(Dr. Chan's website, and "Scaling up analogical innovation with crowds and AI")
He has spent years working on platforms which enable collective sensemaking and encourage creativity, and we picked his brain on these and related efforts.
Some major themes:
- What prior attempts have been made to encourage creativity and crowdsourced innovation? Why did they fail?
- In academia and research it's typical to treat the 'paper' as the basic relevant unit, but might there be ways to represent individual concepts, arguments, and lines of evidence? If so, what kinds of emergent activity might that enable and encourage?
- Are there ways to structure scientific disciplines, so as to better notice gaps in understanding or potentially fertile new directions of inquiry?
- What is the role of analogy in cognition and understanding? How might this help us build tools like really advanced semantic search?
- Could it be possible to scale and automate large parts of the research and problem-solving process? If so, what does that look like?