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Early Human Development as a Source of AI Learning
October 15, 2019
If you realized how powerful your thoughts are, you would never think a negative thought.
-Peace Pilgrim

In his article, “The Mind at Work: Alison Gopnik on learning more like children,” on the dropbox.com website, Anthony Wing Kosner writes:

“As Gopnik wrote about in her earlier book, The Scientist in the Crib, from the time they are babies, children learn by testing their theories of the world. And there’s evidence from the work in Gopnik’s lab that young children are quite good at calculating statistical likelihood and updating their beliefs like any good Bayesian scientist. They are driven by curiosity to develop a causal theory of the world. 

Until recently, both curiosity and causality were curiously left out of the standard machine learning toolkit. In this sense, Gopnik has become an influential person in artifical intelligence (AI) circles for being an early proponent of early human development as a source of models for machine intelligence. She wrote a chapter for John Brockman’s recent book Possible Minds on ‘AIs Versus Four-Year-Olds: Looking at what children do may give programmers useful hints about directions for computer learning,’ joining a virtual who’s-who of AI luminaries.”

And in her article, “Building Brains One Relationship at a Time,” (included in the Exchange Essentials article collection, “Growing Brains”), Gina Lebedeva reminds early educators of their role in healthy brain development:

“Take a moment to celebrate by reflecting on all the ways you have observed or supported young children experiencing everyday interactions that were literally growing their brains, enriching their minds, and creating the blueprint for healthy lifelong learning:

  • An embrace, for as long as it takes, during a meltdown that tells a child, ‘I’m always here for you, even when your feelings are so overwhelming and scary to you, that you do scary things to yourself or others.’
  • A child being bathed in rich language, sophisticated vocabulary words, and open-ended questions that offer opportunities to wonder, connect, describe, create, or express.
  • A child sharing a ‘belly-laugh’ with important people in her life, that comes in even the most ordinary moment.

The examples above, and many others, can each be considered applied brain science, and are part of a ‘neuro-relational’ framework to early learning.”

Source: “The Mind at Work: Alison Gopnik on learning more like children,” by Anthony Wing Kosner, dropbox.com, October 7, 2019





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Comments (1)

Displaying 1 Comment
Francis Wardle · October 15, 2019
CSBC
Denver, CO, United States


How is this different from Piaget's schema theory? Its a theory about how children theorize about the world through collecting data and continually refining their theory - schema. Piaget said this years ago - and I've been teaching it in my classes since I started to teach.



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