1. EP2.
Social learning
Elena Pasquinelli
Educa4on, cogni4on, cerveau
Cogmaster 2010‐2011
2. Transmission of generic knowledge
• “There is … a unique way to acquire generic • Induc4on problem: Humans are capable of
knowledge from a single instance of transmiTng/extrac4ng general knowledge
informa4on intake, namely, when it is from par4cular instances.
transmiEed through human communica4on. • When such instances are repe44ve and
• Moreover, the transmission of such generic frequent, sta$s$cal mechanisms* are
knowledge is not restricted to linguis4c invoked.
communica4on. • When this is not the case (single instance) we
• … you acquire kind‐generalizable knowledge need a further mechanisms for explaining
from a single manifesta4on. induc4on.
• In such cases, the observer does not need to • Such a mechanisms is hypothesized to rely
rely on sta4s4cal procedures to extract the on human‐human communica4on
relevant informa4on to be generalized as this • Verbal and not verbal (demonstra4on)
is selec4vely transmiEed to her by the
communica4ve demonstra4on.
• Such a short‐cut to generic knowledge
acquisi4on relies heavily on the
communica4ve coopera4on and epistemic
benevolence of the communica4ve
partner.” (Gergely & Csibra, p. 3)
4. Learning = modifica4on of behavior as a
consequence of experience
• “the modifica$on of behavior in the light of • Learning is a common func4on to
experience. Even simple organisms such as
Aplysia learn according to this defini4on. In different animal species
fact, a number of different kinds of learning
have been iden4fied in work with animals. • Different forms of learning:
These include habitua$on, associa$ve – Habitua4on, associa4on,
learning, social learning (e.g. by emula4ng
others), and “insight” learning, where imita4on, explana4on‐analogy
solu4ons to problems come “in a flash”.
Habitua4on and associa4ve learning in
infants have already been discussed. In
cogni)ve psychology, learning is usually
measured in terms of what has been
remembered as a result of learning, either
via measures of recogni)on, or via
measures of recall. We will examine learning
by imita$on, learning by analogy, and
explana$on‐based learning here, none of
which are found in animals (apart perhaps
from excep4onal animals such as language‐
reared chimps). Explana4on‐based learning is
a form of causal learning. Causal learning is
extremely important in cogni4ve
development, and is found in animals in
some forms…” (Goswami, 2008, p. 61‐62)
5. Early learning mechanisms
• “The assump4on will be one of common learning mechanisms, namely
• sta4s4cal learning,
• learning by imita4on,
• explana4on‐based or causal learning
• and learning by analogy.
• Using these simple learning mechanisms, the brain appears to build up complex representa4ons
about how the world is.” (Goswami, 2008, p. 52)
• “At least three types of learning also appear to be func4oning from very early in development. One
is associa$ve learning. Babies appear to be able to make connec4ons between events that are
reliably associated, even while in the womb.
• Once outside the womb, they appear to be able to track sta$s$cal dependencies in the world, such
as condi4onal probabili4es between visual events or between sounds. This turns out to be a very
powerful learning mechanism.”
• “The second type of learning that appears to be available early is learning by imita$on. This may be
par4cularly important for the development of social cogni4on.”
• “Finally, infants appear to be able to connect causes and effects by using “explana$on based”
learning. … The causal inferences made by infants provide an extremely powerful mechanism for
learning about the world. Infants are not simply detec4ng causal regulari4es but appear to be
construc4ng causal explana4ons for new phenomena on the basis of their prior knowledge. One
mechanism they use is learning by analogy” (Goswami, 2008, p. 3‐4)
6. Sta4s4cal learning
• « When we make inferences that are not • Sta4s4cal learning is involved in the processing of
necessarily deduc4vely valid (when we go beyond interrela4ons between features and the
the informa4on given) we are reasoning induc4vely. differen4a4on of prototypes
… For example, when children learn about the • Experiments of Rosch, 1978; Younger & Cohen,
category « birds », they may learn about one or two 1983; Younger, 1985; Kirkham et al., 2002
exemplars (e.g. the robins and sparrows in their
back garden). However, they are happy to generalize • Kirkham, et al., 2002: a visual habitua4on task is
proper4es like « lives in a nest » to other birds... based on simple colored geometric shapes (blue
» (Goswami, 2008, p. xvii) cross, yellow circle, green triangle) presented as a
con4nuous stream in a par4cular order; each infant
• “Younger’s cartoon‐animal experiments saw a stream of 6 shapes with tree pairings;
demonstrated that infants could code the following habitua4on the infants saw 6 test displays,
correla4onal structure between the different half of which comprised the familiar sequence and
features being manipulated by the experimenters. half new sequences with different transi4onal
This suggests a form of sta4s4cal probabili4es. All groups looked significantly longer
learning.” (Goswami, 2008, p. 18) to the new sequences.
• “Using the regulari4es in input to learn which
features co‐occur together.” (Goswami, 2008, p. 18)
• “… infants have an impressive ability to keep track of
the sta4s4cal structure of the input”
• “This experiment with geometrical shapes suggests
that infants are able to learn about environmental
structure at a fairly abstract level.
• The ability to track condi4onal probabili4es provides
a very powerful domain‐general learning
mechanism for extrac4ng structure from the
physical world of objects. ” (Goswami, 2008, p. 19)
7. Language acquisi4on
• Language acquisi4on has provoked a debate • “Humans’ capacity for speech and language provoked classic debates on nature
on nature (Chomsky) vs nurture (Skinner) versus nurture by strong proponents of na4vism (Chomsky, 1959) and learning
• Cri4cal periods in language learning differ in (Skinner, 1957).
the three aspects of language: phone4cs • Language learning is a deep puzzle that our theories and machines struggle to solve
(before 12 months), syntax (18‐36), lexicon but children accomplish with ease. How do infants discover the sounds and words
(forever) used in their par4cular language(s) when the most sophis4cated computers cannot?
• Why are children beEer than adults? What is it about the human mind that allows a young child, merely one year old, to
• Kuhl, 2004: neural commitment understand the words that induce meaning in our collec4ve minds, and to begin to
use those words to convey their innermost thoughts and desires? A child’s budding
– Once perceptual systems are commiEed ability to express a thought through words is a breath‐taking feat of the human
they filter new informa4on mind.
– Commitment is done between 6 and 12
months (for phone4cs): before, children • Studies indicate, for example, that the cri4cal period for phone4c learning occurs
dis4nguish all the phone4c units of all prior to the end of the first year, whereas syntac4c learning flourishes between 18
languages and 36 months of age. Vocabulary development ‘‘explodes’’ at 18 months of age, but
does not appear to be as restricted by age as other aspects of language learning—
one can learn new vocabulary items at any age.
• How can children succeed in a difficult task as
iden4fying and grouping the more or less 40 • Work in my laboratory led me to advance the concept of neural commitment, the
phonemes that compose their language? In idea that neural circuitry and overall architecture develops early in infancy to detect
the middle of a great variability of speech? the phone4c and prosodic paEerns of speech (Kuhl, 2004; Zhang et al., 2005, 2009).
This architecture is designed to maximize the efficiency of processing for the
• Implicit learning processes commit the brain language(s) experienced by the infant. Once established, the neural architecture
to the proper4es of na4ve language speech arising from French or Tagalog, for example, impedes learning of new paEerns that
do not conform
• Infants’ ability to learn which phone4c units are relevant in the language(s) they are
exposed to, while decreasing or inhibi4ng their aEen4on to the phone4c units that
do not dis4nguish words in their language, is the necessary step required to begin
the path toward language.
• These data led to a theore4cal argument that an implicit learning process commits
the brain’s neural circuitry to the proper4es of na4ve‐language speech, and that
neural commitment has bi‐direc4onal effects – it increases learning for paEerns
(such as words) that are compa4ble with the learned phone4c structure, while
decreasing percep4on nonna4ve paEerns that do not match the learned scheme
(Kuhl, 2004). (Kuhl, 2010)
8. Sta4s4cal learning and language
• Sta4s4cal learning (Saffran, et al, 1996) • “Sta4s4cal learning is computa4onal in nature, and reflects implicit rather than
applies to the capacity to iden4fy phonemes explicit learning. It relies on the ability to automa4cally pick up and learn from the
and to the capacity of segmen4ng words sta4s4cal regulari4es that exist in the stream of sensory informa4on we process, and
– Japanese and English infants are both strongly influences both phone4c learning and early word learning.
exposed to both /r/ and /l/ sounds, but in • To illustrate, adult speakers of English and Japanese produce both English r‐ and l‐like
Japanese the sound /r/ is much more sounds, even though English speakers hear /r/ and /l/ as dis4nct and Japanese adults
frequent hear them as iden4cal. Japanese infants are therefore exposed to both /r/ and /l/
– Babies spot the transi4onal probabili4es sounds, even though they do not represent dis4nct categories in Japanese. The
between syllables presence of a par4cular sound in ambient language, therefore, does not account for
infant learning. However, distribu4onal frequency analyses of English and Japanese
show differen4al paEerns of distribu4onal frequency; in English, /r/ and /l/ occur
very frequently; in Japanese, the most frequent sound of this type is Japanese /r/
which is related to but dis4nct from both the English variants.
• studies indicate infants pick up the distribu4onal frequency paEerns in ambient
speech, whether they experience them during short‐term laboratory experiments, or
over months in natural environments, and can learn from them.
• Sta4s4cal learning also supports word learning. Unlike wriEen language, spoken
language has no reliable markers to indicate word boundaries in typical phrases. How
do infants find words? New experiments show that, before 8‐month‐old infants know
the meaning of a single word, they detect likely word candidates through sensi4vity
to the transi4onal probabili4es between adjacent syllables. In typical words, like in
the phrase, ‘‘preEy baby,’’ the transi4onal probabili4es between the two syllables
within a word, such as those between ‘‘pre’’ and ‘‘Ey,’’ and between ‘‘ba’’ and ‘‘by,’’
are higher than those between syllables that cross word boundaries, such and ‘‘Ey’’
and ‘‘ba.’’ Infants are sensi4ve to these probabili4es. When exposed to a 2 min string
of nonsense syllables, with no acous4c breaks or other cues to word boundaries, they
treat syllables that have high transi4onal probabili4es as ‘‘words’’ (Saffran et al.,
1996) ” (Kuhl, 2010)
9. Language : sta4s4cal learning is not
enough
• Sta4s4cal learning can have strong and • At 9 months of age, the age at which the ini4al universal paEern of infant percep4on
durable effects on phone4cs at 9 months of has changed to one that is more language‐specific, infants were exposed to a foreign
age, and with short‐4me exposure to language for the first 4me (Kuhl et al., 2003). Nine‐month‐old American infants
sta4s4cal regulari4es listened to 4 different na4ve speakers of Mandarin during 12 sessions scheduled over
– 9 months old children can learn to 4–5 weeks. The foreign language ‘‘tutors’’ read books and played with toys in
dis4nguish Mandarin phonemes from sessions that were unscripted. A control group was also exposed for 12 sessions but
exposure to play and interac4on with a heard only English from na4ve speakers. Ayer infants in the experimental Mandarin
Mandarin speaking tutor exposure group and the English control group completed their sessions, all were
• But is sta4s4cal learning enough? tested with a Mandarin phone4c contrast that does not occur in English. Both
– 9 months old children cannot learn to behavioral and ERP methods were used. The results indicated that infants had a
dis4nguish Mandarin phonemes from a remarkable ability to learn from the ‘‘live‐person’’ sessions – ayer exposure, they
Mandarin speaking TV‐canned / performed significantly beEer on the Mandarin contrast when compared to the
audiotaped tutor control group that heard only English. In fact, they performed equivalently to infants
• Social interac4on is required of the same age tested in Taiwan who had been listening to Mandarin for 10 months
(Kuhl et al., 2003). The study revealed that infants can learn from first‐4me natural
exposure to a foreign language at 9 months, and answered what was ini4ally the
experimental ques4on: can infants learn the sta4s4cal structure of phonemes in a
new language given first‐4me exposure at 9 months of age? If infants required a long‐
term history of listening to that language—as would be the case if infants needed to
build up sta4s4cal distribu4ons over the ini4al 9 months of life—the answer to our
ques4on would have been no.
• Would infants learn if they were exposed to the same informa4on in the absence of a
human being, say, via television or an audiotape? If sta4s4cal learning is sufficient,
the television and audio‐only condi4ons should produce learning. Infants who were
exposed to the same foreign‐language material at the same 4me and at the same
rate, but via standard television or audiotape only, showed no learning—their
performance equaled that of infants in the control group who had not been exposed
to Mandarin at all.” (Kuhl, 2010)
10. Language : sta4s4cal learning is not
enough
• Social interac4on • “social interac4on creates a vastly different learning situa4on, one in
can have an effect which addi4onal factors introduced by a social context influence
learning. Ga4ng could operate by increasing: (1) aEen4on and/ or
on learning arousal, (2) informa4on, (3) a sense of rela4onship, and/or (4) ac4va4on
of brain mechanisms linking percep4on and ac4on.
through: • Infant aEen4on, measured in the original studies, was significantly
higher in response to the live person than to either inanimate source
– Enhancement of (Kuhl et al., 2003). … AEen4on has been shown to play a role in the
sta4s4cal learning studies as well.”
aEen4on • during live exposure, tutors focused their visual gaze on pictures in the
books or on the toys as they spoke, and the infants’ gaze tended to
– Addi4onal follow the speaker’s gaze, as previously observed in social learning
studies (Baldwin, 1995; Brooks and Meltzoff, 2002). Referen4al
informa4on (gaze informa4on is present in both the live and televised condi4ons, but it is
to object) more difficult to pick up via television, and is totally absent during
audio‐only presenta4ons. … Infants who shiyed their gaze between the
– Ac4va4on of tutor’s eyes and newly introduced toys during the Spanish exposure
sessions showed a more nega4ve MMN (indica4ng greater neural
mirror systems, discrimina4on) in response to the Spanish phone4c contrast. Infants
who simply gazed at the tutor or at the toy, showing fewer gaze shiys,
and other produced less nega4ve MMN responses. The degree of infants’ social
engagement during sessions predicted both phone4c and word learning
mechanisms for —infants who were more socially engaged showed greater learning as
percep4on‐ac4on •
reflected by ERP brain measures of both phone4c and word learning.
Social interac4on may ac4vate brain mechanisms that invoke a sense of
linking in the brain rela4onship between the self and other, as well as social understanding
systems that link percep4on and ac4on “ (Kuhl, 2010)
11. Implicit learning
• “There is no doubt that many of our most fundamental abili4es, whether they • Implicit learning theories are based on the
concern language, percep4on, motor skill, or social behavior, reflect some kind of capacity of extrac4ng regulari4es, e.g. from
adapta4on to the regulari4es of the world that evolves without inten4on to learn, language:
and without a clear awareness of what we know. This ubiquitous phenomenon was • Reber, 1967, 1989: implicit learning allows
called ‘implicit learning’ (IL) by Reber 40 years ago.” the acquisi4on of complex, abstract
• Origina4ng from a different research tradi4on, the term ‘sta4s4cal learning’ (SL) knowledge without awareness and effort
was proposed 10 years ago by Saffran and collaborators to designate the ability of (extrac4on of abstract rules)
infants to discover the words embedded in a con4nuous ar4ficial language, and • Pacton & Perruchet, 2006: acquisi4on of
this field of research is now growing exponen4al. the ap4tude to correctly answering to
• There are obvious similari4es between SL and IL. As in IL, par4cipants in SL certain situa4ons, without the inten4on of
experiments are faced with structured material without being instructed to l earn. learning (no extrac4on of abstract rules;
They learn merely from exposure to posi4ve instances, without engaging in the learning of rules requires explicit
analy4cal processes or hypothesis‐tes4ng strategies.” learning)
• “Introduc4on There is no doubt that many of our most fundamental abili4es, • It does not mean one can learn without
whether they concern language, percep4on, motor skill, or social behavior, reflect aEen4on (concurrent aEen4onal tasks
some kind of adapta4on to the regulari4es of the world that evolves without lower the capacity of implicit learning)
inten4on to learn, and without a clear awareness of what we know. This • But the crucial variable is the exposi4on to
ubiquitous phenomenon was called ‘implicit learning’ (IL) by Reber 40 years ago. regulari4es in the environment
Since then, several studies have explored this form of learning with several
experimental paradigms (mainly finite‐state grammars and serial reac4on 4me
tasks; for reviews, see).
• Ten years ago, it seemed possible to contrast IL and SL on their main issues of
interest, namely syntax acquisi4on and lexicon forma4on, respec4vely. Indeed, the
to‐be‐ learned material used in ar4ficial grammar learning research is typically
governed by rules, that is by organizing principles which are independent of the
specific material used in a given instance. If par4cipants learned the rules, then
this form of learning would be out of the scope of SL studies, in which the no4on
of rules is a priori irrelevant. However, research from the past few years has made
it increasingly clear that par4cipants in ar4ficial grammar learning experiments do
not need to extract the rules to perform well, even in situa4ons involving transfer
across surface forms…” (Pacton & Perruchet, 2006, p. 1)
13. Implicit & explicit learning
• “This form of learning is unconscious and con4nues • Perruchet & Pacton, 2006: Explicit learning
throughout life.” (Goswami, 2008b, p. 5) completes implicit learning with rules
• ‘In one of the most famous early studies comparing • Perruchet & Pacton, 2006: In any case, explicit
the effects of "learning a procedure" with "learning learning raises performances in comparison with
with understanding," two groups of children implicit learning (school instruc4on demands more
prac4ced throwing darts at a target underwater than above chance performances)
(Scholckow and Judd, described in Judd, 1908; see a • Reber, 1989: introduc4on of explicit instruc4on is
conceptual replica4on by Hendrickson and expecially useful when informa4on is provided
Schroeder, 1941). before (rather than during or ayer the implicit
• One group received an explana4on of refrac4on of learning phase), maybe because it helps direc4ng
light, which causes the apparent loca4on of the aEen4on on mearningful aspects
target to be decep4ve. The other group only • Bransford, Brown, & Cocking, 2000: Judd &
prac4ced dart throwing, without the explana4on. Scholckow 1908’s experiment confirms that explicit
Both groups did equally well on the prac4ce task, instruc4on (before training) enhances performances
which involved a target 12 inches under water. But for new situa4ons
the group that had been instructed about the
abstract principle did much beEer when they had to
transfer to a situa4on in which the target was under
only 4 inches of water. Because they understood
what they were doing, the group that had received
instruc4on about the refrac4on of light could adjust
their behavior to the new task.” (Bransford, et al.,
2000, p. 44)
14. Implicit learning of errors
• “One concern about mul4ple‐choice tests is that • If implicit learning can happen by repeated
they rou4nely expose students to wrong answers. If exposi4on (with aEen4on), then the repeated
subjects read all choices carefully ,they read three exposi4on to errors favors the learning of errors
(usually) plausible wrong answers and only one • Mul4ple choice tests enhance learning of good, and
correct answer. Even if subjects pick the correct bad, answers
answer, reading the wrong statements may make
those answers seem true later. That is, simply
repea4ng statements increases the probability that
those statements will be judged true late r(Hasher,
Goldstein,&Toppino,1977). Consistent with this
analysis, tes4ng increases later ra4ngs of the truth
of mul4ple‐choice lures, although they are s4ll rated
as less true than known facts (Toppino&Brochin,
1989;Toppino& Luipersbeck,1993). Similarly, tes4ng
increases the produc4on of mul4ple choice lures as
answers to later cued recall ques4ons, even when
students are strictly warned against guessing
(Roediger&Marsh,2005). Specifically, mul4ple‐
choice lures were used to answer 5% of ques4ons
when subjects had not been previously tested;
tes4ng increased the use of these specific wrong
answers to 12% on the later cued recall test.”
Marsh, et al., 2007, p. 195)
15. Sta4s4cal learning & Extrac4on of
causal structures
• “… specific perceptual features of two objects in a “launching” event • In terms of neural sta4s4cal
(where object A impacts object B, causing it to begin to move) may vary, learning, the infant brain is
but spa4o‐temporal dynamics (and therefore causal structure, i.e., the essen4ally learning about
fact that A causes B to move) will vary less. The perceptual “illusion” of dynamic spa4o‐temporal
causality during launching and other visual events noted by MichoEe structure across sensory
(1963) is one example of how perceptual covaria4on can yield causal modali4es
structure (Scholl & Tremoulet, 2000). • The brain automa4cally generates
• Most recently, it has been demonstrated that 6‐month‐old infants who causal inferences from observed
watch geometric shapes (with eyes) that engage in self‐ini4ated mo4on events
extract causal structure that an be interpreted as “moral” causal • Causal structures can be induced
structure (“helping” versus “hindering”). For example, in one scenario, from sta4s4cal learning
the babies watched as a blue circle with eyes tried to move up a mechanisms
“hill” (piece of green apparatus), but repeatedly failed to get beyond a
half‐way “plateau”. A yellow triangle with eyes then appeared and
“pushed” the blue circle on up the hill (or a red square appeared and
pushed the blue circle back down the hill). The babies were then
allowed to reach for both the “helper” and the “hinderer”. Twelve out of
12 babies reached for the yellow triangle (the “helper”, see Hamlin,
Wynn & Bloom, 2007).
• The spa4o‐temporal structure of these objects and their “ac4ons” was
sufficient for the infants to interpret the movements as goal‐directed
ac4ons with moral content. The level of knowledge that can be
abstracted from spa4o‐temporal structure (perceptual causal
informa4on) about different en44es has in important cases been
transcended by modern physics and biology. A good example is the
medieval “impetus” theory of mo4on, which has been supplanted by
Newtonian physics (Kaiser, ProfiE & McCloskey, 1985). According to the
impetus theory of mo4on, every mo4on must have a cause. ” (Goswami,
2008b, p. 9)
16. Explana4on‐based learning
• “Explana4on‐based learning … is the core • Children use previous (domain) knowledge in order
mechanism used by infants to iden4fy new variables to construct explana4ons for new situa4ons
as they build their knowledge of the physical world. (generaliza4on)
• As infants experience more and more events, more • Iden4fy variables that are relevant for events to
elaborate representa4ons are developed in which happen in a certain way
variables that are relevant to the events’ outcomes • It is essen4ally causal learning
are iden4fied and represented, such as degree of
contact for support events. This process whereby
infants iden4fy new variables in event categories is
thought to be explana4on‐based learning.
• In the field of machine learning, explana4on‐based
learning depends on construc4ng causal
explana4ons for phenomena on the basis of specific
training examples, using prior domain knowledge.
• If infants were merely learning condi4on‐outcome
rela4ons, as in associa4ve learning, then they would
be unable to make predic4ons about novel events.
• However, infants who understand why (for example,
short covers cannot conceal tall objects should be
able to reason about height informa4on in any
covering event, even if this event is very remote in
perceptual terms form the learning events.
• The infants, like the machines, would be able to
formulate valid generaliza4ons from single
instances.” (Goswami, 2008, p. 66)
17. Learning by analogy
• “Finding correspondences between two events, situa4ons, or domains • Children learn by analogy
of knowledge and transferring knowledge from one to • This is a specifically human
another.” (Goswami, 2008, p. 52) capacity
• “In learning by analogy, “we face a situa4on, we recall a similar • It can be found in children before
situa4on, we match them up, we reason, and we learn” (Winston, language but is powered by
1980). We may decide whether a dog has a heart by thinking about language
whether people have hearts (young children use “personifica4on
analogies” to learn about biological kinds, see Inagaki & Hatano,
1988), or we may solve a mathema4cal problem about the interac4on
of forces by using an analogy to a tug‐of‐war (young children use
familiar physical systems to reason about unfamiliar ones, see Pauen,
1996). Reasoning by analogy has usually been measured in children
aged 3 years or older (see Goswami, 1992, 2001, for reviews), but can
also be demonstrated in infancy. However, so far, analogy has not
been found in the animal kingdom, sugges4ng that it is especially
important for human learning.
• Early analogies tend to depend on func4onal or causal rela4ons, but
once language is acquired analogies can be quite abstract (e.g. 3‐year‐
old children deciding how animals can evade predators by using
different forms of mimicry, see Brown, 1989). The use of analogy
depends crucially on the knowledge base. Children can only use
analogies based on familiar rela4ons, rela4ons that they have
experienced or that they understand. ” (Goswami, 2008b, p.13‐14)
18. Learning by imita4on
• “Learning by imita4on can be defined as B learns from A • Infants imitate adults’ behavior
some part of the form of a behavior… One example is • Children learn by imita4on, e.g.
learning the use of a novel tool by imita4ng the ac4ons of the use of tools
another user with that tool. Most defini4ons of imita4on
require that something new is learned, and such learning • Learning by imita4on is present
has proved remarkably difficult to dis4nguish in animals … in the human baby by the age of
(Goswami, 2008, p. 62‐63) at least 9 months (Meltzoff,
1988)
• Learning by imita4on is another cri4cal form of early • At 14 months, babies imitate
learning. Here the infant or child reproduces observed with a delay (1 week) and
ac4ons as a way of understanding them beEer. The ra4onally:
importance of reproducing observed ac4ons was core to
Piaget’s theory of the “sensory motor stage” (0 – 2 years) of – They imitate certain features of
the ac4on if and only if they
cogni4on. (Goswami, 200b8, p. 11) consider that they are
• Piaget argued that inten4onal imita4on emerged at around func4onal to the reaching of
18 months, but it has since been shown that babies as young the goal, not if they are
as 1 hour old can imitate facial ac4ons (Meltzoff & Moore, con4ngent to the situa4on
• (Meltzoff, 2005)
1983). In Meltzoff and Moore’s classic 1983 study, adults • (Gergely, et al., 2002)
modelled gestures like tongue protrusion and mouth
opening in a quiet environment, and the infants reproduced
these gestures. By around 9 months, babies can learn how
to manipulate novel objects such as experimenter‐built toys
by watching others manipulate them (Meltzoff, 1988).
(Goswami, 2008b, p. 11)
• Older babies can even imitate intended acts which are never
observed.
19. Imita4on as the basis of mind reading
• The like‐me hypothesis states that • “My thesis is that imita4on and
infants grow to understand others: understanding other minds (oyen
• First comes imita4on: babies come to referred to as a theory of mind or
understand (or experience) the mind reading) are causally related.
intrinsic connec4on between But which way does the causal arrow
observed and executed acts, as run? Some have argued that
manifest by newborn imita4on understanding other minds,
• The comes First‐person experience: especially judgments of others'
inten4ons, underlies imita4on (e.g.,
Infants experience the regular
rela4onship between their own acts Tomasello et al., 1993). This puts the
and underlying mental states. cart before the horse, in my opinion. I
wish to show that imita4on, and the
• Finally, arrives the Understanding neural machinery that underlies it,
Other Minds: Others who act "like begets an understanding of other
me" have internal states "like me.” minds, not the other way around.
– (Meltzoff, 2005) ” (Meltzoff, 2005)
20. Imita4on, social cogni4on & mirror
neurons
• “Social cogni4on is currently an ac4ve area of research in • Among the studies on social
developmental cogni4ve neuroscience. Interest has focussed on a cogni4on, mirror neurons have
neural system called the “mirror neuron system”, which is known to gained lot of aEen4on
be important for ac4on and imita4on. Mirror neurons were • Mirror neurons are involved in the
discovered in monkey research on the representa4on of ac4on. These representa4on of an ac4on
neurons were found to become ac4ve when the monkey performed
object‐directed ac4ons such as tearing, grasping, holding and • Mirror neurons are ac4vated when
manipula4ng. Furthermore, the same neurons became ac4ve when observing an ac4on, independently
the animal observed someone else performing these ac4ons, such as from the specific motor realiza4on of
someone else tearing paper. Mirror neurons were even ac4vated by the ac4on
the sound of an ac4on, such as the sound of paper ripping (RizzolaT • Mirror neurons are related to the
& Craighero, 2004). RizzolaT and his colleagues pointed out that an goal, and the agent
ac4on implies a goal and an agent, and therefore argued that mirror • Mirror neurons could be involved in
neurons may play an important role in understanding inten4ons. It the understanding of others’
has since been shown that mirror neurons are ac4ve during imita4on, inten4ons
and are only ac4vated by biological ac4ons (e.g., a human hand • Specula4vely, in empathy
grasping, Tai et al., 2004).
• Mirror neurons are not ac4vated by mechanical ac4ons such as a
robot hand grasping, and Meltzoff has shown that babies will imitate
ac4ons on objects made by human hands but not iden4cal ac4ons
made by mechanical hands (Meltzoff, 1995).
• It is therefore thought that the mirror neuron system may be a neural
substrate for understanding the ac4ons and internal states of others.
Interes4ngly, children with disorders of social cogni4on such as
au4sm appear to have very liEle mirror neuron ac4vity (DapreEo et
al., 2006). It is thus speculated that the mirror neuron system plays a
role in the development of empathy.” (Goswami, 2008b, p. 23)
21. Learning by imita4on & TV
• “Meltzoff (1988) has evidence that infants of 14 moths of age can indeed learn • 14 months’ babies can learn the same
novel ac4ons from watching television.” (Goswami, 2008, p. 62‐63) ac4ons from real experimenters and from
experimenters canned in a TV video (on live)
• But they learn less than from live ac4on
(video deficit effect)
• “Empirical research conducted using a number of different experimental
paradigms has demonstrated that infants, toddlers, and preschool children learn – Maybe because the processing of 2D
less from television and 2D s4ll images than from live face‐to‐face interac4ons … s4muli is poorer than the processing of
3D s4muli
This has been termed the video deficit effect: Infants’ ability to transfer learning
from television to real life situa4ons is rela4vely poor … compared to their – Or because 2D s4muli are poorly
impressive transfer of learning from a live demonstra4on to a different understood and their rela4on to 3D real
objects is not granted
situa4on” (Zack, et al. 2009, p. 14)
– Or because of poor representa4onal
flexibility (and memory requirements)
• Is that because of 2D/3D encoding
differences? What happens with 3D models?
– An experiments conduced by Zack and
coll. would show that the limit comes
from the transfer of informa4on from
one dimension to another (live adult
demonstra4on)
– Infants do just as well imita4ng 2D/2D
than 3D/3D: 2D is not as impoverished as
to block imita4on, and 2D does not
represent a poorly understood condi4on
in comparison with 3D (but live adult
demonstra4on could help the
understanding)
– Representa4onal flexibility seems to be
the problem, thus memory would be the
key
22. Human imita4on
• Infants understand and
• Tomasello has argued that humans differ profoundly from apes in their imitate adults’ inten4ons
skills of imita4on and imita4ve learning, because the ability to learn novel • This seems to be a specifically
behaviors via imita4on depends on the ability to understand the inten4ons human learning capacity
of others. • Learning by imita4on seems
• Most of our knowledge about imita4ve learning in infants comes from the to require the understanding
pioneering work of Meltzoff … Many of his more recent experiments of others’ inten4ons
depend on the use of deferred imita4on … to see whether infants can (Tomasello, 1990)
reproduce a novel ac4on that they have observed previously even if they
are not allowed access to the cri4cal materials at the 4me of learning.”
• Older babies can even imitate intended acts which are never observed.
Meltzoff manipulated a number of novel events (e.g., inser4ng a string of
beads into a cylindrical container) so that the adult demonstrator
accidentally failed to demonstrate the event (e.g. fumbled the beads so
that they missed the opening). The observing infants took the beads and
put them into the container successfully (Meltzoff, 1995).
• Empirical studies such as these show that the infants are going beyond
what is observed and are aEribu4ng goals and inten4ons to the
demonstrator (see also Tomasello and colleagues, e.g. Carpenter, Call &
Tomasello, 2005). Understanding the goals of another person transforms
their ac4ons into purposive behaviour (Gergely et al., 2002).
23. Understanding human inten4ons
• Three levels of imita4on/understaninding
• “Ac4ng animately. An observer perceives that the actor has generated his mo4on autonomously; that is, she others’ ac4ons & reading of inten4ons)
dis4nguishes animate self‐produced ac4on from inanimate, caused mo4on. There is no understanding that – Perceiving others as actors that
the actor has a goal, and so means and ends are not dis4nguished, nor are successful and unsuccessful produce their ac4ons (6 months old
ac4ons. Although observers may learn from experience what animate actors typically do in familiar children)
situa4ons, predic4ng behavior in novel circum‐ stances is basically impossible. – Perceiving others as having goals for
their ac4ons (9 months)
• Pursuing goals. An observer perceives and understands that the actor has a goal and behaves with
persistence un4l reality matches the goal; that is, she understands that the actor recognizes the success or – Perceiving others as making plans for
reaching their goal, and choosing the
failure of his ac4ons with respect to the goal and con4nues to act in the face of failure. This understanding most ra4onal ac4on (14 months)
implies that the observer also knows that the actor sees things (e.g., objects with respect to which he has (Tomasello, et al. 2005)
goals, poten4al obstacles to goals, the results of ac4ons) and that this helps to guide ac4on and determine
sa4sfac4on with results. Understanding ac4on in this way enables observers to predict what actors will do in
at least some novel situa4ons.
• Choosing plans. An observer perceives and under‐ stands that the actor considers ac4on plans and chooses
which of them to enact in inten4onal ac4on (and these may be more or less ra4onal depending on their fit
with perceived reality). She also understands that in ac4ng toward a goal the actor chooses which en44es in
its perceptual field to aEend to. In general, the observer understands that actors act and aEend to things for
reasons, which enables her to predict what an actor will do in a wide variety of novel situa4ons. (All
elements of Fig. 1 present.) Children’s understanding of these different aspects of inten4onal ac4on and
percep4on emerge, in this order, at different points in infancy“
• “Six‐month‐old infants perceive animate ac4on and follow gaze direc4on, which enables them to build up
experiences on the basis of which they predict people’s ac4ons in familiar contexts. By 9 months of age,
infants understand that that people have goals and persist in behaving un4l they see that their goal has
been reached (avoiding obstacles and persis4ng past accidents and failures in the process) –be‐ ing happy
when the goal is reached and disappointed if it is not. By 14 months of age, infants begin to understand full‐
fledged inten4onal ac4on –including the rudiments of the way people make ra4onal decisions in choosing
ac4on plans for accomplishing their goals in par4cular reality contexts and selec4vely aEending to goal‐
relevant aspects of the situa4on.“ (Tomasello, et al., 2005)
24. Engaging in shared inten4ons
• 3 levels of engagement in • “Human infants are extremely sensi4ve to social con4ngencies. In their face‐to‐face interac4ons
shared inten4ons: with adults, infants from just a few months of age display the ability to take turns in the sense of
– Dyadic engagement: ac4ng when the adult is more passive and being more passive when the adult is ac4ng
face to face (Trevarthen 1979). When these con4ngencies are broken –for example, in experiments in which
interac4ons and the adult’s behavior is preprogrammed (or played to the infant over delayed video) –infants
protoconversa4ons show various signs of being out of sorts (for reviews, see Gergely & Watson 1999 and Rochat &
with shared emo4ons Striano 1999). Infants’ early social interac4ons thus clearly show mutual responsiveness on the
– Tryadic engagement: behavioral level. But there is another dimension to these interac4ons that goes beyond simple
doing things together, 4ming and con4ngency. Human infants and adults interact with one another dyadically in what
but without assigning are called protoconversa4ons. These are social interac4ons in which the adult and infant look,
roles for the reaching touch, smile, and vocalize toward each other in turn‐taking sequences. But as most observers of
of the goal; sharing infants have noted, the glue that holds proto‐ conversa4ons together is not just con4ngency but
percep4on and goals
(9‐12 months) the exchange of emo4ons (Hobson 2002; Trevarthen 1979).
– Collabora4ve • At around 9 to 12 months of age, as infants are beginning to understand other persons as goal
engagement = sharing directed, they also begin to engage with them in ac4vi4es that are triadic in the sense that they
ac4on plans (12‐15 involve child, adult, and some outside en4ty to‐ ward which they both direct their ac4ons. These
months) are ac4vi4es such as giving and taking objects, rolling a ball back and forth, building a block
tower together, puTng away toys together, “pretend” games of ea4ng or drinking, “reading”
books, and poin4ng‐and‐naming games (Hay 1979; Hay & Murray 1982; Verba 1994). During
these ac4vi4es, infants’ looking becomes coordinated with that of the other person triadically
toward the relevant outside objects as well. When researchers focus on this aspect of the joint
ac4vity, it is most oyen called “joint aEen4on” (e.g., see papers in Moore & Dunham 1995) –
what we will call at this level joint percep4on.
• At around 12 to 15 months of age, infants’ triadic engagements with others undergo a At around
12 to 15 months of age, infants’ triadic engagements with others undergo a significant
qualita4ve change. In a classic longitudinal study, Bakeman and Adamson (1984) categorized
infants’ interac4ons with their mothers as involving, among other things, either “passive joint
engagement” or “coordinated joint engagement.” Passive joint engagement referred to triadic
interac4ons in general, whereas coordinated joint engagement referred to triadic interac4ons in
which the infant was much more ac4ve in the interac4on –not just following adult leads, but also
some4mes direc4ng adult behavior and aEen4on as well in a more balanced manner. The
empirical finding was that al‐ though 9‐month‐old infants engaged in much passive joint
engagement, it was not un4l 12 to 15 months of age that infants engaged in significant amounts
of coordinated joint engagement.
25. Humanness
• “We propose that the crucial difference between human cogni4on and
that of other species is the ability to par4cipate with others in • At the origin of human
collabora4ve ac4vi4es with shared goals and inten4ons: shared culture and cogni4on
inten4onality. Par4cipa4on in such ac4vi4es requires not only especially stand two capaci4es:
powerful forms of inten4on reading and cultural learning, but also a • ‐ mind reading, and in
unique mo4va4on to share psychological states with oth‐ ers and unique par4cular: the capacity of
forms of cogni4ve representa4on for doing so. The result of par4cipa4ng perceiving and
in these ac4vi4es is species‐unique forms of cultural cogni4on and understanding others’
evolu4on, enabling everything from the crea4on and use of linguis4c inten4ons
symbols to the construc4on of social norms and individual beliefs to the • ‐ a mo4va4on for
establishment of social ins4tu4ons. In support of this proposal we argue engaging in shared
and present evidence that great apes (and some children with au4sm) inten4on ac4vi4es
understand the basics of inten4onal ac4on, but they s4ll do not
par4cipate in ac4vi4es involving joint inten4ons and aEen4on (shared
inten4onality). Human children’s skills of shared inten4onality develop • So: shared inten4onality
gradually during the first 14 months of life as two ontogene4c pathways is what makes humans
intertwine: (1) the general ape line of understanding others as animate, special in the animal
goal‐directed, and inten4onal agents; and (2) a species‐unique mo4va4on reign
to share emo4ons, experience, and ac4vi4es with other persons. The • (Tomasello, 2005)
develop‐ mental outcome is children’s ability to construct dialogic
cogni4ve representa4ons, which enable them to par4cipate in earnest in
the collec4vity that is human cogni4on” (Tomasello, et al., 2005)
26. Cultural intelligence hypothesis
• Baby humans differ • “Some other ape species transmit some behaviors socially or culturally , but their
from primates on species‐ typical cogni4on does not depend on par4cipa4ng in cultural interac4ons in
social abili4es the same way as it does in humans, who must
• Humans have • (i) learn their na4ve language in social interac4ons with others,
developed special • (ii) acquire necessary subsistence skills by par4cipa4ng with experts in established
cogni4ve skills as a cultural prac4ces, and
result of the • (iii) (in many cultures) acquire skills with wriEen language and mathema4cal symbols
development of
specialized skills for through formal schooling.
absorbing • In the end, human adults will have all kinds of cogni4ve skills not possessed by other
knowledge and primates, but this outcome will be due largely to children’s early emerging,
prac4ces of their specialized skills for absorbing the accumulated skillful prac4ces and knowledge of
social group their social group (so that a child growing up outside of any human culture would
develop few dis4nc4vely human cogni4ve skills). Humans’ especially powerful skills
of social‐cultural cogni4on early in ontogeny thus serve as a kind of “bootstrap” for
the dis4nc4vely complex development of human cogni4on in general. We may call
this the cultural intelligence hypothesis”
• “However, we should note that because the children were somewhat more skillful
than the apes in the causality tasks not involving ac4ve tool manipula4on, as well as
in the tasks of social cogni4on, it is possible that what is dis4nc4vely human is not
social‐cultural cogni4on as a specialized domain, as we have hypothesized. Rather,
what may be dis4nc4ve is the ability to understand unobserved causal forces in
general, including (as a special case) the mental states of others as causes of
behavior. Even in this case, however, it is a plausible hypothesis that understanding
hidden causal forces evolved first to enable humans to understand the mental states
of other persons, and this generalized only later to the physical domain”. (Herrmann,
et al., 2007)
27. Meltzoff
• Imita4on is a central feature of human beings,
and precedes mind reading and other social
capaci4es
Gergely & Csibra
• Joint collabora4on requires mind Tomasello
reading
• Mind reading is a crucial social
• But not a mo4va4on for sharing capacity and enables imita4on
inten4ons
• The mo4va4on for sharing of
• Rather, the capacity to communicate
inten4ons is the other crucial social
relevant informa4on
capacity
• This capacity might have evolved • They both allow shared inten4onality
under the pressure of teaching/
learning of opaque knowledge • Shared inten4onality has evolved
(technology) under the pressure of collabora4on
29. Natural pedagogy
• “… human communica4on is specifically • Development of natural pedagogy:
adapted to fulfil the funciton of transmiTng
generic knowledge between • Development of tools’ making prac4ces
individuals.” (Gergely & Csibra, p. 3) represents an evolu4ve pressure
• “A new type of communica4ve learning • Because these prac4ces cannot be learned/
system based on ostensive‐referen4al transmiEed by other, available mechanisms
demonstra4ons of knowledge … expert user of learning from imita$on/observa$on*
ac4vely guide the novice by selec4vely
manifes4ng the informa4on to be acquire • Because they represent opaque contents for
and generalized. cogni4on
• … children … are always novices with respect • Thus, humans have evolved mechanisms that
to the accumulated knowledge of their serve the pedagogical func4on of
culture. transmiTng cogni4vely opaque contents
• This is why we call the specific aspects of • These mechanisms are part of the more
human communica4on that allow and general communica4on system
facilitate the transfer of generic knowledge • They consist of demonstra4on acts:
to novices Natural Pedagogy. ” (Gergely & ostensive‐referen4al demonstra4ons
Csibra, p. 4)
30. Adults/children natural pedagogical
system
• “When children are shown an ac4on • Children observe and imitate adults
performed in a par4cular style leading to a – Children spontaneously imitate causal ac4ons
clear end state (e.g. a mouse is hopping that lead to achieve goals, and ignore other
across the table into a house), they tend to components of the global ac4on
reproduce only the end state (put the mouse – The others components of the ac4on are
into the house), oyen ignoring the manner of opaque to children’s cogni4on
ac4on (hopping). However, if the relevant – But, when the “teacher” makes it clear that
informa4on concerning the end state is these components of the ac4on are relevant,
communicated to them verbally by the actor children do pay aEen4on, and imitate
before the demonstra4on (“the mouse lives • Adults use their communica4on system to
in the house”), they reproduce the ac4on facilitate children’s learning
style more oyen. • Young children are recep4ve to adult’s
• Ostensive communica4on does not only ostensive demonstra4on before they are able
make children pay more aEen4on to the to use it for learning
demonstra4on but they also see it as a
special opportunity to acquire generalizable
knowledge.” (Gergely & Csibra, p. 5)
• Ostensive signals allow to
• “recent studies ...demonstrate this – Disambiguate the nature of the ac4on
preparadness in the form of three kinds of (communica4on, not just using the tool)
early perceptual and cogni4ve biases: – Disambiguate the target of the
communica4on (you)
31. Ostensive signals
• Preference for ostensive • 1. preferen4al aEen4on for
signals : the sources of ostensive
– Gaze contact signals
• Newborns preferen4ally look at
schema4c face‐like paEerns with
direct gaze vs averted gaze;
preference disappears when
faces are upside‐down;
preference disappears when the
typical iris/sclera paEers of eyes
is inverted
• Same neural ac4va4on for
infants and adults in response to
direct gaze and common neural
ac4va4on for two different
ostensive s4muli (direct gaze &
eye‐brow raise)
– Motherese
– Mo4onese
32. Referen4al expecta4ons
– Infants follow the gaze of interac4ng
• 2. Referen4al expecta4on
adults to iden4fy what they are looking induced by ostensive contexts
at, before they can understand language • Eight‐months olds observed
– Useful for sampling parts of someone on a computer screen
the world that others found ostensively looking at and
interes4ng, and present in gree4ng them before shiying her
other animals gaze to llok behind one of two
– Human infants followgaze barriers. Following this, an object
shiys only when these are
preceded by ostensive signals was revealed either at the
(gree4ng, gaze contact) targeted or at the other occluded
– Infants expect to find an object at the loca4on. Infants’ looking paEern
“end” of a gaze‐following in an ostensive suggested that they expected to
context find an object at the loca4on
– 13 months old Infants expect to where the person’s gaze wwas
find the named object (if its name directed at, just like older infants
is part of their vocabulary) do in similar live
– But not if the gesture and word are situa4ons.” (Gergely & Csibra, p.
emiEed by different persons 5‐8)
33. Interpreta4on bias
– Not only infants are prepared to receive ostensive–referen4al • 3. interpreta4on bias to
communica4on, but they do expect to learn something generalizable
from it (and not just a par4cular instance) = to learn about referent preferen4ally encode the
kinds
– When infants (18 months old) observe adults expressing content of ostensive‐
emo4onal valence in rela4onship to an object in a non‐
communica4ve context, they infer that person’s par4cular
preference (she does not like it). But when the same paEern
referen4al communica4on as
of valence expression is inserted in a communica4ve
context, infants aEach the expressed value to the object and
represen4ng generalizable
expect that other people will react in the same manner to
the object (it is disgus4ng for everybody) knowledge”
– Infants (9 months old) shiy their encoding paEern from
loca4on to appearance features when the situa4on shiys
from non‐communica4ve to communica4ve.
• “this is what dis4nguishes our
– They are more likely to detect change in loca4on in hypothesis in the first place
a non‐communica4ve situa4on, but detect more
oyen features change in a communica4ve situa4on
and neglect loca4on; and this happens even in
from compe4ng proposals,
situa4ons in which loca4on is important,
pragma4cally, such as hiding games
according to which human
– This bias could explain A not‐B task errors: children
stop being interested in loca4on and do not mind
communica4on originates
about the new loca4on, because the
communica4ve contexts has made them focus on evolu4onarily and
the features of the object. In fact, once
communica4ve cues are removed, the errors ontogene4cally from a basic
–
diminish.
Appearance features are beEer candidates for mo4ve to cooperate with
later use and object iden4fica4on, thus for
generaliza4on. others to achieve shared
– Communica4on has evolved not only for collabora4on‐purposes but goals.” (Gergely & Csibra, p.
also under the pressure of learning/teaching purposes
5‐9)
34. Social learning mechanisms
• “There are many types of social learning • Social learning mechanisms are common to several
mechanisms in the animal kingdom, and they all animal species
involve some form of observa4onal learning, where • Learning generalizable knowledge from social
the observa4on of an adap4ve behavior of another interac4ons seems to be specific to humans
individual makes it more likely that the observer will • Natural pedagogy seems to be universal, thus
produce the same or similar behaviors in the future.
In this sense, social learning represents transmission “natural”
of general knowledge or skills from one individual to
another.
• Non‐human animals communicate about episodic,
non‐generalizable informa4on (that applies only to
the here and now), and learn new skills by
observa4on or scaffolded individual learning, they
do not seem to use communica4on to pass on
generalizable knowledge to others.”
• “ This discrepancy between general claims about
the absence of teaching and the actual reports is
likely to reflect the enormous differences between
teaching in Western socie4es and in more
tradi4onal cultures. It is not just that Western
educa4on relies heavily on formal schooling but also
that it aims to provide verbal explana4on and
jus4fica4on for what is being taught. … however,
Natural Pedagogy … seems to be
universal.” (Gergely & Csibra, 2009, p. 12‐14)
35. • “Child development is today conceptualized
as an essen4ally social process, based on
incremental knowledge acquisi4on driven by
cultural experience and social context. We
have “social” brains.” (Goswami, 2008b, p. 1)
37. Socially distributed cogni4on
• Distributed “ If we want to explain the informa4on processing proper4es
cogni4on: of individuals, we have no choice but to aEempt to infer what
– The unit of is inside the individual’s mind. Cogni4ve scien4sts do this by
analysis of construc4ng carefully selected contexts for elici4ng behavior
cogni4ve from which they can aEribute internal states to actors.
performanc However, if we take the cockpit system as the unit of analysis,
es should
be we can look inside it and directly observe many of the
extended phenomena of interest. In par4cular, we can directly observe
beyond the the many representa4ons that are inside the cockpit system,
individual yet outside the heads of the pilots. We can do a lot of
so as to research on the cogni4ve proper4es of such a system (i.e., we
encompass
social and can give accounts of the system’s behavioral proper4es in
material terms of its internal representa4ons), without saying
interac4on anything about the processes that operate inside individual
s with tools actors (Hutchins, 1990, 1991, 1995). This suggests that rather
than trying to map the findings of cogni4ve psychological
studies of individuals directly onto the individual pilots in the
cockpit, we should map the conceptualiza4on of the
cogni4ve system onto a new unit of analysis: the cockpit as a
whole. ” (Hutchins, 1995, p. 267)
38. Socially distributed cogni4on
• Distributed • “Let us now apply the cogni4ve science frame to the cockpit as a cogni4ve
cogni4on: system. How are the speeds represented in the cockpit? How are these
– Remebember representa4ons transformed, processed, and coordinated with other
ing the speed representa4ons in the descent, approach, and landing? How does the
is the task cockpit system remember the speeds at which it is necessary to change
and result of the configura4on of the wing in order to maintain safe flight?
cogni4ve
processes • The observable representa4ons directly involved in the cockpit processes
involving the that coordinate airspeed with flap and slat seTngs are: the gross weight
pilots of the display (Figure 2), the speed card booklet (Figure l), the two airspeed
cockpit as indicator instruments with internal and external bugs (Figure 3), the
well as speed select window of the flight guidance control panel, and the speed‐
various
instruments related verbal exchanges among the members of the crew. The speed‐
related verbaliza4ons may appear in the communica4on of the values
from PNF to PF while seTng the speed bugs, in the ini4al slat extension
cross‐check, in the sub‐ sequent configura4on changes, in the cross‐check
phase of the before‐landing checklist performance, in the PNF’s approach
progress report at 500 feet AFL, and in any required speed devia4on call
outs on the final approach segment ayer the selec4on of the landing flap
seTng.
• In addi4on to the directly observable media listed earlier, we may also
assume that some sort of representa4on of the speeds has been created
in two media that are not directly observable: the memories of the two
pilots, themselves. ” (Hutchins, 1995, p. 275)
39. Distributed cogni4on
• Distributed • “We will advocate an externalism about mind, but one that is in no way
cogni4on: grounded in the debatable role of truth‐condi4ons and reference in fixing
– Performance the contents of our mental states. Rather, we advocate an “ac4ve
s typically externalism”, based on the ac4ve role of the environment in driving
described as cogni4ve processes.”
cogni4ve are
significantly
worst in • “The informa4on in OEo's notebook, for example, is a central part of his
absence of iden4ty as a cogni4ve agent. What this comes to is that OEo himself is
interac4on best regarded as an extended system, a coupling of biological organism
with tools,
others, or of and external resources.
epistemic • The informa4on in OEo's notebook, for example, is a central part of his
ac4ons that iden4ty as a cogni4ve agent. What this comes to is that OEo himself is
have no best regarded as an extended system, a coupling of biological organism
other aim and external resources.” (Clark & Chalmers, 1998)
than favoring
a beEer
knowledge of
the world
40. Social neurosciences
• Strong accent on social cogni4on, in • “Panoramic photographs of the earth from space
cogni4ve sciences and in the new reveal agricultural runoffs that stretch hundreds of
science of learning miles out to sea …From this ionospheric perspec4ve,
– Social neuroscience: importance of one could easily visualize effects that could not be
mul4level, integra4ve analysis of fully comprehended from a closer focal point. This
complex psychological phenomena simple example from space sciences illustrates a
principle that seems so obvious … but that oyen
appears incomprehensible in the psychological
sciences and neurosciences. There are phenomena
that may be explicable in terms of events at a
microlevel of analysis but that are more easily
studied and more fully comprehended by reference
to broader and mul4ple levels analysis.” (Cacioppo &
Berentson, 1992, p. 1019)
• “Cogni4ve behavioral and developmental
neuroscience, for instance, are all ac4ve areas of
research, but social neuroscience strikes some as
being an oxymoron (see ScoE, 1991). It is
not…” (Cacioppo & Berentson, 1992, p. 1020)
