Up until fairly recently, scientists, writers and philosophers alike have viewed human babies as little more than primitive adults. Through love and attention, babies were to be shaped into autonomous thinkers—like us. It was almost as if their brains were like new computers, whose software we needed to install over time.
But in the past few decades, explains University of California-Berkeley psychologist Alison Gopnik, science has turned this view on its head. Not only are babies' brains structurally quite different from those of adults, but they also function in a way that makes them better than adults at learning new things. In other words, babies seem to be specially designed for exploration and finding out how things work. They're little scientists...at least, that is, until those exploratory habits get replaced over time by less flexible thinking styles.
"Babies have many, many more neural connections being formed, many more synapses being formed, than we adults do," says Gopnik. "So it's as if early on, we have this brain that is really designed for learning, a brain that's very flexible and plastic and responds a lot to experiences. And then later on, as we get older, we have a brain that's more sort of a lean, mean machine, really designed to do things well, but not nearly as flexible, not nearly as good at learning something new."
Gopnik spoke with Inquiring Minds last weekend at the Bay Area Science Festival. You can listen to the interview above.
An internationally recognized leader in the study of children's development, Gopnik was the first to argue that children's minds could help us understand deep philosophical questions. She's written more than 100 journal articles and several books, including "The Scientist in the Crib" and "The Philosophical Baby," and her 2011 TED talk has generated over a million views.
"Babies and young children are like the research and development division of the human species, and we grownups are production and marketing," Gopnik says. What this means is that in many ways, babies are very good at thinking scientifically—as a number of experiments have shown–while many adults are not.
Understanding statistics and probabilities, for instance, is something that is difficult for most adults. So it's striking that young children are actually quite good at solving problems using an intuitive understanding of probability.
Take one study of babies' statistical prowess by Cornell psychologist Tamar Kushnir and her colleagues, who had 20-month-old infants watch while an experimenter pulled either yellow rubber ducks or green rubber frogs from a clear plastic box. Sometimes the box contained mostly ducks, and other times mostly frogs—meaning that if the experimenter pulled five frogs in a row from a duck box, she was doing something statistically improbable, something that could only have been done by choice.
Infants knew that too: When their turn came to choose either a frog or a duck for the experimenter to play with, they often chose the statistically unlikely option when the experimenter herself had done so. If the experimenter had pulled frogs from the duck box, then the infants tended to choose a frog as well. However, in scenarios where the experimenter had done nothing improbable—e.g., simply pulling ducks from the duck box—the infants' choices were less clear, as presumably they were inferring that since the experimenters' choice wasn't improbable, she didn't much care what kind of animal she got. In other words, even 20-months-olds can figure out that by defying probabilities, the experimenter was showing a preference for a particular kind of toy.
"To a striking extent, children use data to formulate and test hypotheses and theories in much the same way that scientists do," writes Gopnik in the journal Science. "Scientists learn about the world in three ways: They analyze statistical patterns in the data, they do experiments, and they learn from the data and ideas of other scientists. The recent studies show that children also learn in these ways."
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