[⚠ This is a draft]
[This post is a part of my intervention at the workshop “Understanding AI and us”, masterfully designed by Christian Djeffal, Stefan Ullrich, Joanna Bryson and Janina Loh, and hosted by the HIIG in June 2018]
In an world eagerly waiting for results, and expecting them, it is more rewarding for an academic scientist researcher to keep to the light: to draw new questions and new answers by combining the answers and prolonging the questions that science already has, to produce information in the light of the scientific knowledge that’s already enlightening our (academic) (scientific) appreciation of the world.
If science is the sport of renewing our shared understanding of the world so that we humans can adapt the way we presently interact with it together, then this suggests academic scientific research might be hung-up on its own sort of drunkard’s search.
If so where do we find the darkness in science? and what’s in it?
[Answer and everything below in green needs developping]
How to find darkness:
- Carrying out Fundamental computer science research.
- Looking behind biologists’ and other model users’ blunders
- Designing and taking Reverse Turing Tests
What to find in it:
- Fresh fundamental questions, often of the kind that obsoletes the enlightened ones.
- Different perspectives/models.
R. Thomas. J Theor Biol.1973. 42(3):563-85.
R. Thomas and M. Kaufman. Chaos: An Interdisciplinary Journal of Nonlinear Science. 2001. 11(1):180-195.