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Making opportunities inclusive for first-time digital users

[By Shrinath V]

A couple of years ago, our house help came in early. She brought her daughter with her. The daughter was working at a nearby fashion store as a salesgirl after her graduation. The previous night, she had arrived home from work, distraught and weeping. The mother could not understand what she was upset about. She thought my wife could help calm her.

After having some coffee, the daughter calmed down a bit and spoke about what had happened the previous day at the store. The store owner was unhappy with her using her mobile during working hours. He had threatened to put up photos of her slacking on Facebook. This had terrified her, as she thought her reputation amongst her friends and her local community was at stake. She could not sleep that night, fearing that she and her family would lose face.

After she narrated the incident, we checked whether the sales manager was a Facebook friend. He was not. She later confessed that she had deleted her Facebook account a while ago. Why was she so agitated then? She assumed that any photos of hers posted there would be seen by all her friends. Facebook’s privacy settings had been too complex for her to understand, so she assumed the worst. We had to reassure her that once she deleted her Facebook account, no one could tag her or make any content public. Even if she had not deleted her account, she could remove tags from photos others posted before any of her friends could see them. It took her a while to get convinced about this, but when she left, she was a lot calmer than she came.  

This incident got me thinking.

I live in Bangalore, often called India’s Silicon Valley. Bangalore has a huge population working in the technology domain. Most college students carry smartphones. Here was a college educated salesgirl in an urban fashion store. We would assume that she would be comfortable with social media usage. And yet, she was so confused by the controls on the site that she thought it was a threat to her reputation. Finer aspects like abuse of power and violation of privacy were tough for her to comprehend. A threat about posting photos on Facebook from someone who was not even her friend had turned her into a nervous wreck.

Image credit: Victorgrigas 

The truth is that this girl is representative of many first-time digital users across growth economies. Thanks to cheaper smartphones and data plans, many users are getting their first taste of the internet. But many aspects that seem trivial to long-time technology users are seen very differently by such new adopters.

New opportunities and challenges

Smartphones have fueled the imagination of many who have just started understanding the power of the internet. In some ways, this has been timely. We are already seeing that the world post COVID-19 will rely a lot more on digital technologies. As we shift to transacting more online, we will see a larger number of gig jobs. From entertainment to education, smartphones, apps, and online services will play a greater role in lives of the new digital initiates.

A lot of this, no doubt, will improve the lives of billions. Going online is opening new vistas for exploration and providing new opportunities. Thanks to smartphones, new entrepreneurs and business models are aplenty. We see housewives post extra plates of lunch on WhatsApp groups for others in their locality to order. Local teachers take to Telegram to coach students appearing for exams. Drivers-on-hire get you and your car safely back home after a late night at the bar, so you need not drive when drunk.

And yet, there are unexpected challenges. Internet-driven models and services are largely designed for people who are comfortable with digital literacy. There are a lot of assumptions baked into how these are designed or delivered. As first-time digital users start using these services, many of these assumptions do not hold.

As digital technologies are likely to play a bigger role in the future of work, here are some points to consider.

Better terminology & representations

Websites and apps often have different privacy and consent policies. These are difficult enough for us to understand but can be befuddling to first-time digital users. Most are written in legal language that is difficult for common users to understand. They are made easy to click through so the apps can claim they received approval from users. As these vary per app or website, it is often easy to lose track of what one has agreed to. A more inclusive design could involve a common set of representations for terms like privacy and consent, preferably with videos explaining what the users are signing up for. For gig workers, this could greatly improve their understanding of what permissions the business asks of them. For example, knowing that you are being tracked only when you are on the job and not otherwise can be reassuring.  

Better explanation of downside risk

Many first-time digital users sign up for gigs based on referrals from friends. But often, the downside risks are not well understood. A while ago, I took an auto rickshaw (tuk-tuk) to office. As I chatted with the driver, I realized that he had earlier signed up as a cab driver for one of the many ride-hailing apps. As part of the deal, he purchased his taxi on a loan arranged by them. After a few months, he wanted to take a vacation and get home. He parked his taxi at their designated garage. When he returned, he was told that he had to pay a huge per-day parking charge before he could take his vehicle. This shocked him, but the company agent said it was part of the initial agreement he had signed. He did not know enough to debate them. After a few days, he realized his negotiation was going nowhere, and the taxi loan payments were due.

Image credit:  Andy Gray

He finally opted to forego the taxi and the money he had paid for the loan as he felt there was no other choice. This made him wary of gig opportunities in the future, and he decided to take up a safer, though less remunerative, option. He would have understood things much better if the downside risks had been better explained. This could again be done by using tools like video in languages that gig workers are comfortable with.

Better avenues for grievance redressal

A food delivery executive I spoke to recently complained about a late-night delivery he had to make a couple of days ago. He had picked up the food but was accosted by local bullies on the way. He could keep his phone, but they grabbed the food. When he rang up the food tech firm, he was told that he would have to pay for the food stolen from his remuneration. As online businesses grow, we will see many such cases of grievances that come up. First-time digital users may not be aware of grievance redressal mechanisms in place. More education on these and better policies will help.


Shrinath V is a product management consultant and founder of The Better Product Studio. In his last corporate role, he was the Head of products for location services on Nokia’s phones built for the Next Billion Users. He has been a mentor to various startups building for this segment over the last several years. 

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Platformizing women’s labour: Towards algorithms of empowerment

[By Pallavi Bansal]

As the fifth-born daughter to a poverty-stricken couple in a small village of Karnataka, Rinky would consider herself fortunate on days she wouldn’t have to sleep on an empty stomach. Her parents pressurised her to take care of her younger brother while they struggled to make ends meet. As the siblings grew up, the brother started going to a nearby school, while Rinky managed the household chores along with her sisters. A curious teenager, Rinky coerced her brother to teach her every now and then, including how to operate a smartphone they had recently acquired. When she turned 19, she mustered the courage to move to Bengaluru in search of a better life. She survived by doing menial jobs in the beginning such as cleaning houses, cooking and washing dishes. She earned a mere amount of Rs 15,000 (about 200 USD) every month, enough just to get by. She always felt disrespected having to deal with constant humiliation until someone in the neighbourhood advised her to learn driving and partner with the ride-hailing platform Ola.  

Image credit: Renate Köppel, Pixabay

While there were initial hiccups in procuring the vehicle and learning how the app works, this move dramatically changed her life as it turned her into a micro-entrepreneur with a lucrative income of Rs 60,000 to take home every month. Besides allowing flexible work hours, the job provided her a sense of independence which was missing when she worked for others. She wasn’t really bothered about how the rides were assigned to her, though she always worried about her safety while boarding male passengers. At the same time, she was unable to comprehend how some of her colleagues earned more than her despite driving for similar number of hours.

“Rinky” is a composite character but represents stories of many such women for whom the platform-based economy has opened up a plethora of employment opportunities. The interesting aspect is that women workers are no longer confined to stereotypical jobs of salon or care workers; they are venturing into hitherto male domains such as cab driving and delivery services as well. The Babajob platform in fiscal 2016 recorded an increase of 153 per cent in women’s applications for driver jobs. According to the Road Transport Yearbook for 2015-16 (the latest such report available), 17.73 % of the 15 million licensed female drivers ride professionally. Though there are no distinct figures available for how many women are registered with Ola and Uber as drivers, ride-hailing app Ola confirmed a rise of 40 % every quarter in the number of female drivers with them. Moreover, cab aggregative service Uber announced to tie up with a Singapore-based company to train 50,000 women taxi drivers in India by this year.

Clearly, the ride-sharing economy is helping Indian women to break the shackles of patriarchy and improve their livelihood. However, the potential of these platforms cannot be fully utilized unless researchers turn an eye on the algorithms that govern them. These algorithms not only act as digital matchmakers assigning passengers to the drivers but regulate almost all aspects of the job – from monitoring workers’ behaviour to evaluating their performance. These machines often fail to treat workers as humans – as people who can fall sick, need a leisure break, socialise with others to stay motivated, de-route to pick up their kids from school, attend to an emergency at home, lose their temper occasionally, and moreover, coming to the work after facing physical abuse at home. In a normal work environment, employers tend to understand their team-members and often deal with compassion during tough times.

Image credit: Satvik Shahapur

Research shows how these data-driven management systems especially in context of ride-sharing apps impact human workers negatively as they lack human-centred design. They discovered that sometimes female drivers did not accept male passengers without pictures at night only to be penalized by these algorithms later. Moreover, drivers complain of rude passengers, which is seldom taken into consideration by platform companies and it only lowers the driver’s acceptance rate and ratings.

Technology creators need to ask themselves how to ensure that algorithms are designed to enable workers and not just be optimized for customer satisfaction. Alternatively, they need to see the extension of worker’s satisfaction as that of customer gratification given these two realms reinforce one another. By sensitizing to the needs of women like Rinky who are perhaps stepping out in this male-dominated world for the first time, programmers could create a more empowering pathway for such women workers. With the entrenched gender norms burdening women with familial duties and limiting their access to education and skills training, the intervention by platform designers can promise genuine change. While cultural change often takes a long course, by placing women at the centre, designers can accelerate this shift.

More concretely, what if platform companies did the following:

  • They create a feedback/resolution system which accounts for rejections and safeguards ratings when women drivers reject certain passengers if they consider them as potential threat.
  • They can institute flexibility in terms of wanting to go home early and this shouldn’t be translated into ‘lower incentives’, after all this is the premise of gig economy.
  • AI should aim at promoting workers’ well-being, which means following a demanding or intensive piece of work (a long ride in this case), AI could recommend a relatively easier task for drivers.
  • Another aspect is to ensure transparency in terms of how the wages are allocated to different people and an understanding of how the autonomous systems impact ratings with also a system of redressal, i.e. one that allows for corrections etc.  
  • Algorithms should encourage a community-building culture rather than individualism-oriented – social incentives could be given to those drivers who pick up rides when an assigned driver is unable to reach the destination instead of penalizing him or her.
  • While the in-built GPS system in apps can help drivers track public toilets and other places that could be used for restroom breaks, algorithms could be trained to adjust routes according to drivers’ needs and availability of amenities.
  • Moreover, popular ride-sharing platforms like Ola and Uber can consider assigning women passengers to women riders especially during the night-time. This move can make both the parties feel secure considering women dread boarding a taxi in an ‘unsafe’ country like India.

Across disciplines, if we brainstorm on reimagining these platforms as cooperative instead of competitive spaces, of human-centered versus optimization-centered, and as feminist-oriented and not just male-oriented, there may be more promise for our digital wellbeing.