David Autor (left), a professor economics, and Asu Ozdaglar, a professor of electrical engineering, discuss 6-14: Computer Science, Economics, and Data Science. The new major is designed to train students to become the unseen game-makers behind virtual markets.
Photo: Lillie Paquette/School of Engineering
Two sciences tie the knot
A new major combining computer science and economics will prepare students for designing the virtual marketplaces of the future.
Alison F. Takemura
Economics and computer science had always been on friendly terms at MIT. With the growth of cloud computing, e-commerce, machine learning, and online social networks, their relationship grew more serious. Now that these tools and applications have become ubiquitous and gone global, economics and computer science are taking their relationship to the next level.
Starting in the fall of 2017, the two academic departments will offer a joint major — Course 6-14: Computer Science, Economics, and Data Science — because elements of the two fields have become, well, inseparable. The new major aims to prepare students to think at the nexus of economics and computer science, so they can understand and design the kinds of systems that are coming to define modern life. Think Amazon, Uber, eBay, etc.
“This area is super-hot commercially,” says David Autor, the Ford Professor of Economics and associate head of the Department of Economics. “Hiring economists has become really prominent at tech companies because they’re filling market-design positions.”
Because these companies need analysts who can decide which objectives to maximize, what information and choices to offer, what rules to set, and so on, “companies are really looking for this skill set,” he says.
Asu Ozdaglar, the Joseph F. and Nancy P. Keithley Professor of Electrical Engineering and acting head of the Department of Electrical Engineering and Computer Science (EECS), says the fields had moved apart in decades prior, but “for the past 10 to 15 years, there’s been a convergence in research areas between economics and facets of computer science, such as optimization and networking.”
“Now, the motivating applications are so vivid, we have to rethink bringing the fields together,” she says.
MIT students agree. In a poll of the introductory economics course 14.01, which all students are required to take, faculty found that a whopping three-quarters of them were interested in the joint major, Ozdaglar says. She believes students are so intrigued because combining engineered systems and economics requires asking profoundly complex human questions, and then creating equally complex technical models to address them.
“If you’re thinking about humans making decisions in large-scale systems, you have to think about incentives,” she says. “How, for example, do you design rewards and costs so that people behave the way you desire?”
These issues will be familiar to any Uber user caught in a downpour. Suddenly, the cost of getting anywhere increases dramatically, which is also an incentive for Uber drivers to move toward the storm of demand. Surge pricing may be a scourge to customers, but it’s also a way to match supply with demand — in this case, cars with riders.
The new major is designed to train students to become the unseen game-makers behind these types of virtual markets — people who can exert their skill by making it “blatantly obvious for people how to play, in accordance with the market designer’s goals,” says Costis Daskalakis, an associate professor of computer science and electrical engineering who is one of the faculty leads in the new major’s creation.
This combination of fields, Daskalakis points out, is hardly new. Many venerated economists were also early computer scientists, he says. John von Neumann, a pioneer of game theory, which uses mathematics to predict human behavior, was involved in one of the earliest articulations of the design for an electronic computer: the Electronic Discrete Variable Automatic Computer (EDVAC) report published in 1945. Herb Simon, a key figure in the development of artificial intelligence, won both a Nobel Prize in economics in 1978 and the prestigious Turing Award from the Association for Computing Machinery in 1975.
Computer science and economics offer complementary tools, Daskalakis says. For example, a computer science technique like machine learning can reveal patterns in data coming from a social platform. But economics helps pull back the curtain of why such patterns emerge, he says, by offering theories of how people strategized for these patterns to arise.
“You can’t just be a plain economist in this environment, because we’re talking about massive amounts of data and systems implemented on computational platforms,” he says. The new major, he says, will give students a firm footing in both disciplines to create — and understand — virtual markets of the future.
Students should contact Anne Hunter in EECS and Eva Economou in the Department of Economics for more information about Course 6-14.
source: Massachusetts Institute of Technology