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Totally, I find that tools mostly augment the induction part of synthesis (logging external facts, “inspiration”), and the later deduction part (once you have a structure, investigate how existing knowledge fits, try to interrogate it, and investigate its implications)

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The model-making part where you work with a limited set of data & make the mental leap definitely happens away from the tool. But the tool’s ability to capture and recall inspiration at a whim can help surface material for connection where you would otherwise forget them.

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Hmm. I agree with most of what you’re saying (and I think the way you put it — re: splitting this to deduction/induction) but I want to push back on this last bit a bit. I know it’s a common narrative that a tool can resurface inspiration — but is this really important?

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I guess where I’m coming from is this: I do a decent job at synthesis, and I am friends with folk who are good synthesisers. And none of us find that resurfacing for connection is a bottleneck for our process. The real difficulty is in the theory crafting/model creation.

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And so I worry that this narrative of ‘oh you can connect your thoughts to resurface / generate new insight’ is a neat story that isn’t built on a actual cognitive task analysis of good synthesisers. It is, instead, built on a toolmaker’s assumptions about synthesis.

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I don’t believe my own argument as well, btw, because it might be a limitation of the tools I (and others like me) use, so I intend to investigate this claim more thoroughly. But it certainly doesn’t match what comes out of a CTA of our process.

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Who are you speaking to who are doing this synthesis work? In what domains? My experience comes from graphic design, product design, UX research.

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Wall Street research, summarising and keeping abreast of the latest research (on aging, expertise, e.g. nintil.org), synthesizing decision making research, keeping track of the metagame of private equity and investing, keeping track of burnout resilience RCTs.