Everywhere you look, pundits are talking about automation, machine learning, and artificial intelligence. For some people, this is exciting. It’s a new world of efficiency and lower costs for goods as we witness the biggest breakthroughs in production since the industrial era began.
However, many people are also scared. Bestselling books and sci-fi blockbuster movies have warned us for decades about the dangers of fully automated, artificially intelligent technology. People are terrified that automation could mean the end of low-skilled jobs. For instance, in 1955, General Motors was the largest company in the United States and employed 576,000 people. Sixty years later, Apple was the most profitable company in the U.S., and it had just 66,000 employees.
Whether you’re excited about automation’s potential or worried about its implications, you can’t deny that automation is here. Fortunately, there’s a way we can work with automation instead of against it.
Outsmarted by Our Own Machines
The fear of automation eliminating the need for human employees is strong. According to the McKinsey Global Institute, up to 73 million workers could be displaced by increasing automation by 2030. This often makes it feel like we’re in competition with machines and losing badly.
That’s not just a metaphor: Humans haven’t seemed on top since Deep Blue beat Garry Kasparov at chess in 1997. In 2011, IBM’s Watson easily outwitted the reigning “Jeopardy!” champion, and in 2016, Google’s AlphaGo beat the best Go player in the world. No-limit Texas Hold ’Em poker is the most recent game to be dominated by a machine.
When it comes to work, it’s easy to see what machines can do and to believe we’re beat. But what if it weren’t a competition?
A chess tournament in 2005 allowed humans and machines to work together. Several top players entered with state-of-the-art software. The winners, though, were two amateurs with average machines. Their secret was their unique and advanced process of interacting with the machines.
A computer can examine every possible move in a chess game, but a human can quickly zero in on the few moves worth considering. Rather than analyzing the entire game, the winning chess players focused the machine on the few most relevant moves. This methodology is called the human-computer symbiosis, and it’s the secret to successfully navigating the future of automation.
The Human-Computer Symbiosis
This concept was first introduced by computer scientist J.C.R. Licklider in 1960. In a short paper titled “Man-Computer Symbiosis,” Licklider started with the assumption that eventually, computers will be able to do everything humans can do. As Licklider says, “It seems entirely possible that, in due course, electronic or chemical ‘machines’ will outdo the human brain” in functions that, today, we consider impossible for technology.
However, he suggested we’d experience a “golden period” when humans and computers would augment each other and achieve more together than either could do alone. We are in that golden age today.
The human-computer symbiosis does not mean full automation, with computers handling every task. Neither is it semi-automation, in which humans do the work that isn’t easily automated. A true symbiosis is humans and systems working as partners, both playing to their individual strengths. Computers have a big role in capturing and analyzing data, but humans are still vastly superior when it comes to identifying new patterns and creating beautiful, meaningful designs.
For example, the 9/11 memorial at the World Trade Center used an algorithm that structures groups of victims by their relations to friends and colleagues rather than alphabetically. The algorithm did all the grunt work, but human graphic designers still needed to take that information and display it beautifully.