I am interested in your take on how much you think about the critique of forecasting itself being harmful in places with deep uncertainty.
I had read a lot of work previously on forecasting and incorporating "knightian uncertainty". However, I never truly understood how this breaks the notion of forecasting until I started getting uncomfortable with certain public forecasts.
Essentially, you probably don't even know what you want to forecast or what will drive the forecast so probabilities could lock in a sub par world view or sub par goal.
However! Good forecasters are strong at breaking apart a problem to the key drivers (at a point in time) and setting points where they would like to "reset" their forecast or change a policy/strategy.
I mean read the steps of a dynamic adaptive pathway
Step 1: Participatory problem framing, describe the system, specify objectives,and identify uncertainties
Step 2: Assess system vulnerabilities and opportunities, and identify adaptation tipping points
Step 3: Identify contingent actions and assess their ATP conditions and timing
Step 4: Design and evaluate pathways
Step 5: Design the adaptive strategy
That sounds a lot like how you build a strong forecast + some steps for actions as a result of the forecast.
I bring this up because I just appreciate this new world view for myself and I feel your piece above just suggests that forecasting under deep uncertainty requires a wide range of possibilities. Rather than a focus on the dynamic plan to deal with the wide range of possibilities.
I noticed you didn't mention any types of strategies for dealing with forecasting in deep uncertainty. Have you read "Decision Making under Deep Uncertainty". It seems related to the post and a de Neufville contributes a chapter.
I am interested in your take on how much you think about the critique of forecasting itself being harmful in places with deep uncertainty.
I had read a lot of work previously on forecasting and incorporating "knightian uncertainty". However, I never truly understood how this breaks the notion of forecasting until I started getting uncomfortable with certain public forecasts.
Essentially, you probably don't even know what you want to forecast or what will drive the forecast so probabilities could lock in a sub par world view or sub par goal.
However! Good forecasters are strong at breaking apart a problem to the key drivers (at a point in time) and setting points where they would like to "reset" their forecast or change a policy/strategy.
I mean read the steps of a dynamic adaptive pathway
Step 1: Participatory problem framing, describe the system, specify objectives,and identify uncertainties
Step 2: Assess system vulnerabilities and opportunities, and identify adaptation tipping points
Step 3: Identify contingent actions and assess their ATP conditions and timing
Step 4: Design and evaluate pathways
Step 5: Design the adaptive strategy
That sounds a lot like how you build a strong forecast + some steps for actions as a result of the forecast.
I bring this up because I just appreciate this new world view for myself and I feel your piece above just suggests that forecasting under deep uncertainty requires a wide range of possibilities. Rather than a focus on the dynamic plan to deal with the wide range of possibilities.
I noticed you didn't mention any types of strategies for dealing with forecasting in deep uncertainty. Have you read "Decision Making under Deep Uncertainty". It seems related to the post and a de Neufville contributes a chapter.
https://library.oapen.org/handle/20.500.12657/22900