Brain Inspired
BI 094 Alison Gopnik: Child-Inspired AI

Alison and I discuss her work to accelerate learning and thus improve AI by studying how children learn, as Alan Turing suggested in his famous 1950 paper. The ways children learn are via imitation, by learning abstract causal models, and active learning by implementing a high exploration/exploitation ratio. We also discuss child consciousness, psychedelics, the concept of life history, the role of grandparents and elders, and lots more.

Take-home points:

  • Children learn by imitation, and not just unthinking imitation. They pay attention to and evaluate the intentions of others and judge whether a person seems to be a reliable source of information. That is, they learn by sophisticated socially-constrained imitation.
  • Children build abstract causal models of the world. This allows them to simulate potential outcomes and test their actions against those simulations, accelerating learning.
  • Children keep their foot on the exploration pedal, actively learning by exploring a wide spectrum of actions to determine what works. As we age, our exploratory cognition decreases, and we begin to exploit more what we’ve learned.

0:00 – Intro
4:40 – State of the field
13:30 – Importance of learning
20:12 – Turing’s suggestion
22:49 – Patience for one’s own ideas
28:53 – Learning via imitation
31:57 – Learning abstract causal models
41:42 – Life history
43:22 – Learning via exploration
56:19 – Explore-exploit dichotomy
58:32 – Synaptic pruning
1:00:19 – Breakthrough research in careers
1:04:31 – Role of elders
1:09:08 – Child consciousness
1:11:41 – Psychedelics as child-like brain
1:16:00 – Build consciousness into AI?