of gig work doesn’t mean employment laws shouldn’t apply. Determining status in ambiguous cases is what labor judges are trained to do. The law must adapt to economic changes like the growth of platform work.
The employment status of gig workers is often ambiguous - platforms classify them as independent contractors to avoid legal obligations, but in reality exercise significant control over their work.
A functional approach should be taken to determine employment status, looking at who actually controls key aspects of the work like pay rates and assignment of tasks, rather than just contractual labels.
Under this approach, platforms that set pay rates, control routes, assign jobs etc. would likely be considered employers with accompanying responsibilities like minimum wage, insurance, non-discrimination etc.
Genuinely independent entrepreneurs using a platform to find customers would not be considered employees.
In some cases, multiple parties like platforms and customers could be joint employers with shared responsibilities. Legal doctrines already exist to handle such situations.
Classifying platforms as employers and gig workers as employees is an important first step to address pressing issues like excessive hours, discrimination, income volatility etc. It establishes a baseline of rights and protections.
But further policy and regulations will likely be needed to fully address the unique circumstances of gig work. Employment classification alone won’t solve everything.
Platform-based gig work raises concerns about unpredictability of working hours, lock-in effects from rating algorithms, and difficulties organizing collective representation.
Employment law can help address some issues by classifying gig workers as employees entitled to basic rights. But more is needed to tackle underlying problems facing intermittent workers.
Policy ideas include:

Minimum working hour guarantees - requiring platforms to promise a minimum number of paid hours per week/month. Helps with unpredictability but has drawbacks like low hour requirements and incentives for employers to terminate workers before thresholds are met.
A ‘surge price’ for gig work - tiered minimum wages requiring higher pay rates if employers don’t provide reasonable advance notice of shifts. Makes flexibility more costly for employers. Based on ‘casual loading’ systems like in Australia.
New rules on ratings systems and dismissal - to reduce lock-in effects and arbitrary termination based on algorithms.
Supporting collective organization - e.g. access to workplaces and worker data to enable organizing, sectoral collective bargaining.

These build on and complement existing employment laws rather than replacing them. Aim is to develop standards tailored to problems facing intermittent on-demand workers, while maintaining worker flexibility.

Here is a summary of the key points about casual loading and portable ratings:

Casual loading was first introduced to compensate casual workers for lack of benefits and job security that permanent employees receive. However, some argue it has also been used to deter challenges to the conception of a permanent employee.
In economic theory, casual loading compensates for fewer fringe benefits, higher productivity during peak times, and shifts risk from employer to employee. It could motivate employers to move to more permanent positions to meet stable demand more cost-effectively.
Implementing differentiated minimum wage rates for casual work raises challenges like defining casual work, managing multiple rates, and preventing exploitation. The rate must not allow employers to “buy out” basic rights.
Portable ratings could empower workers to change platforms without losing their reputation. Inspired by EU corporate takeover law protecting workers and GDPR data portability rights.
With portable ratings, workers could freely move between platforms, benefiting worker mobility and potentially innovation. Concerns like workers abandoning past ratings would need addressing.
Overall, measures like casual loading and portable ratings could help rebalance bargaining power of workers and platforms, if carefully designed to avoid unintended consequences.
Proper classification of gig economy workers as employees is critical to address issues like low pay and lack of benefits. Platforms wrongly classify workers as independent contractors to avoid legal responsibilities.
Employment law does not inherently contradict flexibility. Platforms falsely claim employment rights are incompatible with flexible work arrangements that workers value. In reality, employers can provide full rights along with flexibility.
Collective action by workers is needed to rebalance power, but faces obstacles like fragmentation across platforms and retaliation. Initiatives like new unions and local regulation are overcoming some hurdles.
Traditional trade unions should embrace technology more to organize gig workers. Workers’ collectives could even develop their own platforms with appropriate standards.
Restoring employment law responsibility will bring major benefits for workers and is key for the gig economy’s long-term sustainability. The myth that rights contradict flexibility must be debunked.
The bargain between consumers and on-demand platforms may not be as good as promised. There are often issues with the quality of services provided.
Low prices come at a cost, as platforms minimize labor costs to offer cheap services. This can lead to problems like discrimination.
Platforms use tactics like initial low price estimates that end up much higher after added fees. Prices can also surge dramatically at peak times.
If issues arise that classify workers as employees rather than contractors, platforms may try to pass liability costs back to the consumer.
When things go wrong, platforms often disclaim responsibility by framing themselves as just an intermediary between consumers and providers.

In summary, while on-demand platforms promise great service at low prices, the reality often falls short. Consumers may end up paying more than expected and have little recourse if there are issues. The bargain between consumer and platform is not as straightforward as it first appears.

Gig economy platforms like Uber avoid paying value added tax (VAT) by claiming they are just intermediaries between workers and customers. This costs governments significant tax revenue.
Classifying workers as independent contractors allows platforms to avoid payroll taxes and social security contributions. This again leads to major tax losses for governments.
Making individual workers responsible for reporting income makes tax collection cumbersome and uneven. This further reduces tax revenue.
As a result, taxpayers indirectly subsidize the gig economy through lost tax income and increased benefit payouts to supplement gig workers’ low and precarious incomes.
Overall, the gig economy business model enables substantial tax avoidance and shifts the burden onto taxpayers. Authorities are starting to challenge platforms’ tax practices, but there is still a long way to go.
Gig economy platforms are struggling to comply with tax laws because the sums at stake for each individual worker are small, leading to significant lost tax revenue.
Treating gig workers as employees and platforms as employers could help solve many problems, including lack of consumer protection, tax non-compliance, and indirect subsidies to platforms.
Employee status would make platforms vicariously liable for harms caused by workers, improving consumer protection.
It would allow centralized tax collection, reducing non-compliance and administrative costs.
Platforms would have to provide baseline benefits like minimum wage, reducing worker reliance on public assistance.
Most importantly, it would level the playing field by making platforms bear the true costs and risks of their business models, rather than offloading them to workers, consumers, and taxpayers.

In summary, regulating gig work as regular employment has the potential to solve many problems by holding platforms to the same standards as other employers.

Employment law plays an important role in regulating the relationship between workers and employers, and in providing social protection for workers.
Platforms that sell labor should be treated as employers and held responsible for the risks and costs associated with the employment relationship. This includes paying minimum wages, insurance premiums, and providing other protections.
Classifying gig economy platforms as employers would eliminate the regulatory arbitrage they currently exploit and force them to compete on a level playing field.
Some platforms claim employment regulations would make their business models unsustainable. But there is little evidence that basic protections like minimum wage caused platforms like Homejoy to fail.
While some disruption is likely in the short-term as platforms adjust, eliminating regulatory loopholes will benefit workers, taxpayers, consumers and markets in the long run. Resources will shift to more efficient and innovative platforms.
The goal should not be to shut down platforms but to ensure they operate sustainably and equitably by bearing the true costs and responsibilities of employing workers. Applying employment law evenly is key to making the gig economy work for all.
Automation and technology are reshaping the labor market, and some predict massive job losses in low-skill occupations like those in the gig economy. However, the extent of automation’s impact is debated.
Critics argue automation threatens gig economy jobs like Uber driving and TaskRabbit tasks. If labor costs rise due to regulation, automation becomes more appealing to platforms.
But the limits of automation suggest many gig economy jobs requiring flexibility, judgement and intuition will prove hard to automate due to “Polanyi’s paradox.”
Automation excels at routine tasks with clear rules, not unpredictable human interactions. Many gig jobs involve physical dexterity and human judgement that current AI/robotics struggle with.
Rather than automating gig work, technology may enable more job fragmentation, allowing lawyers and other professionals to outsource discrete tasks to the crowd.
While some job destruction is likely, claims that automation will imminently eliminate most gig economy jobs seem exaggerated. The nature of gig work provides shelter from immediate automation threats.

Here is a summary of the key points about crowdsourcing and the gig economy from the introduction:

Crowdsourcing refers to outsourcing tasks traditionally performed by employees to a large, undefined group through an open call online. The term was coined by Jeff Howe in 2006.
The gig economy is a subset of crowdsourcing that focuses on on-demand labor platforms like Uber, Deliveroo, and Amazon Mechanical Turk. These platforms match workers with customers to provide services like transportation, delivery, and basic tasks.
Advocates see the gig economy as providing flexibility, entrepreneurship, and efficiency. Critics argue it leads to precarious work and enables exploitation of workers.
Core debates concern the status of gig workers as independent contractors vs employees, the sustainability of gig work, and the broader societal impact of platforms.
Key challenges include ensuring decent working conditions and rethinking employment law to provide worker protections in light of technological change. The book argues gig workers should be treated as employees under existing law.

Here is a summary of the key points from the given sources:

The gig economy involves exchange of labor through digital platforms like Uber, TaskRabbit, Handy, etc. It is growing rapidly, with some estimates suggesting the number of workers could reach 7.6 million by 2020. However, estimates vary widely due to lack of consistent measurements.
Gig economy platforms operate in diverse sectors like transportation, delivery, home services, skilled tasks, etc. Geographic coverage is expanding to cities globally.
Motivations for gig work include desire for flexibility and extra income as well as lack of other options due to economic conditions. Demographic groups like young people, low-income workers, immigrants are disproportionately attracted to gig work.
The market size of the gig economy is projected to grow substantially in coming years. However, much of the population still remains unaware of these platforms. So there is significant potential for further expansion.
Major platforms like Uber and Handy are handling over $1 million per week in transactions, demonstrating rapid growth. Uber’s valuation exceeds major automakers, though profitability remains elusive.

Here is a summary of the key points from the excerpt:

The gig economy promises flexibility and autonomy but can lead to precarious work and lack of protections for workers. Platforms like Uber avoid costs and regulations by classifying workers as independent contractors rather than employees.
Uber has grown quickly but its business model and path to profitability are questionable. It uses regulatory arbitrage to avoid costs like minimum wage, benefits, and employment taxes.
Uber promotes itself as empowering workers but the reality can be low wages, lack of benefits, and insecurity. Stories of successful “micro-entrepreneurs” mask more common experiences of precarious work.
While the gig economy provides convenience for consumers, it shifts risks like illness, disability, and old age to workers. It also avoids regulations meant to protect workers and taxpayers.
Possible negative societal impacts include growth of the “cybertariat” - a class of digitally mediated workers who lack economic security and employment rights. The gig economy raises questions about fair competition and labor protections in the digital age.

Forbes (15 January 2015), http://www.forbes.com/sites/ellenhuet/

2015/01/15/lyft-buys-carpooling-startup-hitch-to-grow-lyft-line/, archived

at https://perma.cc/EA9A-8WHC

Danielle Furfaro, ‘Uber gobbles up rest of Zimride’, New York Post (23 August

2013), http://nypost.com/2013/08/23/uber-gobbles-up-rest-of-zimride/,

archived at https://perma.cc/BU2D-UEH9

The primary exception in Western legal regimes being the limited case of

merger remedies, where crowns sometimes require demergers of recently

amalgamated entities.

‘Employee Pay-Roll Taxes, Social Security and Medicare 2003–2012’, Tax Policy

Center: The Urban Institute and Brookings Institution (16 March 2012), http://

www.taxpolicycenter.org/statistics/employee-pay-roll-taxes-social-security-and-

medicare-2003-2012

Vidhya Alakeson and Paul Leonard, Limousine Liberals, International Labor

Organization ILO (2014).

The official regulator’s Twitter account notably categorizes itself as existing to

‘Protect and inform consumers’ (@Ofcom).

The sharing economy is, if anything, vastly more complex than the simplistic

dichotomy suggests: see, e.g., Abby Alpert, ‘Uber: an intermediary or digital

platform provider?’ (17 June 2015) Juste Competition, http://justecompetition.

org/2015/06/uber-an-intermediary-or-digital-platform-provider/, archived at

https://perma.cc/84KC-3CHN (on the Uber litigation in the state of California,

where my dichotomous model is ill-suited to the subtleties of both application

and adjudication). The present analysis necessarily involves simplification:

Abby Alpert’s three-level schema, based on the Federal Trade Commission’s

Internet Policy Task Force’s Report paper (‘Beyond neutrality: applying the FCC’s

general conduct rule to the new battle over net neutrality’ (2011) Federal Trade

Commission, https://www.ftc.gov/sites/default/files/documents/public_com-

ments/broadband-industry-practices-070000-12527/070000-12527.pdf, archived

at https://perma.cc/6ABW-8G6E), may better capture these complexities; its

levels include: (1) conduits that merely transmit information but do not provide

access to any services; (2) entities that provide consumers access by connecting

them to providers; (3) entities that, in addition to connecting, also provide their

own goods and services. In her analysis, ‘Uber offers some characteristics of a

digital platform provider like Apple’s App Store [at level (2)], but retains too

much control over transactions to qualify’: at level (3) Uber controls pricing, can

reject drivers, and limits communications between drivers and riders in a manner

absent from ‘true’ platforms.

The present analyses assume capital-heavy industries characterized by high

barriers to entry. For sectors with low start-up costs, any incumbency benefits are

correspondingly smaller. However, because the gig economy is dominated by

Uber-like examples (featuring substantial technology and marketing costs, etc.),

this focus seems justified.

Lawrence Lessig, ‘The law of the horse: what cyberlaw might teach’ (1999) 113

Harvard Law Review 501.

Rachel Botsman, ‘The sharing economy lacks a shared definition’, Fast Co.Exist

(21 November 2013), http://www.fastcoexist.com/3022028/the-sharing-econ-

omy-lacks-a-shared-definition, archived at https://perma.cc/UE3Q-C67Y

Alex Rosenblat and Luke Stark, ‘Algorithmic labor and information asymmetries:

a case study of Uber’s drivers’, (2015) 10 International Journal of Communication

3758, 3759–62.

Emiliano Huet-Vaughn, Book Review: ‘Who owns the future? By Jaron Lanier’,

Population and Development Review (2014) 787.

‘All complex societies have tax-and-transfer systems, and all developed econo-

mies have sizeable service sectors. They are fundamental aspects of modernity.

It is odd and potentially hazardous to claim that both could be under threat

simultaneously’: Martin Wolf, ‘Enslave the robots and free the poor’ Financial

Times (11 February 2014), http://www.ft.com/cms/s/0/dfe218d6-9038-11e3-

a776-00144feab7de.html

Two recent accounts cast serious doubt on the supposedly innovative nature of

the developments. In the first, William Lazonick poses the provocative question,

‘Uber: innovative business model or reversion to exploitation?’, INET Blog (16

December 2014), http://ineteconomics.org/ideas-papers/blog/uber-innova-

tive-business-model-or-reversion-to-exploitation, archived at https://perma.

cc/QZ8M-TBF2. The second, from Mike Bulajewski, is titled ‘Misunderstanding

Uber as a Platform for Innovation’, Mr.Teacup (5 April 2015), http://mrteacup.

org/post/115486814503/misunderstanding-uber-as-a-platform-for, archived

at https://perma.cc/AND4-CVTN. Both make important points that help

contextualize the purported novelty.

154

Notes

Evgeny Morozov, ‘Tech gurus plan a Silicon Valley for socialist entrepreneurs’,

Morning Star (3 October 2016).

Tom Slee, ‘Sharing and caring’, Jacobin (24 January 2014), https://www.jacobi-

nmag.com/2014/01/sharing-and-caring/, archived at https://perma.cc/

E3GR-YLVM

Max Weber, The Theory of Social and Economic Organization (Simon and Schuster

2009), 154.

Rory Carroll, ‘Airbnb listings mostly illegal, New York attorney general finds’,

The Guardian (16 October 2014), http://www.theguardian.com/technol-

ogy/2014/oct/16/airbnb-listings-mostly-illegal-new-york-attorney-general-

finds, archived at https://perma.cc/8J46-GNVW

This is illustrated starkly in the case of Uber, which (unlike other platforms) sets

the exact price that must be charged by users of its technology: ‘Uber confirms

price surging scheme during Sydney hostage siege’, Reuters (17 December

2014), http://www.reuters.com/article/us-uber-sydney-siege-idUSKBN0JV07S-

20141217, archived at https://perma.cc/V3DA-RQRQ; see further Mathew

Feeney, ‘Is Uber’s surge pricing ethical?’, Cato Institute (8 December 2014),

http://www.cato.org/blog/ubers-surge-pricing-ethical, archived at https://

perma.cc/VMM5-42VS

The argument is echoed frequently within the on-demand community. Witness

Handy CEO Oisin Hanrahan in an interview with Conor Dougherty: ‘This is

about creating a level playing field for people to participate in the economy’:

Conor Dougherty, ‘Handy raises $30 million to give pressing start-ups

some company’, New York Times (26 November 2014), http://nyti.ms/15Av-

yCa, archived at https://perma.cc/9RVR-XUZ7

Nick Wilson and Susie Lonie, ‘Digital equality and the future of work’, Sharing

Economy UK (22 June 2015), http://www.sharingeconomyuk.com/digital-

equality-future-of-work/, archived at https://perma.cc/7QY3-MMCC

Nick Grossman, ‘Regulation, the Internet way’, Harvard Business Review (17

September 2013), https://hbr.org/2013/09/regulation-the-internet-way,

archived at https://perma.cc/QAF7-2RNC

Orly Lobel, ‘The law of the platform’ (2016) 101(1) Minnesota Law Review 87,
See further Stephen R. Miller, ‘First principles for regulating the sharing econ-

omy’, Harvard Journal on Legislation (Forthcoming), https://ssrn.com/abstract=

2568016, archived at https://perma.cc/8CDV-GZV4; and Benjamin G. Edel-

man and Damien Geradin, ‘Efficiencies and regulatory shortcuts: how should

we regulate companies like Airbnb and Uber?’ (2016) 19 Stanford Technology Law

Review 293–328.

Lawrence Lessig, Code: And Other Laws Of Cyberspace, Version 2.0 (Basic Books 2009).
Molly Cohen and Arun Sundararajan, ‘Self-regulation and innovation in the

peer-to-peer sharing economy’ (2015) 82 University of Chicago Law Review

Dialogue 116.

Chris Dixon, ‘The sharing economy’, A16Z Blog (26 February 2014), http://

a16z.com/2014/02/26/the-sharing-economy/, archived at https://perma.cc/

V82L-UHAG: ‘Regulators should continue acting to protect public health and

safety, but when possible, they should let peer-to-peer markets find their equilib-

rium.’

Nick Grossman, ‘Regulation, the Internet way’, Harvard Business Review (17

September 2013), https://hbr.org/2013/09/regulation-the-internet-way,

archived at https://perma.cc/QAF7-2RNC

Janelle Orsi, Practicing Law in the Sharing Economy (ABA Publishing 2012).
Sofia Ranchordás, ‘Does sharing mean caring? Regulating innovation in the

sharing economy’ (2015) 16 Minnesota Journal of Law, Science and Technology

Organization for Economic Cooperation and Development (OECD), ‘Taxi services:

competition and regulation’ (2007) Competition Policy Roundtables, http://

www.oecd.org/regreform/sectors/41472612.pdf, archived at https://perma.

cc/VUA4-XJ4D

Susan Crawford: quoted in Evgeny Morozov, To Save Everything, Click Here:

Technology, Solutionism and the Urge to Fix Problems That Don’t Exist (Allen Lane 2013).

Jacob Silverman, ‘Sharing economy’ is just entrepreneurship Uber-ised’, Financial

Times (28 October 2014), http://www.ft.com/cms/s/2/abdea4ca-5d0a-11e4-

9781-00144feabdc0.html

Faizan Syed, ‘The battle is for the customer interface’, TechCrunch (3 March

2015), http://techcrunch.com/2015/03/03/in-the-age-of-disintermediation-

the-battle-is-all-for-the-customer-interface/, archived at https://perma.cc/

NC7W-7VV7

Scott Duke Kominers (quoted in ‘A paper by any other name?’, The Economist

(4 February 2015), http://www.economist.com/whichmba/paper-any-other-

name, archived at https://perma.cc/W7ME-C7Z2) gives the example: ‘“Uber

for laundry” does not sound like a coherent concept … But “Uber for dog walk-

ing” makes sense as a platform for allowing urban dog owners to find local dog

walkers.’

Miriam Cherry, ‘Beyond Misclassification: The Digital Transformation

of Work’ (2016) 37 Comparative Labor Law & Policy Journal 577.

Andrew McAfee and Erik Brynjolfsson, ‘Investing in the IT that makes a com-

petitive difference’, Harvard Business Review (July–August 2008).

Notes 155

Including opt-out technical solutions (as well as opt-in alternatives) for workers

who wish to avoid constant connectivity.

Ursula Huws and Simon Joyce, Size of the UK’s ‘Gig Economy’ revealed for the first

time: 1.1 million people in Britain rely on platform like Deliveroo and Uber to find work

(University of Hertfordshire 2016), http://www.fepseurope.eu/assets/a82bcd12-

fb97-43cd-9b3d-24b733869ad5/crowd-working-surveypdf.pdf, archived at

https://perma.cc/9GX3-8Q9J

As the European Commission has already intimated in the case of Airbnb.
Nick Grossman, Alex Moazed and Elizabeth Christian (Applico), Regulation 2.0:

The Marriage of New Regulatory Frameworks with Innovative Business Models (Applico

2013), 24.

chapter 2b

Valerio De Stefano, ‘The Rise of the “Just-in-Time Workforce”: On-Demand

Work, Crowdwork and Labor Protection in the “Gig-Economy”’ (2016) ILO

Conditions of Work and Employment Series No. 71; Miriam A. Cherry, ‘Beyond

Misclassification: The Digital Transformation of Work’ (2016) 37 Comparative

Labor Law & Policy Journal 577; Hannah Johnston and Chris Land-Kazlauskas,

Organizing On-Demand: Representation, Voice, and Collective Bargaining In The Gig

Economy (Worker’s Lab 2018).

Valerio De Stefano, ‘The Rise of the “Just-in-Time Workforce”: On-Demand

Work, Crowdwork and Labor Protection in the “Gig-Economy”’ (2016) ILO

Conditions of Work and Employment Series No. 71, 13–14.

Valerio De Stefano, ‘The Rise of the “Just-in-Time Workforce”: On-Demand

Work, Crowdwork and Labor Protection in the “Gig-Economy”’ (2016) ILO

Conditions of Work and Employment Series No. 71, 2.

Valerio De Stefano, ‘The Rise of the “Just-in-Time Workforce”: On-Demand

Work, Crowdwork and Labor Protection in the “Gig-Economy”’ (2016) ILO

Conditions of Work and Employment Series No. 71, 16.

Valerio De Stefano, ‘The Rise of the “Just-in-Time Workforce”: On-Demand

Work, Crowdwork and Labor Protection in the “Gig-Economy”’ (2016) ILO

Conditions of Work and Employment Series No. 71, 18.

Janine Berg, ‘Income security in the on-demand economy: findings and policy

lessons from a survey of crowdworkers’ (2016) ILO INWORK Policy Brief No.

1, 3.

Berg, Janine, ‘Income security in the on-demand economy: findings and policy

lessons from a survey of crowdworkers’ (2016) ILO INWORK Policy Brief No.

See also: Berg, Janine, ‘Is the sharing economy increasing inequality within

the EU? Evidence from a new survey of platform workers’ Bruegel (7 March

https://bruegel.org/2019/03/is-the-sharing-economy-increasing-inequal-

ity-within-the-eu-evidence-from-a-new-survey-of-platform-workers/

Valerio De Stefano, ‘The Rise of the “Just-in-Time Workforce”: On-Demand

Work, Crowdwork and Labor Protection in the “Gig-Economy”’ (2016) ILO

Conditions of Work and Employment Series No. 71, 18.

Janine Berg, ‘Income security in the on-demand economy: findings and policy

lessons from a survey of crowdworkers’ (2016) ILO INWORK Policy Brief No.

1, 4.

Janine Berg, ‘Income security in the on-demand economy: findings and policy

lessons from a survey of

Transforming on Demand Labour with a Conversational AI Assistant (2016), 8.

Notes 157

Oisin Keegan, ‘The gig economy: market failure in social regulation?’ (2017)

38(1) Irish Jurist 113, 115:

Assumption of choice fails to account for the structural constraints that make gig

work the best option for some marginal workers. The absence of any guaranteed

hours allows flexibility for those with caring responsibilities or other commitments.

Those denied access to welfare due to migration status can find some income in the

gig market. Students seeking to pay fees and bills, over-employed yet underpaid

workers, those in poverty, the precariat class, the near-homeless; all rely on gig work

for access to limited autonomy and income in the absence of viable alternatives.

Valerio De Stefano, The Rise of the Just-in-Time Workforce: On-Demand Work, Crowd-

work, and Labour Protection in the Gig-Economy (International Labour Office

2016), 12.

See ibid, 9–13 with references. Stefano notes (12):

In September 2015, 44% of U.S. workers participating in the on-demand economy

reported that their financial situation was worsening. As mentioned before, they are

more likely to come from lower-income minority groups and immigrant households.

Some are already unemployed, underemployed or discouraged workers falling

outside the labour market before joining the on-demand economy.

Similarly, Hall and Krueger (13–14, noting that background rates of poverty are

already above baseline):

38.1 percent of UberX drivers, 32.8 percent of UberXL and UberSelect drivers, and

33.5 percent of Lyft drivers are union members. However, this directly reflects their

status as many were already hired taxi drivers or chauffeurs, not to mention among

the subset of workers eligible to unionize. It takes on a different complexion when

we learn that 22% of respondents qualified or applied for Medicaid at some point

since beginning to drive for ridesharing services, and 7% received Medicaid after

joining the sector. And 18% have joined SNAP (food stamps) since starting this

work (that figure bears watching; given that most have driven for ridesharing

services for less than 4 years, it suggests a very high uptake rate relative to poverty

benchmarks for adults.) Rapid growth of a high poverty sector raises structural

concerns; equally implosive impacts on neighbouring taxis, a long-unionized sector

with drivers often in ethnic minority groups, are troubling from an equity lens.

For some cities, this would not reflect any shift: employment has long been pre-

carious, irregular, poorly-paid, unrecorded, and informal. For middle income

groups, though, the experience of piecing a living together—and not having

employments records leading into old age—reflects a long and troubling trend.

Aimee Picchi, ‘The gig economy’s dark side for workers: “Poverty wages” ’,

CBS MoneyWatch (4 November 2016), http://www.cbsnews.com/news/

gig-economys-dark-side-for-workers-poverty-wages, archived at https://perma.

cc/ND9S-494F

Balaram, Fair Share (n. 37), 11.

158

Notes

Technology Policy Institute, Unlocking the Sharing Economy: An Independent Review

(November 2014), 3, http://www.techpolicyinstitute.org/files/ambler_unlocking_

the_sharing_economy_submitted.pdf, archived at https://perma.cc/5Q47-9LWA

See, eg, Hall and Krueger (n. 9), Table 5. For Germany, the figure is even lower:

PwC Strategy& et al., Einfach flexibel? Eine Studie zu Solo-Selbstständigkeit und

Crowdworking in Deutschland (2016), 53. The British survey of 2004 independent

contractors (n. 9) did suggest rather less reliance, though the UK has lower rates

of welfare support. Only 18% made all their working income from their main

contracting activity; 75% got more than 50% of their income from that activity

(and many had retired from salaried work and so had pensions). It does not deal

with the vulnerability of short-notice hour cuts.

Arnosti, Quan, and Sunderam gives a 20 percent vulnerability figure: Niti Bhan Saikia

Arnosti, Sanhita Sahoo Sunderam, and Shobhit Pratap Quan, ‘Re-bundling: A Study of

Independent Workers on Online Platforms in India’ (2019) Berkman Klein Center

Research Publication No. 2019-9, https://dash.harvard.edu/handle/1/38659286,

(page numbers and quotations refer to a pre-print version, independently paged) 27.

Humans as a Service The Promise and Perils of Work in the Gig Economy - Jeremias Prassl