The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies Read Free Page A

the Chauffeur team rode up front.
    When one of the Googlers hit the button that switched the car into fully automatic driving mode while we were headed down Highway 101, our curiosities—and self-preservation instincts—engaged. The 101 is not always a predictable or calm environment. It’s nice and straight, but it’s also crowded most of the time, and its traffic flows have little obvious rhyme or reason. At highway speeds the consequences of driving mistakes can be serious ones. Since we were now part of the ongoing Chauffeur experiment, these consequences were suddenly of more than just intellectual interest to us.
    The car performed flawlessly. In fact, it actually provided a boring ride. It didn’t speed or slalom among the other cars; it drove exactly the way we’re all taught to in driver’s ed. A laptop in the car provided a real-time visual representation of what the Google car ‘saw’ as it proceeded along the highway—all the nearby objects of which its sensors were aware. The car recognized all the surrounding vehicles, not just the nearest ones, and it remained aware of them no matter where they moved. It was a car without blind spots. But the software doing the driving was aware that cars and trucks driven by humans do have blind spots. The laptop screen displayed the software’s best guess about where all these blind spots were and worked to stay out of them.
    We were staring at the screen, paying no attention to the actual road, when traffic ahead of us came to a complete stop. The autonomous car braked smoothly in response, coming to a stop a safe distance behind the car in front, and started moving again once the rest of the traffic did. All the while the Googlers in the front seat never stopped their conversation or showed any nervousness, or indeed much interest at all in current highway conditions. Their hundreds of hours in the car had convinced them that it could handle a little stop-and-go traffic. By the time we pulled back into the parking lot, we shared their confidence.
    The New New Division of Labor
    Our ride that day on the 101 was especially weird for us because, only a few years earlier, we were sure that computers would not be able to drive cars. Excellent research and analysis, conducted by colleagues who we respect a great deal, concluded that driving would remain a human task for the foreseeable future. How they reached this conclusion, and how technologies like Chauffeur started to overturn it in just a few years, offers important lessons about digital progress.
    In 2004 Frank Levy and Richard Murnane published their book The New Division of Labor . 1 The division they focused on was between human and digital labor—in other words, between people and computers. In any sensible economic system, people should focus on the tasks and jobs where they have a comparative advantage over computers, leaving computers the work for which they are better suited. In their book Levy and Murnane offered a way to think about which tasks fell into each category.
    One hundred years ago the previous paragraph wouldn’t have made any sense. Back then, computers were humans. The word was originally a job title, not a label for a type of machine. Computers in the early twentieth century were people, usually women, who spent all day doing arithmetic and tabulating the results. Over the course of decades, innovators designed machines that could take over more and more of this work; they were first mechanical, then electro-mechanical, and eventually digital. Today, few people if any are employed simply to do arithmetic and record the results. Even in the lowest-wage countries there are no human computers, because the nonhuman ones are far cheaper, faster, and more accurate.
    If you examine their inner workings, you realize that computers aren’t just number crunchers, they’re symbols processors. Their circuitry can be interpreted in the language of ones and zeroes, but equally validly as true or