THE EVOLUTIONARY ROLE OF CHILDHOOD

08 MINDFIELDS | JUNE 2012 WWW.MINDFIELDS.IN

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THE EVOLUTIONARYROLE OF CHILDHOODChildren learn about the world just as scientists do – making predictions, conducting

experiments, analyzing statistics and forming theories. Drawing on her most recent research,renowned scholar and best selling author, Alison Gopnik, demonstrates how cognitive abilities

of babies and young children far surpasses what adults normally attribute them with.

Illustration by Amruta Patil

Some of the research my colleaguesand I have done over the lastthirty years has completely

revolutionised the way we think about babiesand young children, and herefore the way wethink about basic human learning capacities.

What we have discovered is that even the veryyoungest of babies and very young childrenhave capacities to learn that are greater thanthose of the most illustrious of scientists.Discovering these tremendous naturalcapacities to learn ought to influence the waywe teach children.

If we think that education is all about trying toencourage learning, then knowing somethingabout just how powerful these natural learningcapacities are, should help us to improve oureducational system. What I am going to dotoday is talk about the fundamental science oflearning that has emerged, especially over thepast ten years.

Let’s start with one of those questions that youthink people would ask, but they rarely do:“Why is it that we have a period of childhoodat all?” In fact, “why do we have children atall?” If you think about it, at least from someperspectives, you could argue that babies andyoung children are useless after all. They don’tgo out and work; they don’t bring home thebacon; in fact, in some ways, they are worsethan useless because we grown-ups have tospend so much of our time and energy justkeeping them alive and taking care of them.

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So, from a scientific perspective, one ofthe questions we want to ask is, “Why,from an evolutionary perspective, do weactually have this period of childhood atall?”; “Why does childhood even exist?”

It’s a particularly interesting question forus because human beings have a muchlonger period of childhood – a muchlonger period of immaturity – than anyother species.

So, our babies and children aredependent on us for much longer thanthe children of any other species aredependent on their grown-ups. Myoldest son is twenty two, and even nowwe, as his parents, continue investing ourresources in taking care of him.

It turns out that when we look atevolution, there is something of anexplanation for this. Consider twoanimals. On the one hand, there is thecrow, in particular the new Caledoniancrow. Crows, ravens and other animals ofthe Corvidae family are extremelyintelligent animals. The new Caledoniancrow was featured on the cover ofScience magazine because it has learnedhow to use a tool, how to bend a wire inorder to be able to get at a piece of food.

Coincidently, crows have extremely longperiods of immaturity as well; crowbabies are immature, helpless anddependent fledglings for as long as a year.In the case of Caledonian crows, thisperiod lasts as long as two years, whichis a very, very long time in the life of acrow. So these are animals that areextremely intelligent, rely a lot onlearning, have relatively large brains, arevery flexible, and are “smart animals.”

On the other hand, we have the domesticchicken. It represents chickens, turkeys,geese, ducks and all of the birds in thisfamily. With apologies to all chickenlovers, these birds are basically dumb.Though these animals are extremelygood at pecking for grain, they are notmuch good at doing anything else. Notethat chicken babies mature within aspace of few weeks or months.

What we observe is that, there seems tobe a correlation between the length ofthe period of immaturity in the young(how long the babies are dependent and

helpless) and the flexibility andintelligence in them as adult animals.Further, this seems true not only forbirds. Recent reports regardingmarsupials are echoing this observation.Marsupials are animals like kangaroosand wombats, found mostly in Australiaand New Zealand. Among marsupials,the longer the babies live in the mother’spouch, the larger the size of the adultbrain.

There is another interesting aspect to thisstory: when babies are immature for suchlong periods, the adults have to put in“greater parental investment.” So thelonger the period of immaturity, thelarger the brain and the better the adultis at learning, the more the time andenergy that the parents invest in raisingthose babies. This is once again evidentwhen you compare quokkas andopossums.

Quokkas are marsupials with very largebrains and generally both the parentquokkas are engaged in taking care ofjust one baby. Opossums, on the otherhand, are much more small-brainedmarsupials, and they often have manymore babies and there is very littleopportunity for parental investment.

The question that arises now is: “Whywould you see this correlation betweenhow smart the adult animal is, how muchthe adult animal relies on learning, andhow long a period of immaturity theadult undergoes as a baby?”

Animals use a number of strategies tosurvive. Some animals, like the chickenand the opossums, might be very good atdoing just one thing over and over again.They are very well-suited for oneparticular evolutionary task.

Other creatures like the crows andhuman beings are not good at doinganything in particular, but are adept atlearning to do new things, things thatwill suit whatever environment they findthemselves in.

In this manner, we learn to be able to doall the things that we need to do, tosurvive as animals. The latter is a verygood strategy in a lot of ways. Verycharacteristic of human beings, it is thisstrategy that has allowed us to exist and

It’s a particularlyinteresting question

for us because humanbeings have a much longer

period of childhood – amuch longer period ofimmaturity – than any

other species.

So the longer theperiod of immaturity,the larger the brainand the better theadult is at learning, themore the time andenergy that theparents invest inraising those babies.

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survive in more environments than anyother animal, including in outer space.

However, this strategy has one greatdrawback: Until you do all of thelearning you have to do, you’re going tobe helpless. For example, suppose amastodon is charging at you. At thatmoment, you cannot say to yourself,“What shall I do about this? Should Iuse a stick or a slingshot? What wouldbe more effective?.” Instead, you shouldhave already figured out how to deal withthe situation, before the mastodonsactually show up.

So, how and when do we learn all thatneeds to be learned? Evolution seems tohave solved this problem by developinga kind of division of labor. As a result, wehave the early protected period ofchildhood (in which all we have to do isto learn) and then we have adulthood(when we take the things we learned asvery young children and put them to use,to solve problems and do all the thingsthat we need to do as adults).

Our babies are like the research anddevelopment division of the humanspecies, while adults are like theproduction and marketing division. So,there are the ones designed to focus onlearning, finding out, and exploring, andthere is us, the ones who have to takewhat we learned in that early period anduse it in our everyday lives.

This division of labor seems to be thereason we see this correlation betweenimmaturity in the young and intelligencein the adult across so many differentspecies and kinds of animals.

Another way to think about it is using acomputer science analogy. Computerscientists differentiate between systemsthat explore (systems that can learneasily, try out lot of different hypotheses)and those that exploit (systems that cantake one thing and do it extremely well).

Computer scientists have discovered thatboth exploiting and exploring are crucialfor a system that is going to be able tolearn effectively. In fact, in machinelearning, for example in a computerlearning system, in the beginning thesystem starts out by being in the exploremode, where it tries lots and lots of

different things, exploring lots ofpossibilities, and even very unlikelyoptions. After a while, however, it movesinto the exploit mode, where it choosesto do the things that are the best andmost effective for itself. Now if thisevolutionary picture is true, I believe thatchildren are designed to be in thisexplore mode. This implies that childrenare literally for learning.

The reason why we have children is sothat they can explore the world and findout all the things they need to do, thatthey can then use and exploit as adults.Now if this were true, we should not bethinking about children as being sort ofdefective grown-ups, or as grown-upsthat do not have some of the wonderfulcapacities we have as grown-ups.

A more appropriate way would be tothink of children as being in a specificdevelopmental phase of the species, thatis different from the phase of being anadult. To clarify, the difference betweenchildren and adults is rather like thedifference between caterpillars andbutterflies.

In our case, however, the children wouldbe the butterflies who are flutteringaround, exploring and discovering theworld, while we would be the adultcaterpillars who are humping along ourparticular narrow adult path.

Now, if childhood is a different phase inthe developmental history of a species,we might expect to see some signs of thisdifference reflected in the brainstructures of children and adults. It turnsout that we do!

When we look at the development ofneuro connections in the brain, there are acouple of interesting things that happenas children grow older. First of all, whenyou look at the brain in the early periodwhen a child is very young, you can seethat many, many new neuro connectionsare being formed across the brain.

As the child grows older, in the laterperiods of a child’s life, the connectionsthat are effective continue to be used andmaintained. However, there is a bunch ofother neuro connections called “prude.”These are neuro connections that arebeing or have been dropped off.

Our babies are likethe research and

development division ofthe human species, while

adults are like theproduction and

marketing division.

The reasonwhy we have

children is so that theycan explore the world

and find out all thethings they need to do,

that they can thenuse and exploit

as adults.



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Further, if you were to plot thesedifferent kinds of neuro connectionsalong a curve, you will see there is anearly period, when many, many newconnections are being formed, and a laterperiod, when this formation drops off.

This process of forming and droppingneuro connections reflects the kinds oflearning that children are doing atdifferent phases. For example, theconnections in the visual cortex, areformed by the time children are about ayear old, implying that by then the visualsystem has already been established.

Various parts of the brain establishthemselves at different times. Forexample, the process of connecting in theauditory cortex, which is responsible forlanguage, isn’t done until the children arefive years old, when they learn to speak.

Connections in the prefrontal cortex, thepart of the brain that is like the chiefexecutive office of the brain, responsiblefor things like planning and control, arenot finished and fully matured until themid-20s, well into adulthood.

So there is an early period when thebrain seems to be trying out lots of newthings, where there is a great deal offlexibility. Then gradually, as children getolder, the flexibility decreases as thebrain gets better and better at doing onething in particular, till it is not as good atbeing flexible and becomes more plasticat changing or managing to learn newthings.

This evolutionary picture of the brainreiterates that, especially in the earlyperiod, children are really designed toexplore and to learn. We don’t have toteach them how to learn or make themlearn; they are designed to learnspontaneously by themselves.

So, if this is the case, when do we see thiskind of learning? Over the last 15 yearsor so, we have discovered that even veryyoung children are capable of usingcomplicated statistical patterns to inferhow the world works, to discover thecausal structure of the world.

What’s even more impressive is thatchildren usually do a set of naturalexperiments that allow them to learn

more about how the world actuallyworks. The way that they do these naturalexperiments is by doing what we grown-ups think of as “just playing around.”

Now it’s been an idea that’s been aroundin developmental psychology and ineducation, I think intuitively, for a longtime – that children are actually learningthrough play; that by playing, by justexploring the world around them, theyare actually figuring out how the world works.

Children Are Learning Through Play

Until recently, however, we didn’t actuallyhave very good systematic scientificevidence to show that children wereactually learning just through theirspontaneous play. Over the past five orsix years, though, an increasing numberof studies have demonstrated that whatjust looks like children’s spontaneous playis really a kind of research strategy that’shelps them figure out how the worldaround them works.

The study by Christine Legare at theUniversity of Texas, Austin, is anexample. Christine gave children aparticular kind of problem to solve andthen asked them to explain how thatparticular system worked. The systemconsisted of a machine made of blocks.

When presented to a little boy, he sawthat some blocks made this machine go,while others did not. Then he noticedthat the red ones made it move while theyellow ones didn’t. Then he saw that oneof the yellow ones did not help themachine move.

So Christine asked him “Can you figureout why that block didn’t work and canyou figure out why the machine goes theway it does?” In answer, the boy beganmanipulating the blocks systematically,one after another, observing all thechanges each manipulation resulted in,and figured out that some machinesneeded two blocks to light up whileothers needed four!

When the same experiment was repeatedwith several other children, all agedbetween four and five, they all followedthe same general pattern ofexperimentation and manipulation toreach their conclusions.

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...there is an earlyperiod when the brainseems to be trying out

lots of new things, wherethere is a great deal of

flexibility. Then gradually,as children get older,

the flexibilitydecreases

...children are actuallylearning through play;that by playing, by justexploring the worldaround them, they areactually figuring outhow theworld works.



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Thus, when you give the children a realproblem to solve with real objects, and particularly when you give them what Christine called an “anomaly”(something unexpected or unusual) andask them to explain it, they produce thesekinds of experimental behaviors in thevery course of their play.

In the experiment, the little boy actuallytested five different hypotheses abouthow that block could work in the courseof two minutes of spontaneous play! So,by giving children a real system, one thatyou really had to understand and explain,or by giving them something that didn’t quite fit (didn’t suit what theyalready believed), you could provoke thechildren to produce extremely intelligentexploratory kinds of behaviors.

In Christine’s experiments, this was truenot just of particularly bright andarticulate children, but about children in general.

Spontaneous Exploratory Play IsActually A Very Systematic ResearchProgram

Another experiment was done by LauraSchulz and her colleagues at theMassachusetts Institute of Technology(MIT). They wanted to try and test moresystematically the idea that whenchildren play, they are spontaneouslyexploring and finding evidence thatwould be relevant to the problems theyare trying to solve.

The team was interested in problemsabout causes, problems about what kindof things make what other thingshappen. In their experiments they usedthe same block and lighting up of themachine – the Blicket Detector – thatwas used in Christine’s experiment. TheBlicket Detector was invented in my laba few years ago and it has turned out tobe incredibly valuable for a very simpleand inexpensive little piece of equipment.

Laura Schulz and her colleagues tried tosee if four year old children would playdifferently, would manipulate a toydifferently, depending on what its causalstructure is like. In the first part of theexperiment, they showed the children anobject – a toy – in one of two different

conditions. What the children saw werea pair of little beads, those that you canput together to make a single pair.

In the first condition, the children sawthat the two beads can be put togetherand when the two beads are together,they always made the toy go.

They also saw that each of the individualbeads could make the toy go. In thesecond condition, the children saw thatsome of the individual beads made thetoy go but some individual beads didn’tmake the toy go.

Finally, the children were all given a pairof beads, and these beads were eitherglued together or were two beads thatthey could pull apart from each other.They were then left to play with the toy.

The inherent assumptions about thecausal structure were as follows. If youhad seen that all of the beads alwaysmake the toy go, then you already knowthat both of the beads you now have inthe pair are likely to make it go. But ifyou had seen that only some of the beadsmake it go and others don’t make it go,then there might be an interestingquestion to ask: “Which of the beads willmake the toy go?”

What was discovered was that thechildren were much more unlikely to pullthe beads apart in the case where thecausal assumption was that all the beadsmade the toy go. When all of the beadsmade it go, they simply put thecombined glued pair onto the detectorand did nothing more.

However, in the case where theassumption was that only some of thebeads made the toy go, the childrenpulled the toy apart and then tried onebead after another on it. This was easilypossible in the case where the childrenwere presented with two beads thatcould be separated.

In the case where the beads were actuallyglued together so you couldn’t separatethem, the children used a strategy ofholding and twisting the glued pair sothat one part (one bead) was in touchwith the toy at first, and then the other.

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Theywanted to tryand test more

systematically the ideathat when children play,they are spontaneouslyexploring and finding

evidence that would berelevant to the problems

they are trying tosolve.

...whenyou give the

children a real problemto solve with real objects,and particularly when yougive them what Christine

called an “anomaly”...and askthem to explain it, theyproduce these kinds of

experimental behaviorsin the very course of

their play.



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So even when they couldn’t solve theproblem by pulling the beads apart, theysolved it by moving the beads in onedirection or another. They never did thatwhen all of the beads had made the toygo, because there was no need to knowwhich bead made it go and which beaddid not.

These experimental scenarios clearlyshow that what looks like justspontaneous exploratory play is actually avery systematic research program thatthese very young children are using, totry to solve problems about the causalstructure of the world around them, totry and figure out how the world aroundthem actually works.

These experiments, along with a numberof other recent experiments, show thateven five-year-olds are using their play tolearn and that the method they use looksa lot like the one that the very brightest,most intelligent, and most illustriousscientists use to learn.

If children are learning so much throughtheir spontaneous enquiries, explorations,and free play, what does this exploratoryenquiry learning look like when we sitdown to teach children about the world?

In the past few years, we have startedlooking much more systematically at therelationship between learning andteaching. To illustrate, let us look at acouple more experiments that havepitted this kind of spontaneousexploratory learning against teaching, asituation where one has an instructortelling you what you are supposed to do.

Good teachers encourage explorationanyway but here we are considering themore common kind of teaching, wherethe teacher knows what the right answeris and is telling the child this before thechild begins the exploration at all.

In the first experiment, conducted inLaura Shultz’s lab at MIT, they showedthe children a novel toy. This toy has fourinteresting properties. The first is that ithas a little squeaker , which if pushedmakes a squeak. Second, it has a lightthat lights up when you look in it. Third,it has a mirror at the end of one of thetubes in the toy where you can seereflections. Fourth, there is another piecethat you can push to make music.

So there are four novel things that thistoy can do, but none of them are obvious.One has to explore a bit to find out thatthe toy can do all of these four things.

These toys were given to the children intwo different conditions. In the firstcondition, while giving the child the toyto play with, the experimenter would sortof accidentally bump into the toy in a way that one of the four things were set off.

For example, the toy would squeak. Theexperimenter would then say somethinglike, “Gee! Wonder why that happened!”Then bump into something else, setting asecond interesting aspect of the toy off.

Then, the experimenter would simplyleave the toy with the child, to see whatthe child would do with it. It was foundthat the child would then play aroundwith the toy and eventually end upfinding the different things the toycould do, in the course of theirspontaneous play.

The second condition had almosteverything that was the same as thefirst, except that this time theexperimenter showed the child thetoy and said, “This is my toy. I’mgoing to show you how it works.”Then the experimenter would showthe child only one of the things thatthe toy does and would then leavethe child alone.

In these cases, the experimentersfound that the child did not explorethe toy and find the other thingsthat the toy does. Instead, the childwould keep doing what theexperimenter had showed him.

From consistent responses to thesescenarios, the experimentersdiscovered that when you give thechildren the answer, they neverreally discover the otherpossibilities within the learningsituation. The implications of thisare multiple.

On the one hand, direct instructions andteaching is a good way of givingchildren a single right answer, andchildren seem to be sensitive to that.

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Theseexperiments,

along with a numberof other recent

experiments, show thateven five-year-olds are using

their play to learn and that themethod they use looks a lot

like the one that the verybrightest, most intelligent,

and most illustriousscientists use to

learn.

From consistentresponses to thesescenarios, theexperimentersdiscovered that whenyou give the childrenthe answer, they neverreally discover theother possibilitieswithin the learningsituation.



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Children seem to know that if theteacher tells you “this is the way the toyworks,” then that is the way the toyworks and that’s all there is to the waythe toy works.

On the other hand, it seems that inthis circumstance the children did notdo the kind of wide rangingexploration that would give them otheranswers, that would let them find amore diverse range of answers for thesame problem.

The experimenters, Laura and Liz,titled their paper reporting thisexperiment “The ‘double-edged sword’of Pedagogy”. The idea is that pedagogyis sort of a double-edged sword. On theone hand, it lets you get a piece ofinformation across to a child veryeffectively. On the other hand, it maylimit the kind of spontaneousexploration children are capable of.

Children Are Good at Learningfrom Complicated StatisticalPatterns.

Another experiment which makes thesame kind of point was done in my lab.It shows that, in addition to havingcapacities for experimentation inexploration that lets them learn,children are also very good at learningfrom statistical patterns, even quitecomplicated kinds of statistical patterns.

This experiment was also to try and see if children could figure out what it isthat caused what. In this experimentwith four-year-olds we gave them amusical toy.

The toy has lots of things that youcould do to it – handles and rings topull, shake the toy, squash the toy, etc.In addition, sometimes the toy playsmusic, and sometimes it doesn’t.

When the experimenter gave the toyto the child, she would produce threedifferent actions. For example, shewould pull the handle, and then squashthe toy, and then shake the toy. Whenshe did this, sometimes the machinewould play music and sometimes itwouldn’t. The children saw tensequences like this; ten combinationsof different actions that sometimes led

to an answer and sometimes didn’t. Atthe end of it, the experimenter wouldgive the child the toy and simply askthe child to have a go at the toy itself.

What the experimenters were lookingto record was what the child woulddecide to do. Which actions wouldthe child produce to make the toyactually go?

Here are the different kind of patternsof actions and outcomes the childrengot to see. If you were a statistician, youwould see that only the last twoactions, the B and C actions, werenecessary to make the toy go in the BCCondition.

You would conclude that the mostlikely alternative is that only the lasttwo actions were necessary to make themachine go. If you were looking at theother patterns of results that we saw,you’d draw different conclusions.

If for instance, you saw that a particularsequence of the three actions alwaysmade it go, you might conclude thatyou needed all three actions to make itgo. Or, if you saw that only the lastaction made it go, the sensible thingwould be to conclude that, in CCondition, only the last action wasnecessary to make it go.

The question that we were askingourselves was, “Would the children usethis statistical pattern to figure out areally intelligent solution to thisproblem?” The most intelligentsolution was to produce just the twoactions by themselves, even thoughthey had seen that demonstrated bythe experimenter.

What we observed was that when achild is shown a complicated patternof actions, one which made the toyplay music and another which resultedin no music, they pulled out the rightsolution, which was that only the lasttwo actions were necessary to producethe music.

This was a sign of that children,spontaneously behaving in thisincredibly intelligent way, are able toanalyze data that even adults have ahard time doing, in somecircumstances.

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The idea is thatpedagogy is sort of a

double-edged sword. Onthe one hand, it lets you get

a piece of information acrossto a child very effectively. Onthe other hand, it may limit

the kind of spontaneousexploration children

are capable of.

...inaddition to

having capacities forexperimentation in

exploration that lets themlearn, children are also very

good at learning fromstatistical patterns, even

quite complicatedkinds of statistical

patterns.



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Then we tried to do a somewhat differentversion of the experiment. This time,when the experimenter gave the childthe musical toy, she would say, “This ismy toy and I don’t even know how itworks…”

Then in another version, we did theexperiment exactly the same way exceptthis time we told the child, “This is mytoy and I’m going to show you how itworks.” Whenever we did it this way, thechildren always just imitated exactlywhat the experimenter did and did noexploration.

They did exactly the same set of threeactions that the experimenter hadperformed, but they literally neverproduced the more intelligent solution,of just using the last two actions, bythemselves. Yet again, there seems to bea kind of double-edged sword regardingteaching or directly instructing a child.

Directly instructing a child may get themto one solution, the one answer that youthink is the right answer, but it mayactually prevent them from spontaneouslygetting to the really intelligent solutions,which they would get to if just you letthem exercise their own naturalspontaneous learning abilities.

For people who are teaching, thissuggests that we have a greatopportunity, because children (even thevery young ones) are equipped byevolution with these extremely powerfullearning abilities. In fact, that is whatchildren are for: children are for learning.It is not just a nice coincidence that theyhave these wonderful learning abilities.

The very reason they are children is togive them a chance to have thesepowerful learning abilities. What wewould suggest for schools, is toencourage and allow these learningabilities to blossom, to get children toapply these learning abilities to a verywide range of subjects and to a widerange of domains. However, what we endup doing is the opposite – squelchingthose learning abilities.

This is not to say that there isn’t a placefor giving children direct instructions. Infact one of the things that our

experiments show is that children asyoung as four and five are alreadysensitive to the fact that a teacher knowssomething that they may not know, andthat they should learn differently whenthey are learning from a teacher.

However, if that be the only way ofteaching children, it is not really takingadvantage of these extremely powerful,inbuilt, evolutionarily determined brainmechanisms that are there, that areallowing them to learn as much as theyactually do. If we are going to teachchildren the way that they are designedto learn, what we need to do is give themopportunities to explore, to enquire, to dothe sort of research and developmentthat they were actually designed for. nAdapted from a talk by Alison Gopnik at the XSEEDSchool of Tomorrow Conference 2011

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Directly instructing achild may get them toone solution, the one answer that you thinkis the right answer, butit may actually preventthem fromspontaneously gettingto the really intelligentsolutions

ALISOn GOPnIk is a professor ofpsychology and an affiliateprofessor of philosophy at theUniversity of California, Berkeley.An internationally recognizedleader in the study of children’slearning and development, she wasthe first to argue that children’sminds could help us understanddeep philosophical questions.

She is the author of over a hundredjournal articles and of severalbooks, including the best-sellingand critically acclaimed books, “TheScientist in the Crib” and “ThePhilosophical Baby.” She has also written widely aboutcognitive science and psychologyfor Science, The Times LiterarySupplement, The New York Review ofBooks, and The New York Times.


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