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Airbnb, airport security, Al Roth, Andrei Shleifer, attribution theory, autonomous vehicles, barriers to entry, Brownian motion, centralized clearinghouse, clean water, conceptual framework, constrained optimization, continuous double auction, deferred acceptance, Donald Trump, Edward Glaeser, experimental subject, first-price auction, framing effect, frictionless, fundamental attribution error, George Akerlof, Goldman Sachs: Vampire Squid, helicopter parent, Internet of things, invisible hand, Isaac Newton, iterative process, Jean Tirole, Jeff Bezos, Johann Wolfgang von Goethe, John Nash: game theory, John von Neumann, Joseph Schumpeter, late fees, linear programming, Lyft, market clearing, market design, market friction, medical residency, multi-sided market, mutually assured destruction, Nash equilibrium, Occupy movement, Peter Thiel, pets.com, pez dispenser, pre–internet, price mechanism, price stability, prisoner's dilemma, profit motive, proxy bid, RAND corporation, ride hailing / ride sharing, Robert Shiller, Robert Shiller, Ronald Coase, school choice, school vouchers, sealed-bid auction, second-price auction, second-price sealed-bid, sharing economy, Silicon Valley, spectrum auction, Steve Jobs, Tacoma Narrows Bridge, technoutopianism, telemarketer, The Market for Lemons, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, trade route, transaction costs, two-sided market, uranium enrichment, Vickrey auction, winner-take-all economy
And it left potential clerks early in their law school careers needing to commit to an offer before exploring other options—or even knowing what kind of law they wished to practice. It happened to the market for slots at sororities, too, which used to be reserved for college seniors, until popular girls started getting invitations to join at the start of their junior, then sophomore, then freshman year. (According to market design guru Al Roth, one theory holds that the term “fraternity/sorority rush,” which today describes the process by which sororities and fraternities recruit new members, comes from the frenzied competition among sororities to lock in new members.4) It’s what prompted medical residency programs to develop a centralized clearinghouse in the 1940s to fend off students receiving exploding offers before they were done with their intro to anatomy course.
But that’s really all that Gale and Shapley provided: a conceptual framework that market designers have, for several decades now, been applying, evaluating, and refining. They’ve learned from its successes and, unfortunately, learned even more from its inevitable failures: modeling real-life exchanges is an imprecise, iterative process in which many of us find ourselves as experimental subjects. The Complicated Job of Engineering Matches Market designer Al Roth likes to use a bridge-building metaphor to explain the contrast between his own work and that of design pioneers like Shapley. Suppose you want to build a suspension bridge connecting Brooklyn and Manhattan. In confronting decisions like where to place the suspension cables and how thick each should be, you’d better have paid attention in physics class. Things like Euler’s buckling equation, which provides the maximum axial load that a long, slender, ideal column can carry before it crumples, are important background knowledge for bridge builders to be.
At no point in the process can you force someone to give up an organ, so it was critical that both donors made their contribution at the same time, lest the second donor back out. You might see why this ad hoc kidney barter system never really amounted to much, rarely getting past the teens in any given year: something like one or two donor-recipient exchanges for every ten thousand cases languishing on the transplant wait list. The market lacked what market designer Al Roth calls thickness—the presence of enough “traders” at the kidney swap to make it worth searching for a partner. It’s a self-fulfilling prophecy: since no one else is showing up to trade, it isn’t worthwhile for anyone to participate. And as a result, there was no kidney exchange platform for traders to show up to in search of a match. Roth and his fellow market designers set about revolutionizing the kidney transplant world in 2003 with an article that observed that kidney exchange bears a close resemblance to a problem that mathematical economists Lloyd Shapley (who you might recall from the Shapley-Gale matching algorithm) and Herbert Scarf examined in 1974.
Affordable Care Act / Obamacare, Airbnb, Al Roth, Black Swan, buy low sell high, Credit Default Swap, cross-subsidies, crowdsourcing, disintermediation, diversified portfolio, experimental economics, George Akerlof, Goldman Sachs: Vampire Squid, income inequality, index fund, Jean Tirole, Lean Startup, Lyft, Mark Zuckerberg, market microstructure, Martin Wolf, McMansion, Menlo Park, moral hazard, multi-sided market, Network effects, patent troll, Paul Graham, Peter Thiel, pez dispenser, ride hailing / ride sharing, Sand Hill Road, sharing economy, Silicon Valley, social graph, supply-chain management, TaskRabbit, The Market for Lemons, too big to fail, trade route, transaction costs, two-sided market, Uber for X, ultimatum game, Y Combinator
Middlemen who play the Insulator role are essential in the many situations that fall within moral gray areas or simply socially awkward domains. By acting as our proxy, the Insulator can enable us to be honest and bold without damaging our image or important business relationships. Instead of connecting two people who don’t otherwise know each other, as a Bridge would, the Insulator steps in when it’s best to keep the two parties apart. These ideas about insulation are very familiar to economist Al Roth, who won the 2012 Nobel Prize for his extraordinarily practical work in applying game theory to the design of real-world markets. Roth says that in every market he’s ever studied, there are some things that some people consider “repugnant” where middlemen can help. “There are some things you’re not allowed to do for yourself but that others can do for you,” Roth says.7 In a negotiation, for example, “It seems impolite for me to say that I have the upper hand, and I should really get 90 percent.
During the holdout, Bryan Goldberg, a senior writer for The Bleacher Report, wrote a column accusing Crabtree’s agent, Eugene Parker, of “brainwashing and ruining the career of a young man who does not know any better.”10 After the deal was done, Pete Prisco, NFL columnist for CBS Sports, proclaimed that “his agent did him a major disservice by keeping him out.”11 The pundits knew that an agent wouldn’t do what the client didn’t want, but still they blamed the agent. Having Their Cake and Eating It Too * * * I first heard Crabtree’s story from a young experimental economist named Lucas Coffman, an assistant professor at Ohio State University who had been a doctoral student of Al Roth’s. Coffman has more than a passing interest in sports. By his own account, he follows football and baseball and basketball more than he should.12 He’s thought so much about the problems with the NFL draft that he’s proposed an alternative. Among the many problems in the current system is that teams pick players one at a time instead of bidding on a group that would play well together. Coffman also has a keen interest in the role of agents, who he’s convinced absorb some of the dislike often directed at players.
And sometimes it’s just an easy way to do someone a favor. When a colleague of mine accompanied her husband to his class reunion, and a classmate asked him what he’d been up to, he gave a brief answer that she didn’t think did justice to his accomplishments, so she piped up to brag on his behalf, mentioning his recent promotion. He came out looking not only more accomplished, but more modest, too. Similarly, the morning Al Roth won the Nobel Prize and Stanford held a press conference, it was not Roth who explained what made his work so impressive, but the department chairman, economist Jon Levin, who mentioned that he was speaking because it would be awkward for Roth to do so. Whether you put in a good word for a deserving colleague or make a request that a friend would feel awkward asking for herself, playing the Insulator is another way to win friends and influence people.
Automate This: How Algorithms Came to Rule Our World by Christopher Steiner
23andMe, Ada Lovelace, airport security, Al Roth, algorithmic trading, backtesting, big-box store, Black-Scholes formula, call centre, cloud computing, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, Donald Trump, Douglas Hofstadter, dumpster diving, Flash crash, Gödel, Escher, Bach, High speed trading, Howard Rheingold, index fund, Isaac Newton, John Maynard Keynes: technological unemployment, knowledge economy, late fees, Mark Zuckerberg, market bubble, medical residency, Narrative Science, PageRank, pattern recognition, Paul Graham, prediction markets, quantitative hedge fund, Renaissance Technologies, ride hailing / ride sharing, risk tolerance, Sergey Aleynikov, side project, Silicon Valley, Skype, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, transaction costs, upwardly mobile, Watson beat the top human players on Jeopardy!, Y Combinator
But an algorithm acting as a doctor could take the information found in the PDR and commit it to memory in seconds, constantly updating itself with nuanced adjustments based on new data pushed out by drug manufacturers. While medicine seems to be rather unhackable on its face, the truth is that it’s already been shaken by algorithms—and the real changes are yet to come. THE ARBITER OF LIFE Sitting in an audience in 2004, Tuomas Sandholm, the creator of poker algorithms, found himself riveted by a speaker and his topic. Al Roth, a Harvard economist, was talking to the World Congress of the Game Theory Society in Marseille, France. Roth was explaining the challenges facing kidney transplant networks in dealing with the circumstances facing each donor or recipient: blood type, location, health, age, relatives, and so on. With tens of thousands of people sitting on waiting lists in America and across the world, maximizing the number of matches between donors and patients is the biggest mission facing the transplant system.
If a second incompatible pair can be found where the second donor matches the first patient and the first donor matches the second patient, then transplants can be made. Finding an opposite pair that satisfies all necessary matching requirements, however, is something of a long shot. Introducing more pairs to the mix creates more available matches, at least theoretically. But throwing thousands of pairs into a bucket and attempting to sort them out efficiently is complicated. Before Al Roth started tinkering with new methods for matching pairs, they were put together by hand with little more than a spreadsheet. If a match wasn’t patently obvious, it wasn’t made. Before Roth’s work, in fact, there were no national or regional pools for kidney matching anywhere in the United States. Roth developed a system that automatically found the most efficient way to put pairs from the pool together, but the algorithm was limited in the numbers it could handle, a problem he lamented at the lectern in Marseille.
A Beautiful Mind by Sylvia Nasar
Al Roth, Albert Einstein, Andrew Wiles, Brownian motion, cognitive dissonance, Columbine, experimental economics, fear of failure, Henri Poincaré, invisible hand, Isaac Newton, John Conway, John Nash: game theory, John von Neumann, Kenneth Rogoff, linear programming, lone genius, market design, medical residency, Nash equilibrium, Norbert Wiener, Paul Erdős, prisoner's dilemma, RAND corporation, Ronald Coase, second-price auction, Silicon Valley, Simon Singh, spectrum auction, The Wealth of Nations by Adam Smith, Thorstein Veblen, upwardly mobile
They devised different games, mostly with four rotating players, one with as many as seven. The game mimicked the general, “n-person” game of von Neumann’s theory. Subjects were told they could win cash by forming coalitions, and the specific amounts that would be awarded to each possible coalition. To be eligible to win, however, the coalition partners had to commit in advance to a given division of the winnings. According to Al Roth, a leading experimental economist, the experiment yielded two insights that proved highly influential.18 For one thing, it drew attention to information possessed by participants: If the same players play the game repeatedly, the authors concluded, players tend to “regard a run of plays as a single play of a more complicated game.” Second, like the Prisoner’s Dilemma experiment devised by Melvin Dresher and Merrill Flood in 1950, it showed that players’ decisions were often motivated by concerns about fairness.
This one was organized by Karl-Göran Mäler with the help of Jorgen Weibull and a Cambridge economist, Partha Dasgupta. Lindbeck, who was spending the spring term in Cambridge, oversaw the preparations by telephone. The dozen or so invited speakers represented two generations of leading game-theory researchers, mostly theorists and experimentalists, among them John Harsanyi, Reinhard Selten, Robert Aumann, David Kreps, Ariel Rubinstein, Al Roth, Paul Milgrom, and Eric Maskin. The topic? Rationality and Equilibrium in Strategic Interaction. Most of the participants took it for granted that they were performing for the benefit of the prize committee and assumed that the three graybeards in the group, Harsanyi, Selten, and Aumann, were the likely Laureates.34 Aumann, the white-bearded Israeli dean of game theory, was strutting around “as if he had already won.”
Nudge: Improving Decisions About Health, Wealth, and Happiness by Richard H. Thaler, Cass R. Sunstein
Al Roth, Albert Einstein, asset allocation, availability heuristic, call centre, Cass Sunstein, choice architecture, continuous integration, Daniel Kahneman / Amos Tversky, desegregation, diversification, diversified portfolio, endowment effect, equity premium, feminist movement, framing effect, full employment, George Akerlof, index fund, invisible hand, late fees, libertarian paternalism, loss aversion, Mahatma Gandhi, Mason jar, medical malpractice, medical residency, mental accounting, meta analysis, meta-analysis, Milgram experiment, pension reform, presumed consent, profit maximization, rent-seeking, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, Saturday Night Live, school choice, school vouchers, transaction costs, Vanguard fund, Zipcar
Not surprisingly, afﬂuent, educated parents with large social networks (they volunteer at school with other afﬂuent, educated parents) learned the tricks ﬁrst. They performed better than less afﬂuent, less educated parents, who routinely listed an overdemanded school as a second choice, the worst mistake they could make. Who knows how many of their children lost out on access to ﬁrst-rate educations because of it? The Boston system is still in place around the country, though not in Boston. In 2003 a group of economists led by Al Roth at Harvard pointed out these problems to initially skeptical Boston school administrators. After letting the economists poke around in the internal data, the administrators became convinced of their system’s ﬂaws.6 In response, they adopted the economists’ new strategy-proof choice mechanism, based on one used to match hospitals and medical residents. IMPROVING SCHOOL CHOICES The mechanism does not penalize parents who are unsophisticated about the choice process, allowing them to spend time visiting schools and seeing teachers, rather than estimating the level of competition to get into each school.
air freight, Al Roth, Bernie Madoff, Burning Man, butterfly effect, Cass Sunstein, collateralized debt obligation, computer vision, corporate governance, credit crunch, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, endowment effect, financial innovation, fudge factor, Gordon Gekko, greed is good, housing crisis, invisible hand, lake wobegon effect, late fees, loss aversion, market bubble, Murray Gell-Mann, payday loans, placebo effect, price anchoring, Richard Thaler, second-price auction, Silicon Valley, Skype, The Wealth of Nations by Adam Smith, Upton Sinclair
What we’ve learned is that relying on standard economic theory alone as a guiding principle for building markets and institutions might, in fact, be dangerous. It has become tragically clear that the mistakes we all make are not at all random, but part and parcel of the human condition. Worse, our mistakes of judgment can aggregate in the market, sparking a scenario in which, much like an earthquake, no one has any idea what is happening. (Al Roth, an economist at Harvard, and one of the smartest people I know, has summarized this issue by saying, “In theory, there is no difference between theory and practice, but in practice there is a great deal of difference.”) A few days after Greenspan’s congressional testimony, the New York Times columnist David Brooks wrote that Greenspan’s confession would “…amount to a coming-out party for behavioral economists and others who are bringing sophisticated psychology to the realm of public policy.