Many of the interesting challenges in computer science, nanotechnology, and synthetic biology entail the construction of complex systems. As these systems transcend human comprehension, will we continue to design them or will we increasingly evolve them? As we design for evolvability, the locus of learning shifts from the artifacts themselves to the process that created them. There is no mathematical shortcut for the decomposition of a neural network or genetic program, no way to “reverse evolve” with the ease that we can reverse engineer the artifacts of purposeful design. The beauty of compounding iterative algorithms (evolution, fractals, organic growth, art) derives from their irreducibility.
Steve covers a wide range of topics (this list from the titles of some of his slides):
Exponential growth of Tech Innovation
Black Swan Events
Building Complex Systems – Top-Down vs Bottom-up
– Diversity vs Ability
– Disagreement vs Consensus
– Voting Policy vs Coherence or Comprehensibility
– Communication Tuning vs Leadership
I think it is one of those talks I will watch a few times and think about a lot.