For sure I agree that the researcher knowing these things is a good start—so getting as many potential researchers to grok these things is important.
My question is about which ideas researchers should focus on generating/elaborating given that they understand these things. We presumably don’t want to restrict thinking to ideas that may overcome all these issues—since we want to use ideas that fail in some respects, but have some aspect that turns out to be useful.
Generating a broad variety of new ideas is great, and we don’t want to be too quick in throwing out those that miss the target. The thing I’m unclear about is something like:
What target(s) do I aim for if I want to generate the set of ideas with greatest value?
I don’t think that “Aim for full alignment solution” is the right target here. I also don’t think that “Aim for wacky long-shots” is the right target—and of course I realize that Adam isn’t suggesting this. (we might find ideas that look like wacky long-shots from outside, but we shouldn’t be aiming for wacky long-shots)
But I don’t have a clear sense of what target I would aim for (or what process I’d use, what environment I’d set up, what kind of people I’d involve...), if my goal were specifically to generate promising ideas (rather than to work on them long-term, or to generate ideas that I could productively work on).
Another disanalogy with previous research/invention… is that we need to solve this particular problem. So in some sense a history of: [initially garbage-looking-idea] ---> [important research problem solved] may not be relevant.
What we need is: [initially garbage-looking-idea generated as attempt to solve x] ---> [x was solved] It’s not good enough if we find ideas that are useful for something, they need to be useful for this.
I expect the kinds of processes that work well to look different from those used where there’s no fixed problem.
For sure I agree that the researcher knowing these things is a good start—so getting as many potential researchers to grok these things is important.
My question is about which ideas researchers should focus on generating/elaborating given that they understand these things. We presumably don’t want to restrict thinking to ideas that may overcome all these issues—since we want to use ideas that fail in some respects, but have some aspect that turns out to be useful.
Generating a broad variety of new ideas is great, and we don’t want to be too quick in throwing out those that miss the target. The thing I’m unclear about is something like:
What target(s) do I aim for if I want to generate the set of ideas with greatest value?
I don’t think that “Aim for full alignment solution” is the right target here.
I also don’t think that “Aim for wacky long-shots” is the right target—and of course I realize that Adam isn’t suggesting this.
(we might find ideas that look like wacky long-shots from outside, but we shouldn’t be aiming for wacky long-shots)
But I don’t have a clear sense of what target I would aim for (or what process I’d use, what environment I’d set up, what kind of people I’d involve...), if my goal were specifically to generate promising ideas (rather than to work on them long-term, or to generate ideas that I could productively work on).
Another disanalogy with previous research/invention… is that we need to solve this particular problem. So in some sense a history of:
[initially garbage-looking-idea] ---> [important research problem solved] may not be relevant.
What we need is: [initially garbage-looking-idea generated as attempt to solve x] ---> [x was solved]
It’s not good enough if we find ideas that are useful for something, they need to be useful for this.
I expect the kinds of processes that work well to look different from those used where there’s no fixed problem.