Conversation

So, mea culpa: what if superforecasting isn't as useful to the average person as I'd like to think? This week's

post is about the evolution of my thinking here:

Is it really worth it to generate well-calibrated probabilistic predictions? Or would you do better if you assume that all prediction is too difficult, and act as if this were the case?

KimSia Sim (I tweet business & software stuff)

Replying to

and

I like the charles koch part. That made me want to buy the book. By the way, what you wrote reminds me of cynefin framework diagram en.wikipedia.org/wiki/Cynefin_f Forecasting then act is probably good for at best 3 out of 4 quadrants. Some situations are pure chaos

Replying to

and

I'm aware of Cynefin, but I've not looked too deeply into it. I wonder if it's useful. Thanks for the link!

10:43 AM · Apr 28, 2020Twitter Web App

KimSia Sim (I tweet business & software stuff)

Replying to

and

For me, the diagram was enough. Nothing deeper than that for me. I could be wrong. It does strengthen, for me at least, the importance of context for (and I hate to use this phrase) mental models :D Shoot first ask questions later has its place in the right context