Summary:
Alison Gopnik, author of many influential books on cognitive development, tells us about the many abilities of babies. She presented her research during an official TED Talk in 2011. Technology, Entertainment and Design (TED) conferences are a series of international conferences organized by the American non-profit foundation “The Sapling Foundation”. Its purpose is to disseminate “ideas that are worth spreading”.
In her conference, Alison Gopnik explains that twenty years ago, people thought that “babies and young children were irrational, egocentric and illogical” (including psychologists). They believed that children were unable to understand cause and effect, imagine the experiences of other people, or appreciate the difference between reality and fantasy. But developmental science has completely overturned that perception. Indeed, studies has shown that this is the other way: babies can think « like most brilliant scientist ». It is like a brilliant mathematician, he develops himself by making hypotheses, testing them and finding alternatives. Since the 2000s, researchers have started to understand the underlying computational, evolutionary and neurological mechanisms that underpin these remarkable early abilities. Babies are in a developmental stage, like a caterpillar for the butterfly. In other words, when you are a baby you learn how works things that you put it in place later.
For example, the baby can represent the feeling of others. Alison Gopnik and Betty’s Rapacholi in 1996 have experimented this. An experimenter showed 15- and 18-month-olds a bowl of raw broccoli and a bowl of goldfish crackers and then tasted some of each, making either a disgusted face or a happy face. Then she put her hand out and asked, “Could you give me some?” The 18-month-olds gave her broccoli when she acted as if she liked it, even though they would not choose it for themselves. But 15-month olds children give what they like themselves regardless of the opinion of experimenter. So, at 15 months, babies do not realize that others can feel differently from themselves. So even at this very young age, children are not completely egocentric. They can take the perspective of another person, at least in a simple way.
In addition, in a study, a four-year-olds and an adult have tested a blicket detector that worked in an odd way, requiring two blocks on it together to make it go. The four-year-olds were better than the adults at grasping this unusual causal structure. The child is able to make five hypotheses in two minutes and put it in a game situation, he is able to make hypothesis alone.
In conclusion, Alison Gopnik speaks about the baby’s brain like the most powerful learning computer. Their brains are compared to a machine with an apprenticeship program.
Personal opinion:
Like many scientists these days, we believe that a baby is smarter than we thought. People still often think that children are defective adults. We disagree with that. Indeed, according to Piaget’s conception, intelligence grows stage by stage. But Alison Gopnik’s comments confirm that Piaget’s model is not the only possibility. We agree with Alison Gopnik: from birth, the brain is organized but even if it contains innate knowledge, they also have sophisticated learning algorithms.
In our opinion, the intelligence of the child’s brain increases dynamically and non-linearly through multiple cognitive strategies. We know that babies show extraordinary imagination and creativity long before they can read and write. Long before they go to school, they have a remarkable learning attitude. Babies are born with much more than just basic reflexes. For example, we now know that babies have representations of the world in the form of reminiscent symbols of computer programs. Thus, babies are able to decode the information they receive through their eyes and ears, especially from people with expressive faces and captivating voices.
To conclude, we think that in their early years, babies learn more than they will never learn. In fact, learning consists of the active and continuous reprogramming of innate programs. The quantity and quality of interactions are then essential to develop their capacities. Thus, their experiences interact with what they already know, increasing their knowledge, allowing them to make new experiences, formulate them and test new hypotheses, increasing their knowledge and so on.
Clearly, childhood experiences have a crucial role in defining who we are as adults today.
What is missing?
Alison Gopnik’s conference proved that children know a lot and can learn at a very young age. The brain is comparing to a computer with powerful learning program. But is there a lack of information, specifically of how babies learn? What theory does Alison Gopnik rely on?
Looking further, Alison Gopnik (2010) explains in an article that computer scientists and philosophers have begun to use mathematical ideas about probabilities to understand the powerful learning capabilities of scientists and children. Computer programs for machine learning use so-called probabilistic models, also known as Bayesian models. The new approach raises the possibility that baby’s brain works like a computer. Probabilistic models combine two basic ideas. First, they use mathematics to describe the assumptions that children might have about things, people, or words. Second, the programs establish a systematic link between the hypotheses and the probability of different event models, the type of models that emerges from experimentation and statistical analysis in science. Alison Gopnik argues that children’s brains can connect their assumptions about world to probability patterns in the same way.
In fact, children learn about the world much as scientists do, conducting experiments, analyzing statistics and forming theories to account for their observations
Keys words: baby, brain, capacities, scientists, development
Words we have learn: Assumption (hypothèse), patterns (schémas / modèles), worth spreading (qui vaut la peine d’être diffusé), underpin (appuyer / renforcer / soutenir / étayer), grasping (saisissant), apprenticeship (apprentissage)
Bibliographie
Gopnik, A., & Tenenbaum, J. B. (2007). Bayesian networks, Bayesian learning and cognitive
development. Developmental Science, 10(3), 281‑287. https://doi.org/10.1111/j.1467-7687.2007.00584.x
Gopnik, A. (2010). How Babies Think. Scientific American, 303(1), 76‑81.
https://doi.org/10.1038/scientificamerican0710-76
Gopnik, A (2011, july). What do babies think? Communication présentée au TED talk.
Repéré à https://www.ted.com/talks/alison_gopnik_what_do_babies_think
(DREAN Marianne, ROLAND Cindy, SENAN Elodie)