Baxter and the Second Machine Age
A Revolution in Mental Power
The following is adapted from The Second Machine Age by Erik Brynjolfsson and Andrew McAfee, out now in hardcover.
The Industrial Revolution of the 18th century is not just the story of steam power, but steam started it all. More than anything else, it allowed us to overcome the limitations of muscle power, human and animal, and generate massive amounts of useful energy at will. This led to factories and mass production, to railways and mass transportation. It led, in other words, to modern life. The Industrial Revolution ushered in humanity’s first machine age—the first time our progress was driven primarily by technological innovation—and it was the most profound time of transformation our world has ever seen. The ability to generate massive amounts of mechanical power was so important that, in anthropologist Ian Morris’s words, it “made mockery of all the drama of the world’s earlier history.”
Now comes the second machine age. Computers and other digital advances are doing for mental power—the ability to use our brains to understand and shape our environments—what the steam engine and its descendants did for muscle power. They’re allowing us to blow past previous limitations and taking us into new territory. How exactly this transition will play out remains unknown, but whether or not the new machine age bends the curve of human development as dramatically as the steam engine, it is a very big deal indeed.
Computers and other digital advances are doing for mental power what the steam engine and its descendants did for muscle power.
When it comes to work in the physical world, however, humans still have a huge flexibility advantage over machines. Automating a single activity, like soldering a wire onto a circuit board or fastening two parts together with screws, is pretty easy, but that task must remain constant over time and take place in a ‘regular’ environment. For example, the circuit board must show up in exactly the same orientation every time. Companies buy specialized machines for tasks like these, have their engineers program and test them, then add them to their assembly lines. Each time the task changes—each time the location of the screw holes move, for example—production must stop until the machinery is reprogrammed. Today’s factories, especially large ones in high-wage countries, are highly automated, but they’re not full of general-purpose robots. They’re full of dedicated, specialized machinery that’s expensive to buy, configure, and reconfigure.
The Jelly Jar Problem
Rodney Brooks, the roboticist and co-founder of iRobot, noticed something about these modern, highly automated factory floors: people are scarce, but they’re not absent. And a lot of the work they do is repetitive and mindless. On a line that fills up jelly jars, for example, machines squirt a precise amount of jelly into each jar, screw on the top, and stick on the label, but a person places the empty jars on the conveyor belt to start the process. Why hasn’t this step been automated? Because in this case the jars are delivered to the line twelve at a time in cardboard boxes that don’t hold them firmly in place. This imprecision presents no problem to a person (who simply sees the jars in the box, grabs them, and puts them on the conveyor belt), but traditional industrial automation has great difficulty with jelly jars that don’t show up in exactly the same place every time.
The Jelly Jar Solution
In 2008 Brooks founded a new company, Rethink Robotics, to pursue and build untraditional industrial automation: robots that can pick and place jelly jars and handle the countless other imprecise tasks currently done by people in today’s factories. His ambition is to make some progress against Moravec’s paradox—the idea, as roboticist Hans Moravec observed, that it’s “comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.” What’s more, Brooks envisions creating robots that won’t need to be programmed by high-paid engineers; instead, the machines can be taught to do a task (or retaught to do a new one) by shop floor workers, each of whom need less than an hour of training to learn how to instruct their new mechanical colleagues. Brooks’s machines are cheap, too. At about $20,000, they’re a small fraction of the cost of current industrial robots. We got a sneak peek at these potential paradox-busters shortly before Rethink’s public unveiling of their first line of robots, named Baxter. Brooks invited us to the company’s headquarters in Boston to see these automatons, and to see what they could do.
Baxter is instantly recognizable as a humanoid robot. It has two burly, jointed arms with claw-like grips for hands; a torso; and a head with an LCD face that swivels to ‘look at’ the nearest person. It doesn’t have legs, though; Rethink sidestepped the enormous challenges of automatic locomotion by putting Baxter on wheels and having it rely on people to get from place to place. The company’s analyses suggest that it can still do lots of useful work without the ability to move under his own power.
To train Baxter, you grab it by the wrist and guide the arm through the motions you want it to carry out. As you do this, the arm seems weightless; its motors are working so you don’t have to. The robot also maintains safety; the two arms can’t collide (the motors resist you if you try to make this happen) and they automatically slow down if Baxter senses a person within their range. These and many other design features make working with this automaton a natural, intuitive, and nonthreatening experience. When we first approached it, we were nervous about catching a robot arm to the face, but this apprehension faded quickly, replaced by curiosity.
Brooks showed us several Baxters at work in the company’s demo area. They were blowing past Moravec’s paradox—sensing and manipulating lots of different objects with ‘hands’ ranging from grips to suction cups. The robots aren’t as fast or fluid as a well-trained human worker at full speed, but they might not need to be. Most conveyor belts and assembly lines do not operate at full human speed; they would tire people out if they did.
Baxter has a few obvious advantages over human workers. It can work all day every day without needing sleep, lunch, or coffee breaks. It also won’t demand healthcare from its employer or add to the payroll tax burden. And it can do two completely unrelated things at once; its two arms are capable of operating independently.
Most of the innovations that make a robot like Baxter possible have occurred in just the past few years. They’ve taken place in areas where improvement had been frustratingly slow for a long time, and where the best thinking often led to the conclusion that it wouldn’t speed up. But then digital progress became sudden after being gradual for so long. This happened in multiple areas, from artificial intelligence to self-driving cars to robotics.
How did this happen? Was it a fluke—a confluence of a number of lucky one-time advances? No, it was not. The digital progress we’ve seen recently is certainly impressive, but it’s just a small indication of what’s to come in the second machine age.
ERIK BRYNJOLFSSON is the director of the MIT Center for Digital Business and one of the most cited scholars in information systems and economics.
ANDREW McAFEE is a principal research scientist at the MIT Center for Digital Business and the author of Enterprise 2.0.
Watch the authors tour the Baxter factory and more on PBS NewsHour: