Humans vs algorithms


Jason Collins


July 14, 2017

My first column over at the Behavioral Scientist is live.

The column is an attempt to bring together two potentially conflicting stories.

The first is that the best decisions result from humans and machines working together. This is encapsulated in the story of freestyle chess, whereby the best software is trumped by a human-computer team.

The other is the deep literature on whether humans or algorithms make better decisions, starting with Paul Meehl’s classic Clinical Versus Statistical Prediction. The common story in this literature is that there are few domains where humans outperform statistical or algorithmic approaches (even relatively simple ones). There is also an admittedly thinner literature on what happens when humans can have the result of the algorithm and decide whether to use or overrule it, and the story there is that people should generally leave the algorithm alone.

If you take the latter to be the usual case, the world will not be so much like freestyle chess, but more a case of steady replacement of humans decision by decision. The humans will remain relevant not because they can improve the algorithm’s decisions, but because there are inputs we need to provide, there are domains the algorithms cannot go yet, or we just don’t want to hand over control.

You can read the column here.