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February 21, 2020
Ola Cabs, the Indian ride-sharing firm, is one of an increasing number of companies around the world whose business model relies on using a digital platform to match the supply and demand for labor. Specifically, Ola’s mobile application allows passengers in need of transportation to connect with a nearby driver. Digital labor platforms like Ola comprise what is commonly referred to as the “gig economy,” where companies - by way of a digital platform (often underpinned by a closely-guarded algorithm) - contract jobseekers to perform short-term “gigs” on a casual and piecemeal basis. The gig economy’s model of algorithmically apportioned and managed employment has made massive inroads into a wide array of economic activities, from ridesharing and delivery, to domestic work and general freelancing.
Ola, a typical gig economy firm, deploys narratives of freedom and flexibility in order to recruit “driver-partners” to drive their cars for the company. In keeping with the foundational mantras of the gig economy, on its website Ola guarantees aspiring drivers “flexible working hours,” “freedom of work,” and the ability to “earn respect.” In addition to allowing people to drive their own cars under Ola’s banner, the company also leases cars to those who don’t own one, for $10-16 per day. Aspiring drivers can “drive a car at zero-risk” after a non-refundable down payment (around $56) and security deposit (between $293 and $432).
In Ola’s narrative, driver-partners are self-empowered go-getters who are freed from the constraints of traditional work, and are bouncing between interesting tasks. Gig work ostensibly offers the attractive prospects of self-management, capitalizing on existing assets, and more time for family or other pursuits. Its allure hinges on offering workers greater control over many aspects of their work and personal lives. The reality, however, is often far from the promise. Overt management by a human boss is replaced by more hidden and pervasive forms of algorithmically-enabled control.
In December 2019, The Economic Times reported that Ola suspended a driver-partner in Mumbai after a passenger complained that he fell asleep at the wheel, and nearly caused them to crash. The driver said he had been behind the wheel for over twenty hours. On the surface, Ola’s action to suspend him is a reasonable measure to ensure passenger and driver safety. However, the episode is illustrative of a range of underlying structural issues characteristic of the ridesharing sector, and the wider gig economy - namely, poor pay, unsafe working conditions, and an absence of due process. The report quotes a representative from a workers’ organization: “If they don’t drive for long periods, like 14-15 hours, they cannot give the daily lease amount to Ola, Uber, etc.”
Gig economy platforms often contend that they are merely technology companies that connect those who want to sell their labor with those who want to buy it. By this logic, across jurisdictions, platforms classify gig workers as “independent contractors,” “self-employed,” or equivalent, rather than employees. This classification belies the relationship of control that exists, whereby platforms dictate terms of work and payment, and deploy highly effective methods of network governance. The result of this contractual sleight of hand is that growing numbers of gig workers are not covered by labor laws and therefore ineligible for protections and benefits, such as sick or holiday pay, and pension contributions. Platforms outsource costs to workers, such as for vehicle rental or maintenance, insurance, and fuel. Workers are responsible for calculating and paying taxes. The supposed flexibility to choose working hours is undermined by a trend of decreasing pay (driven by platforms rapidly expanding their workforce), and a gamified digital interface that rewards those who work longer. Moreover, platforms are under no obligation to guarantee a minimum amount of work, with an oversupply of labor power leading to periods of lower job availability, and longer unpaid wait times between jobs. This same oversupply of labor power means that customers rarely have long to wait for the services they desire. Combined, all of these factors constantly push workers to work longer shifts, as a result taking on greater risks and potentially endangering themselves and others, as in the case of the sleepy Ola driver.
Neither Ola, nor the Indian context, is unique - similar issues of low pay, overwork, and exposure to risk regularly surface across the gig economy globally. These conditions can and are being addressed in a variety of ways, including through regulation targeting the employment status of workers and obligations of platforms. Underpinning this has been bottom-up collective action and worker organization, and third-party efforts to raise public awareness and incentivize fairer practices.
It was in the latter spirit that the Fairwork Foundation, an action-research project based at the University of Oxford, was founded in 2018 as a collaboration between social scientists and labor lawyers working to address unfair practices in the gig economy. Drawing on evidence gathered from over 300 gig workers across countries in Africa, Asia, and Europe, we have developed five principles of fair platform work: fair pay, fair conditions, fair contracts, fair management, and fair representation.
We carry out research (including interviews with workers and platform management) on a yearly cycle to evaluate gig economy platforms against these principles. We then award them scores out of 10, and display their scores both in individual scorecards and comparatively in a league table of “fairness.” To do this, we set thresholds for each of the five principles based on local circumstances (for example, “fair pay” is interpreted differently in different places). Platforms that score well are allowed the use of our kite mark to signal that they are a fairer employer.
Through this work, we aim to provide a framework for workers, firms, consumers, and regulators to imagine a platform-based economy that delivers on its promise of expanded employment opportunities, sustainable livelihoods, and worker empowerment.
Following the passenger’s complaint, Ola took immediate disciplinary and corrective action against its fatigued driver, including requiring that he attend counselling. But perhaps not all the blame should be laid at the driver’s feet. It is not possible to counsel somebody to be less tired, or less dependent on a precarious source of income. If Ola, and platforms like them, were instead to proactively incorporate the Fairwork principles into the ways that workers are managed, we might see safer and fairer outcomes for workers in the gig economy. Drivers paid a fair net wage (pay) and working for platforms that do not have built-in bonus structures that reward overwork (conditions) would likely choose to log off instead of accepting another job at the tail end of a hard day’s work. In cases where payment obligations are clearly communicated, workers would likely weigh their options carefully before signing up (contracts). Workers at platforms with responsive due process procedures (management) would be able to appeal disciplinary action and have their case heard by a human. And workers who are able to have an independent collective body recognized by platforms (representation) would likely be able to demand a fairer deal on their own terms. Instead, Ola and most other platforms have succeeded in outsourcing not only costs and risks, but responsibility for unsafe working conditions to workers.
Fundamentally we want to reinforce through our principles that insecure, unsafe work is not a natural, necessary, or acceptable condition of a modern platform-based economy. Hard-fought and -won labor rights are being undermined by smart workarounds in ever more sectors. While the sense that there is no alternative is deeply entrenched and platforms may appear untouchable, they are highly sensitive to public perception. Platform users (both workers and consumers) have much more power than we may imagine in envisioning and realizing a fairer future of work.
Srujana Katta, Oxford Internet Institute, University of Oxford, UK <email@example.com>
Kelle Howson, Oxford Internet Institute, University of Oxford, UK <firstname.lastname@example.org>
Mark Graham, Oxford Internet Institute, University of Oxford, UK <email@example.com>
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