I’m very much not a visual person, so I’m probably not the most helpful critic of diagrams like this. That said, I liked Ozzie’s points (and upvoted his post). I’m also not sure what the proper level of abstraction should be for the diagram—probably whatever you find most helpful.
A couple preliminary and vague thoughts on the substantive use cases of forecasting that insofar as they currently appear do so in a somewhat indirect way:
Developing Institutionally Reliable Forecasts: This seems to fall under the “track record” and maybe “model of the world” boxes, but my idea here would be if you can develop a track record of accurate forecasting for some system, you can use that system as part of an institutional decision-making process when it forecasts a result at a certain probability. Drug development would be a good example: the FDA could have a standard of authorizing any drug that a reliable forecaster gave a >95% probability of licensure (or of some factual predicate like efficacy). Another set of applications could be in litigation (e.g. using reliable forecasters in a contract arbitration context). The literature around prediction markets probably has a lot of examples of use cases of this type. It might be difficult, though, to create a forecasting system robust to the problem of becoming contaminated and gamed when tied to an important outcome.
Predictive Coding: There’s an idea in neuroscience that perception involves creating a predictive model of the world and updating the model in response to errors reported by sensory data. Some people (like Karl Friston and Andy Clark) argue that action and perception are largely indistinct and run on the same mechanism—so you act (like lifting your hand) via your brain predicting you will act. SlateStarCodex has a good summary of this. It seems like developing more fine-grained, reliable, and publicly legible forecasting machinery may have useful applications in policy-making by perhaps allowing the construction of a rudimentary version of something analogous. Some of the ideas under my first bullet might fit this concept, but you could also imagine having mechanisms that target the reliable forecast (using the forecast as a correlate of whatever actual change you’re trying to achieve in the world). Another way of thinking of this might be to use forecasting to develop a more sophisticated perceptual layer in policy-making.
I’m very much not a visual person, so I’m probably not the most helpful critic of diagrams like this. That said, I liked Ozzie’s points (and upvoted his post). I’m also not sure what the proper level of abstraction should be for the diagram—probably whatever you find most helpful.
A couple preliminary and vague thoughts on the substantive use cases of forecasting that insofar as they currently appear do so in a somewhat indirect way:
Developing Institutionally Reliable Forecasts: This seems to fall under the “track record” and maybe “model of the world” boxes, but my idea here would be if you can develop a track record of accurate forecasting for some system, you can use that system as part of an institutional decision-making process when it forecasts a result at a certain probability. Drug development would be a good example: the FDA could have a standard of authorizing any drug that a reliable forecaster gave a >95% probability of licensure (or of some factual predicate like efficacy). Another set of applications could be in litigation (e.g. using reliable forecasters in a contract arbitration context). The literature around prediction markets probably has a lot of examples of use cases of this type. It might be difficult, though, to create a forecasting system robust to the problem of becoming contaminated and gamed when tied to an important outcome.
Predictive Coding: There’s an idea in neuroscience that perception involves creating a predictive model of the world and updating the model in response to errors reported by sensory data. Some people (like Karl Friston and Andy Clark) argue that action and perception are largely indistinct and run on the same mechanism—so you act (like lifting your hand) via your brain predicting you will act. SlateStarCodex has a good summary of this. It seems like developing more fine-grained, reliable, and publicly legible forecasting machinery may have useful applications in policy-making by perhaps allowing the construction of a rudimentary version of something analogous. Some of the ideas under my first bullet might fit this concept, but you could also imagine having mechanisms that target the reliable forecast (using the forecast as a correlate of whatever actual change you’re trying to achieve in the world). Another way of thinking of this might be to use forecasting to develop a more sophisticated perceptual layer in policy-making.
I don’t have any immediate reply, but I thought this comment was thoughtful and that the forum can probably use more like it.
thanks!