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“The support has to come from home”: Evidence-based assessment of platform work in India

[By Sreelakshmi Ramachandran]

When considering the strategies for India’s economic rebound, it is imprudent to overlook the potential of the wider digital economy, as this all-pervasive technology has altered urban landscapes and living in the last decade in the country. An explosive combination of cheap handsets, lowest data costs in the world and rapid advances in vernacular language processing, has led us to this moment. Therefore, a platform economy of service providers and users can prove to be a robust vehicle for post-pandemic growth. Platform sectors span mobility, logistics, home improvement, beauty & wellness and many others, and the workers deriving their livelihoods from these jobs stand to gain from the safety and hygiene measures put in place to transition to an economy opening up.

Mahalakshmi is a Bangalore citizen in her mid-thirties. Her greatest joys are her ability to support herself in life and driving. She is a partner with a ride-hailing aggregator service in India, and regularly takes up trips in her self-owned sedan during the night – at least, till the pandemic hit and lockdowns and other restrictions were put in place. Through her children, whom she has enrolled in ICSE schools (Indian Certificate of Secondary Education; a school syllabus regarded as more competitive, elite and expensive by India’s mean income standards) to attain world-class education, she vicariously lives her unfulfilled academic dreams that ended in high school. Mahalakshmi represents many platform-entrepreneurs, especially women workers, whose lives have been transformed by the digital revolution and advent of the platform economy in India.

Women like Mahalakshmi still are a rarity in the mobility platform economy of India, despite best efforts directed at increasing representation of women in unconventional jobs like driving or delivery work. In the Indian society, conservative dictums situate women’s “proper” place in the domestic sphere, let alone in service jobs like driving which have traditionally been men’s forte. But it is important for women to be ridesharing service providers, from not just the perspective of their economic mobility; it also makes streets safer, mobility more accessible to women, and brings gender parity to public spaces that are otherwise dominated by  men.

Mahalakshmi, who especially enjoys the longer trips outside her regular city beat, is one of an even rarer group, but signals a shift of gears. There is an active effort by digital mobility platforms tailored towards skilling women in such jobs, mediating their financial access to improve their chances at micro-entrepreneurship through the platform economy, and in acknowledging that structural changes – such as hygienic public restrooms and gender-sensitised traffic police, toll booth operators, male drivers, etc. – are needed. By increasing women’s public participation in this sector, social change is expected to follow.

Apart from the mobility economy, women platform entrepreneurs are found in the services of home-based spa and salon service providers. Women in India are regarded as primary caregivers of their families, and the conventional job market also prioritises women providers for services such as healthcare, primary education, childcare, geriatric care, or beauty work. Replicating such historic trends in care work, but with greater pay, perks and flexibility than available in any other type of jobs, women have found lucrative opportunities in the at-home services platform, and stand to gain the most when the economy reopens post-COVID: Platforms are prioritising partner vaccinations, compliance with COVID-Appropriate Behaviour (CAB) and ensuring safety and hygiene for all actors.

Image credit: Jorge Royan / Wikimedia

The Ola Mobility Institute (OMI) has undertaken extensive research on the Indian digital platform economy and documented trends across urban services sectors that are now online; primarily, the digital economy of services is found in mobility, e-commerce & logistics, on-demand food delivery and at-home services, including home maintenance and salon services. Platform companies focus on matching skilled professionals with urban consumers in need of their services, and essentially act as digital intermediaries or online marketplaces. OMI studies the Future of Work from the prism of platform partners as micro-entrepreneurs, while fully accounting for nuances in a market like India where the conventional economy has a high number of self-employed workers and an even higher proportion of wage workers. These trends are replicated within platform relationships, and makes for a comparative study between work in and outside of the platform economy.

In the report, “Unlocking Jobs in the Platform Economy: Propelling India’s post-Covid Recovery”, OMI has collected primary data and presents the trends in the mobility platform economy in mid-2019; it shows how pre-pandemic, workers associated with platforms consistently supported more dependents than those outside of it, earned a higher income based on hours inputted, accessed finance and bought assets for the sharing economy, all different from the trends spotted in the traditional economy. Since the beginning of the pandemic and the resultant economic shutdown, platform workers have accessed more immediate relief, welfare nets and found work in emergency response operations coordinated by platform companies, thus securing incomes in albeit small ways.

A platform-led recovery from the economic effects of COVID-19 cases surging in 2021 can be realised: combined with meaningful reform, platform work can be made more secure, remunerative and an effective form of micro-entrepreneurship. Self-employment has long been the mainstay of the Indian labour market: the challenge is to prevent it turning exploitative. The study from OMI reveals that self-employment and asset ownership have important roles to play in buoying incomes in and outside the platform economy, and this can be achieved through reforms in the financial sector and lending practices. Driver-partners such as Mahalakshmi also benefit from being asset owners, i.e., owners of the means of their work, such as a vehicle, in the case of the mobility economy, and therefore are able to attain socio-economic mobility rapidly, through the platform economy.

Much of the debate around regulating work hinges on ‘on-the-job-benefits’. Therefore, to achieve universalised social security, well-funded state-led social safety schemes such as family healthcare and small savings for dignified retirement, and beneficiary qualification independent of worker status has to be normalised. This would require the recognition that equitable schemes can be designed only based on:

  • recognising the variety of platform work
  • augmenting social security financing through innovative means (like multi-source funding including civil society contributions)
  • institutionalising scientific methods to design these schemes
  • supporting workers and ensuring benefits reach them,
  • and welfare-state governments like India can lead the charge in effective labour reform.

This is the spirit of the recommendations in the “RAISE framework” captured in OMI’s report on ways to achieve lucrative and secure platform jobs, without burdening the job creator alone.

Women like Mahalakshmi deserve the chance to explore productive micro entrepreneurship. Future of Work is about equitable access and remunerative jobs which accommodate flexible needs without penalising workers with respect to their social security. The digital economy is the perfect testing grounds for such a solution, to benefit skilled workers across the spectrum, and it is time to acknowledge that truly socialised security is the only way to equalise our job market.


Sreelakshmi Ramachandran leads the Future of Work track at the Ola Mobility Institute, where she works on the experience of mobility workers in and outside the platform economy, social security systems and opportunities for mobile-based skilling. She also examines job creation in the light of the sustainability push, as well as financing public infrastructures and asset creation. She holds a Master’s degree in Development Studies from IIT-Madras and is interested in all things urban.

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Centered but invisible – On the contradictions of service design at Urban Company

[By Sai Amulya Komarraju]

Ting! A beauty worker checks her mobile. A ‘lead’ appears on her mobile screen from the platform service aggregator she has registered with. She accepts it, calls the customer through the platform that has helped her become a microentrepreneur, confirms the request and location of the customer and rides off to the location. She rings the bell. Once the customer greets her, the worker does what has become a routine since the onset of COVID-19: She sanitises her hands, dons a fresh pair of gloves, face mask, and face shield before entering the house. She sets her products neatly and gets to work. Once finished, she sprays everything she has touched with sanitiser, from the doorbell she rang to the tap she used in the customer’s washroom to fill water for a pedicure session. She packs all her belongings and collects soiled products (used waxed strips and such) to dispose of them on her way to another gig.

Meanwhile, the now relaxed customer is asked by the app to rank the beauty worker on her hygiene: Did she wear a mask? What about gloves? Did she leave any used products behind? In short, how successful was the worker in her attempts to disappear without leaving any proof of her physical presence?

Behind all this is a Standard Operating Procedure that regulates the worker’s behaviour, which is then monitored by the app with the help of the data provided by the customer. Based on this feedback, the worker receives a hygiene rating. Moreover, Machine Learning (ML) is utilized to recognize if the worker was wearing masks and gloves through pictures that the worker has to provide before the gig.

The above describes a day in the life of service partners (who provide services and are variously refereed to as service partners, providers or professionals) and customers (who avail services through the platform) associated with the app-based, on-demand platform aggregators. On-demand platforms (like Urban Company and Housejoy) match service partners or ‘pros’ with customers in need of home-based services such as cleaning or salon treatments, through leads. To do this, they charge a commission. Any hitch or issue within the service partner app or the customer app leads to the breakdown of the entire ecosystem. This is where the Software Development Engineers step in. They ensure that the entire experience from booking a service to feedback remains seamless. These engineers must at all times remain alert to whatever complaints arise, either from service partners or customers, even while working to eliminate manual intervention in other aspects. I spoke with a couple of Software Development Engineers (on the condition of anonymity) working for Urban Company to gather insights about their role within the organization, the importance of service partners and customers in process of designing technologies.

Image credit: ivabalk / Pixabay

Role of Software Development Engineers (SDEs)

On-demand platforms are veered towards maximising customers’ experience (which has long been established as a brand on its own). This is also reflected in the kind of words one uses in industrial design and innovation—such as experience economy or service economy. In order to keep up with such a fundamental organizational change, companies turn towards the concept of ‘service design’.

Speaking about what companies expect Software Development Engineers to do, SDE 2 explains:

“we translate all the business fundamentals, business logics into tech solutions. Essentially, automate the entire process. So, this is what the expectation is from you when you are working as a software developer.”

But this is not the only requirement. The idea, another SDE from Urban Company says, is to make sure that the service partners and customers (who book services on the app) are comfortable with the environment provided for them within their separate apps:

“[…] for instance, we need to create a solution to the problem of auto-suggestion of products. If a service partner working in the beauty segment is ordering products, we have to work with the team that predicts market trends and make sure that their suggestions appear at the top of the page. Then we must take into account if pros are comfortable with that placing. Should it appear right at the very top of the page, or when they go to the particular product’s page, is that where the prompt should go?” (SDE 3)

The SDEs I spoke with agree that creating smooth environments for service partners or pros is more complicated than the flows involved with customers. Therefore, more engineers work on the service partner app. SDE 4 notes that the design of the interface is such that one must take into account what the service partners are making of any new feature launched (whether in terms of understanding what it does or ease of use). SDEs must also co-ordinate with other teams that are most likely to be affected by changes they make. They must also adhere to the company’s business goals in order to create something that works, fixes, and reduces the burden of manual intervention. Although, the SDE says, “you cannot always predict how something might turn out to be, but that is what makes it exciting as well”. This mostly invisible work of making sure that features do all these things–enhance customer experience, reduce manual intervention, help service partners make decisions, but above all improve the business logic of profit-making for the company is done by the SDEs.

Asked if engineers undergo any training since they design technologies for those who are marginalized due to multiple factors (gender, class, type of work they are engaged in), I received no definite answer.

The Urban Company ecosystem. Image credit: Sai Amulya Komarraju

Service design: From productivization to servitization

The concept rather the philosophy of service design is broadly understood as the activity of planning and organizing the resources of a business, i.e., people (in the case of the platform ecosystem: service partners, employees, customers), props (AI and ML based algorithms), and various other processes (workflows, Standard Operating Procedures and other dimensions involved in order to ensure smooth services) to directly improve the employees’ experience (in this case it is would include both SDEs and service partners). This ensures that every component is laid out and thought through in detail to ensure a smooth ecosystem. Ecosystems are best understood as collaborative environments where various resources of the company work together to co-create values.

The philosophy of service design shines through in what my interviewees explain: UC assumes that SDEs take into account the views of service partners during all stages of development of a feature. SDE 1 and 2 report that UC focuses on a ‘win-for-all’ approach. In fact, a recent study by Fairwork India has found that UC tops the list of companies that provide “fairwork” based on 5 principles: 1) Fair pay 2) Fair conditions 3) Fair contracts 4) Fair management 5) Fair representation. Confirming this, SDE 3 states that engineers regularly call partners (personal information is encrypted and not shared with anyone) to check if a particular feature seems okay to them. “It is common sense, you know, I mean you are making something for someone, whom to call, if not the recipient?” SDE 2 says that it is easier to guess what a customer wants “because you are one yourself… we have all availed services… but understanding the POV of the pros is difficult… we all call and talk with pros as and when required”. In fact, SDE 2 also admits that when she joined the platform, she was uncomfortable with “round the clock tracking” of service partners. However, when the service providers themselves expressed that this was an acceptable trade-off, she made her peace with it.

“I think the idea is you want them [service partners] to succeed as well. They do really work hard. So, again, no one tells you to do it, but you think about it, how do we give them the best chance to succeed and then create a feature” says SDE 4. For instance, SDEs collaborated closely with the business team to anticipate “sprees” (such as the sudden demand for roll-on waxing), so that service partners could stock up on products needed for such services. However, this view must be balanced by the fact that the business logic of profit-making is supreme, in the face of which even long-term, scalable tech solutions must take a backseat accruing what SDE 2 refers to as a “tech debt”.

This logic inevitably organizes the relationships within the ecosystem in a hierarchical fashion. Customers and their experience and satisfaction are placed at the apex since they bring business, and software engineers enable “extra-legal” mechanisms (rating, tracking etc.) to monitor the service partners through the app in order to ensure quality of services. Even though service partners are considered as a crucial resource (SDE 3), the oversupply of workers compared to the demand, and control mechanisms in the form of rating and reviews serve to maintain power asymmetries between the platform, customer, and the service partner.

The inadequacy of service design

In some sense, when SDEs speak of developing Standard Operating Procedures in order to provide a holistic experience for the customer, they move beyond thinking about mere productivity of service partners. But this does not take away from the fact that workers are still expected to display skill and dexterity at work. They are expected to take a minimum number of leads (which can be read as productivity of a particular partner) and their ratings and continued association with the platform depends on customer satisfaction.

The aim of service design is to move beyond thinking in narrow terms of providing “goods” to the broader concept of offering services. In short, not productivization but servitiziation is the goal. However, this necessarily requires productizing the worker’s skills. We need to problematize this move from good-dominant to service-dominant logic. The burden of delivering the actual experience ultimately falls squarely on the shoulders of service partners. This is especially so in the case of home-based services such as beauty and wellness, where a worker’s physical labor involved in the performance of beauty-work contributes the most in creating a feeling of wellbeing for customers. This burden is reinforced by the fact that their work is constantly supervised by both the app and the customers. The multitude of problems and the high degree of precarity gig workers in the home-based sector face is well documented. Therefore, despite of the human-centric focus of service design, the burden of delivering customer satisfaction with the goal to generate profit is felt more keenly by the service partner first and foremost.

My interviews reveal that SDEs do think about the service partners and that there is a modicum of care they feel towards them. Still, there is much left to be desired in terms of ensuring that all resources are equally empowered within the ecosystem. For human-centric design to live up to its name, it is imperative that businesses adopt an ethics of care within design that could help balance logics of business, technology and the needs of workers.

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Is feminist design a solution to platform workers’ problems?

[By Pallavi Bansal]

Imagine a scenario in which you do not get shortlisted for a job interview – not because you are underqualified – but because the algorithms were trained on data sets that excluded or underrepresented your gender for that particular position. Similarly, you found out that you are consistently paid less than your colleagues in a sales job – not because of your inability to fetch clients or customers for the company – but because the rewarding algorithms favoured clients belonging to a certain religion, race or ethnicity. Further, you are asked to leave the company immediately without any notice or opportunity to interact with your manager – not because you committed a mistake – but because the clients rated you low based on prejudice.

While these biases, favouritism and discrimination could soon become a reality in mainstream workplaces due the exponential growth of decision-making algorithms, it is already causing disruption in the online gig economy. Recently, researchers at George Washington University found social bias in the algorithms related to dynamic pricing used by ride-hailing platforms Uber, Lyft and Via in Chicago, US. The study found “fares increased for neighbourhoods with a lower percentage of people above 40, a lower percentage of below median house price homes, a lower percentage of individuals with a high-school diploma or less, or a higher percentage of non-white individuals.” The authors of this paper Akshat Pandey and Aylin Caliskan told the American technology website, VentureBeat, “when machine learning is applied to social data, the algorithms learn the statistical regularities of the historical injustices and social biases embedded in these data sets.”

These irregularities are also spotted in relation to gender. A study conducted by Stanford researchers documented a 7% pay gap in favour of men, using a database of a million drivers on Uber in the United States. However, this study highlighted an even bigger problem that the researchers attributed to the following factors – differences in experience on the platform, constraints over where to work (drive), and preference for driving speed. A Cambridge University researcher Jennifer Cobbe told Forbes, “rather than showing that the pay gap is a natural consequence of our gendered differences, they have actually shown that systems designed to insistently ignore differences tend to become normed to the preferences of those who create them.” She said the researchers shifted the blame to women drivers for not driving fast enough and ignored why the performance is evaluated on the basis of speed and not other parameters such as safety. Further, in context to women workers in the Indian gig economy, it is imperative to understand whether these biases are socially inherent. For instance, if certain platform companies segregate occupations based on gender, then the resulting pool will inherently lack gender variation. This also compels us to ponder whether the concentration of female labour in beauty and wellness services, cleaning or formalised care work is a result of an inherent social bias or technical bias.

To make sense of all of this and understand how we can improve the design of these digital labour platforms, I spoke to Uday Keith, a Senior AI Developer with Wipro Digital in Bengaluru. His responses drew my attention towards Informatics scholar Bardzell’s feminist human-computer interaction design paradigm, which I use to contextualize them.

Illustration by Pallavi Bansal

PB: How can we overcome biases in algorithms?

UK: First of all, algorithms are not biased, it is the datasets which are biased. The imbalances in the datasets can be corrected via a method known as SMOTE (Synthetic Minority Over-sampling Technique) where the researchers recommend over-sampling the minority and under-sampling the majority class. In order to achieve this, we need to bring diversity to our training datasets and identify all the missing demographic categories. If any category is underrepresented, then the models developed with this data will fail to scale properly. At the same time, it is essential for the AI developers to continuously monitor and flag these issues as the population demographics are dynamic in nature.

This points us toward the two core qualities proposed by Bardzell – Pluralism and Ecology.  According to her, it is important to investigate and nurture the marginal while resisting a universal or totalizing viewpoint. She stresses to consider the cultural, social, regional, and national differences in order to develop technology. The quality of ecology further urges designers to consider the broadest contexts of design artifacts while having an awareness of the widest range of stakeholders. This means AI developers cannot afford to leave out any stakeholder in the design process and should also consider if their algorithms would reproduce any social bias. 

PB: Can there be a substitute for the gamification model?

UK: To simplify the process and ensure equity in the gig economy, platform companies can advise AI developers to introduce a “rule”. This would mean fixing the number of minimum rides or tasks a platform worker gets in a day, which can also help in ensuring a minimum wage to them and provide a certain level of income security. The introduction of a fixed rule can even eliminate social biases as this would not result in a particular gender or social group getting less work. Further, the reward system can undergo a major overhaul. For instance, rather than incentivizing them to drive more and indulge in compulsive game-playing, platform companies can build algorithms that provide financial rewards when the drivers follow traffic rules and regulations, drive within permissible speed limits, and ensure a safe riding experience. In fact, we can even provide options to the customers where they could be given discount coupons if they allow drivers to take short breaks.

Elaborating on participation, Bardzell suggests ongoing dialogue between designers and users to explore understanding of work practices that could inform design. This also means if the platform companies and AI developers are oblivious to the needs and concerns of labour, they may end up designing technology that could unintentionally sabotage users. Secondly, an advocacy position should be taken up carefully. In the earlier example, “driving fast” was considered as a performance evaluator and not “safety”, which usually happens because the designers run the risk of imposing their own “male-oriented” values on users.

PB: How work allocation can be more transparent?

UK: Well, deep learning algorithms used by various companies have a “black box” property attached to them to a certain extent. These algorithms are dynamic in nature as they keep learning from new data during use. One can only make sense of this by continuously recording the weightage assigned to the pre-decided variables.

The quality of self-disclosure recommended by Bardzell calls for users’ awareness of how they are being computed by the system. The design should make visible the ways in which it affects people as subjects. For instance, platform companies can display the variables and the corresponding algorithmic weightage per task assigned on the smartphone screen of the workers. So, if a platform driver has not been allocated a certain ride due to his past behaviour, then the technology should be transparent to reveal that information to him. Uncovering the weightage given to various decision-making algorithms will enable the platform worker to reform their behaviour and gives them a chance to communicate back to the companies in case of discrepancies or issues.

PB: How can we improve the rating systems?

UK: The platform companies have started using qualitative labels that could help users to rate the workers better. However, we do need to see whether sufficient options are listed and suggest changes accordingly. Moreover, if we want to completely avoid the numerical rating system, we can ask the users to always describe their feedback by writing a sentence or two. This can be analysed using Natural Language Processing (NLP), a subfield of Artificial Intelligence that helps in understanding human language and derive meaning.

Bardzell writes about the quality of embodiment in respect to meaningful interactions with the technology and acknowledging the whole humanness of individuals to create products that do not discriminate based on gender, religion, race, age, physical ability, or other human features. This concept should also be applied in relation to how users rate workers and whether they discriminate on the basis of appearances or other factors. Hence, there is a strong need to include the qualitative rating systems along with the quantitative ones.

Additionally, Uday Keith recommends defining “ethics” and frequently conducting ethics-based training sessions since a diverse set of people form the team of data scientists, which comprises of roughly 10% of women in an urban Indian city Bengaluru. He concluded by remarking that the issues in the platform economy are more of a system design fault than that of an algorithmic design – the companies consciously want to operate in a certain way and hence do not adopt the above recommendations.

These pointers make the case for the adoption of a feminist design framework that could bring about inclusive labour reforms in the platform economy. As Bardzell says, “feminism has far more to offer than pointing out instances of sexism,” because it is committed to issues such as agency, fulfilment, identity, equity, empowerment, and social justice.

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“Side hustle” is not a swear word: How to make gigs work for young Africans

[By Sharmi Surianarain and Julia Taylor]

Across the African continent, the concept of a “side hustle” is not new. Slow job growth, accompanied by a high number of labour market entrants, has meant that young people have for a long time been engaging in informal ‘side’ work to make ends meet. Young people in African countries experience unemployment rates double that of adults (UN, 2017). Around 63 % of the labour force in Africa is involved in some type of self-employment (McKinsey and Company, 2012), and even in South Africa, famous for its inexplicably small informal sector, 30 % of millennials have a side hustle (Geopoll, 2017).

However, the connotation has almost always been pejorative—even the terms used for this kind of work are belittling. Side hustle—something that you do on the side, with a hidden meaning that you aren’t serious. Informal. This is not formal enough, and formal is what is desirable. Young people and societies alike have relatively little respect for these ‘jobs’; informal or gig workers are under-valued and they remain perched on the margin of our imaginations and our institutions. Governments have long been focused on how to formalize informal business to increase the tax base, when in fact formalization is not always the right step (often because it doesn’t work), and social protection and support for such workers would be more valuable (Rogan & Skinner, 2019).

While there is no doubt that these jobs have been plagued by precariousness, the myth and promise of the ‘formal sector job’ must be challenged. Formal sector jobs have long been held in high prestige—built on the narrative that a college degree and a steady desk job signal success and prosperity. Side hustles are seen just as stepping stones to a more stable and prosperous future.

But, as country after country across Africa, and indeed the world, fail to deliver on this promise, the false narrative of an aspirational linear pathway—from school to college to work—has to be interrogated. Recent data from an intervention by Harambee Youth Employment Accelerator in South Africa finds that young people are divided 50/50 between wanting a job and wanting to start a business. We need more realistic and viable pathways to both options.

Without romanticizing the precariousness of side hustles, we must accept that they are here to stay. Informal work and businesses have been around for a long time, especially in low-income countries, and the precarity of work is only increasing. African institutions—our schools, financial institutions and governments—have to reconfigure themselves to adapt to the world of the side hustles, making these opportunities work for young people, rather than ignoring them and hoping they go away or using regulation to fight against their existence.

Firstly, education and training institutions need to shift to keep up with young people’s lived reality. Young people who do not have a formal job are rarely idle,often keeping busy through volunteering, hustling, or doing piece work alongside many other responsibilities including secondary and higher education. But rarely does a side hustle transform into a more meaningful opportunity. Young people often rely on sheer luck to break out of the cycle of low-level equilibrium gigs.

Image credit: Minette Lontsie / Wikimedia Commons

Xoliswa “Lizzy” Skosana started We Like Cake while she was studying for her Master’s degree and also while concluding another business venture. Her passion for baking drew in her sister as well, who had completed matric (South Africa’s high school examination) and did not know where to go next. The pair started the business from their mother’s kitchen. Slowly, and with the help of the “university of YouTube”, they started growing and moved into a garage, kitted-out with professional equipment. The business grew alongside school and other work, but they continued to need significant support, and were lucky to receive this from family. From her mother’s kitchen to her garage, Lizzy now has a storefront in Booysens, in Johannesburg, and in the three years of running her business, only started as ‘full time’ this past year.

Our institutions—in this case schools and universities—need to accommodate Lizzy’s circumstances, potential, and ideas, instead of waiting for her to work around them to get to her next step, and figure it out. Schools and colleges need to not only offer training in entrepreneurship and importantly, financial literacy, but also actively encourage side hustles as part of their curriculum, providing flexibility for young people to start and continue such businesses. Schools and colleges could partner with an array of entrepreneur support organisations, financial institutions, and investors to actively encourage young people on their side hustles—instead of exclusively focusing on a linear path through to graduation and employment. Young people could be studying and earning cash from a side hustle and this should be encouraged and accommodated by schools and universities.

Secondly, financial services institutions should keep up with the times. There are many examples of young women and men who struggle to access financial services products that suit their circumstances—whether loans and startup capital, or products to improve their business productivity such as vending platforms and mobile banking. These products, importantly, need to be accompanied by the basic financial literacy training that is needed for young people to sustain and grow their gigs.

Take the case of Masingita Maluleke, a partner of Harambee from Soweto, Johannesburg. Armed with a bucket and soap, she started her side hustle while still in college, working to make ends meet. When Masingita’s high school teacher said to her “you won’t pass matric”, because she was unable to read and write on account of her dyslexia, she fell into a deep depression, even attempting suicide. She partnered up with a friend to start a cleaning and laundry business and slowly got it off the ground by using her networks at church and handing out flyers at the local mall. They started attracting more clients and when someone suggested they apply for a tender they had no idea what to do as they did not have a bank account, and they did not know how to register the business. Getting all the documents in order to register took a lot of time and money, as they had to pay someone to help them, even though the process should not cost anything. Managing the finances and administration became a huge burden and they were frustrated and ready to give up. The time lost on the administration meant lost business. Eventually, with some luck in meeting mentors and investors, the side hustle took off, and now Masingita has two licensed businesses under her belt and is also employing others. Had Masingita not found someone willing to support her to get her business investment-ready, she would have lost a lot more time. For many young people, such delays could push them irretrievably into poverty.

Innovations like A2Pay and Yoco in South Africa (fintech companies that provide simple digital technology to support emerging traders to drive growth, efficiency, financial oversight and more) fill a critical need in South Africa, where mobile banking is still in its infancy. By meeting informal and gig workers where they are instead of waiting for infrastructure to improve and coupling these innovations with community-based interventions that drive financial education, we can improve productivity. Community based organisations can also act as “ombudsmen” of these products—flagging malfeasance and exploitation and encouraging inclusion and fair practices.

Lastly, public institutions and labour market platforms need to reconfigure to this new normal. Everything about labour market institutions in Africa and much of the world is informed by labour norms of nearly a century ago—our laws, policies, regulations, and ideas around what constitutes ‘work.’

Even though gig work can be precarious, it offers young people the flexibility to engage in a portfolio career. A formal job may not be the best option for all, and in fact, informal work may even be preferred. Blattman and Dercon’s study on textile workers in Ethiopia found that many of those who got a job—in a beverage bottler, garment factory, shoe factory and industrial greenhouse operations—soon changed their minds and quit those jobs, instead opting for gig jobs that their counterparts had—working on the family farm, construction, or even hawking. While these findings may be hardly generalizable, it is clear that our outdated notions of what constitutes an ideal job for young people may be failing both the market and young people themselves.

However, flexibility does not have to mean precariousness. Instead of presuming access to formal sector jobs, which get the bulk of protections in the form of unemployment insurance, governments should plan to design social protections around informal work as well as zig-zagging or unconventional pathways. These could range from conditional grants for young adults looking for work, to livelihood grants and business support to encourage young people to start their own work and side hustles. Such efforts could particularly shield informal and gig workers from crises like COVID-19.

Labour regulations need to be reformulated to suit this new reality, as Uber’s CEO outlines. We need to move away from the false binary of choosing between full time, formal, protected work, versus non-formal, unprotected and precarious work. Labour market platforms could build pooled benefits funds subsidized by the government and serving gig workers across multiple platforms. Gig work and linkages platforms should themselves be subject to ratings—to benefit from tax and other incentives.

The need to reimagine systems to support gig and informal work has never been more urgent.
In South Africa alone, 3 million people have thus far lost jobs due to COVID-19, and of those, two-thirds are women (Spaull et. al., 2020). The informal sector has been particularly impacted— and again, women, particularly those in informal self-employment, recorded large cuts in working hours and earnings. While some jobs may be recovered as the government finally eases lockdown measures and the economy hobbles back open, many jobs may be permanently lost. There is no doubt that gig and informal work are on the rise for many youths without other options in the months and years to come.

We need to actively invest in developing scenarios for institutional support of informal work and side hustles. Our institutions must be fundamentally reimagined—education, finance, governments, and linkages platforms—to unlock the potential of these gigs and to allow young people to reach their fullest potential.

Side hustles, given their increasing presence in lives (and economies) across the world, can no longer be relegated to the margins of institutional and regulatory systems. Indeed, they will form the main narrative of the book on the future of work.


Julia Taylor is part of the Impact and Storytelling team at Harambee Youth Employment Accelerator in South Africa.  Harambee Youth Employment Accelerator develops African solutions for the global challenge of youth unemployment. Julia is committed to addressing inequality and creating a more just and sustainable world. Julia’s work at Harambee has involved implementing new opportunities for youth employment and ensuring impact and strategic alignment for new initiatives. She holds a B.Com from the University of Cape Town, a PGD in Sustainable Development from Stellenbosch University’s Sustainability Institute, and a Masters in Environment and Development from Edinburgh University.

Sharmi Surianarain serves as the Chief Impact Officer, Harambee Youth Employment Accelerator in South Africa.  Harambee Youth Employment Accelerator develops African solutions for the global challenge of youth unemployment. Sharmi is an activist for opportunity creation for young people, particularly women. She is an Aspen African Leadership Initiative Fellow, Class of 2020 and sits on the Boards of Emerging Public Leaders, Ongoza, Metis, Instill Education and is on the Advisory Council for the NextGen Ecosystem Builders Africa 2020. Sharmi holds a B.A. from Harvard University, a master’s degree from the Harvard Graduate School of Education and a master’s degree from Northwestern University’s Kellogg School of Management.

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Platform drivers: From algorithmizing humans to humanizing algorithms

[By Pallavi Bansal]

I remember getting stranded in the middle of the road a few years ago when an Ola cab driver remarked that my trip had stopped abruptly and he could not take me to my destination. Frantic, I still requested him to drop me home, but he refused saying he cannot complete the ride since the app stopped working. On another unfortunate day, I was unable to find a cab back home as the drivers kept refusing to take up what they saw as a long ride. When I eventually found a cab, the driver continuously complained about how multiple short rides benefit him more. I tried to tip him after he finished the ride, but instead he requested me to book the same cab again, for a few kilometres, as that would reap more rewards. While I wanted to oblige, I couldn’t find the same driver, even though he had parked his car right outside my house. In yet another incident, I spent the entire night at the airport as I was terrified to book a cab at that late hour. I regretted not checking the flight timings before confirming the booking, having overlooked the fact that women need to be cautious about these things. 

Image credit: Pixabay / Pexels

Although my first response was to blame the cab drivers for what I saw as an unprofessional attitude, it slowly dawned on me that they have their own constraints. In the first scenario, the app had actually stopped working, so he couldn’t complete the ride due to the fear of getting penalized, which also resulted in a bad rating by me. In the second situation, I wondered why the algorithms reward shorter rides rather than longer ones. Moreover, how do they assign drivers if proximity isn’t the only factor and why was my driver not aware of that? In the third instance, why couldn’t I be assigned a woman driver to make me feel safer when traveling late at night?

I spoke to a few senior managers and executives working at popular ride-sharing apps in India to find the answers.

Constant tracking

A senior manager of a well-known ride-sharing platform explained their tracking practices on condition of anonymity:

“The location of driver-partners is tracked every two-three seconds and if they deviate from their assigned destination, our system detects it immediately. Besides ensuring safety, this is done so that the drivers do not spoof their locations. It has been noticed that some drivers use counterfeit location technology to give fake information about their location – they could be sitting at their homes and their location would be miles away. If the system identifies anomalies in their geo-ping, we block the payment of the drivers.”

While this appears to be a legitimate strategy to address fraud, there is no clarity on how a driver can generate evidence when there is an actual GPS malfunction. Another interviewee, a person in a top management position of a ride-sharing company, said, “it is difficult to establish trust between platform companies and driver-partners, especially when we hear about drivers coming up with new strategies to outwit the system every second day.” For instance, some of the drivers had a technical hacker on board to ensure that booking could be made via a computer rather than a smartphone or artificially surging the price by collaborating with other drivers and turning their apps off and on again simultaneously.

Though the ‘frauds’ committed by the drivers are out in the public domain, it is seldom discussed how constant surveillance reduces productivity and amplifies frustration resulting in ‘clever ways’ to fight it. The drivers are continuously tracked by ride-sharing apps and if they fail to follow any of the instructions provided by these apps, they either get penalized or banned from the platform. This technology-mediated attention can intensify drivers’ negativity and can have adverse effects on their mental health and psychological well-being.

Algorithmic-management

Algorithms control several aspects of the job for the drivers – from allocating rides to tracking workers’ behaviour and evaluating their performance. This lack of personal contact with the supervisors and other colleagues can be dehumanizing and disempowering and can result in the weakening of worker solidarities.

When asked if the algorithms can adjust the route for the drivers, especially for women, if they need to use the restroom, a platform executive said, “They always have the option not to accept the ride if there is a need to use the washroom. The customers cannot wait if the driver stops the car for restroom break and at the same time, who will pay for the waiting time?”

Image credit: Antonio Batinić / Pexels

While this makes sense at first glance, in reality, algorithms of a few ride-sharing platforms like Lyft penalize drivers in such cases by lowering their assignment acceptance rate (number of ride requests accepted by the driver divided by the total number of requests received). Lee and team, HCI (Human Computer Interaction) scholars from Carnegie Mellon University explored the impact of algorithmic-management on human workers in context of ride-sharing platforms and found:

 “The regulation of the acceptance rate threshold encouraged drivers to accept most requests, enabling more passengers to get rides. Keeping the assignment acceptance rate high was important, placing pressure on drivers. For example, P13 [one of the drivers] stated in response to why he accepted a particular request: ‘Because my acceptance rating has to be really high, and there’s lots of pressure to do that. […] I had no reason not to accept it, so […] I did. Because if, you know, you miss those pings, it kind of really affects that rating and Lyft doesn’t like that.’”

Uber no longer displays the assignment acceptance rate in the app and states that it does not have an impact on drivers’ promotions. Ola India’s terms and conditions state “the driver has sole and complete discretion to accept or reject each request for Service” without mentioning about the acceptance rate. However, Ola Australia indicate the following on their website: “Build your acceptance rate quickly to get prioritised for booking! The sooner and more often you accept rides (as soon as you are on-boarded), the greater the priority and access to MORE ride bookings!”

The lack of information coupled with ambiguity complicates the situation for drivers, who would try not to reject the rides under any circumstances. Moreover, the algorithms are designed to create persistent pressure on the drivers by using psychological tricks as pointed out by Noam Scheiber in an article for The New York Times:

“To keep drivers on the road, the company has exploited some people’s tendency to set earnings goals — alerting them that they are ever so close to hitting a precious target when they try to log off. It has even concocted an algorithm similar to a Netflix feature that automatically loads the next program, which many experts believe encourages binge-watching. In Uber’s case, this means sending drivers their next fare opportunity before their current ride is even over.”

The algorithmic decision-making also directs our attention to how the rides are allocated. The product manager of a popular ride-sharing app said:

“Apart from proximity, the algorithms keep in mind various parameters for assigning rides, such as past performance of the drivers, their loyalty towards the platform, feedback from the customers, if the drivers made enough money during the day etc. The weightage of these parameters keep changing and hence cannot be revealed.”

All the four people interviewed said that number of women driving professionally is considerably low. This makes it difficult for the algorithms to match women passengers with women drivers. Secondly, this may delay ride allocation for women passengers as the algorithms will first try to locate women drivers.

A lack of understanding of how algorithms assign tasks makes it difficult to hold these systems accountable. Consequently, a group of UK Uber drivers have decided to launch a legal bid to uncover how the app’s algorithms work – how the rides are allocated, who gets the short rides or who gets the nice rides. In a piece in The Guardian, the drivers’ claim says:

“Uber uses tags on drivers’ profiles, for example ‘inappropriate behaviour’ or simply ‘police tag’. Reports relate to ‘navigation – late arrival / missed ETA’ and ‘professionalism – cancelled on rider, inappropriate behaviour, attitude’. The drivers complain they were not being provided with this data or information on the underlying logic of how it was used. They want to [know] how that processing affects them, including on their driver score.”

The fact is that multiple, conflicting algorithms impact the driver’s trust in algorithms as elaborated in an ongoing study of ‘human-algorithm’ relationships.  The research scholars discovered that Uber’s algorithms often conflict with each other while assigning tasks, such as, drivers were expected to cover the airport area but at the same time, they received requests from a 20-mile radius. “The algorithm that emphasizes the driver’s role to cover the airport was at odds with the algorithm that emphasizes the driver’s duty to help all customers, resulting in a tug o’ war shuffling drivers back and forth.” Similarly, conflict is often created when drivers are in the surge area and they get pings to serve customers somewhere out of the way.

Ultimately, we need to shift from self-optimization as the end goal for workers to that of humane algorithms – that which centres workers’ pressures, stress, and concerns in this gig economy. This would also change the attitudes of the passengers, who need to see platform drivers as human drivers, facing challenges at work, like the rest of us.

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Digital pessimism: Can we break out of the negativity loop?

[By René König]

A few years ago, when I was in Cape Town, South Africa, I quickly learned that Uber rides were the best way to navigate the city. They seemed relatively affordable, quick, comfortable, reliable, and safe. But I was a little conflicted about my choice, being well-aware of the long list of scandals surrounding the company and I was reluctant to endorse it in any way. Bearing this in mind, I asked the Uber drivers about their experience working for the company, fully prepared to hear accounts of injustice and exploitation.

To my surprise, the stories the drivers told defied my expectations. Most of them came from Zimbabwe, a much poorer neighbouring country. In 2018, the year of my visit, Zimbabwe’s GDP per capita was 1306 USD while South Africa’s was 7434 USD. Zimbabwe had endured a series of severe droughts as well as floods; it had also suffered considerably under Robert Mugabe. Once praised for liberating the country from colonialism, the leader was later blamed for driving Zimbabwe into “hyperinflation, isolation, and political chaos.”

Learning where these Uber drivers came from made me realize how privileged I was for being able to travel to the other side of the world to take a comfortable ride with them. I also began to understand that the perspective of the distanced critic (taken from the countless articles and reports criticizing Uber) does not fully represent how their drivers feel. As Payal Arora has pointed out, such critical takes “do not account for the tremendous optimism expressed by the vast millions of people coming online for the first time in the Global South.” Arguably, the average Uber driver is more concerned with making a living, and less about the politics surrounding this company. For them, Uber is the best choice from a short list of available options. Yet, the discrepancy between the stories I read and those the Cape Town Uber drivers told me, made me wonder: Why was I so overprepared to confront Uber’s exploitative practices and so underprepared for these drivers’ optimism?

From techno-optimism to techno-pessimism

During the nascent years of the internet, many scholars and other observers painted a fairly bright picture of our future. There was a widespread expectation that the internet will have inclusive and democratizing effects on society, a hope for a newfound independence from the gatekeepers who controlled information flows. While this sentiment still circulates among a few techno-enthusiasts, the predominant narrative has completely flipped. Just take a glimpse at these popular recent book titles:

Popular books on the negative impact of digital technologies

The list goes on. Readers with an appetite for doomsday literature have a lot to chew on. It seems like the internet is no longer a driver for progress but for oppression and inequality. Even some key figures who helped building the big platforms have joined the critique. A recent example is the Netflix documentary “The Social Dilemma”, which is full of accounts from regretful developers.

Narrative of doom: The Netflix documentary “The Social Dilemma”

Trapped in the negativity loop

It is hard to argue with these critical perspectives. Such books and films are full of examples and quite well-researched. However, there is another side to the story that doesn’t get heard as much – the optimism emerging from the vast underprivileged populations due to these digital alternatives. More importantly, I am concerned that the sheer dominance of dystopian narratives may actually negate what actually works for these people, throwing the baby with the bathwater.

It is not easy to introduce examples of hope that go against the current mainstream barrage of negativity. Anyone who attempts this, becomes a suspect of whitewashing the addressed problems. Not without grounds. Silicon Valley spends hundreds of millions on lobbying to brighten its image. Moreover, the most powerful and privileged benefit from the existing inequalities and have little desire to change them.

Nevertheless, key stakeholders who shape the debates – journalists, activists, academics – have few incentives for taking positive perspectives, while there is significant peer pressure to join the paradigm of pessimism. These groups are critical by default. From their perspective, it is much easier to add to the overwhelmingly negative narrative, while any optimism makes them suspicious of being naïve at best and complicit at worst.

This incentive structure results in a negativity loop: Negative stories produce negative stories. While I am deeply sympathetic about the contemporary critical takes on issues like tech monopolization, digital surveillance and algorithmic black-boxing, it is essential to balance this against the user perspective, especially those who have few choices to begin with. In their worlds, with limited options, digital platforms can be genuinely liberating in spite of their oppressive tactics. My concern is that the negativity loop may blind us from even seeing any hope, the essential raw material for progress.

Uber’s gender gap – to bridge or not to bridge  

To illustrate what I mean, let’s take a close look at my initial example of Uber in South Africa. There are many aspects one could criticize about the company’s engagement there. An obvious one is the shocking gender gap: In 2017, only 3.8 % of the Uber drivers were female (IFC 2018, p. 24). There are many reasons for this discrepancy – from cultural stereotypes that render women unfit for driving to real safety concerns. Not only are Uber drivers in South Africa exposed to the country’s notoriously high rate of violent crime, they were also subject to brutal attacks from meter taxi drivers who felt that they created unfair competition.   

In 2015, aware of the striking gender gap between professional drivers (not only in South Africa), UN Women and Uber planned to launch a campaign with the ambitious goal to create one million jobs for female drivers within five years. The cooperation did not last long. The International Transport Federation published an open letter arguing “[w]omen already make up a high percentage of the precarious workforce, and increasing informal, piecemeal work contributes significantly to women’s economic dis-empowerment and marginalization across the globe”. Shortly after, UN Women cancelled the partnership.

Certainly, a cooperation with such a controversial partner leaves an organization like UN Women vulnerable to criticism. However, the swift cancelation strikes me as somewhat defeatist. Whatever problems there were, shouldn´t the aim be to solve them together especially given that companies like Uber provide employment to many in these contexts, due to their low barrier of entry?

One of the few voices who dared to argue in this direction was Charles Kenny. In an article for the Center for Global Development he argued:

“Doubtless the positions would appeal to few women who were already in full-time stable jobs with heath care, guaranteed pay and other benefits. But, of course, the vast majority of women working in the developing world aren’t in such jobs. Many are engaged in far less lucrative and less safe activities than driving a cab. So perhaps some of them would feel economically empowered by the new jobs on offer. At the very least it might be worth finding out rather than assuming the opposite on their behalf.”

(Charles Kenny, CGD)

Can Uber be empowering?

Five years later, Uber still holds its controversial status. What also continues is the tendency among some critics to refuse to acknowledge the legitimacy and realities of empowerment Uber drivers may share. A case in point is the interpretation of interviews with numerous drivers in South Africa by Andrea Pollio, a geographer at the Future Urban Legacy Lab. Many of them were enthusiastic about their experience, similar to the ones I spoke to. For example, two of his interviewees stated this:

“the great thing is you don’t have specific working hours. You can work whenever you want, I can go offline if I’m busy. It’s a great business innovation, it allows me to work when I can. True, Uber tells you when there are more people on the streets and less cars, they recommend a timetable, but you are free to comply or not (…).”

(Pollio 2019, p. 769)

“I think this is a much better life that I have. I just wait, and a client will eventually come. I don’t drive around, and that allows me not to waste fuel, and so I don’t need clients desperately because I’ve wasted fuel … I just wait, and that’s the best thing, the satellite will eventually send a client (…).”

(ibid.)

Pollio explains that this “self-empowerment” through Uber is just a “tale” (Pollio 2019, p. 766) and implies that such statements are merely “echoing the language” of a promotional video the company had released. This ‘correction’ of the optimism emerging from the lived realities of these drivers speaks to a long standing development practice of making subjects fit the script.

Uber’s shiny self-portrait

As much as tech companies like Uber try to overemphasize their emancipatory power (which they clearly do), we see an equal and opposite force of critical observers downplaying the positive impacts these digital platforms may have at the ground level. One reason Pollio gives for his dismissal of the drivers’ optimism is that many of them were forced to rent cars, which leads him to conclude:

“Despite the empowerment rhetoric, or the fact that drivers described themselves as entrepreneurs, they did not own idle capital, but accessed ridesharing through a mediating technology of subordination.”

(Pollio 2019, p. 767)

As precarious as such arrangements may be, they are not a contradiction to empowerment. Take the story of Tsungi Pamela Kujinga, a woman from Zimbabwe, desperate to make a living in Cape Town while providing for her two children. Since her car did not meet Uber’s minimum standards, she was forced to work for a commission under another driver. While this practice could be judged as exploitative, one needs to also acknowledge that it eventually helped her to buy her own car and create her own business.

She is not alone. 90 % of the few female Uber drivers in South Africa stated that “working with Uber allowed them to purchase products or services they hadn’t been able to afford before.” Moreover, these drivers noted that Uber’s GPS tracking makes them feel safer. Indeed, Charles Kenny pointed out the increased safety Uber drivers enjoy:

“Compared to a traditional taxi system where drivers pick up at random and passengers can pay in cash, Uber at least ensures that every driver (and the company) knows who is taking and paying for the trip – it is recorded as part of the transaction on the application.”

(Charles Kenny, CGD)

As obvious as this may seem, the now popular critical focus on “surveillance capitalism” will likely miss such promising opportunities of tracking technology. 

Embracing experiences of empowerment

Let me be clear: I have no doubt that there is a lot wrong with Uber and other digital platforms as they build market concentration and dominance, and we should demand change in these arenas. It is equally obvious that nobody should be forced to work under precarious conditions. However, it is just as clear that for people like Ms. Kujinga, Uber provides an opportunity to improve their situation and gain independence. Beyond individual perspectives, the gig economy might also have side-effects that are particularly beneficial for the Global South, for instance, an increased formalization of its vast informal labour market.

We need to break out of the negativity loop. We should seek to shape our future technologies by taking into account the full spectrum of user experiences, especially in the all too often marginalized Global South. Let us not downplay or negate experiences of empowerment because it doesn’t fit the narrative of oppression. Rather, we should aim at discovering and strengthening the agency of the marginalized and attend just as much to what works and what to keep, while we continue to push for change. In Ms. Kujinga’s words:

“As women, let’s take the opportunities we have and make a better life for tomorrow’s female generation. Let’s pave the way!”   

(Tsungi Pamela Kujing, Wow Woman)