After one of my colleagues posted this article on what makes teams work, I was inspired to read Geoff Colvin’s latest book, Humans Are Underrated: What High Achievers Know That Brilliant Machines Never Will
The first chapters of this book give Clive Barker a run for the money, as Colvin walks through the many different ways in which the economy is going to transform in short order due to computer automation and robotics. I found myself continually having to put down the book to work my way through the implications of some of this:
- I’ve thought a lot about how autonomous cars are going to change the economy from a car-buying perspective. A likely shift towards a sharing model for car-ownership would certainly have broad impacts on jobs – from manufacturing to sales to repairs and parts. And the impact to taxi-drivers has been clear to me, but I never considered the impact on delivery vehicles. Truck driving is the number one job among American men, and it’s hard to believe that this job will exist in a few decades.
- We all know that computers outperform humans at chess, but Colvin runs through other things they have been doing more recently, including reading emotions better than humans, writing articles for publication, and moving into increasingly creative fields like creating recipes for chili and chocolate burritos that were well received at SXSW in 2014.
- Colvin runs through some terrifying human fallibilities as well, like the impact of lunchtime on a judge granting parole. (Did you that while overall, judges grant 35% of paroles, but that the number jumps to 65% immediately following lunch?). While humans are currently skeptical of computers’ ability to handle tasks involving the freedom of humans, it’s hard to look at statistics like that and not acknowledge that algorithmic judgement would be more consistent.
After a few chapters of doom and gloom, Colvin makes his case that the future will involve a shift where economic rewards are centered on deeply human traits – most especially the ability to empathize, rather than the current reward structure towards analytic thought. Although he sometimes undermines his own arguments, he continues to weave together deeply interesting facts.
Colvin makes a strong case for colocated teams in the section on the square of the distance rule. While I’ve personally seen highly effective remote team-members who are able to form deep ties to a mostly colocated team, I found Colvin’s evidence here quite though provoking.
The best measure that we currently have for human empathy, the Reading the Mind Between the Eyes test is something that Colvin talks about quite a bit, as is Collective Intelligence. If you’re responsible for hiring a collaborative team, this book is almost certain to change the way you think about hiring.
In fact, one of the things Colvin probably underplays is the following:
It has become a cliché to say that bringing women into a corporate team, for example, improves the group’s thinking because it introduces a wider variety of thoughts and experiences. That assumes the team was mostly men, and greater diversity improves performance. But the finding of this research is exactly the opposite. It shows that the more women in a group, the smarter it is, plain and simple. The smartest groups in the research had zero gender diversity; they were all women. If the diversity argument held, then replacing a woman with a man would make the group smarter. But it didn’t. On average, it made the group dumber.
Why isn’t this a part of the conversation? It is one of the most perspective-changing things I’ve ever read, and is worth the investment in the book right there.
So yeah, you should probably read this book.