a16z Podcast - a16z Podcast: An Economics Take on the Sharing Economy

Episode Date: June 16, 2016

Love the term or hate it, the concept and reality of the "sharing economy" (or "gig economy" and so on) is here to stay. And in fact, argues NYU Stern professor and researcher Arun Sundararajan, it may even reduce the income distribution gap between the haves and have-nots in a way that previous shifts -- like the Industrial Revolution and traditional 20th century institutions -- never did. How? Because it's a new model for (crowd-based) capitalism -- one where we're increasing the segment of the population that owns the means of production. Or... have we just shifted value from traditional institutions to the platforms instead? Well, let's see what the data tells us. In this episode of the a16z Podcast, Sundararajan (who is also affiliated with NYU's Center for Urban Science+Progress and at NYU's Center for Data Science) shares the latest findings, economics research, and more from his new book on The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism. We cover the challenges of capturing this shift in GDP (as well as the challenges of GDP and measuring tech progress in general); the challenges of creating a new funding model for the "social safety net of the 21st century workforce"; the challenges of "data darwinism", reputation, and ratings; and finally, how and just who should regulate the sharing economy? The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

The content here is for informational purposes only, should not be taken as legal business tax or investment advice or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16Z fund. For more details, please see A16Z.com slash disclosures. Hi, everyone, welcome to the A6NZ podcast. I'm Sonal, and I'm here today with Arun Sundara Rajin, who's a professor at NYU's Stern School of Business. And he's a longtime expert on the so-called sharing economy. The reason I say so-called is because a lot of people have a love-hate relationship with that phrase. They've proposed alternatives like gig economy. There are lots of other

proposals on the table. For lack of a better phrase, we're going to stick to it. And the other reason we're going to stick to it is because it happens to be the title of Arun's new book, which is called the sharing economy, the end of employment and the rise of crowd-based capitalism. Welcome, Arun. Good to be here, Sonal. Well, it's funny, Arun, because as you recall, we wrote an op-ed about over four years ago in Wired. And I think it was one of the very early op-eds. We didn't coin the term by any means, but I did do a Google search at the time, and I only saw it use in a few places. And I remember having a little fight with the headline desk, because the title of the op-ed is why the government should not regulate the sharing economy. And they were like, what the hell is the sharing

economy? Well, for the next few years, I had to deal with being the guy who wrote, why the government doesn't need to regulate. Every time I spoke to government officials. And so the positive part of that, I guess, is that, like, a lot of people in government did, in fact, read that op-ed. And, yeah, first one I wrote about regulating the sharing economy. Well, that makes me happy to hear that. The term has been around for a while, and I think we do talk about it a lot. But you're writing one of the early definitive books on the topic. I actually would love to deep dive on some of the things that people don't talk about. You have a subtitle called The End of Employment and the Rise of Crowd-based Capitalism. And that part is what I find very intriguing. Do you want to quickly break down for us what you mean by the rise of crowd-based?

capitalism? The crowd-based has to do with a shift away from traditional 20th century institutions that would hire their own employees and acquire their own resources and, you know, then produce goods and services for us. And the capitalism part is to underscore the fact that while the term-sharing economy might sound like we are not engaging in commerce, what's happening is very commercial. It's bringing a little bit of gift into the capitalism, but at its heart that our prices being set, their supply and demand being matched, and it is just a new way of organizing economic activity that at its heart is capitalist. One of the themes that came up on a recent podcast we did with the U.S. Secretary of Commerce, Fannie Pritzker, was that the Department of Commerce

is looking into figuring out how to actually capture this new kind of capitalism into the economic measures of GDP. And so I'd love to hear from you on you're an economist. by training on why that is such a challenge. And we don't have to go in a great detail on this, but I think it's important to talk about because it's a topic that comes up a lot. And whether you agree with the academic nature of the discussion or not, it does impact where people put funding, how people allocate resources, how they think about policy and everything related to the topic of the future of work, just at a very basic level. Like, what's the main problem with GDP as a measure for soft rating the world? I think we can break down the trouble with GDP into at least

three buckets. The first is that there's a lot of value that's created by technological progress, like, you know, the value you get from Google searches, the value you get from sort of connecting with other people on Facebook. There's sort of the surplus that, you know, consumers enjoy that aren't captured. This isn't captured by GDP. And so if that's relatively small, it doesn't matter. But technological progress, especially progress with digital technologies, seems to make this consumer surplus piece pretty big, and GDP is not measuring that. It's just measuring the flows. It's measuring the prices that we pay and the revenues that firms get. So that's one problem. A second problem has to do with distribution. GDP is a total measure, meaning it's

adding up all of the dollars, and it's not giving us a sense for how equally or unequally they're distributed. So, for example, about 80% of India now has access to a mobile phone. A couple of decades ago, that was just 10%. And so we've not just seen an increase in consumer surplus here, but we've seen like a tremendous reduction in inequality of access that just doesn't get picked up by GDP. Right, the distribution of those smartphones. Absolutely. And a third reason has to do with other quality of life measures that are becoming increasingly important. If all that you care about is how much money you earn, then GDP is a good measure of how much everybody is earning, or at least one form of GDP.

But once you start to value other things like the work-life balance that you get from providing through the sharing economy or by running your small business on Etsy, the fact that you're doing something that you like and you have the flexibility of switching to something else, none of these aspects of work are well captured by GDP.

And this wouldn't matter if it was just sort of a small handful of people who were engaging in this kind of freelance activity. But now as crowd-based capitalism goes mainstream, it's going to highlight how there's a big disconnect between what we're measuring, which is GDP, and what we value as things that really point to progress. And so as this gap starts to grow, I think much like there's a gap between the observations and the theories that leads to a paradigm shift in Kuhn's theory of the structure of scientific revolutions, it's going to take something.

like the expansion of the sharing economy to highlight how there's a big disconnect between what we're measuring, which is GDP, and how much an economy is progressing or not progressing. So people have had problems at GDP forever, but you're arguing that the gig economy and the sharing economy or crowd-based capitalism, as we're calling it,

that that will be a driver for getting people to really push economists towards this shift. It could sort of be the change that triggers, the paradigm shift away from GDP as the measure of progress and towards something that is more inclusive. Right. Well, let's spend a few minutes talking about the economic effects of the sharing economy because, you know, for better or worse, you are an economist by training. You've done a lot of research on the sharing economy.

In traditional economic terms, how do you think about the impact of what it brings? So I have categorized the traditional economic impacts of the sharing economy or crowd-based capitalism into four key impacts. The first is how we are increasing capital of assets of money through more efficient use of it. So you might think of this as leading in the long run to an increase in productivity because you're using stuff more efficiently.

And so that's one impact. A second impact has to do with an increase in consumption that comes from greater variety. So let's contrast, for example, level of variety that you have on Airbnb, with the level of variety you have in the hotel industry. There's just so much more choice of so many different configurations and kinds of accommodation on a platform like Airbnb. Economists disagree about most things, but there are two things that economists agree about. One is that when you increase efficiency and you increase

productivity, this leads to long-run economic growth. And the second thing they agree about is that when you increase variety, you increase the amount that people consume and increased consumption also leads to economic growth. So those two factors, increased capital impact and increased variety, have a decidedly positive prognosis for how crowd-based capitalism is going to alter the economy. You're also really talking about people who maybe couldn't have afforded certain choice, like before choice was a province of the wealthy. You're also describing a phenomenon where people just get more choice, whether they can afford it or not. There's this democratization of opportunity here.

And this goes back to what we were discussing when we talked about GDP a little, because it points to the fact that maybe we shouldn't be measuring just how equal or unequal income and wealth are, but how equal or unequal are access to things that give you a high standard of living. So, you know, if I can buy a Tesla, use it when I want to use it, and then rent it out on a peer-to-peer car rental marketplace when I'm not using it, I'll be able to afford a better car. If I can't afford that car, I might still be able to access it when I want it if there's a fluid peer-to-peer rental market. And so by removing ownership as a barrier to access, you're in some ways equalizing people's opportunity to go after that high-to-year-old. a standard of living. But there's more to that democratization of opportunity because what we're also doing as we shift the workforce away from being providers of labor and towards tiny business

owners, we're increasing the fraction of the population that owns the means of production. And one of the things we learned a couple of years ago from Pekeri's book, Capital in the 21st century. That book that everybody talks about, but nobody's actually read. Well, you know, I talk about it and I've read it. I'm just choosing you because you're allowed to talk about it anyway. Oh, yeah, everybody quotes from it, but nobody's actually read the whole thing from start to finish. Anyway, the core of Piquetti's argument about inequality increasing over time is that people who own capital, who own the means of production, see a faster rate of growth of income than people who earn wages. And so the gap between the haves and the have-nots spans over time.

So by the same argument, if we increase the fraction of the population who are owners, if we shift people away from being labor providers and towards being owners, of tiny short-term accommodation businesses on Airbnb, of tiny retail operations on Etsy, of like tiny grocery stores on LaRush Kivir, then you're increasing the fraction of the population who will see those faster rates of growth, and over time this could reduce inequality. So that's the third aspect, the democratization of not just access to stuff, but also of ownership of the means of production of society. I want to hear your fourth bucket,

and then we'll come back to that. Okay, well, the fourth bucket is really, it's where we're going to see some positives and some negatives, and this has to do with some gains and some losses of economies of scale. For those of us who aren't economists, an economy of scale is when, as you increase the amount of something that you produce, your costs go down or your ability to produce it

improves relative to the competition. Traditional economies of scale come from having a big manufacturing plant. And so it's possible that as we move from massive industrial production to millions of makers who are making things, that we may lose some economies of scale. But I argue in the book how we're probably going to reclaim some of those. Okay. So I do want to go back to the point you mentioned about the democratization of opportunity. And the reality is that I have yet to be in a lift or an Uber where someone is actually taking their Tesla out in the road. And so I want to probe on this idea of how democratizing it really is, because one of the common prevailing complaints that I've heard is that, well, okay, come on, is that are the benefits really accruing to the

producers now? Or have we just shifted that it's now just going to the platform owners? And they're the ones who are really extracting all the value and that no one else is. How would you respond to those critics? I think we should look at the data. I've done some research on my own. I've seen research done by others. Fundamentally, we should realize that the nature of the relationship between the individual and the institution shifts from the 20th century industrial model of you are a provider of labor to one in which you are a small business owner. And so however much wealth is created by the platforms, this is something that is empowering for the individuals. and maybe later in the conversation, we can talk about policy challenges that come up around

labor protection. But that's an important starting point, that this is fundamentally empowering for the individual. Alongside each tech billionaire that the sharing economy creates, it also creates millions of small entrepreneurs. And this distinguishes the sharing economy from some of the technological advances that preceded it. It's not just the software engineers and the people with Google stock who are benefiting financially. It's also the millions of entrepreneurs who are providing through the platform. My own research has shown that if you project what the sharing economy is doing forward, a significant fraction of the value creation is captured by people below median income. In fact, the rate of growth of the value creation for people below median

income is significantly higher. I'm glad that you can bear that out in the numbers because people always tout those values, but it's nice to have data to actually back it up. There's some research from JPMorgan Chase that looks at today's distribution I project into the future. They find that the top 20% of income earners are earning a little more through the sharing economy than the bottom 20%. But you look at that distribution, you compare that to the actual income distribution, and you see that it's redistributive, which is that people in the top 20% earn 10 times as much as, say, people in the bottom 20%, but they're earning a dollar. $20 for every dollar that someone in the bottom 20% is earning from the sharing economy.

So fundamentally, that income is reducing the inequality. Okay. So then on the policy side, what's your views on how we should then consider protecting the benefits of people who are in these systems? This is the big policy challenge for the next 20 years. So I think the question of how do we create a new funding model for the social safety net of the 21st century workforce. That is exactly the question.

Here's why it's a challenge today. It's because over the 20th century, we made great strides in constructing a social safety net for the full-time employee. And it made sense to do that because that was the dominant way in which people made a living. So now you've got that status of full-time employee

and it's got a good funding model. You work for someone full-time. They pay you a salary. They spend some more money on providing your safety net, whether it's income stability or paid vacations or health insurance, some other benefits. But once you move away from being a full-time employee to being a small business owner through a platform, a comparable funding model for the safety net doesn't yet exist. That doesn't mean that the model of micro entrepreneurship is flawed. It just means that it hasn't

been around for long. So we haven't spent the last few decades creating the funding model. I think the answer is going to come from some partnership in the short term between the individual, the government, and some third-party institution. I don't see the U.S. at least, as moving towards a model where the government is going to provide the entire social safety net. This may work in some countries in Europe, like Finland and Sweden, where the population is small and the tax rates are high, and there's a history of a government-provided safety net. But in the U.S., in a similar way to how we created 401K plans as a response to companies not paying pensions, in the 50s, you worked for a company, you retired, they give you a pension, that funding model stopped working. And so we created the partnership model where the individual contributes, the company matches, and the government gives you a tax break. And so we need to create similar funding models for other slices of the social safety net.

and I actually am pretty optimistic about the fact that we can create them because every company today that employs people full time is also sort of like an insurance company. I think that's the crux of the issue and how do you move from that to this world where you may have a lot more gig economy workers than captive workers in a company for 20 years. How do you then solve for that? It just means that we've got to move the role of the insurance provider in some sense away from the company of the 20th century. Now, we've got to create a way in which that insurance comes from somewhere else. But we've got like a pool of millions of providers to sort of diversify this risk over. So I actually think that where we end up eventually will be far more efficient

than each company individually stabilizing income and paying for vacation for their full time employees. I always make the argument on this podcast as well that the third-party ecosystem for those types of services just hasn't grown up yet because we're still in the early days and we have yet to see what's going to come out. I'm confident that the pace at which we make progress in creating this new social safety net will be far more rapid over the next 20 years than it was like 100 years ago. Just a quick question then, what does this mean for regulation and the government's role in this? What you're really talking about, Arun, is a shift to the new future of work. What do you see as the key challenges of that shift? Well, let me start with some of the

benefits of that shift because, you know, we can tie what's happening here to offshoring, which dominated the conversation about the future of work about a decade ago, and automation, which is dominating the conversation about the future of work today. The conversation is often dominated by work going to other countries and by work being taken over by robots. The point I'm trying to make here is that there's a contemporaneous change in how we organize work, the extent to which work is organized through marketplaces, the extent to which we're becoming generalists, and the immediacy with which you can tap into resources and labor, that's equally important for the future of work. I don't think we'd contest that. The question for me is, if we accept as a

given that this might be the future of work and that it changes the nature of the firm, the topic I love talking about this podcast. How do we answer the questions to people who are going to be completely affected by this? Well, you know, as we make this transition from a workforce that is inside companies to one that is sort of connected to these new firm market hybrids, these platforms that are somewhere in between a firm and a market. That's an interesting phrase for market hybrids. It's a natural next step. We had markets in the 18th century. We had organizations in the 19th and 20th, and now we've got this interesting in between. So there's the social scene. safety net challenge that we've already talked about in some detail. I think that there's a parallel

conversation about decentralizing the ownership of the platforms themselves. There's a lot of excitement in certain circles about the potential from provider-owned platforms or platform cooperatives. Most companies in the United States are organized as shareholder cooperation. A cooperative says, well, there is shared ownership among the people who are providers or who are sort of doing the work. And so a worker cooperative would be like SunKist. Every farmer is a part owner of a cooperative, and they all share in the ownership of the enterprise itself. There's a lot of excitement today about the potential for creating new shared ownership models for platforms. Some people label them platform cooperatives.

I'm cautiously optimistic about their potential in certain spheres. To me, the shareholder cooperation is still a good model that's got plenty of life in it. The challenge that gives me the most concern is something that Omalik a few years ago labeled Deda Darwinism. It raises the specter that as we become providers through platforms, that rating that you have through a platform and that portfolio of work that your platform provision represents will increasingly become what determines whether or not you get access to future opportunities. The ratings are incredibly important component of the sharing economy,

and you made this very argument to me four years ago, that it's a way that you know that you can trust and a peer-to-peer way. It's a way that you can create a reputation, build that sort of currency. That's part of it for sure. But there's also the fact that this reputation is created in part by, other people perceiving how good you were. And so if you happen to have a bad day, that could curb your access to future driving jobs. Or if there are people who decide that they just don't like you for some reason, I mean, there are so many biases that human beings have. Exactly.

You happen to belong to a particular category where people are biased against you. Your ratings are going to suffer as a consequence. And so that's something that we have to think about carefully. How do we design our algorithms in a way that corrects for any bias that might be inherent in these reputation systems so that you don't create a new division of access between one category of people and another? In a lot of ways, it's no different than what happens in real life, institutions where you have probably a far, far worse system. You're so subject in a lot of companies to the whims of one person's review and it could make or break you in certain opportunities. There's a lot of interpersonal politics that can come into play. At least in this case, there's some instrumentation, there's some systematic approach, there's some way of getting multiple data points.

Yeah, there's really a lot of opportunity here because we're well aware of the biases that exist in traditional organizational evaluation, and we've got laws that are in place. Now, we need to bring that thinking into a world in which your reputation is your gateway to access. So what are some of the solutions that you? see to the data darbinism? I mean, there are two solutions, right? One is you can either remove bias from human society. Impossible. Yes. The other solution is to train your algorithms, to recognize and correct it. And in some ways, if an algorithm is monitoring the ratings that might represent a vast improvement over human judgment that happens within an organization,

but we've got to make sure that the platforms that are running these reputation systems are consciously aware of it, maybe are even required to be aware of it in the same way that companies are required to comply with anti-discrimination laws, and that they program their algorithms to look for, detect, and correct this kind of bias. I don't like it when people treat algorithms as this, you know, Uber-A-Lis solution to everything, but what is inherently interesting in this is this idea that whereas in human life, the very things that are your limitations are also your advantages, but they actually are often in conflict, at least in the algorithmic world, you could turn the problem on its head and turn it into a solution.

So one last question, Arun, then, to come full circle to where we started, not on this podcast, but four years ago, with the regulation side of things. What have you seen change in that four-year period in terms of where the government is going with regulating the sharing economy? I want to know what you've been seeing from the front lines. What seems to be happening is that regulation is actually growing, except the party that is conducting the regulation is largely non-governmental. Oh, so what do you mean by that?

you know, 10 years ago with New York City taxis, there was a bunch of regulations and the Taxi and Limousine Commission was setting those regulations, was enforcing them, was doing the inspections, was sort of screening the drivers. Now, with Lyft and Uber, you've actually got a greater amount of regulation because there are so many more drivers. There's a whole host of guidelines that they have to follow. There are rules that they have to follow. But a lot of the regulatory responsibility for enforcement has been delegated to the platforms themselves. So there's more regulation going on. It's just that a lot of it has been moved to a different stakeholder.

It's not the government doing it directly, but it's the government playing a different role of like maybe setting some of the regulations, providing advice on them. And then some other party in society, which happens to be the transportation network company, is actually enforcing the regulations. And do you think that's the direction that it should continue in? do you see that evolving over time? Well, I think it's actually going to evolve to other stakeholders and not just the platforms also being part of the regulatory solution.

For example, homeowners associations may become the entity that decides a building's policy towards Airbnb. That's another example of a party other than the government taking on some of that regulatory responsibility. I think the most exciting potential comes from looking where the data to solve a problem is, and then delegating regulatory responsibility to the party that holds the data. That's really interesting, because data is such a key part of this. There's a lot of excitement, and there has been for the last decade, about open data,

which is sort of an idea of going in the opposite direction, where platforms or other entities hand over data to the government for regulatory reasons. What I'm suggesting instead is that let's hand over regulatory responsibility to the party that has the data. And so instead of telling hosts to register with the city and then the city collecting taxes from them, let's just tell Airbnb, listen, you have the data, you figure out who owes what, you collect it, and you remit it to the government, and we'll maybe subject you to an audit. Or instead of telling Uber and Lyft, give us your data so we can figure out if there's any sort of, you know, ethnicity-based discrimination that your drivers are

practicing. We tell Uber and Lyft, listen, here are the laws. We want you to invent new machine learning-based ways of detecting and correcting this and give us some sort of compliance. If you think about what's happened with credit card fraud detection, the credit card companies in some sense have been delegated the responsibility of detecting fraud. The science has advanced so dramatically over the last 20 years. Imagine what would have happened if the government had instead said, listen credit card companies, give me all your data. And we'll detect the fraud. I think that the potential for creating new ways of enforcing existing laws and new solutions

to problems ranging from discrimination to safety screening to a whole host of other problems is the greatest when instead of saying, give me your data, we say, here's the responsibility. You do the regulation. Well, the incentives are more aligned because everyone benefits. Yeah, and if the incentives aren't perfectly aligned, if you worry that perhaps Uber might not take safety as seriously as society wants to take safety, there are quick fixes for that. It doesn't mean that you take back all of the responsibility. You just align the incentives a little. I'm imagining an example like discrimination at local levels, but if you have a widespreading, you know, regulation that this is how you're going to comply with it and you have to do this, then everybody has to adhere to that. And that's one way of resolving the tension for those kinds of cases. In some sense, if you think about the future of regulation, we've come full circle. We started out by talking about how the government doesn't need to regulate the sharing economy,

which was the headline, which sort of captured the idea of that article. But you might modify it to say, well, the government doesn't need to regulate the sharing economy, the way it regulated the industrial economy, because there's going to be a whole host of other stakeholders who are participating in the regulation. That's exactly the direction that makes sense, given the evolution of the future of work, the firm, this ecosystem, and the way people work. Well, thank you, Arun. People should just read your book because it's a wonderful output of so much research and thoughtfulness about this topic. I don't think there's actually anything else like it. It's great to hear, especially from you.

Oh, welcome, and thanks for joining the I-6-N-Zy podcast.