Do What Computers Can't

Zero To One I read Peter Thiel's new book, Zero To One, the other night. I highly recommend it. It's a quick read (about 240 pages) and is full of great insights on startups and growth. He talks about the fears that the public has over technology. At one time, everyone was afraid that globalization was going to take all of America's jobs because there'd be someone overseas that would do our jobs cheaper than we would. Instead, American jobs have simply transformed. While's there's always some short term pain caused by a transforming economy, unemployment isn't all that much different than it was 20 years ago. The new fear is that software and technology will take all of our jobs. Thiel points out that this is a myth as well. See this excerpt:

Now think about the prospect of competition from computers instead of competition from human workers. On the supply side, computers are far more different from people than any two people are different from each other: men and machines are good at fundamentally different things. People have intentionality—we form plans and make decisions in complicated situations. We’re less good at making sense of enormous amounts of data. Computers are exactly the opposite: they excel at efficient data processing, but they struggle to make basic judgments that would be simple for any human. To understand the scale of this variance, consider another of Google’s computer-for-human substitution projects. In 2012, one of their supercomputers made headlines when, after scanning 10 million thumbnails of YouTube videos, it learned to identify a cat with 75% accuracy. That seems impressive—until you remember that an average four-year-old can do it flawlessly. When a cheap laptop beats the smartest mathematicians at some tasks but even a supercomputer with 16,000 CPUs can’t beat a child at others, you can tell that humans and computers are not just more or less powerful than each other—they’re categorically different.

I love this. There are things that humans can't do as well as computers and things that computers can't do as well as humans. There is now and will always be a ton of opportunity to do things that computers can't.