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On Gig Economy with Professor Noopur Raval

Professor Noopur Raval is an interdisciplinary researcher of issues relating to society and technology. Until July 2022, she was a post-doctorate researcher at the AI Now Institute at New York University. In fall 2023, Professor Raval will be starting as an assistant professor at UCLA at the department of Information Studies. She has analyzed trends and written several research papers on gig economy algorithms. It was a pleasure to talk to her.

The following is a summary of our interview with her.

  • How do gig economy algorithms affect gig workers?

Some of the functions that algorithms perform in the gig economy decide which task to assign to which gig worker. So for instance, in an Uber set up, it would decide which ride to assign to a driver. In a food delivery set up, it would decide which person to assign to deliver that order. These decisions made by algorithms are informed by data.

There is a certain algorithmic opacity. Companies often withhold information regarding the data that goes into these algorithms. The algorithms are black boxes where unknown variables and data are fed in, and the results impact millions of workers. This data could include the ratings of the gig worker, reviews, feedback and comments. But it could also include controversial aspects such as gender, experience, age, etc. in the service of optimization and efficiency.

  • What does the lack of transparency in the algorithmic system mean?

In companies such as Uber and Ola, very often drivers were unsure of the reason behind receiving a low aggregate rating. When they saw ratings such as 3.8, or 3.9; they were confused because they were never informed of the reasons behind their negative ratings. This was detrimental, because drivers did not know what they were doing wrong, and kept getting poor ratings. However, low ratings often meant that their Ola/Uber app was locked, and under pressure for possible suspension.

This information asymmetry is typical across the gig economy. While customers are informed of the details and situation of their booking, a majority of gig workers are not given access to similar information about their own performance. Providing more information to gig workers, planning information ahead of the rides/delivery could be a huge benefit to gig workers.

  • What does the algorithmic system not account for? And why are those factors important to consider?

The algorithmic system also doesn’t consider incredibly important parts of a gig worker’s performance. For instance, making sure the customer doesn’t get angry, accommodating requests beyond their simple delivery, etc.

Gig economy services fail to account for the emotional labor of workers. Customers often expect that after a long day of driving, drivers are still positive, do not talk on their phones, offer water/mints etc. But those aspects of emotional labor are not accounted for.

  • How can gig platforms account more for emotional factors?

There are numerous things gig platforms can do, but are reluctant to because it would cut down on their profits.

However, platforms are increasingly trying to recognize the humanity of delivery people and taxi drivers and acknowledge their emotional labor: giving some information about the gig worker to customers while they await their delivery, or talking about gig workers managing to make a delivery despite severe rains etc. One aspect of the issue is acknowledging the emotional labor of gig workers, and gig companies are increasingly doing that.

But the other aspect is rewarding that emotional labor. And the big issue right now, is that the gig economy is unwilling to compensate workers, either through bonuses or other benefits, for driving in the rain, or during peak traffic hours, or making long journeys etc.

  • How do gig economies affect overall society?

An important feature of gig economies is that they are private companies which use private products on public land. For instance, companies like Uber operate on public infrastructure like roads and bike-rental companies like Bounce and Yulu rely on footpaths.

In the initial stages, they are able to deploy their vehicles across the streets. But as the number of customers start to increase, these gig companies are able to gain critical mass to lobby against regulation. Once companies such as Yulu had sufficient users, they were able to convince the city governments to make exceptions and allow them space on footpaths.

For privileged people who are able to sit in their homes and order their food from Zomato, this flouting of regulations is not a direct problem. But for the common person, who cannot afford to use these gig companies, the quality of life in the city becomes worse.

  • What can we do to reduce the effects of algorithmic opacity on gig workers?

In the light of these conditions, workers are beginning to form Mutual Aid Stations and worker solidarity groups where they are able to help each other through issues both within and outside of the gig economy. These groups have been a major step towards helping gig workers. However, that should not be an excuse to wipe our hands clean and not improve conditions for gig workers any further. Gig workers find the necessity to form Mutual Aid Stations precisely because of severe inaction from the Government and consumers regarding the algorithmic opacity.

Government regulation can be a huge step in improving this transparency. Governments should impose strong labor laws to protect gig workers. Laws on privacy also play a huge part in transparency. In the EU, the rights enshrined under the GDPR are greatly improving the access to information for gig workers. Under Article 40 of the GDPR, gig economy workers have a right to the information and criteria through which they have been processed and assessed in the gig economy algorithm. This step has enabled many gig workers in the UK to get information and improve their working conditions.

As consumers, all of us could try and develop a culture of tipping the workers who deliver items in order to compensate them for their emotional labor. The importance of spreading awareness about the gig economy algorithms is that gig workers can have greater solidarity and support from society. When they have campaigns and protest for better treatment, there will be a larger group of people pushing for such changes.

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