(Post 6/N with some rough notes on AI governance field-building strategy. Posting here for ease of future reference, and in case anyone else thinking about similar stuff finds this helpful.)
Some heuristics for prioritising between talent pipeline interventions
Explicit backchaining is one way to do prioritisation. I sometimes forget that there are other useful heuristics, like:
Cheap to pilot
E.g. doesn’t require new infrastructure or making a new hire
Cost is easier to estimate than benefit, so lower cost things tend to be more likely to actually happen
Visualise some person or org has been actually convinced to trial the thing. Imagine the conversation with that decision-maker. What considerations actually matter for them?
Is there someone else who would do most of the heavy lifting?
(Post 6/N with some rough notes on AI governance field-building strategy. Posting here for ease of future reference, and in case anyone else thinking about similar stuff finds this helpful.)
Some heuristics for prioritising between talent pipeline interventions
Explicit backchaining is one way to do prioritisation. I sometimes forget that there are other useful heuristics, like:
Cheap to pilot
E.g. doesn’t require new infrastructure or making a new hire
Cost is easier to estimate than benefit, so lower cost things tend to be more likely to actually happen
Visualise some person or org has been actually convinced to trial the thing. Imagine the conversation with that decision-maker. What considerations actually matter for them?
Is there someone else who would do most of the heavy lifting?