Where Humans Will Always Beat the Robots

Software might be eating the world, but Rob Miller, a professor of computer science at MIT, foresees a "crowd computing" revolution that makes workers and machines colleagues rather than competitors.

As much as we depend on our gadgets and their accompanying software to do more of our daily tasks—from reminding us to go to meetings to crunching stats for our favorite sports players—human intelligence is far from obsolete. On the contrary, MIT computer science professor Rob Miller believes there will always be a margin between what humans understand and what computers can do.

He provides the following example: Give a computer a paragraph of terribly hard- to-read handwriting today and no available algorithms can decipher the scrawls. But give it to a group of people, and with each other's help, they're able to fairly accurately glean words out of the seemingly unreadable.

"There are a bunch of things that human beings can do that we don't know how to model with computers," Miller says. "One of those is bottom-up and top-down perception. With the handwriting example, you look at individual stroke or mark and say that looks like an 'e' or 'a' or 'i.' That's bottom-up perception. But then top- down is the context around it. Is it by itself with white space around it? Well then it's not an e. That's actually where multiple people tend to help each other."

Miller studies human-computer interaction, specifically a field called crowd computing. A play on the more common term "cloud computing," crowd computing is software that employs a group of people to do small tasks and solve a problem better than an algorithm or a single expert. Examples of crowd computing include Wikipedia, Amazon's Mechanical Turk (where workers outsource projects that computers can't do to an online community) a Facebook's photo tagging feature.

But just as humans are better than computers at some things, Miller concedes that algorithms have surpassed human capability in several fields. Take a look at libraries, which now have advanced digital databases, eliminating the need for most human reference librarians. There's also flight search, where algorithms are much better than people at finding the cheapest fare.

That said, more complicated tasks even in those fields can get tricky for a computer.

"For complex flight search, people are still better," Miller says. A site called Flightfox lets travelers input a complex trip while a group of experts help find the cheapest or most convenient combination of flights. "There are travel agents and frequent flyers in that crowd, people with expertise at working angles of the airfare system that are not covered by the flight searches and may never be covered because they involve so many complex intersecting rules that are very hard to code."

Social and cultural understanding is another area in which humans will always exceed computers, Miller says. People are constantly inventing new slang, watching the latest viral videos and movies, or partaking in some other cultural phenomena together. That's something that an algorithm won't ever be able to catch up to. "There's always going to be a frontier of human understanding that leads the machines," he says.

A post-employee economy where every task is automated by a computer is something Miller does not see happening, nor does he want it to happen. Instead, he considers the relationship between human and machine symbiotic. Both machines and humans benefit in crowd computing, "the machine wants to acquire data so it can train and get better. The crowd is improved in many ways, like through pay or education,” Miller says. And finally, the end users "get the benefit of a more accurate and fast answer."

Presented by

MIchael Copeland

Michael Copeland is a partner at the venture-capital firm Andreessen Horowitz. He was previously a senior editor at Wired.

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