This week, I’ve been writing about forecasting, mainly inspired by Jesse Colombo and all his “The Bubble Is Now!” evangelism – which I wrote about on Monday (“Disaster is Inevitable When The Two-Decades Old Stock Bubble Bursts” and other crazy). And the prelude to this post is yesterday’s How To See Into The Future, You Sexy Beast.
Here is where I was yesterday, based on the original Philip Tetlock 28,000 prediction 18 year study:
- Human forecasters are worse than basic computer algorithms.
- Eclectic pluralists are better forecasters than non-pluralists*.
*What would you call a “non-pluralist”? Totalitarian? Monist?
- And my favourite: famous forecasters are worse than non-famous forecasters.
Oddly – one of the people least convinced by Philip Tetlock’s findings turned out to be Philip Tetlock himself, who maintained that there really are good forecasters out there.
So alongside a long list of academics, he started the Good Judgment project (here’s the website) to try and establish whether they could find any; and if so, what made them different to all the other ‘forecasters’ on the market.
The good preliminary news is: good forecasters exist. He calls them “the superforecasters” – and they’re just better than everyone at calling things right.
Now I accidentally shared this short video clip from youtube yesterday (I thought I’d removed it before posting – turns out, bad internet connection and a dash to board my plane meant that a 2-minutes-older version of the post went out), but it’s four minutes of Tim Harford explaining what makes for a superforecaster.
If you’re too busy to watch the clip, here are:
The three summarised secrets of superforecasting
Also known as “learn from your mistakes” over “explain why you were right to be wrong”. Superforecasters will go back and learn from their bad predictions – because this tells them what they should, and what they should not, be making predictions about.
The basic idea being: some things you can forecast about with some accuracy; some things, less so. So don’t make predictions for the second kind, because it makes you a much more average forecaster on average, rather than being a good forecaster within a limited sphere.
2. Work in Teams
Other people make you justify your predictions. They point out flaws in your logic. You’re forced to rethink and identify your own logical flaws.
There’s also less room for bias when people are busy accusing you of it*.
*Of course, you could refuse to see that you’re biased. But then you’d be a bad forecaster. Because you’d be unable to work in teams. And see point 3 below.
Being convinced that you’re right, and refusing to consider alternatives…well that’s probably unhelpful when there is literally an entire infinite Universe of things that you don’t know.
So really, superforecasters are:
- Humble foxes
- Who work in teams
- And who have learned to tell the difference between the predictable and the unpredictable