I think this is obfuscating the good points, I appreciate many of the points but they seem to be ticked off rather than front and center.
I am afraid the frame of “When to” is promoting a binary mindset which is fundamentally opposed to proper decision making.
I am reading it as attempting to have decision points for when to collapse distributions to point estimates. “Use of explicit probabilities”
You always have the explicit distribution. You always have a policy (why didn’t it say policy in the alliterative p title) You always break apart the timeline and draw the causal dag.
This is offensive to reasonable planning: “Some creatures would be better served by mapping out the dynamic dependencies of the world” Always draw the dependencies!
The question is when to communicate the point estimate versus distribution. When to communicate the dependencies or just the final distribution.
People allege the crazy train when you are imagining a point estimate represents the best information that is used for making a decision. That is the implicit suggestion when you discuss point estimates.
Quick suggestions, communicating a point estimate is poor:
When the outcomes have unequal weightings across decision makers. So each decision maker needs to attach their weights to get the weighted EV
When decisions are sensitive to reasonable perturbation of the point estimate. Ie when two good models disagree to the point that it implies different decisions.
When the probability is endogenous to the decisions being made.
Poker is unnecessary for the analogy, just probability of a draw from an urn.
We are speculating on how many balls are in the urn when a much better question would be Given we get the urn will we know how many balls are in it? How much does that cost? Can we do things before opening the urn that change the contents? How much does that cost?
Can we not sign for the urn when the Amazon delivery guy arrives? How much does that cost?
Ok that is a joke, but the idea is that we don’t know what recourse we have and those actually are important and affect the point estimate.
The probability is downstream from certain decisions, we need to identify those decisions that affect the probability.
Does that mean the point estimate is useless, well maybe because those decisions might reduce the probability by some relative amount, ie if we get congress to pass the bill the odds are half no matter what they were before.
If you go, yeah but I say it is 27.45% and 13.725% is too high. They a decision maker goes “Sure, but I still want to halve it, give me something else that halves it stop telling me a number with no use”
You mention relative likelihood, but it is buried in a sentence of jargon I just had to search for it to remember if you said it.
Finally, frame the analysis relative to a better considered approach to Robust Decision Making, a la Decision Making Under Deep Uncertainty, not relative to Scott or Holden’s world view which are just poor starting points.
https://twitter.com/jhaushofer/status/1685541903813804033?s=20
″Malengo sent two pilot cohorts of students from Uganda to Germany (6 in Fall 2021, 17 in Fall 2022). All of these students are currently in Germany and making progress towards their degrees.
Students come from low-income families, living on USD 1.40 per person per day (USD 42 per person per month) before program entry
After 11 months in Germany, students earn on average USD 095/month in their part-time jobs (after tax), representing a 2200% increase (1000% after taking prices into account).
While studying, students send an average of USD 120 per month to their families in Uganda, representing a 110% increase in the remaining family members’ income.
All current Malengo students expect to graduate within 4 years; the current average (and median) grade is 2.5 (1=best, 4 = pass, 5=fail)
″