REPORT
People’s Intuitions About Innateness
1
Iris Berent
, Melanie Platt
1
1
, and Gwendolyn M. Sandoboe
1Department of Psychology, Northeastern University
a n o p e n a c c e s s
j o u r n a l
Keywords: innateness, core knowledge, dualism, essentialism
ABSTRACT
Few questions in science are as controversial as the origins of knowledge. Whether
knowledge (per esempio., “objects are cohesive”) is partly innate has been debated for centuries.
Here, we ask whether our difficulties with innate knowledge could be grounded in human
cognition itself. In eight experiments, we compared reasoning about the innateness of traits
that capture knowledge (cognitive traits) with noncognitive (sensorimotor and emotive)
traits. Experiments 1–4 examined adult and infant traits; Experiment 5 presented detailed
descriptions of published infant experiments. Results showed that people viewed cognitive
traits as less likely to be innate in humans—the stronger the association with “thinking,” the
lower the rating for “innateness.” Experiments 6–8 explored human, bird, and alien traits
that were presented as innate. Participants, Tuttavia, still considered cognitive traits as less
likely to emerge spontaneously (cioè., be innate). These results show that people are
selectively biased in reasoning about the origins of knowledge.
INTRODUCTION
The origin of knowledge is one of the most controversial questions in the history of ideas. A
stake is whether knowledge (per esempio., the notion of an “object”) is induced from experience, O
whether certain cognitive concepts and principles are innate in humans. These debates have
been raging since the times of the ancient Greeks, and they show no sign of abating in the
current scientific literature.
Why is innateness such a hard question? There is no doubt that the innateness challenge
is partly due to the complexity of the problem at hand—the intricacy of human cognition and
its mostly unknown instantiation in the brain. But perhaps the reasons for the stalemate lie
not only with the topic of inquiry but also with the human inquirer. Here we ask whether our
understanding of innateness could be constrained by systematic biases that shape how people
reason about innate knowledge.
The possibility that people are not impartial to innateness has not gone unnoticed.
Cosmides and Tooby (1994) have argued that people suffer from “instinct blindness,” and
Pinker (2002) has warned against the denial of human nature. But these assertions are based
on anecdotal evidence. The question thus remains whether people are indeed blind to
innateness—no previous study has examined this possibility. Inoltre, no research has asked
whether our blindness to innateness is particularly acute when it comes to knowledge (con
the exception of Wang & Feigenson, 2019, published in this issue).
Citation: Berent, I., Platt, M., &
Sandoboe, G. M. (2019). People’s
Intuitions About Innateness. Open
Mind: Discoveries in Cognitive
Scienza, 3, 101–114. https://doi.org/
10.1162/opmi_a_00029
DOI:
https://doi.org/10.1162/opmi_a_00029
Supplemental Materials:
https://doi.org/10.1162/opmi_a_00029
Received: 26 Gennaio 2019
Accepted: 21 agosto 2019
Competing Interests: The authors
declare that they have no competing
interests.
Corresponding Author:
Iris Berent
i.berent@northeastern.edu
Copyright: © 2019
Istituto di Tecnologia del Massachussetts
Pubblicato sotto Creative Commons
Attribuzione 4.0 Internazionale
(CC BY 4.0) licenza
The MIT Press
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Knowledge, here, refers to tacit concepts and principles. Examples of putative in-
nate knowledge include tacit principles of core physics (per esempio., “objects are cohesive”; Spelke &
Kinzler,
2007) and core psychology (per esempio., “agents’ actions are determined by their
mental states”; Baron-Cohen, Leslie, & Frith, 1985), as well as their constituent concepts
(object; agent). Our research asks whether people are reluctant to accept that knowledge
can be innate.
There are various reasons to believe that the notion of innate knowledge might present a
special challenge to intuitive human cognition, reasons we explore in the General Discussion.
Our present inquiry, Tuttavia, does not seek to explain why people are biased against innate
knowledge, and we certainly do not intend to determine whether knowledge is in fact innate.
Invece, we strictly ask whether people are guilty as charged—are we systematically biased in
evaluating the origins of our knowledge?
A tal fine, we examine reasoning about the origins of various types of cognitive traits
that capture knowledge and compare them to sensory, emotional, and motor traits. We refer
to these traits generically as cognitive, but our interest is strictly in innate knowledge (per esempio.,
“objects are cohesive”), as opposed to “knowhow” (per esempio., playing the violin) or “horizontal”
faculties (per esempio., Attenzione, memory, and problem solving).
In this investigation, we define “innate” psychological traits as psychological primitives—
ones that are acquired in the normal course of development without relying on other psy-
chological processes, most notably, apprendimento (Samuels, 2004, 2007). To gauge laypeople’s
reasoning about innateness, we thus asked participants to reflect on the tendency of psycho-
logical traits to emerge spontaneously in all members of the species and their early onset in
development (a hallmark of many innate traits). We also asked people to explicitly indicate
whether or not cognitive traits are innate.
We conducted two sets of experiments. In one set, we presented people with various
traits—both cognitive and noncognitive—and asked them to reason about their innateness.
To determine whether reasoning about innateness is biased, we next presented people with
detailed vignettes, stating that all traits in question are innate. Of interest is whether people
are reluctant to view cognitive traits as innate despite evidence that is clearly indicative of
innateness.
REASONING ABOUT HUMAN COGNITIVE TRAITS
Experiments 1–2: Rating Human Traits
Experiments 1–2 each presented people with a list of human traits. Experiment 1 featured
adult traits that have been documented cross-culturally; Experiment 2 featured infant traits.
In each case, half of the traits were cognitive and half were noncognitive, either motor and
emotive, or motor and sensory (in Experiments 1–2, rispettivamente). Per esempio, adult cognitive
traits included “forming sentences” and “having a concept of ‘person’”; infant cognitive traits
included “Expecting objects to move as connected wholes (per esempio., without disintegrating)."
To ensure that these traits are perceived as indicative of cognition, we asked one group
of participants to classify the traits into three bins (per esempio., “thinking,” “emotion,” or “action”). UN
second group of participants evaluated the innateness of these traits, operationalized as their
propensity to emerge spontaneously, in a “desert island” situation.
We examined three questions. Primo, do people view these cognitive traits as ones that are
indicative of “thinking”? Secondo, do people believe that cognitive traits are less likely to emerge
OPEN MIND: Discoveries in Cognitive Science
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spontaneously (cioè., be innate)? And third, is the rating of a trait for innateness associated with
its classification as “thinking”?
Experiment 1: Rating Adult Human Traits
Methods
Two groups of participants (N = 20 each) were each assigned to the trait classi-
Participants
fication and innate rating tasks. In this and all subsequent experiments, participants were adult
English speakers, recruited through Amazon Mechanical Turk.
The materials consisted of a randomized list of 80 human traits—
Materials and Procedure
half were cognitive—and half were noncognitive traits, either emotive (20 traits) or motor
(20 traits).
The trait list was presented to two groups of participants. One group classified each trait
into one of three bins—“thinking,” “action,” or “emotion.” A second group rated the traits for
innateness. Specifically, people indicated on a 1–7 scale (1 = very unlikely; 7 = very likely)
how likely it is that a person would exhibit this trait spontaneously, in a desert island situation,
even if they did not have the opportunity to learn it from others. For additional method details,
see the Supplemental Materials; Berent, Platt, & Sandoboe, 2019B, which include the stimulus
materials and instructions for this and all subsequent experiments in Appendices 1–2.
Results
To determine whether most classification responses were congruent with
Trait Classification
the intended category (per esempio., “thinking,” for cognitive traits), we first computed the congruence
scores for cognitive and noncognitive traits (noncognitive traits were averaged over the “motor”
and “emotive” subcategories). We then compared the proportion of “congruent” responses
against chance (.5) using a mixed-effects logistic regression model (with participants and items
as random effects). Results demonstrated that ratings of cognitive (M = 0.79, β0 = 2.14,
Z = 5.00, SE = 0.43, P < .0001) and noncognitive (M = 0.90, β0 = 3.58, Z = 7.58,
SE = 0.47, p < .0001) traits were congruent with the intended category.
Innateness Rating We next examined the rating of these traits for innateness (see Figure 1A).
People rated noncognitive traits significantly higher than the scale’s “neutral” midpoint, 4;
M = 5.65, t1(19) = 7.91, p < .0001, d = 1.77; t2(39) = 13.37, p < .0001, d = 2.11. For
cognitive traits, by contrast, this difference was not significant across participants, M = 4.44,
t1(19) = 1.68, p < .11, d = 0.38; t2(39) = 4.58, p < .0001, d = 0.72. A matched sample t test
further showed that cognitive traits were rated as less likely to emerge spontaneously compared
to noncognitive traits, and these results were significant across participants, t1(19) = 7.61,
p < .0001, d = 1.10, and items, t2(78) = 7.76, p < .0001, d = 1.73.
Finally, we examined whether reasoning about the innate-
The “thinking”–“innateness” link.
ness of cognitive traits is linked to their association with “thinking” (see Figure 1B). To this end,
we correlated the rated propensity of each of our 80 traits to emerge spontaneously (our gauge
of “innateness”) with its classification as “thinking.” The correlation was highly significant and
negative, r(78) = −.680, p < .0001—the stronger the association of a trait with “thinking,” the
less likely it was to be seen as spontaneously emerging (i.e., innate).
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Figure 1. The presumed innateness of adult human traits (A) and its association with “thinking” response (B). In this and all subsequent
experiments, the scale’s midpoint is indicated by a dashed line. Error bars are 95% confidence intervals for the difference between the means.
Scatter symbols indicate individual traits.
Experiment 2: Rating Infant Human Traits
Method
Participants
and innateness-rating tasks.
Two groups of participants (N = 20 each) were assigned to the trait-classification
The materials consisted of a randomized list of 32 infant traits:
Materials and Procedure
16 cognitive and 16 noncognitive (10 motor and 6 sensory traits). Participants in the classi-
fication task assigned each trait into one of three bins (“thinking,” “action,” or “sensation”). In
the innateness-rating task, participants indicated “how likely it is that an infant would exhibit
this behavior spontaneously, without being shown or taught by a parent, caregiver, or any other
person” (1 = very unlikely; 7 = very likely).
Results
Trait Classification We first confirmed (via mixed-effects logistic regression) that the majority
of classification responses were congruent with the intended category (e.g., “thinking,” for cogni-
tive traits), and this was the case for both cognitive, M = 0.71, β0 = 1.33, Z = 2.78, SE = 0.48,
p = .005, and noncognitive, M = 0.65, β0 = 0.88, Z = 2.15, SE = 0.41, p = .03, traits.
Figure 2A plots participants’ ratings for the propensity of cognitive and
Innateness Rating
noncognitive traits (motor and sensory) to emerge in infants. Noncognitive traits were rated sig-
nificantly higher than the scale’s “neutral” midpoint (4), M = 4.67, t1(19) = 4.44, p < .0003,
d = 0.99; t2(15) = 3.38, p = .004, d = 0.85, but that was not the case for cognitive traits,
M = 3.54, t1(19) = −2.04, p = .055, d = −0.46; t2(15) = −1.78, p = .095, d = −0.45.
Critically, cognitive traits were rated as significantly less likely to emerge spontaneously com-
pared to noncognitive traits, t1(19) = 5.94, p < .0001, d = 1.27; t2(30) = −3.66, p < .001,
d = 0.81.
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Figure 2. The presumed innateness of infant traits (A) and its association with “thinking” response (B). Scatter symbols indicate
individual traits.
The “thinking”–“innateness” link. We next examined whether the perceived propensity of a
trait to emerge spontaneously (a gauge of innateness) is associated with its classification as
“thinking” (see Figure 2B). The correlation was negative and highly significant, r(30) = −.793,
p < .0001—the stronger the association of the trait with “thinking,” the less likely it was to be
viewed as innate.
Experiments 3–4: The Innateness of Adult and Infant Traits (Forced Choice)
Experiments 1–2 demonstrate that people believe that cognitive traits are less likely to emerge
spontaneously relative to noncognitive traits. To further clarify people’s innateness intuitions,
in Experiments 3–4, we next asked people to explicitly indicate whether or not these traits are
inborn. Experiment 3 featured the adult traits; Experiment 4 presented the infant traits.
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Method
Experiments 3–4 presented two groups of participants (N = 20 each) with the adult and infant
traits from Experiments 1–2, respectively. Participants were asked to make a forced choice as
to whether each trait is inborn.
Experiment 3 (Adult Traits): Results and Discussion
We first compared the mean response for each trait type against chance (.5) using a mixed-
effects logistic regression model; another model contrasted responses to cognitive and noncog-
nitive traits (with random intercepts by subject and items, and random slopes for trait type by
subjects and items).
Noncognitive traits were rated significantly higher than chance (M = 0.63, β0 = 0.84,
Z = 2.55, SE = 0.33, p = .01, see Figure 3). Cognitive traits, by contrast, were rated reliably
lower than chance (M = 0.30, β0 = −1.25, Z = −3.61, SE = 0.35, p < .0004). This result
demonstrates that people believe that cognitive traits are not innate.
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Figure 3. The presumed innateness of adult traits (A) and its association with “thinking” response (B). In Panel A, scatter symbols indicate
the responses of individual participants; in Panel B, they reflect individual traits.
A comparison of cognitive and noncognitive traits further confirmed that people were
less likely to view cognitive traits as innate than noncognitive traits (β1 = 2.09, Z = 5.75,
SE = 0.36, p < .0001). The correlation between the rating of the traits for “innateness” and
“thinking” (from Experiment 1) was highly significant, r(78) = −.638, p < .0001.
Experiment 4 (Infant Traits): Results and Discussion
Responses in Experiment 4 were analyzed as described in Experiment 3. A comparison of
the “inborn” responses against chance showed that people believed that cognitive traits are
not inborn in infants (M = 0.36, β0 = −0.85, Z = −2.03, SE = 0.42, p = .04), whereas
noncognitive traits were considered innate (M = 0.66, β0 = 0.94, Z = 2.55, SE = 0.37,
p = .01, see Figure 4). Additionally, cognitive traits were rated as less likely to be inborn
relative to noncognitive traits (β1 = 1.78, Z = 4.11, SE = 0.43, p < .0001). The rating of the
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Figure 4. The presumed innateness of infant traits (A) and its association with “thinking” response (B). In Panel A, scatter symbols indicate
the responses of individual participants; in Panel B, they reflect individual traits.
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traits for “innateness” correlated significantly with their rating for “thinking” (from Experiment
2), r(30) = −.761, p < .0001.
Experiment 5: Infant Experiments
Experiments 3–4 showed that people believe that cognitive traits are unlikely to be innate. It
is possible, however, that people are not inherently biased against innate knowledge. Rather,
people do not understand how one could evaluate the cognitive capacities of infants, as they
are unaware of the experimental methods of infant research. To address this possibility, in
Experiment 5, we presented people with detailed vignettes, adapted from four published infant
experiments (complete with methods, rationale, and predictions), and elicited a binary yes/no
response as to whether those traits are present in newborns.
Two of the vignettes clearly captured knowledge. One vignette concerned newborns’
rudimentary numeric cognition—their capacity to match the number of sounds and dots (Izard,
Sann, Spelke, & Streri, 2009). A second vignette described infants’ moral preferences—the
preference of 3-month-olds for “helpers” over “hinderers” (Hamlin, Wynn, & Bloom, 2010).
The third scenario concerned newborns’ preference for syllable structure (e.g., blog>lbog;
Gómez et al., 2014); since this preference could be based on either abstract linguistic knowl-
edge or sensorimotor restrictions, this case was intermediate between cognition and sensation.
The fourth vignette, by contrast, featured an unambiguous emotional trait—the preference for
happy vs. angry faces (shown in 7-month-old infants, Datyner, Henry, & Richmond, 2017). If
people are reluctant to view cognitive traits as innate, then they should conclude that infants
are unlikely to exhibit knowledge of number and moral preferences. Emotions, on the other
hand, will be viewed as innate (Lindquist, Gendron, Oosterwijk, & Barrett, 2013).
Methods
Twenty participants took part in the experiment. The materials described four published experiments,
examining infants’ sensitivity to four traits: lingua, number, moral preferences, and emotion.
Participants made a binary yes/no response as to whether newborns will be likely to exhibit
sensitivity to the relevant distinction and provided a brief explanation for their response.
Results
As predicted, people believed that the two unambiguous cognitive traits—numeric cognition
(M = 0.25, p = .04) and moral cognition (M = 0.20, p = .01)—are absent at birth (Vedere
Figura 5), and binomial tests indicated that the frequency of these responses differed signif-
icantly from chance. For the language task, responses were at chance (M = 0.45, p = .82).
Most participants who asserted that newborns prefer syllables like “blog” mentioned the sound
of these syllables in their explanations; this is in line with the possibility that people attribute
syllable structure to sensory, rather than cognitive constraints. In contrasto, in the emotion task,
people asserted that newborns will show a preference for smiling faces (M = 0.85, p = .004),
and their justifications often appealed to emotion (per esempio., “I think infants can distinguish between
happy and sad faces”; for all justifications, see the Supplemental Materials; Berent et al., 2019B,
Appendix 3).
REASONING ABOUT INNATE COGNITIVE TRAITS
Why do people assert that cognitive traits are less likely to be innate? One possibility is that this
belief is due to innocent misinformation. People, Infatti, know that young infants can smile and move,
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Figura 5. The presumed spontaneous emergence of cognitive and emotive traits of newborn
infants.
but few are aware of research on infant cognition. Accordingly, participants have no reason to
suspect that some cognitive traits are present at birth. On an alternative account, participants’
behavior reflects an active bias. People, in this view, are not simply unaware of innate knowl-
edge. Piuttosto, they are unwilling to entertain the possibility that some knowledge is innate.
To adjudicate between these possibilities, in Experiments 6–8 we presented people with
detailed vignettes featuring a single trait. Cognitive traits underscored information structure
(per esempio., the rule-based structure of communication), whereas motor traits featured physical ac-
zione. To reduce interference from relevant experience, Experiments 6–7 featured bird and alien
species; Experiment 8 reexamined the basis of the human capacity for language. Critically, par-
ticipants were provided with evidence indicating that all traits are innate. Of interest is whether
participants would still consider cognitive traits as less likely to emerge spontaneously.
Experiment 6: Bird Traits
Methods
Participants
Forty participants took part in this experiment.
The vignettes featured four traits of distinct bird species—two behav-
Materials and Procedure
iors were related to flying, the other two concerned singing. The vignettes were arranged in
matched pairs (see the Supplemental Materials; Berent et al., 2019B, Appendix 1); one pair
member featured a cognitive trait (per esempio., structure of the swamp sparrow’s song); its matched
member featured a motor trait (per esempio., the quail’s head-bobbing, produced during singing). Par-
ticipants were explicitly informed that researchers believe that each of the four traits are likely
inborn, universal to all members of the species, and early emerging in development. Partici-
pants were next invited to imagine that the bird’s fertilized eggs were incubated in isolation;
the hatched chicks would be well cared for, but without exposure to the behavior at hand.
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Figura 6. The presumed innateness of cognitive and motor traits of birds (in Experiment 6).
They were asked to rate on a 1–7 scale (1 = very unlikely; 7 = very likely) how likely the bird
is to produce the relevant behavior once it matures.
Results and Discussion
Figura 6 plots participants’ rating of the propensity of bird traits to emerge spontaneously (UN
gauge of their perceived innateness). We first confirmed that cognitive, M = 5.74, T(39) = 8.86,
P < .0001, d = 1.40, and noncognitive, M = 6.13, t(39) = 14.64, p < .0001, d = 2.31, traits
were each rated higher than the scale’s “neutral” midpoint. This suggests that people heeded
the instructions, indicating that both traits are innate. Of interest, though, is whether they were
equally likely to accept these facts in both conditions.
partial
A 2 Trait (Cognitive/Motor) × 2 Vignette pair ANOVA yielded a reliable effect of Trait,
F(1, 39) = 7.05, p = .01; η2
= .153. There was also a marginally significant effect of
Vignette pair, F(1, 39) = 4.07, p = .05; η2
= .094, as people gave higher innateness
partial
ratings to the vignette pair concerning flying compared to those concerning singing. The Trait
x Vignette interaction, however, was not significant (F < 1). Thus, despite being explicitly
informed that all bird traits are early emerging, adaptive, and likely inborn, people viewed
cognitive traits as less likely to emerge spontaneously (relative to noncognitive traits).
Experiment 7: Alien Traits
Method
Participants
Twenty participants took part in this experiment.
The materials consisted of four vignettes arranged in pairs, matched
Materials and Procedure
for narrative structure and length. One pair contrasted the cognitive capacity of the alien
species to communicate using light signals and their motor capacity for locomotion using
a circular movement style. The second pair of vignettes contrasted the cognitive ability of the
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Figure 7. The presumed innateness of cognitive and motor traits in aliens (in Experiment 7).
aliens to reckon their navigational path by integrating multiple cues, and their motor capacity
for flying by “bounding.” Each such trait was explicitly described as innate, universal, and early
emerging in development.
Participants were asked to imagine that infant members of the species were reared in
isolation (fully cared for) and rate (on a 1–7 scale) how likely each trait is to emerge in those
aliens as they grew into adults.
Results
A comparison of the means against the scale’s “neutral” midpoint confirmed that people thought
cognitive, M = 5.10, t(19) = 2.81, p = .01, d = 0.63, and noncognitive, M = 6.03,
t(19) = 8.89, p < .0001, d = 1.99, traits would each emerge spontaneously in aliens (see
Figure 7). This is only expected given that the instructions explicitly presented both traits as
innate. But an inspection of the means suggests that the innateness ratings were nonetheless
lower for cognitive traits.
A 2 Trait (Cognitive/Motor) x 2 Vignette pair ANOVA yielded a reliable effect of Trait,
= .227. No other effects were significant (all F < 1). Thus,
F(1, 19) = 5.59, p = .03; η2
people viewed cognitive traits of aliens as less likely to emerge spontaneously.
partial
Experiment 8: Human Language
Methods
Participants
Forty participants took part in this experiment.
The materials consisted of two matched vignettes, describing a re-
Materials and Procedure
striction on the sequencing of linguistic elements. One story described an abstract cognitive
constraint on the syntactic sequencing of actors and actions (e.g., “dogs bark” vs. “bark dogs”);
the other story described a motor articulatory constraint on the sequencing of speech sounds
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Figure 8. The presumed innateness of cognitive and motor aspects of human language (in
Experiment 8).
(e.g., blog vs. lbog). Each such restriction was explicitly described as universal and sponta-
neously emerging (without learning). Each story was assigned to a distinct subgroup of partici-
pants (N = 20 each). Participants rated (on a 1–7 scale) how likely it is that the restriction will
emerge spontaneously among a group of children who are raised together, fully cared for, but
devoid of exposure to spoken language.
Results
Although both traits were presented as innate, participants viewed the cognitive syntactic
restriction as significantly less likely to emerge spontaneously than the articulatory motor re-
striction on sound combinations, t(38) = 2.12, p = .04, d = 0.67 (see Figure 8). It is unlikely
that people simply ignored the instructions. Indeed, cognitive, M = 4.9, t(19) = 2.71, p = .01,
d = 0.61, and noncognitive, M = 5.85, t(19) = 6.14, p < .0001, d = 1.37, traits were each
rated higher than the scale’s midpoint. Nonetheless, people were reliably less likely to accept
the conclusion that syntactic cognitive traits will emerge in humans spontaneously.
GENERAL DISCUSSION
This investigation evaluated how laypeople reason about the innateness of cognitive traits.
Across eight experiments, we found that people consistently consider traits associated with
“thinking” as less likely to be inborn.
Experiments 1–2 found that people rated cognitive traits as less likely to emerge spon-
taneously in both adults and infants. Experiments 3–4 explicitly asked participants whether
psychological traits are inborn. To further encourage participants to contrast innate and ac-
quired traits, we elicited a forced choice. Here, people responded that noncognitive traits of
adults and infants are inborn, but cognitive traits are not. Experiment 5 observed that people
were disinclined to believe that infants exhibit certain cognitive traits when they were pre-
sented with detailed descriptions of infant research. Finally, Experiments 6–8 presented people
with detailed descriptions of various traits of birds, aliens, and humans, suggesting each such
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trait is innate. But despite clear evidence for innateness, people remained less likely to enter-
tain the possibility that cognitive traits will emerge spontaneously (i.e., be innate) relative to
noncognitive traits.
The resistance to innateness was specific to cognitive traits that encompass knowledge.
Participants in Experiments 1–4 consistently rated noncognitive traits higher than the scale’s
neutral midpoint, but for cognitive traits, they were either neutral (in Experiments 1–2) or ac-
tively averse to innateness (in Experiments 3–4). Moreover, the reluctance to view a given trait
as innate was negatively correlated with its association with “thinking.” Likewise, participants
in Experiment 5 clearly viewed emotions as innate, but they selectively rejected the innateness
of numeric and moral cognition. Experiments 6–8 documented the same phenomenon in de-
tailed, closely matched vignettes featuring cognitive and motor traits. Whether cognitive traits
are in fact innate is a critical question that falls beyond the scope of our research. Our results,
however, do suggest that people are reluctant to entertain this possibility.
Why are people resistant to the notion of innate knowledge? Our results are not readily
explained by previous accounts of antinativism. One such proposal asserts that people are
generally resistant to nativism because they are concerned about the social implications of
innate individual differences (Pinker, 2002). Another theory suggests that people are blind
to nativism because innate mechanisms are incapsulated, and as such, they are opaque to
introspection (Carruthers, in press; Cosmides & Tooby, 1994). While these results could offer a
partial explanation for our findings, they fail to explain why these biases are selective to innate
knowledge, specifically.
Another possibility is that participants’ reactions are informed by related life experience
suggesting that cognitive traits, such as language and math, are learned. Although this possibil-
ity cannot be ruled out, we note that daily experiences also present evidence for the learning
of motor skills (e.g., riding a bike, typing, and playing a musical instrument). Additionally, it is
unclear why people would maintain this position in the face of explicit information suggesting
that the relevant traits are innate, and why they would extend it to a nonhuman (i.e., less famil-
iar) species. One could respond by saying that people discount evidence for innate knowledge
because they question its reliability; perhaps they assume that cognitive traits are immaterial, so
they cannot be measured precisely. Such beliefs, to be sure, are unjustified, as the information
presented to participants (in Experiments 6–8) indicates that such traits are innate. Moreover,
modern neuroscience tells us all psychological traits—cognitive or not—correspond to phys-
ical brain states. So, this explanation begs the question of why people believe that cognitive
traits are immaterial, and how this presumption is linked to the bias against innate knowledge.
In a fourth explanation, the bias against innate knowledge is at the core of human cog-
nition itself (Berent, in press). Past research suggests that people (including young infants) are
intuitive Dualists (Bloom, 2004). We view objects as material entities, operating according to
the laws of physics (Spelke, 1994; Spelke & Kinzler, 2007), but we attribute the actions of
agents to immaterial mental states– their beliefs, knowledge, and goals (Onishi & Baillargeon,
2005; Woodward, 1998). It is precisely because mental states are presumed immaterial that
children and adults believe they are more likely to transfer to the afterlife (Bering & Bjorklund,
2004) and migrate from one body to another (Cohen & Barrett, 2008; Cohen, Burdett, Knight,
& Barrett, 2011) relative to noncognitive traits.
Other results indicate that people are also Essentialists (Gelman, 2003; Keil, 1986). A
careful reading of the Essentialism literature further suggests that the essence of living things
must be material. It is this presumption that explains why children attribute a doggy’s brown
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color to a tiny piece of matter transmitted from its mother (Springer & Keil, 1991), why they
believe that the essence of a fossilized animal resides in a specific physical location (at its
center, Newman & Keil, 2008), and why infants expect animate agents to have a material
“insides” (Setoh, Wu, Baillargeon, & Gelman, 2013). Discreteness and localization are the
defining features of chunks of matter.
These two principles of core cognition—Dualism and Essentialism—collide in reasoning
about innate knowledge. If cognitive traits are immaterial (per Dualism) and innate traits are
material (per Essentialism), then cognitive traits cannot be innate.
This proposal explains both why people readily assume the innateness of noncognitive
traits and why they are resistant to innate knowledge. Noncognitive traits (sensations, motor
traits, and emotions) can be easily mapped to material bodily states, so a mechanism for in-
heritance is easy for us to identify. But if, in our eyes, cognition (specifically, knowledge) is
immaterial, then it is devoid of the potential for physical inheritance. A bias against innate
knowledge, then, could well be the unintended casualty of the collision between two old evo-
lutionary forces that shape human reasoning about the physical, psychological, and natural
worlds—Dualism and Essentialism. If so, our resistance to innate knowledge could be in our
nature. When it comes to knowledge, antinativism could be innate.
A series of experiments from our lab is in line with this possibility (Berent et al., 2019a).
We found that (a) people consider cognitive traits (from Experiments 1–2) as less material
than noncognitive traits (in line with Dualism) and (b) they consider innate traits (i.e., those
that define human essence) more material compared to when the same traits are presented as
acquired (in line with Essentialism). Moreover, reasoning about innateness can be altered by
manipulating Dualism and Essentialism: people become more likely to view cognitive traits
as innate when they are prompted to think about minds and bodies as one or the same (in
line with Physicalism) compared to situations presenting minds and bodies as distinct (per
Dualism). Additionally, when led to believe that the relevant traits are materially represented
in the brain (per Essentialism), participants are more likely conclude that the traits are innate
(compared to when the traits lack brain instantiation).
A second set of experiments (Berent, Feldman Barrett, & Platt, 2019) demonstrate the
opposite biases for emotions—traits that are readily linked to the material body. We found
that (a) participants assume that emotions are innate and embodied (facially and internally);
(b) when told that emotions are localized in the brain (i.e., embodied), people conclude that
emotions are innate; and (c) this naïve belief persists even when people are explicitly informed
that the emotions in question are in fact acquired. Together, Dualism and Essentialism explain
both our negative bias against innate knowledge as well as our positive bias to presume that
emotions are innate.
Our present results cannot determine why people are resistant to innate knowledge.
However, the findings do suggest that people are systematically biased in reasoning about the
origins of knowledge. These conclusions shed new light on human nature and suggest caution
in the scientific evaluation of innate knowledge.
FUNDING INFORMATION
This research was supported in part by the Humanities Fellowship (to IB) from Northeastern
University.
AUTHOR CONTRIBUTIONS
IB: Conceptualization: Lead; Formal analysis: Lead; Methodology: Lead; Writing – Original
Draft: Lead; Writing – Review & Editing: Lead. MP: Data curation: Supporting; Methodology:
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Supporting; Writing – Review & Editing: Supporting. GMS: Data curation: Supporting;
Writing – Review & Editing: Supporting.
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