Deep listening sessions produce dense transcripts; people have to make sense of that data for it to have an impact on an institution’s decision-making. That synthesis work is the slowest part of the research process and arguably the least valuable. How can we speed that up so museums can get from learning to application sooner and more often?
The bet: A tool can do the synthesis, leaving humans to do the meaning-making.
It succeeds if we can review the output and can move to pattern work without going back to the raw transcript.
It fails if the distinctions are too subtle to encode.
Current status: Iterating based on our first tests.