Social networks were ablaze with the picture of a young mother, with a baby hanging from her chest and delivering food on a bicycle. The company was Pedidos Ya, one of the most established delivery platforms in Argentina. 

In 2016, on International Women’s Day, Uber announced that the freedom granted by its platform “is helping – literally – to fuel another wave of women’s empowerment: the opportunity to adapt work to life, and not the other way around. Uber offers something unique: work on demand, only when you want it. Women drivers can earn money on their own terms and set their own hours”.

According to the new capitalist terminology, the woman on a bicycle could be categorized as a mompreneur, a neologism used to name mothers and female entrepreneurs as new models of success. But the image of mompreneurs promoted by platforms is accompanied by images  that are not new: photographs on networks of women who seamlessly combine their role as caregivers with that of good professionals, women without dark circles under their eyes and perfectly coiffed, smiling and with the ideal house – because this is still their territory – and who work with the latest technology. But the reality of mompreneurs is more in line with that of the young delivery girl, forced to carry her baby on a bicycle through a large city pressured into this by precariousness and a lack of resources. 

Discrimination on platforms is still a little studied phenomenon, but it seems that the data dismantle these arguments and prove the opposite. “Technology reproduces the biases we have in reality, it reproduces what society already is. The platforms where women are most active are the care platforms, the platforms that have to do with a sexual division of labor. It reinforces the idea that women work at home and men can go out to work. Men who design technology are generating a systemic and structural problem, because technology is reproducing inequalities in a silent, almost invisible way,” says Sofia Scasserra, an economist, researcher, teacher and adviser on economic and international trade issues at the Argentine Federation of Trade and Service Employees. The same goes for the income they produce, which is much lower for women than for men.

The researchers Arianne Renan and Anat Ben-David, in their article entitled “Inequality in the platform: gender in the Gig-economy” have studied the wage gap between men and women in service work managed through a platform, and the differences they have found have been tremendous: despite the fact that the number of women and men offering work on the platform was similar, that the work done by men was scored with an average of 3.17 and of women 3.21 and that women had worked more hours than men, 773 versus 611, women were paid $28.20 per hour compared to $45.07 for men, 37% less.

Abigail Hunt and Emma Samman, in their article “Gender and gig economy” and citing numerous previous investigations, claim that women earn less on average than men. In the UK, it has been shown that 75% of women earn less than £11,500 per year, compared to 61% of men. Another study conducted by Cook in 2018 entitled “The Gender Pay Gap in the Collaborative Economy” which analyses the wages of one million Uber drivers in the United States, revealed that there is a 7% gap between men’s and women’s earnings.

Platforms determine the amount to be paid per order through an algorithm. This algorithm pays according to the time of day when the person has worked, the number of hours worked, or the speed of delivery, and this type of criteria reproduces the prevailing biases. “Women choose certain hours because they are the hours they can work, not the hours they want to work. The times they can work are usually determined by  when they take over the care economy at home,” says Scasserra. The economist states that platform biases occur at three levels: The first is in the loading of data, which is already biased at birth. This is a social bias where technology is not involved. The second is in the categories we use to systematize data: the binary sex category, and finally, programming bias, where an algorithm is designed to determine the appropriate way to do a task. “Algorithms tend to repeat classist, racial and patriarchal biases,” says Scasserra. 

We must not only take into account the discrimination of the algorithms, but the agent behind it, the company, plays a fundamental role in the modeling of reality. “In the framework of platforms, in most cases there is an asymmetry of power between the parties. On the one hand, the intermediary company, the platform, which has more data than anyone else about the workers, as well as the capacity to process it, and on the other hand, the client, with a global market of competing workers. But there is also a strong investment behind it that allows it to always negotiate downwards. Most platforms are heavily financed by hedge funds that support them so that they can put themselves, at least temporarily, in this position of power over any other type of individual or collective competition,” says Javier Sánchez Monedero, a researcher at Cardiff University’s Data Justice Lab. 

The algorithms are nothing more than a new generation of tools for the exploitation of the workforce, which have brought precariousness and the sexual division of roles to the maximum for the benefit of a few. “Jeff Bezos is rich not because Amazon uses artificial intelligence and big data to know what we want, but because of a network of investment funds that have allowed him to spend his first 10 or 15 years in losses, unlimited labor exploitation and fiscal engineering techniques,” concludes Sánchez.

We not only found differences in earnings, but also in the type of platform. Balaram studied the distribution of work according to the type of platform with a sample of over one million people in the UK. Helping, the platform par excellence for finding cleaning services for the home, has 86.5% of women, while 94% of Deliveroo deliverers and 95% of Uber drivers are men. 

In the case of Argentina, the Center for the Implementation of Public Policies for Equity and Growth published a survey in 2018 studying the distribution of sexes by platform. Iguanafix is a platform for home repair services such as plumbing and has 100% male workers, Zolvers, offering cleaning services, has 100% women workers. For Cabify, Glovo or Uber, the number of men is 96%. For Airbnb 57% are women. In the latter case, in a study published by the company itself, the best rated hosts are women over 60, who receive a higher percentage of five star ratings which is the maximum score a host can have at Airbnb. Thanks to the platform they get an extra $6000 per year, which is needed to supplement their retirement income.

The case of the young mother delivering with her baby and the one of the retired hostess (Airbnb) are a clear example that the platform economy should be called a needs economy, arrangement economy or complement economy. It is not based on freedom, but on the need for extra money; it is not based on flexibility, but on scarcity.

The operation of the platforms is not irrevocable, it can be changed. Scaserra suggests that it is necessary to generate an affirmative agenda of algorithms, which favour women in a positive way. “If the rules are the same for everyone, they are definitely favouring the most powerful”, says the researcher.

The Dimmons research group has created the collaborative star, a framework for analysis to determine whether a platform is truly collaborative or not, where gender diversity, not just binary genders, is one of the elements to take into account. Thais Ruiz de Alda, member of Dimmons, Digital Fems activist and technology consultant, states that “if there are women in the platforms’ environment, it is clear that the social impact generated by this platform, having more women in its ecosystem of resources, is positive. If the governance model of the platform is hierarchical and there are few women, inclusion will be scarce”.

Javier Sánchez says that there are numerous communities like barrapunto where “karma” systems have been created to value a person’s contribution to the community. “On the platforms it happens that it is the company that decides a series of parameters, through an intelligent or semi-intelligent data system, so that in the end it calculates the remuneration of the work, for example, according to the activity and time of day. On the platforms it is imposed from outside, where, of course, reproductive tasks, care and so on are not taken into account. The platforms are designed by people very far from the impacted community, where typically there are Silicon Valley engineers along with economists and where there are many things that are left out of what they consider efficient or inefficient, so it’s interesting to take up the idea again where the communities are the ones who decide.”

Aurora Gómez, a psychotherapist specializing in digital behavior and gender, points out that for a platform to be considered feminist it must seek equality on three levels: “With users, with workers and taking into account behavior with other companies and providers.” According to Silvia Diaz Molina, researcher at P2P Models and feminist activist at Las Taradas, “it must propose measures of boycott and hacking, agreements on working hours and not allow them to stretch like chewing gum. There has to be space for communication, agreements, consensus, it will ultimately put life at the center […]It seems unbelievable, but once you get past the personal side of things, you have to remember that the work side is also political, and of course the technological side also has to be established as a space for struggle, in which you have to take a stand”, she says. 

Image: Patricia Bolinches.

Text originally published: El Salto Diario.

Translation: Genoveva López and Tabitha Whittall