UC Berkeley's Alison Gopnik: "Babies are the ultimate supercomputers"
Danny In The Valley
The Sunday Times’ tech correspondent brings on Dr Alison Gopnik, a developmental psychologist, to talk about why babies could be the key to artificial intelligence (3:45), the limits to current systems (5:40), infants as supercomputers (8:00), the power of experimentation (10:15), how young brains learn (12:50), coding curiosity (16:15), how the tech industry has come around to kids (17:35), recreating the human brain (20:30), what electricity can tell us about AI regulation (23:00), whether we should be worried (25:35), why we’re just starting to understand the brain (33:20), why we should expect unexpected outcomes (34:35), nerd machismo (37:15), and why babies can teach engineers to improve the world (39:50) For information regarding your data privacy, visit acast.com/privacy
In this episode
- 04:50 - Why are people who work in artificial intelligence coming up against many barriers ?
- 07:21 - How do children learn?
- 08:49 - What are key characteristics of what babies and children are doing in solving problems?
- 16:46 - What is curiosity-based reinforcement?
- 21:11 - What is a key reason as to why children are such good models for artificial intelligence development ?
- 30:34 - What is the next step in how artificial intelligence advances?
- 40:55 - Is it fair to think that the principle of going back to young minds and how they work is where the leading edge of artificial intelligence is currently headed ?
Smash Notes summary for this episode
Why are people who work in artificial intelligence coming up against many barriers ?
Techniques that have been used aren't powerful enough to do the type of learning that humans do. The people who do most of that learning are babies and young children.
How do children learn?
From small amounts of data, they can make very impressive generalizations. Studies show that they are often better than adults at coming up with unlikely ideas.
What are key characteristics of what babies and children are doing in solving problems?
MES:
M - Model building
E - Exploration
S - Social learning
What is curiosity-based reinforcement?
It is a developmental psychology concept that rewards one for making predictions that do not fit with what one already knows.
What is a key reason as to why children are such good models for artificial intelligence development ?
Children are the ones who are actually doing the most learning. A child's brain is going to be better at learning than an adult's brain.
What is the next step in how artificial intelligence advances?
Part of it may involve determining if it is best to develop systems that humans can't do well vs. what they can do well (i.e. processing enormous amounts of data vs. creativity/curiosity).
Is it fair to think that the principle of going back to young minds and how they work is where the leading edge of artificial intelligence is currently headed ?
Yes. The general idea of the way to go is to continue to develop these structured models surrounding the brain development of babies and young children.