Podcast appearances and mentions of Hal Varian

Beim Kampf gegen den Klimawandel taucht immer wieder ein Begriff auf: Externalisierung. Externe Effekte, zum Beispiel Umweltverschmutzung, entstehen, wenn wirtschaftliche Aktivitäten Dritte beeinflussen, ohne dass eine Marktbeziehung zu diesen besteht. Ökonomen wie Hal Varian glauben deshalb, das Problem müsse durch die Einführung eines Marktes behoben werden. Das ist die theoretische Grundlage der CO2-Bepreisung. Übersehen wird dabei jedoch: Nicht jede Situation benötigt einen Markt zur Lösung; oft reichen soziale Normen oder gesetzliche Vorgaben aus. Außerdem mag eine CO2-Steuer zur Internalisierung externer Effekte zwar theoretisch sinnvoll sein. Jedoch ist sie in der Praxis schwer umsetzbar und trifft durch die soziale Ungleichheit besonders die ärmeren Schichten. Wer Geld hat, kann sich einen schlanken Fuß machen und weiterhin die Umwelt verpesten. Wer den Preis nicht entrichten kann, soll verzichten. Mehr zu den Paradoxien der Externalisierung von Ole Nymoen und Wolfgang M. Schmitt in der neuen Folge von „Wohlstand für Alle“! WERBUNG: Alle Informationen zum Theorie-Podcast "tl;dr" der Rosa-Luxemburg-Stiftung findet ihr unter: https://rls-theoriepodcast.podigee.io/ Wolfgangs Literaturhinweise: Die Geschichte mit dem Zahnlabor stammt nicht von Passig, sondern von Anne Weber: "Gold im Mund". Suhrkamp. Javíer Marias: Mein Herz so weiß. Fischer. Termine: Die Veranstaltung mit Dietmar Dath und Wolfgang ist ausverkauft. Am 2.11. ist Wolfgang in Heidelberg zu Gast: https://dropoutcinema.org/politsalon/ Am 5.11. hält Wolfgang in Düsseldorf einen Vortrag über Ideologiekritik: https://www.instagram.com/p/DBs_hfgtljh/ Unser Kinderbuch namens "Die kleinen Holzdiebe" ist nun erschienen! Alle Informationen findet ihr unter: https://www.suhrkamp.de/buch/die-kleinen-holzdiebe-und-das-raetsel-des-juggernaut-t-9783458644774 Unsere Zusatzinhalte könnt ihr bei Steady und Patreon hören. Vielen Dank! Patreon: https://www.patreon.com/oleundwolfgang Steady: https://steadyhq.com/de/oleundwolfgang/about Ihr könnt uns unterstützen - herzlichen Dank! Paypal: https://www.paypal.me/oleundwolfgang Konto: Wolfgang M. Schmitt, Ole Nymoen Betreff: Wohlstand fuer Alle IBAN: DE67 5745 0120 0130 7996 12 BIC: MALADE51NWD Social Media: Instagram: Unser gemeinsamer Kanal: https://www.instagram.com/oleundwolfgang/ Ole: https://www.instagram.com/ole.nymoen/ Wolfgang: https://www.instagram.com/wolfgangmschmitt/ TikTok: https://www.tiktok.com/@oleundwolfgang Twitter: Unser gemeinsamer Kanal: https://twitter.com/OleUndWolfgang Ole: twitter.com/nymoen_ole Wolfgang: twitter.com/SchmittJunior Die gesamte WfA-Literaturliste: https://wohlstand-fuer-alle.netlify.app

While AI doomers proselytize their catastrophic message, many politicians are recognizing that the loss of America's competitive edge poses a much more real threat than the supposed “existential risk” of AI. Today on Faster, Please!—The Podcast, I talk with Adam Thierer about the current state of the AI policy landscape and the accompanying fierce regulatory debate.Thierer is a senior fellow at the R Street Institute, where he promotes greater freedom for innovation and entrepreneurship. Prior to R Street, he worked as a senior fellow at the Mercatus Center at George Mason University, president of the Progress and Freedom Foundation, and at the Adam Smith Institute, Heritage Foundation, and Cato Institute.In This Episode* A changing approach (1:09)* The global AI race (7:26)* The political economy of AI (10:24)* Regulatory risk (16:10)* AI policy under Trump (22:29)Below is a lightly edited transcript of our conversationA changing approach (1:09)Pethokoukis: Let's start out with just trying to figure out the state of play when it comes to AI regulation. Now I remember we had people calling for the AI Pause, and then we had a Biden executive order. They're passing some sort of act in Europe on AI, and now recently a senate working group in AI put out a list of guidelines or recommendations on AI. Given where we started, which was “shut it down,” to where we're at now, has that path been what you might've expected, given where we were when we were at full panic?Thierer: No, I think we've moved into a better place, I think. Let's look back just one year ago this week: In the Senate Judiciary Committee, there was a hearing where Sam Altman of OpenAI testified along with Gary Marcus, who's a well-known AI worrywart, and the lawmakers were falling all over themselves to praise Sam and Gary for basically calling for a variety of really extreme forms of AI regulation and controls, including not just national but international regulatory bodies, new general purpose licensing systems for AI, a variety of different types of liability schemes, transparency mandates, disclosure as so-called “AI nutritional labels,” I could go on down the list of all the types of regulations that were being proposed that day. And of course this followed, as you said, Jim, a call for an AI Pause, without any details about exactly how that would work, but it got a lot of signatories, including people like Elon Musk, which is very strange considering he was at the same time deploying one of the biggest AI systems in history. But enough about Elon.The bottom line is that those were dark days, and I think the tenor of the debate and the proposals on the table today, one year after that hearing, have improved significantly. That's the good news. The bad news is that there's still a lot of problematic regulatory proposals percolating throughout the United States. As of this morning, as we're taping the show, we are looking at 738 different AI bills pending in the United States according to multistate.ai, an AI tracking service. One hundred and—I think—eleven of those are federal bills. The vast majority of it is state. But that count does not include all of the municipal regulatory proposals that are pending for AI systems, including some that have already passed in cities like New York City that already has a very important AI regulation governing algorithmic hiring practices. So the bottom line, Jim, is it's the best of times, it's the worst of times. Things have both gotten better and worse.Well—just because the most recent thing that happened—I know with this the senate working group, and they were having all kinds of technologists and economists come in and testify. So that report, is it really calling for anything specific to happen? What's in there other than just kicking it back to all the committees? If you just read that report, what does it want to happen?A crucial thing about this report, and let's be clear what this is, because it was an important report because senator Senate Majority Leader Chuck Schumer was in charge of this, along with a bipartisan group of other major senators, and this started the idea of, so-called “AI insight forums” last year, and it seemed to be pulling some authority away from committees and taking it to the highest levels of the Senate to say, “Hey, we're going to dictate AI policy and we're really scared.” And so that did not look good. I think in the process, just politically speaking—That, in itself, is a good example. That really represents the level of concern that was going around, that we need to do something different and special to address this existential risk.And this was the leader of the Senate doing it and taking away power, in theory, from his committee members—which did not go over well with said committee members, I should add. And so a whole bunch of hearings took place, but they were not really formal hearings, they were just these AI insight forum working groups where a lot of people sat around and said the same things they always say on a daily basis, and positive and negatives of AI. And the bottom line is, just last week, a report came out from this AI senate bipartisan AI working group that was important because, again, it did not adopt the recommendations that were on the table a year ago when the process got started last June. It did not have overarching general-purpose licensing of artificial intelligence, no new call for a brand new Federal Computer Commission for America, no sweeping calls for liability schemes like some senators want, or other sorts of mandates.Instead, it recommended a variety of more generic policy reforms and then kicked a lot of the authority back to those committee members to say, “You fill out the details, for better for worse.” And it also included a lot of spending. One thing that seemingly everybody agrees on in this debate is that, well, the government should spend a lot more money and so another $30 billion was on the table of sort of high-tech pork for AI-related stuff, but it really did signal a pretty important shift in approach, enough that it agitated the groups on the more pro-regulatory side of this debate who said, “Oh, this isn't enough! We were expecting Schumer to go for broke and swing for the fences with really aggressive regulation, and he's really let us down!” To which I can only say, “Well, thank God he did,” because we're in a better place right now because we're taking a more wait-and-see approach on at least some of these issues.A big, big part of the change in this narrative is an acknowledgement of what I like to call the realpolitik of AI policy and specifically the realpolitik of geopoliticsThe global AI race (7:26)I'm going to ask you in a minute what stuff in those recommendations worries you, but before I do, what happened? How did we get from where we were a year ago to where we've landed today?A big, big part of the change in this narrative is an acknowledgement of what I like to call the realpolitik of AI policy and specifically the realpolitik of geopolitics. We face major adversaries, but specifically China, who has said in documents that the CCP [Chinese Communist Party] has published that they want to be the global leader in algorithmic and computational technologies by 2030, and they're spending a lot of money putting a lot of state resources into it. Now, I don't necessarily believe that means they're going to automatically win, of course, but they're taking it seriously. But it's not just China. We have seen in the past year massive state investments and important innovations take place across the globe.I'm always reminding people that people talk a big game about America's foundational models are large scale systems, including things like Meta's Llama, which was the biggest open source system in the world a year ago, and then two months after Meta launched Llama, their open source platform, the government of the UAE came out with Falcon 180B, an open source AI model that was two-and-a-half times larger than Facebook's model. That meant America's AI supremacy and open source foundational models lasted for two months. And that's not China, that's the government of the UAE, which has piled massive resources into being a global leader in computation. Meanwhile, China's launched their biggest super—I'm sorry, Russia's launched their biggest supercomputer system ever; you've got Europe applying a lot of resources into it, and so on and so forth. A lot of folks in the Senate have come to realize that problem is real: that if we shoot ourselves in the foot as a nation, they could race ahead and gain competitive advantage in geopolitical strategic advantages over the United States if it hobbles our technology base. I think that's the first fundamental thing that's changed.I think the other thing that changed, Jim, is just a little bit of existential-risk exhaustion. The rhetoric in this debate, as you've written about eloquently in your columns, has just been crazy. I mean, I've never really seen anything like it in all the years we've been covering technology and economic policy. You and I have both written, this is really an unprecedented level of hysteria. And I think, at some point, the Chicken-Littleism just got to be too much, and I think some saner minds prevailed and said, “Okay, well wait a minute. We don't really need to pause the entire history of computation to address these hypothetical worst-case scenarios. Maybe there's a better plan than that.” And so we're starting to pull back from the abyss, if you will, a little bit, and the adults are reentering the conversation—a little bit, at least. So I think those are the two things that really changed more, although there were other things, but those were two big ones.The political economy of AI (10:24)To what extent do you think we saw the retreat from the more apocalyptic thinking—how much that was due from what businesses were saying, venture capitalists, maybe other tech . . . ? What do you think were the key voices Congress started listening to a little bit more?That's a great question. The political economy of AI policy and tech policy is something that is terrifically interesting to me. There are so many players and voices involved in AI policy because AI is the most important general-purpose technology of our time, and as a widespread broad base—Do you have any doubt about that? (Let me cut you off.) Do you have any doubt about that?I don't. I think it's unambiguous, and we live in a world of “combinatorial innovation,” as Hal Varian calls it, where technologies build on top of the other, one after another, but the thing is they all lead to greater computational capacity, and therefore, algorithmic and machine learning systems come out of those—if we allow it. And the state of data science in this country has gotten to the point where it's so sophisticated because of our rich base of diverse types of digital technologies and computational technologies that finally we're going to break out of the endless cycle of AI booms and busts, and springs and winters, and we're going to have a summer. I think we're having it right now. And so that is going to come to affect every single segment and sector of our economy, including the government itself. I think industry has been very, very scrambled and sort of atomistic in their approach to AI policy, and some of them have been downright opportunistic, trying to throw each other's competitors under the busNow let me let you go return to the political economy, what I was asking you about, what were the voices, sorry, but I wanted to get that in there.Well, I think there are so many voices, I can't name them all today, obviously, but obviously we're going to start with one that's a quiet voice behind the scenes, but a huge one, which is, I think, the National Security community. I think clearly going back to our point about China and geopolitical security, I think a lot of people behind the scenes who care about these issues, including people in the Pentagon, I think they had conversations with certain members of Congress and said, “You know what? China exists. And if we're shooting ourselves in the foot, we begin this race for geopolitical strategic supremacy in an important new general-purpose technology arena, we're really hurting our underlying security as a nation. I think that that thinking is there. So that's an important voice.Secondly, I think industry has been very, very scrambled and sort of atomistic in their approach to AI policy, and some of them have been downright opportunistic, trying to throw each other's competitors under the bus, unfortunately, and that includes OpenAI trying to screw over other companies and technologies, which is dangerous, but the bottom line is: More and more of them are coming to realize, as they saw the actual details of regulation and thinking through the compliance costs, that “Hell no, we won't go, we're not going to do that. We need a better approach.” And it was always easier in the old days to respond to the existential risk route, like, “Oh yeah, sure, regulation is fine, we'll go along with it!” But then when you see the devilish details, you think twice and you realize, “This will completely undermine our competitive advantage in the space as a company or our investment or whatever else.” All you need to do is look at Exhibit A, which is Europe, and say, if you always run with worst-case scenario thinking and Chicken-Littleism is the basis of your technology policy, guess what? People respond to incentives and they flee.Hatred of big tech is like the one great bipartisan, unifying theme of this Congress, if anything. But at the end of the day, I think everyone is thankful that those companies are headquartered in the United States and not Beijing, Brussels, or anywhere else. It's interesting, the national security aspect, my little amateurish thought experiment would be, what would be our reaction, and what would be the reaction in Washington if, in November, 2022, instead of it being a company, an American company with a big investment from another American company having rolled out ChatGPT, what if it would've been Tencent, or Alibaba, or some other Chinese company that had rolled this out, something that's obviously a leap forward, and they had been ahead, even if they said, “Oh, we're two or three years ahead of America,” it would've been bigger than Sputnik, I think.People are probably tired of hearing about AI—hopefully not, I hope they'll also listen to this podcast—but that would all we would be talking about. We wouldn't be talking about job loss, and we wouldn't be talking about ‘The Terminator,' we'd be talking about the pure geopolitical terms that the US has suffered a massive, massive defeat here and who's to blame? What are we going to do? And anybody at that moment who would've said, “We need to launch cruise missile strikes on our own data centers” for fear. . . I mean! And I think you're right, the national security component, extremely important here.In fact, I stole your little line about “Sputnik moment,” Jim, when I testified in front of the House Oversight Committee last month and I said, “Look, it would've been a true ‘Sputnik moment,' and instead it's those other countries that are left having the Sputnik moment, right? They're wondering, ‘How is it that, once again, the United States has gotten out ahead on digital and computational-based technologies?'” But thank God we did! And as I pointed out in the committee room that day, there's a lot of people who have problems with technology companies in Congress today. Hatred of big tech is like the one great bipartisan, unifying theme of this Congress, if anything. But at the end of the day, I think everyone is thankful that those companies are headquartered in the United States and not Beijing, Brussels, or anywhere else. That's just a unifying theme. Everybody in the committee room that day nodded their head, “Yes, yes, absolutely. We still hate them, but we're thankful that they're here.” And that then extends to AI: Can the next generation of companies that they want to bring to Congress and bash and pull money from for their elections, can they once again exist in the United States?Regulatory risk (16:10)So whether it's that working group report, or what else you see in Congress, what are a couple, three areas where you're concerned, where there still seems to be some sort of regulatory momentum?Let's divide it into a couple of chunks here. First of all, at the federal level, Congress is so damn dysfunctional that I'm not too worried that even if they have bad ideas, they're going to pursue them because they're just such a mess, they can't get any basic things done on things like baseline privacy legislation, or driverless car legislation, or even, hell, the budget and the border! They can't get basics done!I think it's a big positive that one, while they're engaging in dysfunction, the technology is evolving. And I hope, if it's as important as I think you and I think, more money will be invested, we'll see more use cases, it'll be obvious—the downsides of screwing up the regulation I think will be more obvious, and I think that's a tailwind for this technology.We're in violent agreement on that, Jim, and of course this goes by the name of “the pacing problem,” the idea that technology is outpacing law in many ways, and one man's pacing problem is another man's pacing benefit, in my opinion. There's a chance for technology to prove itself a little bit. That being said, we don't live in a legislative or regulatory vacuum. We already have in the United States 439 government agencies and sub-agencies, 2.2 million employees just at the federal level. So many agencies are active right now trying to get their paws on artificial intelligence, and some of them already have it. You look at the FDA [Food and Drug Administration], the FAA [Federal Aviation Administration], NHTSA [National Highway Traffic Safety Administration], I could go all through the alphabet soup of regulatory agencies that are already trying to regulate or overregulating AI right now.Then you have the Biden administration, who's gone out and done a lot of cheerleading in favor of more aggressive unilateral regulation, regardless of what Congress says and basically says, “To hell with all that stuff about Chevron Doctrine and major questions, we're just going to go do it! We're at least going to jawbone a lot and try to threaten regulation, and we're going to do it in the name of ‘algorithmic fairness,'” which is what their 100-plus-page executive order and their AI Bill of Rights says they're all about, as opposed to talking about AI opportunity and benefits—it's all misery. And it's like, “Look at how AI is just a massive tool of discrimination and bias, and we have to do something about it preemptively through a precautionary principle approach.” So if Congress isn't going to act, unfortunately the Biden administration already is and nobody's stopping them.But that's not even the biggest problem. The biggest problem, going back to the point that there are 730-plus bills pending in the US right now, the vast majority of them are state and local. And just last Friday, governor Jared Polis of Colorado signed into law the first major AI regulatory measure in Colorado, and there's a bigger and badder bill pending right now in California, there's 80 different bills pending in New York alone, and any half of them would be a disaster.I could go on down the list of troubling state patchwork problems that are going to develop for AI and ML [Machine Learning] systems, but the bottom line is this: This would be a complete and utter reversal of the winning formula that Congress and the Clinton administration gave us in the 1990s, which was a national—a global framework for global electronic commerce. It was very intentionally saying, “We're going to break with the Analog Era disaster, we're going to have a national framework that's pro-freedom to innovate, and we're going to make sure that these meddlesome barriers do not develop to online speech and commerce.” And yet, here with AI, we are witnessing a reversal of that. States are in the lead, and again, like I said, localities too, and Congress is sitting there and is the dysfunctional soup that it is saying, “Oh, maybe we should do something to spend a little bit more money to promote AI.” Well, we can spend all the money we want, but we can end up like Europe who spends tons of money on techno-industrial policies and gets nothing for it because they can't get their innovation culture right, because they're regulating the living hell out of digital technology.So you want Congress to take this away from the states?I do. I do, but it's really, really hard. I think what we need to do is follow the model that we had in the Telecommunications Act of 1996 and the Internet Tax Freedom Act of 1998. We've also had moratoriums, not only through the Internet Tax Freedom Act, but through the Commercial Space Amendments having to do with space commercial travel and other bills. Congress has handled the question of preemption before and put moratoria in place to say, “Let's have a learning period before we go do stupid things on a new technology sector that is fast moving and hard to understand.” I think that would be a reasonable response, but again, I have to go back to what we just talked about, Jim, which is that there's no chance of us probably getting it. There's no appetite in it. Not any of the 111 bills pending in Congress right now says a damn thing about state and local regulation of technology!Is the thrust of those federal bills, is it the kinds of stuff that you're generally worried about?Mostly, but not entirely. Some of it is narrower. A lot of these bills are like, “Let's take a look at AI and. . . fill in the blank: elections, AI and jobs, AI and whatever.” And some of them, on the merits, not terrible, others, I have concerns, but it's certainly better that we take a targeted sectoral approach to AI policy and regulation than having the broad-based, general-purpose stuff. Now, there are broad-based, general-purpose measures, and here's what they do, Jim: They basically say, “Look, instead of having a whole cloth new regulatory approach, let's build on the existing types of approaches being utilized in the Department of Commerce, namely through our NIST [National Institute of Standards and Technology], and NTIA [National Telecommunications and Information Administration] sub-agencies there. NIST is the National Standards Body, and basically they develop best practices through something called the AI Risk Management Framework for artificial intelligence development—and they're good! It's multi-stakeholder, it's bottom up, it's driven by the same principles that motivated the Clinton administration to do multi-stakeholder processes for the internet. Good model. It is non-regulatory, however. It is a consensus-based, multi-stakeholder, voluntary approach to developing consensus-based standards for best practices regarding various types of algorithmic services. These bills in Congress—and there's at least five of them that I count, that I've written about recently—say, “Let's take that existing infrastructure and give it some enforcement teeth. Let's basically say, ‘This policy infrastructure will be converted into a quasi-regulatory system,'” and there begins the dangerous path towards backdoor regulation of artificial intelligence in this country, and I think that's the most likely model we'll get. Like I said, five models, legislative models in the Senate alone that would do that to varying degrees.AI policy under Trump (22:29)Do you have any feel for what a Trump administration would want to do on this?I do, because a month before the Trump administration left office, they issued a report through the Office of Management and Budget (OMB), and it basically laid out for agencies a set of principles for how it should evaluate artificial intelligence systems, both that are used by the government or that they regulate in the private sector, and it was an excellent set of principles. It was a restatement of the importance of policy, forbearance and humility. It was a restatement of a belief in cost-benefit analysis and identifying not only existing regulatory capacity to address these problems, but also non-regulatory mechanisms or best practices or standards that could address some of these things. It was a really good memo. I praised it in a piece that I wrote just before the Trump administration left. Now, of course, the Trump administration may change.Yes, and also, the technology has changed. I mean, that was 2020 and a lot has happened, and I don't know where. . . . I'm not sure where all the Republicans are. I think some people get it. . .I think the problem, Jim, is that, for the Republican Party, and Trumpian conservatives, in particular, they face a time of choosing. And what I mean by this is that they have spent the last four to six years—and Trump egged this on—engaging in nonstop quote-unquote “big tech bashing” and making technology companies in the media out to be, as Trumps calls them, “the enemy of the American people.” And so many hearings now are just parading tech executives and others up there to be beaten with a stick in front of the public, and this is the new thing. And then there's just a flood of bills that would regulate traditional digital technologies, repeal things like Section 230, which is liability protection for the tech sector, and so on, child safety regulations.Meanwhile, that same Republican Party and Mr. Trump go around hating on Joe Biden in China. If it's one thing they can't stand more than big tech, it's Joe and China! And so, in a sense, they've got to choose, because their own policy proposals on technology could essentially kneecap America's technology base in a way that would open up the door to whether it's what they fear in the “woke DEI policies” of Biden or the CCP's preferred policy agenda for controlling computation in the world today. Choose two, you don't get all three. And I think this is going to be an interesting thing to watch if Mr. Trump comes back into office, do they pick up where that OMB memo left off, or do they go right back to beating that “We've got to kill big tech by any means necessary in a seek-and-destroy mission, to hell with the consequences.” And I don't know yet.Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

This is the Google on Trial podcast.Here is an update on the United States v. Google trial for September 20-22, 2023, The second week of testimony began on September 19th with Kent Walker, the company's senior vice president of global affairs, testifying that Google does not engage in anticompetitive behavior and that the company's dominance in the online advertising market is the result of "innovation and merit."On September 20th, Google called economists Hal Varian and Paul Milgrom to testify on its behalf. Varian and Milgrom argued that Google's dominance in the online advertising market is beneficial to consumers because it leads to lower prices and higher quality products.On September 21st, the government called economists Carl Shapiro and Fiona Scott Morton to testify on its behalf. Shapiro and Morton argued that Google's dominance in the online advertising market is harmful to consumers because it leads to higher prices and lower quality products.On September 22nd, Google called Sundar Pichai, the company's CEO, to testify on its behalf. Pichai testified that Google's dominance in the online advertising market is the result of "innovation and merit," and that the company does not engage in anticompetitive behavior.The trial is expected to last for several weeks. It is unclear when the jury will begin deliberations.The economists who testified on behalf of Google and the government presented conflicting views on the impact of Google's dominance on the online advertising market. Google's economists argued that Google's dominance is beneficial to consumers, while the government's economists argued that it is harmful.Pichai's testimony was closely watched by both sides, as he is the most senior Google executive to testify in the trial. Pichai's testimony was generally seen as favorable to Google, but the government's lawyers were able to cross-examine him on a number of points.Thanks for listening to the Google on Trial podcast. Please make sure you subscribe and never miss an update.The trial is still in its early stages, and it is unclear how the jury will rule. However, the testimony that has been presented so far suggests that the government has a strong case against Google.

Chris Nosko is a PhD economist. He did his PhD in economics at Harvard in the mid 2010s before going to Chicago Booth take a job as an assistant professor. But for a year prior to taking that job, between Harvard and Chicago, he did a postdoc fellowship at eBay where he, Thomas Blake and Steve Tadelis met and worked together on a project involved a serendipitous event at the company in which eBay quit paying for branded key words (e.g., “eBay Volvo decals”, “eBay typewriters”) on some but not all search engine auctions. They asked for the data on traffic to the site before and after eBay quit paying for branded keywords for all search engines (both those they kept paying and those they didn't), ran a simple event study diff-in-diff and found evidence that search engine marketing at eBay was perhaps not causing increased traffic to the site. They convinced management to field a large RCT which confirmed their diff-in-diff results, and that study was published in Econometrica. Not a shabby way to start a career as an economist. For many of us, a PhD in economics from Harvard, a successful partnership with eBay resulting in a study destined for a Top 5 and a tenure track job at Chicago Booth meant staying at Booth and having a career as an academic. No one outrightly says that the only meaningful life you can have as an economist is to be an academic, as it's vulgar, opinionated and obviously false to talk that way about how someone else should live their life, but the norms are pretty powerful nonetheless. Well, starting around the time that Chris got his job at Booth, tech began experiencing a surge in hiring of PhD economists, largely driven by Amazon's nearly insatiable appetite for them. Talking with people at Amazon, I have learned that behind this push was Pat Bajari, and behind Pat Bajari was Jeff Bezos who had long believed economics, and economists more specifically, had unique value. As Susan Athey said to me, though, in an interview earlier, Bajari though had to do pull a rabbit out of a hat. Whereas the first wave of economists to tech — people like Hal Varian, Susan Athey, Preston McAfee — had largely been micro theorists helping craft the foundations of a business model through auctions and advertising that would support search engines, arguably the core arteries of the internet itself — Bajari would have the task of bringing in young people, fresh out of grad school, and in Athey's words, make them productive. And one of the people Bajari would ultimately tap do that was Chris Nosko, an assistant professor at Chicago Booth and someone trained in structural industrial organization, one of the economics' more interesting experiments of fusing deep microeconomic theory with econometric estimation. Scott's Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Nosko was a Ariel Pakes student at Harvard and was well versed in so many different parts of economics and modern technology that it almost seems predestined that he would ultimately leave Chicago Booth permanently and go to Amazon when Bajari finally convinced him to, but that's all selection on the dependent variable reasoning. When we look back in time at decisions we made, our mind tends to forget that there was a moment when we could've gone left instead of right. The same with Chris — there was a decision that had to be made to leave a career as an academic. The decision materialized into what it materialized, but to pretend it was easy, or that it didn't have risk, or that Chris didn't try to manage that risk in some ways is really unfair to our earlier selves or even our future selves who are in situations facing, not probabilistic risk but more like Knightian uncertainty in which no one truly has a clue what possibly could happen. But Chris did leave. Sort of. He took “a leave of absence” from Booth in 2015 and took a job at Amazon, then permanently left Booth in 2016. He spent four years at Amazon before leaving for Uber, one of the more impressive firms to ever exist for creating an actual open marketplace solving two sided matching problems through algorithms and prices. Algorithms, prices and rules — three ways, no doubt there are others, in which modern economies coordinate productive activity. Is it really so surprising that economics might be valued by tech firms given the complex coordination they try to solve using all three?Thank you for reading Scott's Substack. This post is public so feel free to share it.Chris has been at Uber for four years. He is now Vice President and Head of Science and Analytics for Uber Product there.  Within tech, economists sort into tons of different jobs with titles that to an academic don't make a ton of sense — just like so much of what academics' lives takes place within administrative units that make little sense to anyone else. If Chris isn't the chief economist, though, at Uber, I figure he's probably up there. And he's my guest this week on The Mixtape with Scott as part of my longer, unfolding series I call “Economists in tech”. Our conversation covered a lot of ground. We talked about growing up in rural Oregon, falling into programming early on and working a few years between high school and college during the early wave tech boom of the late 1990s and early 2000s as a programmer. It wasn't exactly what he would do later, as that was more web design and less machine learning and statistics, but the aptitude of programming is very portable and his deep knowledge of tech sectors was anyway established or at least re-invested in while there. We talked about his love for his liberal arts education at the University of Chicago where he did his undergraduate degree, and his broad navigation of economics as a field and a career.  All in all, it was a fun opportunity to talk to Chris, to learn more about his own path, about the world out there outside of academia, what economists do in tech, and how all of these things fit together for both economics but maybe more importantly just for Chris himself. I think a lot of people are going to find Chris's story very interesting and personally intriguing as they may see him in themselves. You can read some of Chris's work here. Thanks again for tuning in! I hope you enjoy this week's interview as much as I did! If you are enjoying these, please consider supporting me by sharing the podcast and/or becoming a paying subscriber!Scott's Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Substack at causalinf.substack.com/subscribe

Chris Nosko is a PhD economist. He did his PhD in economics at Harvard in the mid 2010s before going to Chicago Booth take a job as an assistant professor. But for a year prior to taking that job, between Harvard and Chicago, he did a postdoc fellowship at eBay where he, Thomas Blake and Steve Tadelis met and worked together on a project involved a serendipitous event at the company in which eBay quit paying for branded key words (e.g., “eBay Volvo decals”, “eBay typewriters”) on some but not all search engine auctions. They asked for the data on traffic to the site before and after eBay quit paying for branded keywords for all search engines (both those they kept paying and those they didn't), ran a simple event study diff-in-diff and found evidence that search engine marketing at eBay was perhaps not causing increased traffic to the site. They convinced management to field a large RCT which confirmed their diff-in-diff results, and that study was published in Econometrica. Not a shabby way to start a career as an economist. For many of us, a PhD in economics from Harvard, a successful partnership with eBay resulting in a study destined for a Top 5 and a tenure track job at Chicago Booth meant staying at Booth and having a career as an academic. No one outrightly says that the only meaningful life you can have as an economist is to be an academic, as it's vulgar, opinionated and obviously false to talk that way about how someone else should live their life, but the norms are pretty powerful nonetheless. Well, starting around the time that Chris got his job at Booth, tech began experiencing a surge in hiring of PhD economists, largely driven by Amazon's nearly insatiable appetite for them. Talking with people at Amazon, I have learned that behind this push was Pat Bajari, and behind Pat Bajari was Jeff Bezos who had long believed economics, and economists more specifically, had unique value. As Susan Athey said to me, though, in an interview earlier, Bajari though had to do pull a rabbit out of a hat. Whereas the first wave of economists to tech — people like Hal Varian, Susan Athey, Preston McAfee — had largely been micro theorists helping craft the foundations of a business model through auctions and advertising that would support search engines, arguably the core arteries of the internet itself — Bajari would have the task of bringing in young people, fresh out of grad school, and in Athey's words, make them productive. And one of the people Bajari would ultimately tap do that was Chris Nosko, an assistant professor at Chicago Booth and someone trained in structural industrial organization, one of the economics' more interesting experiments of fusing deep microeconomic theory with econometric estimation. Scott's Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Nosko was a Ariel Pakes student at Harvard and was well versed in so many different parts of economics and modern technology that it almost seems predestined that he would ultimately leave Chicago Booth permanently and go to Amazon when Bajari finally convinced him to, but that's all selection on the dependent variable reasoning. When we look back in time at decisions we made, our mind tends to forget that there was a moment when we could've gone left instead of right. The same with Chris — there was a decision that had to be made to leave a career as an academic. The decision materialized into what it materialized, but to pretend it was easy, or that it didn't have risk, or that Chris didn't try to manage that risk in some ways is really unfair to our earlier selves or even our future selves who are in situations facing, not probabilistic risk but more like Knightian uncertainty in which no one truly has a clue what possibly could happen. But Chris did leave. Sort of. He took “a leave of absence” from Booth in 2015 and took a job at Amazon, then permanently left Booth in 2016. He spent four years at Amazon before leaving for Uber, one of the more impressive firms to ever exist for creating an actual open marketplace solving two sided matching problems through algorithms and prices. Algorithms, prices and rules — three ways, no doubt there are others, in which modern economies coordinate productive activity. Is it really so surprising that economics might be valued by tech firms given the complex coordination they try to solve using all three?Thank you for reading Scott's Substack. This post is public so feel free to share it.Chris has been at Uber for four years. He is now Vice President and Head of Science and Analytics for Uber Product there.  Within tech, economists sort into tons of different jobs with titles that to an academic don't make a ton of sense — just like so much of what academics' lives takes place within administrative units that make little sense to anyone else. If Chris isn't the chief economist, though, at Uber, I figure he's probably up there. And he's my guest this week on The Mixtape with Scott as part of my longer, unfolding series I call “Economists in tech”. Our conversation covered a lot of ground. We talked about growing up in rural Oregon, falling into programming early on and working a few years between high school and college during the early wave tech boom of the late 1990s and early 2000s as a programmer. It wasn't exactly what he would do later, as that was more web design and less machine learning and statistics, but the aptitude of programming is very portable and his deep knowledge of tech sectors was anyway established or at least re-invested in while there. We talked about his love for his liberal arts education at the University of Chicago where he did his undergraduate degree, and his broad navigation of economics as a field and a career.  All in all, it was a fun opportunity to talk to Chris, to learn more about his own path, about the world out there outside of academia, what economists do in tech, and how all of these things fit together for both economics but maybe more importantly just for Chris himself. I think a lot of people are going to find Chris's story very interesting and personally intriguing as they may see him in themselves. You can read some of Chris's work here. Thanks again for tuning in! I hope you enjoy this week's interview as much as I did! If you are enjoying these, please consider supporting me by sharing the podcast and/or becoming a paying subscriber!Scott's Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Substack at causalinf.substack.com/subscribe

In this interview, I talk with the esteemed economist, Susan Athey, a professor of economics at Stanford University and a recently elected President of the American Economics Association. She was one of a handful of micro theorist pioneers, like Hal Varian to Google and Preston McAfee to Yahoo, who in the early 2000s traveled from academia to work for large technology firms to work on market design elements, such as the design of auctions, that would enhance the productivity of the firms themselves. Dr. Athey did this first as a consultant at Microsoft, then as its first chief economist, then later on the board of more than a half dozen firms. She has since returned to her alma mater, Stanford University, where among her many activities she established a lab on social impact, and has written countless influential articles drawing on the strengths of machine learning methods and approaches at the service of causal inference. Just as Dixit predicted that she would win the John Bates Clark award, I'll state the obvious that it will not be the last major Prize she wins. I hope you enjoy!

In this interview, I talk with the esteemed economist, Susan Athey, a professor of economics at Stanford University and a recently elected President of the American Economics Association. She was one of a handful of micro theorist pioneers, like Hal Varian to Google and Preston McAfee to Yahoo, who in the early 2000s traveled from academia to work for large technology firms to work on market design elements, such as the design of auctions, that would enhance the productivity of the firms themselves. Dr. Athey did this first as a consultant at Microsoft, then as its first chief economist, then later on the board of more than a half dozen firms. She has since returned to her alma mater, Stanford University, where among her many activities she established a lab on social impact, and has written countless influential articles drawing on the strengths of machine learning methods and approaches at the service of causal inference. Just as Dixit predicted that she would win the John Bates Clark award, I'll state the obvious that it will not be the last major Prize she wins. I hope you enjoy! Get full access to Scott's Substack at causalinf.substack.com/subscribe

https://astralcodexten.substack.com/p/mantic-monday-let-me-google-that Let Me Google That For You New from Google this month: Creating A Prediction Market On Google Cloud. Google announces that they've been running an internal prediction market for the past year, with “over 175,000 predictions from over 10,000 Google employees”. 1 Predictive analytics.jpg Most of it's classified because they're predicting stuff about Google's corporate secrets, but some friendly Googlers were at least willing to walk me through the article and clarify pieces I didn't understand. The market, called Gleangen, is actually the second prediction market Google's tried. The first, in 2007, was called Prophit - the team included occasional ACX commenter Patri Friedman, who's since moved into the charter city space. (source) Prophit wound down because the founders left and nobody really knew what to do with; you can read about some of their findings here. In 2020, with all the uncertainty around coronavirus, some Googlers decided to try again. Gleangen is the result. Unlike most prediction markets, anybody can create a question on Gleangen. This usually goes badly: most people are terrible at writing questions with objective resolutions. Google manages by having a dedicated team of moderators who go over everything and amend it when needed. The market pays out in play money and the right to be on a leaderboard. So far it's not doing much else. The Googlers I talked to saw no evidence that company executives were paying much attention to it when making decisions. Why not? Hal Varian, Google's chief economist, said in a Conversation with Tyler Cowen: COWEN: Why doesn't business use more prediction markets? They would seem to make sense, right? Bet on ideas. Aggregate information. We've all read Hayek. VARIAN: Right. And we had a prediction market [referring to Prophit in 2007]. I'll tell you the problem with it. The problem is, the things that we really wanted to get a probability assessment on were things that were so sensitive that we thought we would violate the SEC rules on insider knowledge because, if a small group of people knows about some acquisition or something like that, there is a secret among this small group.

Over the last decade, we have seen tremendous advances in big data, data science, artificial intelligence and machine learning. Every compnay wants to be a tech-first comapny now, and wants to “do data science". Companies can probably double their valuation by just adding a “.ai" to their names. Companies that actually use artificial intelligence and machine learning maybe have an even higher premium on their valuations. However, is Data Science worth the hype? Is AI going to take over the world? And why is data science being eaten by computer science? What happned to classical analytics, operations resarch and statistics? This week's guest is someone who did data science even before the phrase had b een invented. Amaresh Tripathy is SVP and Analytics Business Leader at Genpact. Till recently he was a Partner with PWC, leading the firm's Data & Analytics Consulting, and helped build a $500mm business. Previously, Amaresh founded and co-led the Information and Analytics Practice for Diamond Management & Technology Consultants, and also serves as Adjunct Professor of Data Science and Business Analytics at the University of North Carolina, Charlotte. Amaresh has helped Fortune 500 companies in multiple industries (healthcare, retail & consumer, communications) to help define and implement their analytics and AI strategies and institutionalize data enabled decision making. He has led organizations to help embed analytics in their front, middle and back office functions and manage the change process. Show Notes: 00:03:00: Definitions - data science, artificial intelligence, machine learning, etc. 00:04:15: The rise of computer science and machine learning 00:10:15: The probelm with Kaggle, and the “race for accuracy” 00:11:30: How to scale analytics without doing bad data analysis 00:18:00: How selling data science has changed over the last decade 00:23:00: The interaction between business and Data Science 00:26:30: “Creating bilinguals at scale” 00:30:30: Machine learning trying to eat data science 00:39:00: Comparing data science practices across countries Links: Thomas Davenport and DJ Patil on Data Science as the “sexiest job of the 21st century” (2012 article) Hal Varian on statistics as a “sexy job” Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". The podcast is hosted by Karthik Shashidhar. He is a blogger, newspaper columnist, book author and a former data and strategy consultant. Karthik currently heads Analytics and Business Intelligence for Delhivery, one of India's largest logistics companies. You can follow him on twitter at @karthiks, and read his blog at noenthuda.com/blog

Public policy may seem like a dull subject fit only for wonks, but it matters: our lives are deeply affected by what our governments do. Pranay Kotasthane joins Amit Varma in episode 233 of The Seen and the Unseen to chat about his intellectual journey, his private beach and why public policy can be so stimulating. He also answers racy questions from the Twitterverse. If you share Pranay's interest in public policy, you should check out Takshashila's Graduate Certificate in Public Policy (GCPP). Also check out: 1. Anticipating the Unintended -- Pranay Kotasthane's newsletter (with RSJ). 2. Puliyabaazi -- Pranay Kotasthane's podcast (with Saurabh Chandra). 3. Foreign Policy is a Big Deal -- Episode 170 of The Seen and the Unseen (w Pranay Kotasthane & Manoj Kewalramani). 4. Radically Networked Societies -- Episode 158 of The Seen and the Unseen (w Pranay Kotasthane). 5. Older episodes of The Seen and the Unseen w Pranay Kotasthane: 1, 2, 3, 4, 5, 6. 6. Raghu Sanjaylal Jaitley's Father's Scooter -- Episode 214 of The Seen and the Unseen (w Raghu Sanjaylal Jaitley). 7. ये लिबरल आख़िर है कौन? -- Episode 37 of Puliyabaazi (w Amit Varma). 8. Amit Varma's tweet thread soliciting questions for this episode. 9. Examples of Pranay Kotasthane's Mind Maps of books: 1, 2, 3. 10. Coggle. 11. The Lessons of History -- Will Durant. 12. Raj Comics. 13. The China Dude Is in the House -- Episode 231 of The Seen and the Unseen (w Manoj Kewalramani). 14. A Case For Societism -- Pranay Kotasthane. 15. Pranay Kotasthane's Manthan talk on societism. 16. The Indian Dream Podcast episode with Amit Varma. 17. 8 things to unlearn before learning public policy -- Pranay Kotasthane. 18. The Double 'Thank-You' Moment -- John Stossel. 19.  Opportunity Cost Neglect in Public Policy -- Emil Persson and Gustav Tinghög. 20. Whose Money is it Anyway? -- Amit Varma. 21. The 4 Ways to Spend Money -- Milton Friedman. 22. Discover Your Inner Economist -- Tyler Cowen. 23. In Service of the Republic — Vijay Kelkar & Ajay Shah. 24. The Art and Science of Economic Policy -- Episode 154 of The Seen and the Unseen (w Vijay Kelkar and Ajay Shah). 25. Amit Varma's prescient 2017 tweet on the price caps on stents. 26. Episodes of the Seen and the Unseen on GST with Devangshu Datta, Vivek Kaul and Shruti Rajagopalan. 26. Most of Amit Varma's writing on DeMon, collected in one Twitter thread. 27. Narendra Modi Takes a Great Leap Backwards — Amit Varma 28. Episodes of The Seen and the Unseen on Demonetisation with Suyash Rai and Shruti Rajagopalan. 29. The Delhi Smog -- Episode 44 of The Seen and the Unseen (w Vivek Kaul). 30. Bootleggers and Baptists-The Education of a Regulatory Economist -- Bruce Yandle. 31. Pigs Don't Fly: The Economic Way of Thinking about Politics -- Russell Roberts. 32. Raees: An Empty Shell of a Gangster Film -- Amit Varma. 33. Shubhra Gupta's review about which Tapsee Pannu kicked up such a fuss. 34. The Tragedy of Our Farm Bills -- Episode 211 of The Seen and the Unseen (w Ajay Shah). 35. Wilson's Interest Group Matrix -- Charles Cameron from The Political Analyst's Toolkit. 36. Government's End: Why Washington Stopped Working -- Jonathan Rauch. 37. The Great Redistribution -- Amit Varma. 38. Behave -- Robert Sapolsky. 39. Robert Sapolsky's lectures on YouTube. 40. Elite Imitation in Public Policy -- Episode 180 of The Seen and the Unseen (w Shruti Rajagopalan & Alex Tabarrok). 41. Taxes Should Be Used for Governance, Not Politics -- Amit Varma. 42. Every Act of Government Is an Act of Violence -- Amit Varma. 43. The First Assault on Our Constitution -- Episode 194 of The Seen and the Unseen (w Tripurdaman Singh). 44. The Emergency -- Episode 103 of The Seen and the Unseen (w Gyan Prakash). 45. How the BJP Wins -- Prashant Jha. 46. The BJP's Magic Formula -- Episode 45 of The Seen and the Unseen (w Prashant Jha). 47. Participatory Democracy — Episode 160 of The Seen and the Unseen (w Ashwin Mahesh). 48. Other episodes of The Seen and the Unseen with Ashwin Mahesh: 1, 2. 49. Understanding India Through Its Languages -- Episode 232 of The Seen and the Unseen (w Peggy Mohan). 50. The Indianness of Indian Food — Episode 95 of The Seen and the Unseen (w Vikram Doctor). 51. Governing the Commons -- Elinor Ostrom. 52. Public Choice Theory -- Episode 121 of The Seen and the Unseen. 53. Fixing Indian Education -- Episode 185 of The Seen and the Unseen (w Karthik Muralidharan). 54. Education in India -- Episode 77 of The Seen and the Unseen (w Amit Chandra). 55. The Economics and Politics of Vaccines -- Episode 223 of The Seen and the Unseen (w Ajay Shah). 56. The Indian Conservative -- Episode 145 of The Seen and the Unseen (w Jaithirth Rao). 57. How to Build an Economic Model in Your Spare Time -- Hal Varian. 58. A Scientist in the Kitchen -- Episode 204 of The Seen and the Unseen (w Krish Ashok). 59. Modeling Covid-19 -- Episode 224 of The Seen and the Unseen (w Gautam Menon). 60. Narratives on Exchange Rates in India -- Pranay Kotasthane. 61. Taking Stock of Our Economy -- Episode 227 of The Seen and the Unseen (w Ila Patnaik). 62. The Power Broker -- Robert Caro. 63. The Death and Life of Great American Cities -- Jane Jacobs. 64. Lessons from an Ankhon Dekhi Prime Minister -- Amit Varma (on the importance of reading). 65. Selling Solutions vs Solving Problems -- Lant Pritchett. 66. Policy Paradox -- Deborah Stone. 67. The Mahatma and the Poet -- The Tagore-Gandhi debates. 68. Factfulness -- Hans Rosling. 69. Humankind: A Hopeful History -- Rutger Bregman. 70. A Practical Guide for Policy Analysis -- Eugene Bardach. 71. Essence of Decision -- Graham Allison and Philip Zelikow. 72. Banishing Bureaucracy -- David Osborne. This episode is sponsored by CTQ Compounds. Check out The Daily Reader, FutureStack and The Social Capital Compound. Use the code UNSEEN for Rs 2500 off. Please subscribe to The India Uncut Newsletter. It's free! And check out Amit's online course, The Art of Clear Writing.

This week's CER podcast is the third of five episodes released in conjunction with the CER's annual economics conference, usually hosted at Ditchley Park but this year held as a webinar series. Christian Odendahl, CER's chief economist, speaks to Stephanie Flanders, head of Bloomberg Economics, about Europe position in the worldwide tech race, the merits of Europen competition policy and Europe’s ability to drive up standards in the digital world. They also discuss the comments from event speakers Hal Varian, Google's Chief Economist, Monika Schnitzer, Economics Professor at LMU in Munich, Thomas Philippon, Finance Professor at NYU Stern School of Business and Merle Maigre, Senior Expert on Cyber Security at the e-Governance Academy in Estonia. Produced by Rosie Giorgi Music by Edward Hipkins

Google economist Hal Varian addresses the concern that technological growth may have been stagnant since the 1960s, and that Big Tech is responsible for the lack of innovation.  The post https://www.aei.org/multimedia/hal-varian-in-defense-of-big-tech/ (Hal Varian: In defense of Big Tech) appeared first on https://www.aei.org (American Enterprise Institute - AEI).

The debate in Washington about the American technology sector has shifted in recent years, going from “Big Tech is leading us to the future” to “What does tech done for us lately?” So has the technology sector failed to deliver for the past few decades? And what should policymakers and scientists be doing to maximize […]Join the conversation and comment on this podcast episode: https://ricochet.com/podcast/political-economy-james-pethokoukis/hal-varian-in-defense-of-big-tech/.Now become a Ricochet member for only $5.00 a month! Join and see what you’ve been missing: https://ricochet.com/membership/.Subscribe to Political Economy with James Pethokoukis in Apple Podcasts (and leave a 5-star review, please!), or by RSS feed. For all our podcasts in one place, subscribe to the Ricochet Audio Network Superfeed in Apple Podcasts or by RSS feed.

This podcast episode was originally posted on July 19, 2019.Jack and Paul talk with Google’s Hal Varian about the future of work, technological innovation in China, competition in Big Tech, blockchain, and why yellow is the best color to draw attention.As always, you can subscribe to Liberty & Justice for All on iTunes, Spotify, Ricochet, Heritage.org, or wherever you get your podcasts. Leave a 5-star review if you enjoy listening and subscribe to get notified when Jack and Paul post new episodes.Have a question, comment, or idea for future episodes? Feel free to contact Jack and Paul at LibertyandJustice@heritage.org. See acast.com/privacy for privacy and opt-out information.

Whether antitrust enforcement against Big Tech is sufficient has been a hot topic in the antitrust world and on Capitol Hill. In this episode, Hal Varian, an industrial organization and information economics scholar and the Chief Economist at Google, speaks with John Roberti and Sergei Zaslavsky about popular attitudes toward Big Tech, the evidence that populist critics of Big Tech may be overlooking, and what historical trends can tell us about the current state of competition in the tech sector. Listen to this episode for a discussion of Big Tech that touches on everything from entry conditions to data portability to coffee in government meetings. Related Links: List of Alphabet acquisitions Data Transfer Project Hosted by: John Roberti, Partner, Allen & Overy and Sergei Zaslavsky, Counsel, O'Melveny & Myers

Matthew Feeney and Peter Van Doren interview Hal Varian about his professional experience starting with his economics column at the New York Times. They also cover other topics like the Google search engine, autonomous vehicles, and working in the age of automation. Varian even suggests that problem with autonomous vehicles is not the vehicle, but the humans that interfere with them.Is there a market for search engines? How do people use search engines? Is Google a monopoly? Which country has the shortest workweek in the developed world? Is our labor market tightening?Further Reading:Sometimes the Stock Does Better Than the Investor That Buys the Stock, written by Hal R. VarianGooglenomics: A long-read Q&A with chief economist Hal Varian, written by James PethokoukisGoogle chief economist Hal Varian says a robot isn’t after your job, written by Olivera PerkinsHal Varian on Taking the Academic Approach to Business (Ep. 69), Conversations with TylerRelated Content:Will Artificial Intelligence Take Your Job?, Building Tomorrow PodcastDoes More Technology Create Unemployment?, written by A.D. Sharplin and R. H. MabryThe Ethics of Artificial Intelligence is Best Left to Researchers, written by Ryan Khurana See acast.com/privacy for privacy and opt-out information.

Jack and Paul talk with Google’s Hal Varian about the future of work, technological innovation in China, competition in Big Tech, blockchain, and why yellow is the best color to draw attention. See acast.com/privacy for privacy and opt-out information.

Before he became the Adam Smith of Googlenomics, Hal Varian spent decades as an academic economist, writing influential papers, a popular book about the information economy, and several textbooks that are still taught today. So how has his nearly twenty years in the business world affected what he’d write and teach now? Is learning Shephard’s lemma really that important anymore? Tyler asks Hal these questions and more: why aren’t there more second-priced auctions — or prediction markets? How have the economics of sales changed with the internet? In what ways did his hiring criteria change between academia and business? What could we learn from the sack of Rome? When should economists avoid looking at the literature? How are we always eking out victory in the war on spam? And what are people least likely to understand about Google? Fear not — Hal has an answer for it all. Transcript and links Follow Hal on Twitter Follow Tyler on Twitter More CWT goodness: Facebook Twitter Instagram Email

ome of you might know him as the author of your microeconomics textbook, others because of his position as chief economist at Google. As a microeconomist prof. Varian has specialized in the role of information in the economy. Starting consulting for Google in 2002 he has been key to Google’s auction design system and corporate strategy. Google has radically changed the way we receive our information, practically serving as the gatekeeper to the internet. However, in recent times there has been increased scrutiny towards superstar firms. During the interview we will discuss among others how information is transforming the economy and the role of Google in the modern economy.

ome of you might know him as the author of your microeconomics textbook, others because of his position as chief economist at Google. As a microeconomist prof. Varian has specialized in the role of information in the economy. Starting consulting for Google in 2002 he has been key to Google’s auction design system and corporate strategy. Google has radically changed the way we receive our information, practically serving as the gatekeeper to the internet. However, in recent times there has been increased scrutiny towards superstar firms. During the interview we will discuss among others how information is transforming the economy and the role of Google in the modern economy.

When grappling with competition issues in the digital economy, Google is often the first name to come up.  The tech powerhouse has been in the firing line of competition authorities in Europe. Its business model and strategies have sparked intense debate about what big data and big analytics mean for competition and how or even whether antitrust enforcers should respond. And, yet, for users who share their most intimate details with the search engine, Google has been equated with a "modern-day God". In this episode of Competition Lore, I am delighted to share the opportunity that I had to discuss these and related issues with Google’s Chief Economist, Hal Varian. Hal was not only generous with his time but with his views ranging from general topics such as the role of economics and populism in antitrust to specific issues raised by the European Commission’s decisions against in the Shopping and Android cases. Aside from setting up the interview, Google had no other input to the production of this episode. Hal hinted in the episode at a second edition of his co-authored best-selling book; let’s hope we can hold him to that!  But if you want to read the first edition, it is Information Rules: A Strategic Guide to the Network Economy.   The episode features an interjection from Professor Scott Galloway with his thesis that Google is a “modern day God”. You may find his book, The Four, of interest or you could listen to his TED Talk. Or, if you’re one of those who likes to contemplate whether there is “life after Google”, then you should read the book by George Gilder, Life After Google: The Fall of Big Data and Rise of the Blockchain Economy, also referred to in the episode. Or you could just watch this on Youtube. Featuring regular cut-through interviews with leading thinkers, movers and shakers, Competition Lore is a podcast series that engages us all in a debate about the transformative potential and risks of digitalised competition. Join Caron Beaton-Wells, Professor in Competition Law at the University of Melbourne, to tackle what it means to participate as a competitor, consumer or citizen in a digital economy and society. Competition Lore is produced by Written & Recorded.

In an age of ubiquitous data, the “scarce factor is the ability to understand that data and extract value from it”. Google’s Chief Economist, Hal R Varian, and Lowy Institute’s International Economy Director Roland Rajah had a discussion on the economics of data, how data can drive innovation and improve our wellbeing, and the debate over its effects on competition and the appropriate role of government. Dr Varian is an emeritus professor at the University of California, Berkeley, in three departments: business, economics, and information management. He has also taught at MIT, Stanford, Oxford, Michigan and other universities around the world. Professor Varian has published numerous papers in economic theory, industrial organisation, financial economics, econometrics, and information economics. He is the co-author of a bestselling book on business strategy, Information Rules: A Strategic Guide to the Network Economy, and wrote a monthly column for The New York Times from 2000 to 2007.

Dr. Hal Varian, Google's Chief Economist and architect of their AdWords platform, joins host Mike Moffatt to chat about data excess, the language gap between business and economics, and nowcasting.

AI's effect on the labour force, who wins man or machine? In a society rapidly moving beyond the traditional employment paradigm, how do we distribute wealth equitably and find our purpose in life? We explore the future of work with Oxford Professor Jonathan Trevor, covering everything from the utility of employment to daily working life in the future. We close out the episode by chatting with Google Chief Economist Hal Varian, who is optimistic about the coming automation revolution and believes we need machines to take over the job hole left by retiring baby boomers.

AI’s effect on the labour force, who wins man or machine? In a society rapidly moving beyond the traditional employment paradigm, how do we distribute wealth equitably and find our purpose in life? We explore the future of work with Oxford Professor Jonathan Trevor, covering everything from the utility of employment to daily working life in the future. We close out the episode by chatting with Google Chief Economist Hal Varian, who is optimistic about the coming automation revolution and believes we need machines to take over the job hole left by retiring baby boomers.

In this episode I talk with Google's chief economist, Hal Varian, about the tech industry, the future of the economy, and much more. The post https://www.aei.org/multimedia/ep-87-googlenomics/ (Ep. 87: Googlenomics— Political Economy with James Pethokoukis) appeared first on https://www.aei.org (American Enterprise Institute - AEI).

The labor force 30 years from now will look very different as working-age populations in advanced economies start to shrink. While some today worry they’ll lose their jobs to robots, economists like Google’s Hal Varian, wonder if technology will boost productivity enough to compensate for the shifting demographics. Varian, and Harvard’s David Canning, discussed the topic during an IMF World-Bank Spring Meetings seminar earlier this month. Hal Varian, Google’s Chief Economist and an Emeritus Professor at UC Berkeley. David Canning, Professor of Population Sciences, Economics and Intl Health, Harvard University, Department of Global Health and Population.

Join Carlos as he explores Psychology of Statistics with Charles Wheelan.Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called “sexy.” From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.And in Wheelan's trademark style, there's not a dull page in sight. You'll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let's Make a Deal—and you'll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.Charles Wheelan is the author of the internationally best-selling Naked Economics and Naked Statistics and a former correspondent for The Economist, and founder of The Centrist Party. He teaches public policy and economics at Dartmouth College and lives in Hanover, New Hampshire, with his family.

The extent to which we are subject to surveillance — the collection of information about us, by government, commercial, or individual agents — is in large part an economic question. Surveillance takes effort and resources — spend more and we can do better surveillance. Protecting against surveillance also takes effort and resources. Given the state of technology, the amount of effort and money each side expends determines what is surveilled and what is kept private. As technology changes, both the cost and the desirability of surveillance, and protection against surveillance, change. We can confidently predict that information technology and communication costs will continue to decrease, and capabilities to surveil and protect against it will improve. What are the consequences for our privacy? Will we have a future with more or less privacy? Which do we want? Bio: Jeffrey MacKie-Mason will be joining UC Berkeley on October 1 as University Librarian and Chief Digital Scholarship Officer. For the past 29 years, Jeff has been a faculty member at the University of Michigan, where he was the Arthur W. Burks Collegiate Professor of Information and Computer Science, and also a professor of economics and a professor of public policy. For the last five years he has been the dean of Michigan’s School of Information. Jeff has been a pioneering scholar of the economics of the Internet and online behavior and a frequent co-author with the Berkeley I School’s first dean, Hal Varian. He has also led the development of the incentive-centered design approach to online information services.

Pour écouter cette chronique donnée sur AligreFMApple et les ouvriers chinoisSteve Jobs est mort il y a tout juste quatre mois entouré de l’admiration générale. Le cours d’Apple, l’entreprise qu’il a fondée, a depuis sa mort, explosé, passant de 410€ à  450$, ses bénéfices n’ont jamais été aussi élevés, 13 milliards de $ pour le seul quatrième trimestre de 20011, soit deux fois plus que pour la même période de 2010, et ses réserves de trésorerie sont considérables. Inutile de donner un chiffre qui à ces niveaux ne veut plus dire grand chose. Il suffit pour donner leur mesure d’indiquer qu’elles sont plus importantes que celles du gouvernement américain. Apple a plus de liquidités que le gouvernement de la plus grande puissance mondiale. Tout cela grâce à ces iphones, ipods et ipads, tout cela grâce à nous en somme.Tout devrait donc aller pour le mieux à Cupertino, au siège social d’Apple et tout irait effectivement pour le mieux si quelques journalistes du New-York-Times n’étaient allés enquêter sur les conditions de travail des ouvriers chinois qui fabriquent ses produits. Car, bien sur, tout est fabriqué en Asie, en Chine. Et le résultat de leur enquête jette une ombre très vilaine sur l’entreprise préférée de tous les amateurs de technologie.On savait depuis longtemps que les conditions de travail sont dans les usines chinoises particulièrement pénibles, mais cette enquête en donne de nouvelles illustrations. Ouvriers qui travaillent de très longues heures, que l’on réveille en pleine nuit pour satisfaire les exigences du client, qui opèrent dans des milieux dangereux… On est plus du coté du servage que des relations industrielles acceptées dans les pays démocratiques.Véritable réquisitoire, cette série d’articles met en évidence la responsabilité d’Apple alors même que ses responsables disent tout faire pour assurer des conditions de travail satisfaisantes aux ouvriers de ses sous-traitants (voir, notamment, ici). Et il est vrai qu’il fait signer des chartes et envoie des inspecteurs mais ses exigences sont si grandes que les entreprises sont amenées à « tourner les coins ronds » pour les satisfaire.Mais tout cela est déjà connu et j’ai évoqué ici même, il y a deux ans, la répression brutale de manifestations d’ouvriers de Wintec, un des sous-traitants chinois d’Apple et de Nokia dont on ne payait pas les heures supplémentaires. Et si je vous parle ce matin de cette enquête, c’est qu’elle nous donne, au delà de ces informations sur les conditions de travail, un éclairage très intéressant sur les méthodes de l’industrie chinoise et sur ce qui fait aujourd’hui son succès. Méthodes qu’il est intéressant de connaître alors que l’on s’interroge sur le meilleur moyen de réindustrialiser la France.Au delà des salairesLorsque l’on parle de la concurrence des pays émergents et, notamment, de la Chine, on pense au coût du travail et on explique leur succès par ce seul avantage. Il existe, naturellement, mais il n’y a pas que lui. Le premier article de cette série donne un exemple éclairant de ces autres avantages. En 2007, à quelques mois de la sortie de l’iphone, Steve Jobs découvre que le revêtement de plexiglass prévu par les ingénieurs d’Apple pour l’écran se raie facilement. Il demande qu’on le remplace par du verre, ce qui est techniquement compliqué. Apple lance un appel d’offre. Une entreprise chinoise répond. Lorsque les ingénieurs du constructeur informatique se rendent sur place, l’entreprise a déjà acheté du verre pour faire des essais de coupe et mis à la disposition de son client potentiel des ingénieurs pour faire presque gratuitement les essais. Un mois plus tard, la solution est trouvée, la production peut commencer, mais les milliers de salariés nécessaires pour  la réaliser ont été recrutés, les dortoirs dans lequel ils vont dormir construits. Incapable de tenir ce rythme l’entreprise américaine qui avait été initialement retenue a perdu le marché.Première caractéristique donc de l’industrie chinoise : son aptitude à anticiper les demandes et à faire gagner à son client quelques semaines, voire quelques mois. C’est au moins aussi important pour Apple qui avait mis en place toute sa politique commerciale que des salaires faibles. Et cela n’est possible que parce que ces entreprises, qui veulent avoir le marché d’Apple, sont disposées à investir massivement pour l’obtenir.Seconde caractéristique : sa capacité à lancer rapidement des productions de masse. Le marché des produits électroniques grand public est mondial. Dès la première année de la commercialisation de son Iphone, Apple en a vendu près d’1,4 millions, l’année suivante, il en a vendu plus de 11 millions et 40 millions en 2010. Les démarrages des produits qui ont du succès sont foudroyants. Et ils ne sont possibles que parce que les industriels chargés de les fabriquer peuvent  quasi instantanément ou, du moins, très rapidement, mobiliser des capacités de production considérables. Et ceci grâce aux conditions de travail de ses salariés, serviables et corvéables à merci, mais aussi grâce à un marché du travail très profond qui lui permet de recruter rapidement , lorsque nécessaire, des milliers d’ouvriers, de techniciens ou d’ingénieurs et de les mettre immédiatement au travail.Lorsque l’on demande aux responsables d’Apple pourquoi ils ne fabriquent plus leurs produits aux Etats-Unis, ils répondent, toujours d’après l’article du New-York-Times : « parce qu’il n’y a tout simplement plus assez d’ouvriers avec les compétences nécessaires aux Etats-Unis, plus assez d’usines avec la réactivité et la flexibilité nécessaire. »Les vertus de l’agglomérationL’article met en avant un autre aspect capital qui explique le succès de l’industrie chinoise : les vertus de l’agglomération. Car, faut-il le rappeler ? les salaires chinois sont depuis longtemps très faibles et ce n’est que depuis quelques années que ce pays est devenu l’usine du monde.L’entreprise américaine qui avait perdu l’appel d’offres d’Apple sur l’écran de verre, Corning Glass, n’a pas abandonné la partie. Bien au contraire, elle a continué de proposer son offre aux concurrents d’Apple, la plupart installés en Asie. Et elle a construit des usines dans cette partie du monde. L’article donne deux chiffres qui expliquent : pour transporter les écrans de l’usine qui les fabrique en Chine à celles qui montent l’iphone, il faut 8 heures de transport. Pour les transporter des Etats-Unis en bateau, il aurait fallu 35 jours. Avec l’avion cela aurait été plus rapide, mais à des coûts extravagants. La puissance industrielle de la Chine tient à sa géographie industrielle. Plutôt que de disperser ses activités industrielles sur tout le territoire elle a su créer des agglomérations industrielles qui mettent au service de ses clients tout ce dont ils ont besoin. Un des responsables d’Apple interrogé par les journalistes du NYT l’explique ainsi : « toute la chaine de production est aujourd’hui en Chine. Vous avez besoin de joints en caoutchouc ? Vous les trouverez dans l’usine à coté ? Vous avez besoin d’un millions de vis ? L’usine est en face. Vous avez besoin d’un tournevis un peu différent ? cela prendra trois heures pour le trouver. »Ce n’est pas une nouveauté. En 2009, Paul Krugman, économiste célèbre qui se trouve être aussi un spécialiste de la géographie économique, publiait un article (Increasing Returns in a Comparative Advantage World) dans lequel il mettait en évidence le rôle de ces effets d’agglomération.Cet effet d’agglomération tient à la géographie, on trouve tout à proximité, ce qui réduit les coûts logistiques, mais aussi à la structure de l’économie chinoise. A l’inverse de la notre, dominée par quelques grands groupes, elle comprend des milliers d’entreprises spécialisées sur un créneau étroit, les vis par exemple, qui sont en concurrence, qui sont à proximité et qui offrent donc à l’industriel à la recherche d’un produit particulier toutes chances de trouver rapidement ce qu’il souhaite et dans les meilleures conditions puisque, concurrence aidant, toutes sont intéressées à répondre au plus vite à la demande. Si j’osais une image et pour en rester aux vis, l’économie chinoise ressemble au sous-sol du BHV où l’on trouve à peu près tout, en matière de vis, sous la main, alors que nos économies ressemblent beaucoup plus à ces grandes surfaces qui n’offrent à leurs clients qu’un nombre limité de références et imposent à celui qui cherche un modèle de vis particulier une longue recherche. On comprend que des industriels soient séduits par ce modèle qui allège considérablement les coûts de développement d’un produit. Une grande flexibilitéL’autre grande caractéristique est la flexibilité. Ces usines savent répondre très rapidement à la demande, elles savent s’adapter à ce que souhaitent leurs clients. Et ceci parce qu’elles utilisent beaucoup de main d’œuvre. Nos industries ont mis l’accent sur l’automatisation pour réduire les coûts du travail humain. Les Chinois ont aussi des usines très automatisées, mais ils en ont d’autres qui utilisent beaucoup de main d’œuvre, tout simplement parce que celle-ci est bon marché. De manière générale, il semble, d’ailleurs, que les Chinois utilisent infiniment plus de main d’œuvre ouvrière que nous dans leurs usines. L’avantage est qu’il est plus facile de reprogrammer une fabrication avec des hommes auxquels on peut demander de modifier quasi instantanément leur production, qu’à des machines dont la programmation est toujours longue et difficile. On peut confier à des hommes des tâches qu’il est très difficile d’automatiser ou qui demanderaient, pour pouvoir l’être de très longs développements que les les fabricants de machines-outils ne pourraient engager que s’ils étaient assurés d’avoir un débouché important. Les clients n’ont évidemment pas le temps d’attendre.Résumons donc : la Chine a un coût du travail bien plus faible que le notre, elle offre à ses salariés des conditions de travail souvent inadmissibles, mais son succès ne tient pas seulement à cela. Il tient aussi, et peut-être surtout pour l’avenir, à sa réactivité, à sa flexibilité, à sa structure et à son organisation géographique qui lui donnent les moyens de mobiliser rapidement les ressources considérables dont ont besoin les industriels aujourd’hui. Et dont ils auront plus encore besoin demain.La concentration des industries capables de travailler ensemble dans la même région est sans doute le trait le plus remarquable de cette organisation industrielle. Je disais tout à l’heure que Paul Krugman en avait fait la théorie dans un article en 2009. Un autre économiste, Richard Baldwin est rentré plus dans le détail (Trade and industrialisation after globalisation’s 2’nd unbundling). Il montre que la fragmentation de la chaine de production, caractéristique de l’industrie moderne, est allée avec une concentration de cette industrie dans des régions géographiques étroites. Les coûts du transport n’ont pas disparu. Je parle aujourd’hui de la Chine, mais ne même phénomène explique sans doute le succès de l’Allemagne dont les industriels ont su nouer des liens étroits avec les industries des ex-pays socialistes qui sont à ses frontières et dont les coûts de main d’œuvre sont plus faibles.Un modèle industriel adaptée à la demande…Au delà des critiques sur la gestion des hommes qui confine, je l’ai dit, à un quasi-servage, c’est la modernité et l’efficacité de l’appareil chinois qui frappe. Il s’est adapté à la demande des industriels occidentaux. Non pas en jouant exclusivement sur le coût du travail comme d’autres pays en voie de développement mais en construisant une économie qui répond exactement aux attentes de l’économie contemporaine. Sa capacité à mobiliser rapidement ressources humaines et techniques lui permet de répondre aux attentes de ces entreprises qui travaillent pour un marché mondial. J’ai donné l’exemple d’Apple et de son iphone, mais plein d’autres industriels sont dans la même logique. Une logique qui suppose que l’on puisse rapidement produire en quantités considérables pour fournir simultanément des clients aux quatre coins du monde mais qui suppose aussi une grande flexibilité : ces produits se renouvellent très vite. Nous en sommes déjà à la troisième ou quatrième génération d’iphone.Sa flexibilité lui permet également de répondre aux exigences du commerce électronique, sur internet, qui demande que l’on se rapproche de la fabrication à la demande. On ne peut pas dans l’univers du commerce sur internet stocker tous les produits que l’on vend, puisque l’on ne sait pas combien on en vendra dans quelques semaines ou quelques mois. Il faut donc trouver une solution industrielle qui permette de les fabriquer pratiquement à la demande. Ce modèle existe, c’est celui qu’avait imaginé le constructeur informatique Dell. L’industrie chinoise, avec son coté BHV dont je parlais tout à l’heure s’y prête particulièrement bien. Le sous-traitant stocke les composants des différents modèles d’un même produit, un téléphone, une tablette électronique… et les assemble à la demande. Et en quelques heures, le produit peut être expédié au client qui l’a commandé. Ce modèle ne peut évidemment fonctionner de manière satisfaisante que si le marché est très vaste, c’est-à-dire global.Cette modernité profonde du modèle chinois de production industrielle est trop rarement soulignée. Or, elle est capitale. Elle veut tout simplement dire que l’industrie chinoise pourra résister à une hausse du coût du travail à laquelle elle ne saurait échapper. Ces salariés que l’on traite si mal vont se rebeller, ils ont commencé de le faire et les pays occidentaux qui voient leurs emplois ouvriers disparaître vont exercer une pression forte sur la Chine pour qu’elle respecte mieux les règles sociales. Mais ces hausses du coût du travail que l’on peut anticiper ne ramèneront pas du travail chez nous. Et les emplois ?Pour se défendre, Apple indique que l’essentiel de la valeur ajoutée de ses produits est restée aux Etats-Unis. Dans un article publié dans le New-York Times en 2007, son économiste en chef, Hal Varian, indiquait, en s’appuyant sur les travaux de jeunes chercheurs, que plus de 54% de la valeur ajoutée d’un ipod fabriqué en Chine restait aux Etats-Unis, dont 46% pour la distribution et près de 50% pour Apple, ses ingénieurs… C’était en 2007, mais on peut penser que les chiffres pour l’iphone sont à peu près du même ordre. Cette ligne de défense n’est évidemment pas complètement satisfaisante : la valeur ajoutée et les emplois sont deux choses différentes. Si plus de la moitié de la valeur ajoutée reste aux Etats-Unis, le plus gros des emplois est en Chine, ce qui ne convient pas évidemment pas aux salariés américains au chômage. Voici, pour finir, quelques chiffres que je tire de cette série d’articles qui a servi de support à cette chronique. Apple emploie 40 000 personnes aux Etats-Unis et 20 000 ailleurs dans le monde tandis que 700 000, oui 700 000, personnes fabriquent et assemblent ses produits en Chine et ailleurs en Asie. Apple crée donc bien des emplois, mais pas là où on les imagine…Face à ces évolutions, on peut être tenté par le protectionnisme, il serait plus sage d’approfondir ce modèle chinois et de voir s’il ne serait pas possible de s’en inspirer.Le 31/01/2012

Dominique Strauss-Kahn's arrest and the future of the IMF; Japan's economic recovery; and Google's chief economist Hal Varian on how the spread of information can prevent banking crises

Varian speaks about "Predicting the Present with Search Engine Data." Varian started at Google in 2002 and has been involved in many aspects of the company, including auction design, econometric analysis, finance, corporate strategy and public policy.

These days nearly every economic transaction involves a computer in some form or other. What does this mean for economics? I argue that the ubiquity of computers enables new and more efficient contractual forms, better alignment of incentives, more sophisticated data extraction and analysis, creates an environment for controlled experimentation, and allows for personalization and customization. I review some of the long and rich history of these phenomena and describe some of their implications for current and future practices.

Audio File:  Download MP3Transcript: An Interview with Rashmi Sinha CEO & Co-founder, SlideShare Date: April 27, 2009 Lucy Sanders: Hi, this is Lucy Sanders, the CEO of the National Center for Women & Information Technology, or NCWIT. This is another of our interviews with women who have started IT companies. I'm very excited today to be interviewing Rashmi Sinha. With me today is Larry Nelson, as usual, from w3w3.com. Larry Nelson: Hello, and it's my pleasure to be here. This is going to be an exciting interview. We'll have this, of course, on w3w3.com also, and it's been a spectacular, popular series. Lucy: Absolutely. And you're doing something else interesting at w3w3 these days, aren't you? Larry: We just launched our own TV show "IPTV." Lucy: You'll have to watch out, Rashmi, he's going to be coming after you for a TV show next. Larry: You betcha. Lucy: Well, Larry, I'm pretty sure all of our listeners know that Facebook, Twitter, blogging, are really part of social media and powerful communication tools, but I'll bet if they're like me they didn't stop to think so much about the fact that PowerPoint is also social media. People don't create PowerPoint presentations to share with themselves, and so they really do create them for communication, and really to reach out to others. So that's really why I'm very excited, being a heavy PowerPointer myself, to be interviewing Rashmi Sinha. She is the cofounder and CEO of SlideShare. It's, I believe, the word's largest community for sharing presentations. Rashmi, you'll have to tell us how many, but the stat I grabbed off the Web was 3,000 PowerPoints created per day? Larry: Per day! Wow. Lucy: Wow. So it's really a great way to get your slides out, and share, and reuse, and really form community around PowerPoint. Welcome, Rashmi! Rashmi Sinha: Thank you, thank you. Glad to be here and sharing a few stories. Lucy: One of the stories I thought we'd start with, before we get to our usual set of questions, is: what kinds of topics are you seeing these days put up on SlideShare? Rashmi: Anything, and everything. conversation, and debate is what this is about. Last year in November, we saw a lot of focus on the credit crisis. Recently we've seen a bunch of Obama presentations. Whatever is the current topic, that definitely shows up, and then there are more stable topics. We always have some things about the latest technologies or whatever people are excited about such as Telescope, or Ruby, or Python. You also have a different, more creative type of presentation, which are basically photographs with some music in the background. So there's a whole range of types of things that show up on SlideShare. Lucy: That's a great transition into our first question. You have a Ph.D. in cognitive neuropsychology. That is just so fascinating, and I know that you really did fall in love with the Web, and Web 2.0, and you really have looked at some of these issues around Web technologies from a perspective of human psychology. It would be very interesting to know how you see the cool technology today. What do you think is hot, especially in Web 2.0? Rashmi: I'm coming up from a little bit of a biased perspective, since I've spend the day kind of behind SlideShare, looking out at what people are doing. What I find really interesting is that so many of what are the more businessy, supposedly boring topics, are kind of the hot topics of conversation that people are participating in. It's not necessarily diluting the level of the conversation. For example, before SlideShare you couldn't really imagine people bonding over these very technical presentations. But you had this mission that people are interested in, and the Web really enables them to find each other, and to bond over these objects. Whether it's on Twitter, or it's on FaceBook, or it's on LinkedIn, or it's on peoples' own websites and broadcasts you really see this ability to have these topic-based conversations, which I find very interesting. I think one of the things that really strikes me is, what's happened with social networking is that the world is much more deeply linked than it used to be. Earlier it was all about just the hyperlinks, how you point to each other, and now you have all these social connections and all these different social spaces that they participate in. Overall I think that the interlinking of people and the web has become much more complex and much realistic in reflecting real world relationships in some way. I find that very interesting overall. Larry: Mm-hmm. Lucy Sanders: I think the idea of communities around PowerPoint presentations is fascinating. What kinds of communities do you see forming? What kind of topic areas seem to be the most popular? Rashmi: A lot of conversation around social media. I think all the social media junkies of the world come to SlideShare and put up presentations and find the other ones. So you see a lot of conversation about that. You see a lot of conversation about marketing, about the web itself, about technology, and about I would say pretty much any topic that people do their presentations around, you see communities forming. The interesting aspect about the community and was something that we had noticed time and again is that it doesn't happen only on SlideShare. It happens outside SlideShare often. It often happens on Twitter or on FaceBook, where people take back the objects and then bond over them. We have tried to embrace that in a natural and fluid manner and let the community formation be anywhere that people are. They can take these presentations, or documents which we also support, back with them. Larry: Wow, you're doing a wonderful job. Now one of the things, Rashmi, I'd like to ask you is, with your background, your education and everything else, why did you become an entrepreneur and what is it about being an entrepreneur that makes you tick? Rashmi: Well I never planned to be an entrepreneur, and it was entirely an accident, maybe a little bit of an accident stemming from what the thing that I wanted to do in life. But I did not, when I was doing my Ph.D., if anybody had asked me "are you going to be an entrepreneur?" I would not have thought that for a moment. I guess I just embrace whatever is in front of me and kind of go with it. And that just led to one thing after the other. So I'd like to share the story of how it happened. I did my Ph.D. and then I came UC Berkeley for a post doc. I was doing psychology, not at all interested in technology. As I said, the Bay Area water, there's something in the water here that gets you interested in technology. So I started just focusing more on technology, found the topics very interesting, and one day walked into the UC Berkeley School of Information which does a lot of human computer direction work, and just said, "I find these topics interesting. I'd like to work on them." And they said, "Great. Why don't you start?" So I switched topics within UC Berkeley, did that for a year, then decided I wanted to do consulting. So I changed to consulting, formed a company, we built our first product, that was MindCanvas. And I formed the company, by the way, with my husband who is a software engineer and who was getting done with his job that he was working in for Commerce One. So we formed the first company, we built our first product, and then he came up with the idea of SlideShare. We launched SlideShare in October 2006 and it just took off, and we kind of followed it. I'm definitely an accidental entrepreneur. Lucy: I like this notion of embracing what you see in front of you, and just moving with it and taking advantage. It's very opportunistic and I think we see that a lot in entrepreneurs. So along that path, I'm sure people influenced you. You had mentors, or maybe not. But we're really interested in understanding who influenced you. Rashmi: Lots of people along the way. So in academia, my teacher was very influential. In terms of the way he taught me to work rather than the specific things that we worked on, I've moved away from them. But the way he was efficient in his working, that really taught me a lot. At UC Berkeley I work with Marti Hearst and Hal Varian they were doing academic admissions and how the end is now economists at guru, and just kind of watching the way the talk about the Web. That's how I was really introduced to technology working with them. That has been very influential in the way I approach things in SlideShare. So, those are just some of the people who've influenced me, but there are lots and lots of people along the way who've helped me figure out things. Larry: Very interesting. Now, I really admire the progress you've made. Somewhere along the line since you've started your company, SlideShare, what was maybe the toughest thing that you had to do. Rashmi: The toughest thing was moving down at a product. I had to do that, it was called MindCanvas, it was a service platform. It was doing well, we were making money off it, it was a profitable business. But SlideShare had more promise, SlideShare had already touched the life of millions of people, and we realized that we could touch the life of millions more. So, we were definitely all in love with SlideShare, and we loved MindCanvas as well, but there was really a moment in time where we realized we could not do both. SlideShare especially was a very demanding application so we had to put all our energies into that. So I remember the day that we realized that we needed to make a decision, it was a very tough day. Lucy: That is tough, you really do get very close to products and companies, I mean they're parts of the family. I had to shut down a few things at Bell Labs and I hated it every time it happened. In fact, I think I just either saw in your Blog, or maybe it was a Tweet. That you had had to tell somebody once again what had happened to MindCanvas, and it is, it's very emotional. Rashmi: I have to do that pretty much every two or three days. We still get a lot of emails about it, and what we really need to do is say so on the Website that we are no longer offering this. But I think somehow or the other that it is hard to, kind of, make that. But we still get a lot of inquiries and we need to make that final. It's a very tough thing, actually. Lucy: Well, I think it is though. It is the flip side to the coin of having great passion and loving what you do as an entrepreneur, that sometimes in the life cycle you have to shut it down. So, if you were sitting here with a young person and telling them about entrepreneurship and giving them advice, what would you tell them? Rashmi: It said so very often but it really is true, is that: have the confidence that if you believe in something and if you think you can do it then you can do it. Maybe there are aspects of it you'll realize that your skills and personality are not suited, but there are other aspects that you will grow into. You know, when I decided to do technology I knew a little bit of computer science, I had taken a few courses but I was definitely not a very technical person. I kind of just went ahead, and forged ahead with it and have learned along the way and have picked things up. I have figured out what my strengths are. I would say that's a very important thing to decide what interests you because you can't do anything as well as the things that truly make you come alive. Larry: When you said, "if you think you can, you can" it reminds me of some things I've read in some books about, "working the mind". Is there any book in particular that has been important to you? Rashmi: I can't think of any particular book. I used to read a lot as a child, and it's kind of like a whole range of books. I always feel that about half my life was in my imagination in these books, and I read very fast. I read in this frenzied manner. So, it's more like I read a lot of books, rather then any particular books. But I will say there is something, one thing, that has been very influential to me as an entrepreneur is my mother. My mother has been a housewife and she hasn't had a career, but she made sure that her daughters would have a career, and in some ways, I have lived her ambitions. What she didn't get an opportunity to, maybe both my parents gave me that opportunity. That's been a very big influence on me. Larry: Kind of following up on that, then, what do you feel are the personal characteristics that make you an entrepreneur like you are, that'd given you that advantage? Rashmi: Well I think these entrepreneurs have to have this optimism, this ability to see the bright. To see that you can do it and what the next thing is. You always have to be able to imagine what's going to happen next and then to make it a reality. So the ability to imagine, to see the positive, and pull ahead and not really care. When we first went out and talked about SlideShare, and this was early on before we had barely a few million visitors, even at that point, I remember some VCs, et cetera, would be like, "how can you have so much traffic?" We just believed that presentation are used every day. There's millions of people sharing it, and we were going to build this site where they would all share it. So, we had this believe no matter how many people doubted us, we just kind of went on with it. That's one very important ability for entrepreneurs. But it's really hard. And there are days you seem really feel down and something has to carry you through that day. Lucy: Well if you'd come and talk to me, I would have told you that probably half of that traffic would have been me. I can give so many power point presentations that, I think it's a fabulous idea. Good for you for sticking with it. You mentioned that it is hard work and sometimes you're down, and you have to keep going, and look at the bright side. What other things besides thinking that way, what other things do you do to bring balance between your personal and professional life? Rashmi: That's the hardest part. We are still trying and it's hard to figure that out. I keep on making resolutions and breaking them. I keep on thinking, I'll go home at a certain point in time. But then I go home and start working again. One thing that we have been trying very hard, and, by the way, it also reflects the fact that my husband, John and I, are both of part of SlideShare. We are the cofounders. So it it's hard for us to leave SlideShare behind. I would say I lead an unbalanced life and I'm probably not the right person to give any advice about leading a balanced life. Larry: Rashmi, I really needed some of that advice because my wife, Pat and I, we work together. And we have this... you talked about our scenario. Rashmi: You can leave the place but you can't leave the, yeah. Lucy: And we've heard the answer before about being rather unbalanced. But we've also heard that sometimes you have years of unbalance and then years of some amount of balance. So it sort of integrates out over decades. So you've achieved a lot. And, I should mention to our listeners as well, that Rashmi was named one of the most influential women in Web 2.0 by "Fast Company." So congratulations for that... Rashmi: Thank you. Lucy: Awesome achievement. And so what's next for you? As SlideShare is up and going and making great progress. I am sure there is more work to do there, but have you looked down the road just a bit to see what you might want to do after SlideShare? Rashmi: Well, I mean, I want to make SlideShare a big independent company. And I'd like to do things along with SlideShare. One day I think I would like to write a book. And I'd like to get more involved in social entrepreneurship. Interesting companies that are doing something in that space. But that's definitely something I would love to do. But right now SlideShare is such a young company, it's just two and a half years old, and it's just starting. So there is a long way to go with that. Larry: Yes, actually just finished the final editing of my latest book. And it's really worth it. It took just about three years to write it and get it edited. So don't forget that, you keep it up. Lucy: It's very good. Well thank you very much, Rashmi. It's been great talking to you. I want to remind listeners that they can find these podcasts at ncwitt.org and w3w3.com and pass them along to your friends. Thank you Larry. Larry: Yeah thank you. And Rashmi, it was a pleasure. Rashmi: Thank you both you. This is a pleasure too. Lucy: Thank you, that's great. Series: Entrepreneurial HeroesInterviewee: Rashmi SinhaInterview Summary: "It was entirely an accident" that Rashmi Sinha became an entrepreneur, she says. After backing into technology and entrepreneurship, however, she advises that it's important to decide what interests you, and then follow your interests. Release Date: April 29, 2009Interview Subject: Rashmi SinhaInterviewer(s): Lucy Sanders, Larry NelsonDuration: 18:21

Hal Varian, Google's Chief Economist and University of California at Berkeley professor, talks with Russ Roberts about Google, the role of technology in our everyday lives, the unintended paths of innovation, and the value of economics.

Hal Varian, Google's Chief Economist and University of California at Berkeley professor, talks with Russ Roberts about Google, the role of technology in our everyday lives, the unintended paths of innovation, and the value of economics.