The Hidden Algorithms of Gig Work: Who Really Profits from Uber and the Platform Economy?

The World Bank estimates there are now more than 435 million online gig workers globally.

Yet for many of those workers, the systems determining what they earn are largely invisible.

Today, we're exploring new research based on data gathered through GigU, a mobile app that helps drivers evaluate whether ride and delivery offers are actually profitable after costs and taxes.

The findings raise important questions about transparency, platform power, and the future of work.

Joining me are Len Sherman from Columbia Business School, Luis Neves, CEO of GigU, and journalist and co-founder of Futuros Posives, an analyst company, and friend of the show, Angelica Mari.

Now, Len, you've analyzed millions of trip offers received by Uber drivers across multiple cities with data collected by GigU.

What's the single most important finding listeners should understand?

Well, I would start by saying that the theme of this show, where tech meets humanity, certainly applies to Uber.

Everyone, I would assume, listening to the show has used Uber or 99 or other ride share companies around the world, but Uber is the undisputed king and leader.

It is a laboratory for us to understand what's going to increasingly happen across multiple parts of the economy where market leading companies who control the data, who control the information about how these marketplaces work and what are in the interest of riders and drivers in this case, are in a position to control setting the price that consumers pay and the pay that drivers receive And they certainly have used that to their advantage, going from a company that initially lost more money than any startup company in history, remarkably, to now being a money-making machine.

And it is largely due to their use of very sophisticated algorithms, massive databases that have remarkable knowledge and insight into the behaviors of both sides of their marketplace, riders and drivers, that they've exploited to full advantage.

And other companies in other sectors are observing this.

And I think we're going to increasingly see across a wide number of sectors, companies turning to algorithm pricing, raising the basic question about who gets to decide what's fair, correct, right for all the constituencies in our economy.

Now, one word or two words that keep coming up in your analysis is take rate.

What is take rate?

Take rate is a commonly used term used across a number of different sectors, particularly involving companies that we describe as market maker platforms.

They're the intermediaries that sit between buyers and suppliers of products and services.

uh apple does this through the app store online travel agencies where you can book you know flights all of these kinds of companies take a cut of what the customer pays for the product or service and the percentage of what the customer pays that goes to the market maker or the intermediary in this case uber is what's called their take rate and the percent that goes to the supplier of the service in this case the driver It is a key metric of who wins and who loses.

And in my research, I was able to show that when Uber first launched its ride-sharing service back in 2011, they typically promised and actually delivered on their take rate, Uber's only meeting 15% to 20%, with drivers getting the remaining 80% to 85%.

And now fast forward to today, you've gone from 15% take rate for Uber to 50 or more percent.

As you can imagine, that's been very beneficial to Uber and for drivers, not so much.

Yeah, absolutely.

Because the numbers that you're coming up with, when a driver started with Uber in the early days, it was around...

the take rate moved from around 15%, right? 15 to 20.

15 to 20.

The World Bank estimates there are now more than 435 million online gig workers globally.

Yet for many of those workers, the systems determining what they earn are largely invisible.

Today, we're exploring new research based on data gathered through GigU, a mobile app that helps drivers evaluate whether ride and delivery offers are actually profitable after costs and taxes.

The findings raise important questions about transparency, platform power, and the future of work.

Joining me are Len Sherman from Columbia Business School, Luis Neves, CEO of GigU, and journalist and co-founder of Futuros Posives, an analyst company, and friend of the show, Angelica Mari.

Now, Len, you've analyzed millions of trip offers received by Uber drivers across multiple cities with data collected by GigU.

What's the single most important finding listeners should understand?

Well, I would start by saying that the theme of this show, where tech meets humanity, certainly applies to Uber.

Everyone, I would assume, listening to the show has used Uber or 99 or other ride share companies around the world, but Uber is the undisputed king and leader.

It is a laboratory for us to understand what's going to increasingly happen across multiple parts of the economy where market leading companies who control the data, who control the information about how these marketplaces work and what are in the interest of riders and drivers in this case, are in a position to control setting the price that consumers pay and the pay that drivers receive And they certainly have used that to their advantage, going from a company that initially lost more money than any startup company in history, remarkably, to now being a money-making machine.

And it is largely due to their use of very sophisticated algorithms, massive databases that have remarkable knowledge and insight into the behaviors of both sides of their marketplace, riders and drivers, that they've exploited to full advantage.

And other companies in other sectors are observing this.

And I think we're going to increasingly see across a wide number of sectors, companies turning to algorithm pricing, raising the basic question about who gets to decide what's fair, correct, right for all the constituencies in our economy.

Now, one word or two words that keep coming up in your analysis is take rate.

What is take rate?

Take rate is a commonly used term used across a number of different sectors, particularly involving companies that we describe as market maker platforms.

They're the intermediaries that sit between buyers and suppliers of products and services.

uh apple does this through the app store online travel agencies where you can book you know flights all of these kinds of companies take a cut of what the customer pays for the product or service and the percentage of what the customer pays that goes to the market maker or the intermediary in this case uber is what's called their take rate and the percent that goes to the supplier of the service in this case the driver It is a key metric of who wins and who loses.

And in my research, I was able to show that when Uber first launched its ride-sharing service back in 2011, they typically promised and actually delivered on their take rate, Uber's only meeting 15% to 20%, with drivers getting the remaining 80% to 85%.

And now fast forward to today, you've gone from 15% take rate for Uber to 50 or more percent.

As you can imagine, that's been very beneficial to Uber and for drivers, not so much.

Yeah, absolutely.

Because the numbers that you're coming up with, when a driver started with Uber in the early days, it was around...

the take rate moved from around 15%, right? 15 to 20.

15 to 20.