Besides the occasional college student too obsessed with Facebook to spend time on anything else, the human race isn’t yet the slave of computers. Machines aren’t mining people for electricity and feeding them a cocktail of dead bodies as imagined by the “Matrix” trilogy. But they are revolutionizing the way we perceive the universe.

On a fundamental level, progress in modern science requires computers. You may remember (or not) that in introductory science courses, things are “ideal”: balls are thrown in rooms without air, gases are made of particles with no mass, magnetic fields are perfectly uniform and football teams never lose. But when things stop being ideal, when wind and mass and randomness are taken into account, things get hairy quite quickly. Researchers in every discipline rely on computers to study these hairier realms of reality.

But it’s interesting to consider whether the rise of computers in science might herald the beginning of the end of human intuition as the driving force in science, as did a recent episode of the WNYC-produced radio show Radiolab, titled “Limits.” Ph.D. students working on Eureka, a computer at Cornell University, set their computer to watch a pendulum swing back and forth. And then, after doing this for 24 hours … boom! Their computer program produced a simple, beautiful equation: F = ma, Sir Isaac Newton’s second law of motion and one of the most important equations in all of science. In one day, Eureka found something that had eluded the human race for millennia.

Something similar happened to a biologist when he fed Eureka data he had collected from cell behavior. Unlike in the case of the pendulum, though, the equation was like nothing biologists had seen before. And while the equation clearly worked, the biologist was at a loss to understand one crucial thing: why.

Computers are giving us extraordinary power. But does that mean that, in general, scientists like the aforementioned biologist have a less intuitive understanding of their science? The answer I’ve come up with is a resounding “no.”

In fact, Sharon Glotzer told me they do just the opposite. “(Computers) can help give intuition,” she said. She’s the Stuart W. Churchill Professor of Chemical Engineering with faculty appointments in four other departments and Director of Research Computing in the College of Engineering. She felt computers can help scientists see trends in data (think of making a graph).

Now, I know what you might be thinking: Eureka isn’t like other computers most scientists are using. But Eureka is more normal than you might think. Like other computers, it’s just providing analysis based on a computer algorithm written by humans. All computers perform a series of calculations that, Glotzer confirmed, could be performed by a billion well-coordinated eighth-grade mathletes.

And that’s really what computing is all about. August Evrard, Arthur F. Thurnau Professor of Physics, uses computers extensively in his work studying cosmology. He told me that the crazy-cool thing about Eureka, and all computation used in modern scientific research, is its ability to make sense of huge, unfathomably large quantities of data. That power is being harnessed by “almost any field you can think of,” Evrard informed me. The ATLAS detector at the Large Hadron Collider in Switzerland, the largest particle accelerator in the world, generates 3,200 terabytes of data every day. It doesn’t matter how decked out your abacus is — you can’t make sense of that without powerful computers.

If Mark Newman, Paul Dirac Collegiate Professor of Physics, could do billions of mathematical calculations in his head every second, he might not need to use computers. But when you want to know how fast a disease spreads, it doesn’t matter how well you intuitively understand that sneezing on other people spreads infection. The only way to know how soon everyone else will be infected, he told me, is to ask a computer to crunch the numbers. There’s a reason most people don’t just run quick, computational simulations in their head. “If the real world is too complicated to understand,” he said, your computer model probably would be as well.

But such models could always be reduced to the underlying scientific or mathematical principles governing them. Computers like Eureka have an important, intriguing role to play in science — a role I don’t think includes replacing human intuition. Computers are still far from being able to “think” for themselves. Eureka’s biologist didn’t understand why his equation worked, but he’ll have to figure that out in order to build on the computer’s discovery — something unthinking computers can’t do for him. Science just doesn’t work without scientists who understand their fields. And for as long as the universe remains fathomable to humans and computers remain unable to “think,” I don’t see that changing.

Nicholas Clift can be reached at nclift@umich.edu.

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