Do a YouTube search for “Milton Friedman.” Most of the hits will be speeches mixing economic theory with political philosophy. You’ll see Friedman talking about the value of greed, for example, or holding forth on socialism versus capitalism. Most entertaining is the series of videos titled “Milton Friedman schools young idealist,” in which young, hippie-looking kids stand up and challenge the old man’s capitalist values, only to be hit over the head with Econ 101.

As an econ blogger, I get the sense that this is exactly how many Americans still think of economists—as self-appointed defenders of the free market, spinning theories to show that greed is good. Watching those old Milton Friedman videos, I wonder if that picture might have been accurate in the 1960s and 1970s. But some big things have changed in the field of economics, and America should know about them. Three big changes stand out in particular: Econ today is more data-driven, far less politically conservative, and in general much more like engineering than it used to be.

From theory to data

In a 2012 interview about the future of energy, Nobel Prize winning physicist Robert Laughlin exclaimed: “Economists are idiots!… They just sit around making theories!” And as recently as the mid-1980s, he was right. As economist Dan Hammermesh found in a recent study, the majority of the papers published in top econ journals in 1963, 1973, and 1983 were theoretical papers. But in recent decades, the digital age has dumped a torrent of new data on the economics world, even as new theories have become harder and harder to think up. The result is that, as of 2011, the percentage of theoretical papers had fallen to under 30%. In recent years, the hot technique has been “structural estimation,” which is a sort of blend of theory and empirical work.

What this means is that, more and more, economists are demanding of each other “Oh yeah? Prove it!” Back in the age when economic data was very hard to gather, all you could really do was sit around and philosophize about how people might behave. A lot of useful stuff came out of that philosophizing, but a lot of non-useful stuff came out of it too. Now, thanks to the information age and the tidal wave of data, it’s becoming possible to see what works and what doesn’t in many arenas.

In fact, data has probably made an even bigger advance than those numbers suggest. A lot of the “theory” these days is pure game theory, which resides in econ departments but could just as easily be regarded as a branch of math. The kind of subjects someone in the 1960s would have probably called “economics”–things like tax policy, trade, industrial organization, or finance – are much more likely to be data-driven than in years past, at least in the top journals.

From laissez-faire to liberal

When people say “Econ 101,” they probably mean a world where free markets work perfectly and government intervention is always bad. But open an actual Econ 101 textbook—say, Greg Mankiw’s Principles of Economics—and you’ll find a whole host of reasons why markets fail. Economists have always known that “negative externalities” (like pollution), “public goods” (like research), and “incomplete markets” could clog up the plumbing of the free market. But since the 1970s, economists have also explored how information problems like “adverse selection” and “moral hazard” can do the same. Game theory, which has become more and more popular, shows many cases in which even perfectly rational people can reach a bad equilibrium that leaves plenty of “free lunches” uneaten on the table. Behavioral economics has documented a host of ways in which humans might not be rational, and institutional economics has shown how even rational individuals can act stupidly en masse.

In other words, the simple story of perfectly oiled markets that was created by pioneers like David Ricardo and Kenneth Arrow turned out to be only a base case–the interesting stuff that went on top of that has made everything a lot more complicated.

Maybe that’s one reason why econ is slowly losing its reputation as the “conservative science.” Or maybe it’s the end of the Cold War, meaning that economists no longer have to serve as a bulwark against the threat of communism. But whatever the reason, the facts speak for themselves. A 2005 survey by economists Dan Klein and Charlotta Stern found that most economists favor government intervention in the economy in a wide range of areas, including income redistribution, minimum wage laws, environmental regulation, anti-discrimination laws, and others (and that was before the financial crisis!). They also found that economists are more likely to vote Democratic than Republican by a margin of 5 to 2. But even the Republican-voting economists tended to favor some amount of government intervention in all of these areas.

And let’s not forget that the most famous and widely-read economist in America, Paul Krugman, is also a liberal pundit. The days of Milton Friedman “schooling young idealists” are long gone.

From policy to engineering

In 1989, the great economist Hal Varian declared that economics is a “policy science.” That is ironic, because in 2002, Varian left academia to serve as the chief economist at Google. Nor was the hire a symbolic one. At Google, Varian implemented the system that would end up making that internet titan much of its profit–the system of auctions that powers its online advertising system. Ever wonder why no search engine made Google-like cash in the days before Google? It’s because they didn’t have auction theory. Everyone knows that Google is staffed by brilliant engineers, but it was economists who designed the real secret sauce.

The rise of auction theory has resulted in a boom in private-sector hiring of economists by technology companies (including startups). Auctions are one of those situations in which the “agents” are close to perfectly rational–just the type of case that the theorists of decades past liked to sit around and theorize about. This theory worked. And what works, makes money.

But it wasn’t the only one! Dan McFadden’s “random utility discrete choice” models have seen a wide array of industrial applications, ever since that fateful day when McFadden (who won a Nobel for his efforts) predicted the number of people who would ride the Bay Area’s new BART train, down to a tenth of a percentage point. The “stable matching theory” of Al Roth and Lloyd Shapley (which also earned a Nobel) has helped revolutionize organ donation and school admissions. And of course, Modern Portfolio Theory has helped the finance industry move away from expensive human stock-pickers toward “passive” allocation of capital.

In other words, as economists find more and more theories that predict how markets actually behave, they’ve moved beyond the policy realm and into the realm of engineering.

What it all means

I have the vague sense that if you were an idealistic, brilliant young libertarian in the 1960s and ’70s, you might naturally dream of growing up to be an economist. You might watch a rousing speech by Milton Friedman, and you might imagine that one day you, too, would use the power of logic and rationality and mathematics to ward off the insanity of socialism. Well, America still has some idealistic, brilliant young libertarians, and some of them probably still dream of becoming economists. But now they will be in the minority. They will be joined by quite a few—maybe more—idealistic brilliant young liberals, who recognize the power of markets but also want to figure out how to fix things when markets go wrong. And they will also be joined by quite a few brilliant engineers, for whom political ideals take a back seat to the solving of practical, real-world problems. Econ isn’t what it used to be. The world turns, and academic disciplines move along with it.