Google is taking some well-deserved heat for the lack of diversity of their employees. You can read plenty of people prosecuting that case, so I won’t add much beyond saying that if we accept it when these companies say “we know we have to get better” and leave it at that, they can just keep kicking the can down the road forever. The time is now.
I just want to point out: the total employee number is also frightening, just in a different sense. Right now, Google employs 49,829 people. Their market cap is $380 billion. Meanwhile, GM employs over 212,000 people. Their market cap is $55 billion. Now, both companies contribute to a subsidiary economy that employs people too– for Google, its software developers and engineers who design apps and hardware that run on Google infrastructure; for GM, its an army of car salesman and parts manufacturers and mechanics. So which of these satellite economics do you want to bet employs more people? And which of these two companies does our media keep referring to as the future?
The giant companies of yesterday employed huge numbers of people to match their huge revenues. The giant companies of today employ very small numbers of people relative to their huge revenues– and that small footprint is key to their turning those huge revenues into huge profits. Google’s workforce may grow, but it will never grow in a way that makes it proportional to the old giant firms of the past. To do so would be to sacrifice part of what makes these tech giants the successes that they are. In a social system that is built around the ubiquity of paid employment, our policy apparatus and media are celebrating those companies that are doing the most to undermine that ubiquity.
Technological change that increases the efficiency of our productive capacity should be an unalloyed good, but in a system where employment is a necessary precondition of a secure and comfortable life, it can be devastating. There has been no meaningful acknowledgement of this fundamental problem from our policy apparatus. Quite the opposite: elites are pushing companies that rely on automation as a model for our future economy while doing nothing to consider the job losses from that automation. Ed Lazowska, a computer science professor at the University of Washington and Bill and Melinda Gates Chair, writes to the country, “Computer science is the future. Is your child going to be ready for it?” But Lazowska surely knows that many students get computer science degrees and are unable to gain employment in that field. And he surely also knows that perhaps the greatest strength of computer science lies in the infinite scalability of its products. If five U of W computer science students write a great app in their dorm room, that app can be downloaded by 5,000 people or 5,000,000 people, with no need to hire more software developers. Choking the labor market with more and more people in the same field is never a good idea, but doing so with computer scientists is totally contrary to what makes software development so profitable in the first place.
The whole point of Google is that they can write programs that do what large numbers of people used to do. They make money because they don’t have to pay those people, but the people still exist. Google has no responsibility to them. But we do. And please don’t give me the old line, if they build robots to replace the workers in the factory, someone has to maintain the robots! Sure. But if you had to pay as many people as much money to maintain the robots, you would never have had any economic incentive to replace the workers in the first place. If automation didn’t cut jobs or cut wages we wouldn’t bother to do it.
I’m not sure how long our national conversation on innovation and the economy can contain all this cognitive dissonance. But I do know that we have failed to acknowledge the catastrophic job losses that could stem from technological innovations like, oh, let’s say, driverless cars. And that threat is far, far greater than the evidence-free fears that we won’t produce enough competent computer scientists.
Update: To be fair, I want to like to this piece by Lazowska that a friend of mine passed along.