If you asked me to describe the rising philosophy of the day, I’d say it is data-ism. We now have the ability to gather huge amounts of data. This ability seems to carry with it certain cultural assumptions — that everything that can be measured should be measured; that data is a transparent and reliable lens that allows us to filter out emotionalism and ideology; that data will help us do remarkable things — like foretell the future.

Over the next year, I’m hoping to get a better grip on some of the questions raised by the data revolution: In what situations should we rely on intuitive pattern recognition and in which situations should we ignore intuition and follow the data? What kinds of events are predictable using statistical analysis and what sorts of events are not?

I confess I enter this in a skeptical frame of mind, believing that we tend to get carried away in our desire to reduce everything to the quantifiable. But at the outset let me celebrate two things data does really well.

First, it’s really good at exposing when our intuitive view of reality is wrong. For example, every person who plays basketball and nearly every person who watches it believes that players go through hot streaks, when they are in the groove, and cold streaks, when they are just not feeling it.