st week New York City set a minimum wage for Uber and Lyft drivers—the first for ride-hail drivers in the US. I wanted to know what that could mean for such drivers around the world, so while I was in New York, I sat down with the author of Uberland: How Algorithms Are Rewriting the Rules of Work, Alex Rosenblat. Rosenblat is a technology ethnographer who rode over 5,000 miles with Uber drivers to uncover how technology is transforming work. We chatted about the implications of this ruling, New York City’s unique power over Uber, and what it’s like to have an algorithm as a boss.

What do you think of NYC’s decision last week to set a minimum wage for Uber drivers? Will it make a difference for the drivers?

I do. I think it’s a remarkable precedent, not just for the drivers, but for providing an example for other cities around the world that are grappling with how to regulate ride-hail companies, and more broadly technology companies. Setting a wage floor is important, but New York is also an anomaly. In many cases Uber has managed to perform a sort of arbitrage between the regulations that cover taxi drivers and the laws that apply to Uber drivers by arguing that it’s a technology company, not a transportation company.

Do you think New York, because of the number of Uber drivers, has some extra power that other cities might not have?

A lot of cities don’t even know how many Uber drivers are on the street. Like, San Francisco had to use a back door and hire a computer scientist to try and figure out how many drivers there were. And Seattle waged this huge legal battle to get zip code data on where Uber and Lyft were providing ride-hail services.

So the vast gap between what New York can do comes both from its power as a market, but also the power of the data it has legislated to collect. That gives it a negotiating or bargaining power with companies that other cities don’t yet have.

In what cities have you seen this disparity in power?

It was really clear in 2016 when Austin tried to pass a municipal ordinance bylaw that would have, among other things, required drivers to undergo a fingerprint-based background check. Uber rose up and said, well, people of color are disproportionately affected by criminalization, and fingerprint-based background checks will therefore subject drivers of colors to be more negatively affected by these types of rules. They united and allied with a morally persuasive case against the legislation.

But what was less evident was, fingerprint-based background checks take longer. And Uber and Lyft drivers can be working within a week, because they undergo relatively light background checks. That’s great if you need a job quickly. And it’s good for the business model, which relies on a lot of churn. After six months on the job, 68% of drivers are no longer there. So if we suddenly have a background check that requires four months, that is a business practice that would undermine your business model.

So Austin tried, and Uber and Lyft pulled out the city. They turned off the app (Uber and Lyft later returned after Texas created statewide rules that superseded Austin’s rules). Which is actually kind of remarkable. Because a lot of companies would say, “We’re going to move our factory to Mexico or overseas if you don’t bargain with us,” but that is a very significant and physical undertaking. Uber and Lyft can turn off the app. It gives them leverage in places where the app is quite popular.

You talk a lot in your book about how algorithms have become the bosses of Uber drivers. Do you think this format is something that will govern or already is governing other areas of work?

I actually don’t think it’s exclusive to work. I think users on Facebook are also managed by algorithms, because they have a news feed as their primary product that is curated by algorithms. It comes with a lot of the same opacity issues. Like, Facebook users were outraged when they learned that Facebook had experimented on their news feeds to show them sadder posts or happier posts. That contradicted the myth of a neutral algorithm on a neutral platform that was sort of objectively and benevolently curating what you saw.

I think that dynamic plays out for Uber as well, which takes a lot of the culture of technology and applies it to the world of work. Uber has narrated its platform as something that is neutral, saying it’s just like a credit card processor for transactions that match a driver in need of a job with a passenger in need of a ride. It has a boss for drivers; it’s just not immediately obvious, because that boss is a series of algorithms that operate within an ecosystem where the rules are encoded in the software. That really gets interesting when Uber experiments with driver pay in the same way that Facebook might experiment with your news feed. It has quietly changed the conditions under which drivers were paid. From Uber’s perspective, this is like, well, we’re kind of within our legal rights to do this. We A/B-test stuff all the time. Why would pay be any different?

 

 

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