Deep learning was not a dominant paradigm 20 years ago when Eliezer started working on alignment; early AI approaches were more legible. It was unknown that 'the bitter lesson' (throwing massive computing power at problems without hand-programming specifics) would be how AI progressed, though deep learning's dominance contradicts the earlier hope of building more understandable AI systems with legible internal cognition.