When you’re writing regularly, even weekly, the stories can start to blur together. For me at least, it can get to the point where it’s hard to answer the question What have you been working on lately? So I decided this year to look back at everything I wrote in 2015. And as I suspected, a couple major themes emerged. I’ve grouped them together here, mostly for my own clarity. Here’s what I wrote about in 2015:
Algorithms, bias, and decision-making
I spent a lot of time reading, writing, and editing about how humans feel about robots and algorithms, and it culminated in this piece for the June issue of HBR on the subject. Long story short, we’re skeptical of algorithms, but give them a voice and put them inside a robot’s body and we start to become more trusting. If you just want to read about the research on our fear of algorithms, I wrote about that here.
If you read too much about algorithms, you can come away believing that people are pretty hopeless at decision-making by comparison. There’s some truth to that. But another theme I covered this year is just how good some people are at making decisions. I wrote about Philip Tetlock’s latest work, I wrote about his work and others on what good thinkers do, I wrote about why people can come to different conclusions about the same data, and then here on this blog I tried to sum it all up and to offer an optimistic view on bias and human belief.
Inequality, wages, and labor
I was excited to write more about inequality this year, but along the way some of the most interesting assignments were about the more fundamental question: how do labor markets work? This piece asked that question from the perspective of a CEO considering raising wages. This one compared skills and market power as explanations for inequality.
I also wrote once more about whether robots are going to take all our jobs.
But it’s not all good news. Here’s why I’m skeptical of new rules to help more people get paid for overtime. And what do you do when finance seems to improve the productivity of businesses, but at the expense of workers?
A bunch of other stuff
Sometimes distrust makes you more effective.
Scientists require more money if their employer won’t let them publish.
Regulators go easier on socially responsible firms, and the values on your company’s website may matter after all.
Predicting a startup’s success based on idea alone is easier in some industries than others.
Startup “joiners” are sort of like founders, but different.