Paradox of diversity in the collective brain

Abstract

Human societies are collective brains. People within every society have cultural brains—brains that have evolved to selectively seek out adaptive knowledge and socially transmit solutions. Innovations emerge at a population level through the transmission of serendipitous mistakes, incremental improvements and novel recombinations. The rate of innovation through these mechanisms is a function of (1) a society's size and interconnectedness (sociality), which affects the number of models available for learning; (2) fidelity of information transmission, which affects how much information is lost during social learning; and (3) cultural trait diversity, which affects the range of possible solutions available for recombination. In general, and perhaps surprisingly, all three levers can increase and harm innovation by creating challenges around coordination, conformity and communication. Here, we focus on the ‘paradox of diversity’—that cultural trait diversity offers the largest potential for empowering innovation, but also poses difficult challenges at both an organizational and societal level. We introduce ‘cultural evolvability’ as a framework for tackling these challenges, with implications for entrepreneurship, polarization and a nuanced understanding of the effects of diversity. This framework can guide researchers and practitioners in how to reap the benefits of diversity by reducing costs.
This article is part of a discussion meeting issue ‘The emergence of collective knowledge and cumulative culture in animals, humans and machines’.

Full text

royalsocietypublishing.org/journal/rstb
Review
Cite this article: Schimmelpfennig R, Razek
L, Schnell E, Muthukrishna M. 2021 Paradox of
diversity in the collective brain. Phil.
Trans. R. Soc. B 377: 20200316.
https://doi.org/10.1098/rstb.2020.0316
Received: 19 June 2021
Accepted: 6 October 2021
One contribution of 17 to a discussion meeting
issue ‘The emergence of collective knowledge
and cumulative culture in animals, humans
and machines’.
Subject Areas:
evolution
Keywords:
cultural evolution, diversity, collective
intelligence, collective brain, innovation,
evolvability
Author for correspondence:
Michael Muthukrishna
e-mail: m.muthukrishna@lse.ac.uk
Electronic supplementary material is available
online at https://doi.org/10.6084/m9.figshare.
c.5704503.
Paradox of diversity in the collective brain
Robin Schimmelpfennig
1
, Layla Razek
2
, Eric Schnell
3
and
Michael Muthukrishna
3,4
1
Department of Organizational Behavior, University of Lausanne (UNIL), Chavannes-près-Renens, Lausanne 1015,
Switzerland
2
Department of Biology, McGill University, Dr Penfield Avenue, Montreal, Canada H3A 1B1
3
Department of Psychological and Behavioural Science, London School of Economics and Political Science (LSE),
Houghton Street, London WC2A 2AE, UK
4
Canadian Institute for Advanced Research, Toronto, Ontario, Canada M5G 1M1
RS, 0000-0002-6506-8183; ES, 0000-0001-9157-5763; MM, 0000-0002-7079-5166
Human societies are collective brains. People within every society have
cultural brains—brains that have evolved to selectively seek out adaptive
knowledge and socially transmit solutions. Innovations emerge at a
population level through the transmission of serendipitous mistakes,
incremental improvements and novel recombinations. The rate of innovation
through these mechanisms is a function of (1) a society’s size and intercon-
nectedness (sociality), which affects the number of models available for
learning; (2) fidelity of information transmission, which affects how much
information is lost during social learning; and (3) cultural trait diversity,
which affects the range of possible solutions available for recombination.
In general, and perhaps surprisingly, all three levers can increase and
harm innovation by creating challenges around coordination, conformity
and communication. Here, we focus on the ‘paradox of diversity’—that cul-
tural trait diversity offers the largest potential for empowering innovation,
but also poses difficult challenges at both an organizational and societal
level. We introduce ‘cultural evolvability’as a framework for tackling
these challenges, with implications for entrepreneurship, polarization and
a nuanced understanding of the effects of diversity. This framework can
guide researchers and practitioners in how to reap the benefits of diversity
by reducing costs.
This article is part of a discussion meeting issue ‘The emergence of
collective knowledge and cumulative culture in animals, humans and
machines’.
1. Introduction
Innovation is often assumed to be the work of a talented few—the giants upon
whose shoulders we stand. This assumption, however, is inconsistent with theor-
etical and empirical research in cultural evolution [1,2] which instead suggests
that innovation is more accurately described as an emergent property of our
species’cultural learning psychology, applied within our societies and social net-
works. Human societies and social networks form ‘collective brains’such that
innovations emerge at a population level requiring a specific innovator no
more than our thoughts require a specific neuron. Indeed, not only is the
world too complicated for even the smartest among us to recreate it is also
more complicated than our psychology allows us to believe.
People are unaware that at best they possess a partial causal model of most
of the world they interact with, what has been referred to as the ‘illusion of
explanatory depth’[3–5]. But as recent experiments reveal, a lack of causal
understanding does not prevent solutions from accumulating through selective
social learning [6]. Partial causal models can drive incremental improvement,
© 2021 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution
License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original
author and source are credited.

but large innovative leaps are rarely a product of causal
cogitation, instead, they are typically driven by serendipity
and recombination of existing ideas [1].
Incremental improvement, serendipity and recombination
are influenced by three key levers: sociality, transmission fidelity
and cultural trait diversity. In the next section, we discuss the
challenges that must be resolved foreach lever to increase inno-
vation. This paper focuses on the effects and challenges of
diversity, in particular cultural trait diversity. Diversity is fuel
for recombination. Recombination has far more potential to
drive innovation than incremental improvement or luck. But to
reap the benefits of cultural trait diversity, researchers and prac-
titioners need to better understand how diversity affects
innovationboth in terms of potential benefits and potential costs.
We discuss the interdisciplinary theoretical and empirical
literature on the relationship between cultural trait diversity
and innovation in terms of the ‘paradox of diversity’—that
diversity is both fuel for recombination and a challenge
to communication and coordination. We present a formal
model that captures this trade-off in the collective brain. We
then introduce the concept of ‘cultural evolvability’as a fra-
mework for understanding and resolving the paradox. We
illustrate the insights using the evolution of overconfidence
and its implications for entrepreneurship. These topics are
of interest to both basic and applied scientists working on
cultural evolution and innovation. In the final section, we
focus on the policy implications of this approach to reaping
the benefits of diversity while minimizing the costs.
2. Trade-offs in the collective brain
Each leverof the collective brain—sociality, transmission fidelity
and cultural trait diversity—presents trade-offs and challenges
to innovation (summarized in figure 1). Here, we discuss these
challenges, how they are resolved, and why cultural trait diver-
sity offers the most potential, but also a difficult challenge.
(a) Sociality
Sociality describes the size and interconnectedness of a
society—larger, more interconnected societies offer more
people from whom to learn and have more ideas that can
more easily flow through denser social networks to meet and
recombine. Early theoretical models [7,8] predicted a positive
relationship between sociality and cultural complexity. This
predicted pattern was supported by correlational [9] and
later experimental evidence [10–12]. But this straightforward
positive relationship has some caveats.
Mesoudi [13], for example, models variable learning costs
in cultural traits, predicting an asymptotic relationship
between sociality and cultural complexity. Some traits are
more difficult to learn, decreasing transmission fidelity as
cultural complexity increases. Mesoudi offers the example
of mathematics and science. Unless they get a PhD, twenty-
first-century students typically do not learn any mathematics
developed after 1900; scientific training takes longer, and
major contributions are made at an older age.
The relationship predicted by Henrich [7] also assumes
sufficiently difficult skills that must be socially (rather than
individually) learned. Sociality would not predict improved
performance in sufficiently simple tasks ( for discussion, see [12]).
Increases in population size can also create coordination
challenges and increases in interconnectivity can reduce
diversity through conformity. Indeed, more recent theoretical
and empirical research suggests a non-monotonic relation-
ship between sociality and cultural complexity [14–19]. Too
small a population means too few models to learn from,
but too large a population creates a coordination challenge
reducing effective sociality.
1
Too little interconnectedness
also means too few models to learn from, but too high
interconnectedness poses a coordination challenge and risks
reducing diversity through conformity. The resolution to
this apparent contradiction is twofold.
First, as societies grow they evolve cooperative substruc-
tures such as departments, firms and regional governments
that reduce the coordination challenges relative to a flat struc-
ture [20]. Indeed, given that smaller cooperative groups can
undermine larger cooperative groups [20–22], resolving
these challenges may be a requirement for large cooperative
populations to thrive. We see a micro version of this process
in organizations. As organizations grow, so too do the chal-
lenges of communication and coordination. Organizations
learn from one another, modifying and implementing a
variety of policies and organizational structures from flat
to hierarchical to matrixed in attempts to resolve these
challenges [23].
Second, sociality is a function of both group size and
interconnectedness [7,24]. Muthukrishna & Henrich [1]
argue that there exists an optimal interconnectedness. Large
populations (e.g. cities and countries) have low network
density and low interconnectedness and thus benefit from
increases in connectivity. By contrast, small populations
(e.g. corporate teams, groups in psychology experiments)
may be easily overconnected, increasing coordination chal-
lenges and reducing diversity through conformity. These
challenges of communication, coordination and conformity
overlap with both the challenges of transmission fidelity
and cultural trait diversity.
(b) Transmission fidelity
Transmission fidelity refersto the degree of information preser-
vation during social learning and is therefore increased by
better means of communication. Early genetically evolved
and culture–gene coevolved improvements to transmission
fidelity may have included joint attention and shared inten-
tionality [25,26], theory of mind [27], social tolerance and
prosociality [20,28], and sophisticated language [29–32]. Later
culturally evolved improvements include information com-
pression through heuristics and biases, easier learning
through simplified steps, the discovery and spread of funda-
mental principles that support triangulation, and teaching.
Muthukrishna et al. [33] argue that improved transmission fide-
lity is under selection in support of keeping up with an ever-
growing body of cumulative cultural information. Observed
differences in teaching practices over history and between
societies support this argument [34]. Explicit and effortful
teaching covaries with cultural complexity.
In many hunter–gatherer societies, teaching occurs by
allowing children to observe, perhaps slowed-down, actions
[34–38]. More explicit and effortful instruction is observed
among many pastoralist societies and compulsory formal edu-
cation emerged as a response to the Industrial Revolution.
Migliano & Vinicius [19] make a complementary argument
that teaching in small-scale societies evolves with growing
tendencies toward pair bonding and shared reproductive
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2

interests, arguing that cooperation with unrelated individuals
can decrease the cost–benefit ratio of learning more complex
technologies and social norms. Cultural evolution continues
to increase transmission fidelity in our increasingly culturally
complex modern world, through technologies such as the
printing press, radio, television, Internet, video conferencing
and social media.
We therefore expect a mechanistic positive relationship
between transmission fidelity and innovation. That is, societies
require improvements in transmission fidelity to support
greater cultural complexity. However, high transmission fide-
lity can also reduce cognitive and cultural diversity and
increase ‘Global WEIRDing’(WEIRD: Western, educated,
industrialized, rich and democratic; [39–43]). There is also a
limit to improvements to cultural complexity via improving
transmission fidelity alone. For example, one solution is more
time to learn such as through a cultural extension of the juvenile
period. But this extension of the time required for sufficient
education to survive and thrive in an industrialized society
requires additional support at an older age, increases the time
to peak productivity, and delays the age of reproduction [1].
These limits mean that improvements in transmission fidelity
alone are insufficient to support continuing increases in inno-
vation. Another solution is to simply divide the information
(and labour) among different people—specialization—creating
cultural trait diversity. Cultural trait diversity can continue to
support increases in innovation as long as sociality is sufficient
to ensure enough specialists in every domain.
Figure 1. Innovation in the collective brain is influenced by three levers: sociality, transmission fidelity and cultural trait diversity. All three levers can increase and
harm innovation. Cultural trait diversity offers the most potential, but also a difficult challenge. This duality of cultural trait diversity creates the paradox of diversity.
We introduce cultural evolvability as a means to better understand and resolve the paradox of diversity. (Online version in colour.)
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(c) Cultural trait diversity
Diversity comes in different types measured in different ways
[44]. We focus on cultural trait diversity—differences in
beliefs, behaviors, assumptions, values, technologies and
other transmissible traits. This could include languages, pro-
cessing techniques and technical skills, but also broader traits
such as family structure and occupation. In the public
discourse, diversity often refers to ancestry or physical
characteristics. These may correlate with cultural trait diver-
sity, though the correlation may weaken over generations
through acculturation [45]. Here ‘diversity’refers to cultural
trait diversity unless otherwise specified. Cultural trait
diversity can be distributed in different ways.
Diversity between populations culturally evolves as
populations adapt to local differences, influencing future gen-
erations through historical path dependence created by past
conditions or founder populations [46–48]. Diversity within
populations evolves as information and labour are divided
[49,50]; a way to handle an ever-growing corpus of cumulat-
ive culture (see the model in the electronic supplementary
material). Within-population diversity includes disciplinary
differences, such as the sciences and humanities, industry
specializations [51], guilds and firms [41]. Diversity can
also be structured as ‘cultural clusters’by ethnicity, class,
wealth, occupation, political alignment, religion or incidental
geographical layout [52]. Cultural clusters may intersect, such
as in ethnic occupation specialization [53]. Finally, cultural
trait diversity may also exist within certain individuals—
multicultural individuals, ‘third culture kids’, interdisciplinary
researchers and so on [54–58].
Cultural trait diversity is therefore both the product of
cultural evolution and fuel for the engine of further inno-
vation. However, like sociality and transmission fidelity, it
also comes with a cost [59]. Without a common understand-
ing and common goals, the flow of ideas in social networks is
stymied, preventing recombination and reducing innovation.
As obvious examples, consider the challenge of communi-
cation without a common language or of collaborations
between scientists and humanities scholars or even between
scientists from different disciplines.
But in contrast to sociality and transmission fidelity,
which have fundamental limits, cultural trait diversity has a
much greater scope as fuel for continuing human innovation.
Recombination through diversity offers almost unlimited
innovation potential but diversity can also make it difficult
to communicate and coordinate: the paradox of diversity.
(d) Modelling the paradox of diversity
To better understand the paradox of diversity, we present a
formal model of the trade-off that arises from the division of
labour. In this model, a group of Nindividuals is faced with
learning Mdomains of knowledge with a limited brain and
cognitive capacity b. At one extreme, individuals become
experts in a single domain. This allows them to achieve greater
skill in this single speciality (b), but makes it difficult for two
individuals to coordinate, having no overlap in knowledge.
At the other extreme, everyone learns all domains, but given
their limited bbrain, they learn very little about every
domain (b/M). This removes the coordination problem but
leaves the group with a low level of knowledge in each
domain. Simply put, the division of labour involves a trade-
off between coordination efficiency and increasing skill
levels. More ideas and ways of thinking on the one hand and
difficulties in coordinating, communicating, and agreeing on
goals on the other.
Figure 2 shows the resultsof this modelledtrade-off (details
in the electronic supplementary material). As population size
increases (figure 2a) the coordination problem is exacerbated
and the skill level increases. As the number of domains being
learnt increases (figure 2b) coordination improves and the
skill level decreases. When a change occursto one of these vari-
ables, the other variable must adapt to resolve this trade-off.
For instance, when population size increases, people can
specialize in fewer domains with the same level of coordi-
nation, but increased innovation. Thus, greater cultural trait
diversity requires greater sociality. For example, in a small
town, there may be a single general physician who needs to
know many domains of medicine. But in New York, a doctor
may specialize in a small part of the renal system and get
very good at treating that one part, because other specialists
0.60
0.55
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.55
0.50
0.45
0.40
0.35
0.30
16 18 20 22 24 26 28
population size
40 50 60 70 80
no. domains
0.8
0.7
0.6
0.5
0.4
knowledge of society
network efficiency
0.7
0.6
0.5
0.4
0.3
knowledge of society
network efficiency
network efficiency (M = 30; K = 0.1; A = 2) network efficiency (N = 30; K = 0.1; A = 2)(b)(a)
network efficiency
knowledge of society
network efficiency
knowledge of society
Figure 2. We simulate the trade-off of knowledge of society (skill levels) and network efficiency (coordination). Each player learns a certain number of domains and
makes a connection to other members with an overlap in skills. Coordination in the society is then measured as the ease of traversing this network. The solid curve
represents network efficiency and the dotted curve represents the knowledge of the society (see electronic supplementary material for details on how these are
calculated). As population size increases (a) network efficiency decreases and the knowledge of the society increases. As the number of domains being learnt
increases (b) network efficiency increases and the knowledge of the society decreases. When a change occurs in population size or the number of domains,
the other variable can resolve this trade-off at a new optimum. For instance, if population size increases, a society can learn more skills to improve coordination.
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4

cover other domains. New York populated entirely by nephrol-
ogists would not survive long.
Increasing coordination will allow for greater specialization
and greater cultural trait diversity, supporting innovation. An
important question of scientific and practical importance is
thus how to reap the recombinatorial benefits of diversity in
the collective brain, without paying possible coordinationcosts.
We turn to the evolutionary biological literature on
evolvability for how to understand this paradox and wield
diversity’s double-edged sword. We can apply this literature
to cultural evolution and the collective brain to develop the
concept of ‘cultural evolvability’.
3. Cultural evolvability applied to the paradox of
diversity
Evolvability refers to the ability of a biological system to
produce heritable, adaptive solutions [60,61]; we focus on
the evolvability of a population rather than specific traits
[62–64]. A population may be highly adapted to the local
environment, but may or may not have the evolvability to
adapt to changes in the environment. For example, consider
Darwin’s finches with beak shapes and sizes that are opti-
mized for the present nut shapes and sizes. For the range
of nut shapes and sizes, there is an optimal range of beak
shapes and sizes. But if the distribution of nut shapes
changes, then the ability of the finches to evolve beak shape
or size to compensate will depend on their evolvability. Vari-
ation or diversity, and the forces that create and stabilize that
diversity are key factors that create evolvability.
Cultural evolvability is a balance between diversity and
selection, exploring and exploiting, sampling and specializ-
ing, convergent and divergent thinking, stability and
change, efficiency and flexibility. If a system features an
abundance of diversity, some of the traits are necessarily
less adaptive than others. But without that range of traits
when the environment shifts, there would be an inability to
adapt. Thus, ensuring evolvability necessarily means accept-
ing some amount of inequality and a population-level payoff
less than the current potential maximum. Within population
genetics, many open questions remain on how evolvability
itself evolves [60,61,65–68]. That is, not how organisms find
the most adaptive traits, but how populations or biological
systems support or generate the diversity necessary to
adapt when circumstances change.
Several papers implicitly tackle the cultural evolvability
trade-off between diversity and selection in cultural inno-
vation and adaptation [1,7,63,69–71]. These are analogous
to the explore–exploit or sampling–specializing trade-off in
development over the lifespan [72,73] and the search for
global solutions and avoidance of saddle points within
machine learning [74].
2
Cultural evolvability refers to the ability of a society
to culturally evolve to changed circumstances. It offers a
framework for understanding and resolving the paradox of
diversity. For example, cultural evolvability can help us
to understand optimal levels of diversity or how popula-
tions can reap the benefits of cultural trait diversity by
reducing diversities’coordination cost. What are these costs
and benefits and how can cultural evolvability help us
understand them?
Here, we review the theoretical and empirical literature
on the effects of diversity in different settings through the
lens of cultural evolvability. But diversity comes in many
forms and interpreting the diverse literature on diversity
poses several challenges:
1. Definitions of diversity differ between academic fields,
and between academia and the general public.
2. Even where definitions are similar, the measurement may
differ.
3. Results are sometimes causal and sometimes correlational.
4. Several causal pathways may exist in parallel. For example,
education creates cultural differences (e.g. low and high
education), but independent of the cultural gap, levels of
education also directly predict economic outcomes.
5. The time frame in which relationships and effects are
measured varies. For example, the effects of diversity
may be negative in the short term, but positive in the
longer term [75].
6. The scale of the relationships and effects vary. For
example, organizations, cities, regions or countries [76].
7. The range of diversity may be biased in terms of the samples
used (often WEIRD societies [39,41,77]), types of diversity
studied, and outcomes of interest; all also shaped by the
diversity of researchers and research teams [42].
8. Factors such as discrimination are often ignored in
straightforward tests of the relationship between diversity
and various outcomes [78].
9. Results may not generalize. For example, findings in one
organization and work context with different compositions
of diversity along different dimensions (e.g. educational
background, identity) may not generalize to another.
We argue that the paradox of diversity emerges as a result of
recombinatorial potential on the one hand and coordination
challenges on the other. This paradox partially overlaps
with the way diversity is often used in public discourses,
where it is often characterized by differences in skin colour,
ethnic origin, religion, sex, gender, sexual orientation, or abil-
ity. Here, we specifically focus on cultural trait diversity,
which can but does not necessarily correlate with these
other characteristics. For example, Americans with different
ancestries may possess similar WEIRD psychology [79].
Cultural trait diversity also partially overlaps with
challenging aspects of psychology, norms and institutions,
such as racism, prejudice, xenophobia, sexism, other forms of
discrimination, power differences, and social and economic
inequalities. Here, we specifically focus on coordination chal-
lenges, which influence and are influenced by these
problematic features of the world. Our goal is to review the
overall patterns in the literature and make sense of these in
light of cultural evolvability, discussing other aspects of diver-
sity where relevant. We begin with reviews of the effect of
different types of diversity in different settings.
Within countries, diversity is often approximated by
birthplace diversity, professional diversity, ethnic diversity
or linguistic diversity. Research looking at the relationship
between diversity and economic growth suggests a positive
effect of birthplace diversity, but negative effect of ethnic
and linguistic diversity [80,81]. Within cities, greater pro-
fessional diversity predicts greater productivity [82], but
greater ethnolinguistic diversity is associated with greater
social tension and conflict [83].
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Looking at a specific case, Moser & San [84] show that the
1924 Quota Act, preventing Eastern and Southern Europeans
from coming to the USA, is associated with a decline in US
scientific innovation. This is consistent with other analyses of
the effect of European migration to the USA in the age of
mass migration (1850–1920); counties with more immigrants
have higher income, less poverty, lower unemployment
and greater educational attainment. On the other hand, at
least in the short term, culturally diverse communities are
less trusting [85,86].
Within organizations, one review showed more innovative
teams are comprised of people with more diversity in edu-
cational background (measured as the subject of major or
degree) and occupational background (e.g. finance, marketing,
business development), but more diversity in race and sex had
a weak negative relationship [87]. Another review revealed that
more innovative firms are comprised of people with more
diversity in education and gender, with no effect of ethnic
diversity [88]. A meta-analysis revealed that deep-level diver-
sity (such as personality, values and attitudes) was positively
related to team creativity and innovation, but surface-level
diversity (such as nationality, race and ethnicity) was nega-
tively related or unrelated [89].
Looking at acculturation at the firm level, employees
who show indications of acculturating to the organizational
culture, such as through language, are more likely to be pro-
moted and less likely to involuntarily exit [90]. Mergers and
acquisitions often fail, and the failure is often attributed to the
poor cultural fit of the merged organizations [75]. In an
experimental test of this hypothesis, Weber & Camerer [91]
created lab ‘firms’with separate organizational cultures cre-
ated through idiosyncratic language which then ‘merged’.
Differences in language reduced performance.
Within teams, measurements of the effect of existing diver-
sity on team performance often reveal mixed effects [92,93]. In
an experimental test looking at group size, composite diversity
(a composite measure of demographic, professional, psycho-
logical and relational variables) and team performance
(measured by score on a geo-political forecasting challenge),
Pescetelli et al. [94] show that more diverse teams increased
team performance in larger groups, but harmed performance
in smaller groups.
Finally, within science, high-impact papers and technol-
ogies are often the result of conventional and atypical
combinations of literature and patents, respectively; that is,
grounded in one discipline or domain but borrowing sol-
utions from another [95,96]. But of course, by looking at
published papers and patented technologies, these data do
not capture the many failed collaborations caused by the
challenges of disciplinary differences.
Together, these reviews and examples paint a mixed pic-
ture of the effect of diversity on performance, innovation and
economic growth. Cultural evolvability can help make sense
of these findings and perhaps guide future research on these
additional challenges. Here, we explore some of these
insights and future directions.
(a) Cultural evolvability means tolerance for diversity
Cultural evolvability means tolerance for diversity, because
currently less adaptive traits may be more adaptive when the
environment changes. Across societies, a useful measure of
this tolerance is tightness and looseness: the degree to which
norms are followed and enforced [97,98]. In tight societies,
such as many Asian countries, norm violations are met with
harsh punishments. Such measures make sense when costs of
deviation are higher, such as when there are threats to material
security [99–102]. Deviations will tend to be less adaptive
than the majority strategy. In such societies, not following a
successful ‘Tiger Mother’[103] type strategy—working hard
to secure scarce educational opportunities and subsequent
employment opportunities—has a much larger cost. Tighter
societies are associated with incremental innovation and
loose societies with radical innovation [104,105]. If you con-
form to the majority, deviations are likely to be smaller. If
you conform less, deviations are likely to be larger. Thus
cultural evolvability means under-optimization and inequality.
(b) Cultural evolvability means under-optimization and
inequality
Culturalevolvability necessarily means inequality in outcomes,
because not all will have the optimal strategy for the current
environment. Organizations, for example, face a trade-off
between strategies that favour efficiency and strategies that
favour flexibility. Early attempts to model this trade-off include
Tushman& Romanelli [106] and Lant & Mezias [107]. Organiz-
ations increase efficiency through consistent, strong cultures
that restrict change. Strong cultures enhance firm performance
by improving coordination, sharing similar goals and maximiz-
ing the effort of employees. This strategy performs well in stable
markets, but poorly during times of change. An analysis of a
range of organizations across 18 industries reveals that strong
cultures are outcompeted by flexible, more diverse cultures
during volatile times [108].
Thus under-optimizingand allowing for flexibility increases
an organization’s evolvability, allowing them to better adapt to
changing market conditions in the longer term. Of course, not
all organizations can bear the cost of under-optimizing in the
short term—high risk, high value approaches may be better
suited to larger organizations or larger countries.
Approaches that take advantage of cultural evolvability
include high-risk, high reward skunkworks (i.e. restricting
the approach to a part of the company), an ecosystem of differ-
ent firms trying different strategies (e.g. Silicon Valley), or
countries composed of different states or regions trying differ-
ent approaches (e.g. what US Supreme Court Justice Louis
Brandeis described as ‘laboratories of democracy’). Similarly,
in programming, and more specifically shared multi-agent
reinforcement learning, diversity has shown to increase
problem-solving performance through exploration and indivi-
dualized behaviours [109]. Cultural evolvability means many
approaches will be suboptimal or even fail, but the successful
approaches can be spread and benefit the group as a whole.
Indeed one of the benefits of access to multiple cultures in
pluralistic, multicultural societies is the ability to forge new
approaches by learning, borrowing, and recombining traits
associated with success. If under-optimizing increases inno-
vation, then why are not all countries and companies using
this approach to innovation?
(c) Cultural evolvability helps explain levels of
entrepreneurship
Cultural evolvability requires doing something different.
Similarly, innovation and entrepreneurship mean deviating
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6

from the status quo. People and organizations vary in their
willingness to take an entrepreneurial risk. Most new
businesses fail and the willingness to take a risk depends
on personal and population-level costs and benefits.
First is the personal cost of deviation; many deviations
will result in lower payoffs than following the majority
trait. If it were obvious how to do better, most of the popu-
lation would already use the better strategy. Tolerating
diversity in traits, thus, means tolerating failure. Reducing
the cost of failure increases entrepreneurship as shown for
bankruptcy laws and social safety nets, all of which increase
entrepreneurship and innovation [110–113]. One of the best
predictors of being an inventor in the USA is having rich
parents—a child with parents in the top 1% income distri-
bution is 10 times more likely to be an inventor than a
child born below the median, controlling for measures of
ability [114]. Explanations for this finding include exposure
to innovation, access to well-connected individuals, but
also the financial resources and safety net, which wealth
provides. When failure causes you to fall, you must not fall
too far.
Second is the potential population-level benefit of
deviation. In a large economy with a large customer base
comes large rewards for large innovations—the few winners
can win bigger. Amazon can make more money in the USA
than in Australia. This logic is captured by a model of overcon-
fidence by Johnson & Fowler [115]. Overconfidence that leads
to competing, a proxy for entrepreneurship, is adaptive
when the ratio of the benefit of success to the cost of failure is
sufficiently high. It is fine to keep losing as long as your
occasional wins are greater than your losses. But we can
apply this logic beyond the model to a population level, even
when individual benefits do not outweigh individual costs at
an individual level.
Third is who pays the cost and who benefits from the
innovation at a population level. This is in part a function
of the scale of cooperation [20]. That is, even if at an individ-
ual level the benefits of entrepreneurship do not outweigh
costs, they may do so at a population level if the innovation
leaves everyone better off. Larger countries and companies
can tolerate more diversity and deviation than can smaller
countries and companies who may be better off copying
and sticking to a successful script.
Silicon Valley offers an example. For every Apple and
Amazon, there are thousands of start-ups that have failed—
most start-ups fail [116] and the overwhelming majority never
receive funding [117]—‘unicorns’are called unicorns for a
reason. Many of those entrepreneurs would have had higher
lifetime earnings by taking a salaried job. But the few successes
pay for the failures in an investor’s portfolio and at a population
level. And for this reason, the population may develop a culture
of individualism, non-conformity [118–120], and overconfi-
dence [121,122]. Indeed, risk-taking and overconfidence can
evolve through success-biased transmission as people see the
successful but not the unsuccessful [118,123].
To be an entrepreneur requires a willingness to deviate
from the majority and a belief that you are not only better
than other potential entrepreneurs (overplacement), but
confidence in that belief (overprecision) [124,125]. Without
overconfidence in overconfidence, one may end up a ‘wantra-
preneur’, holding the belief that one would succeed as an
entrepreneur but not being sufficiently confident in the
belief to take the risk. Thus, looseness as a cultural package
can encourage diversity and that diversity creates more rad-
ical innovation, but also more inequality in outcomes. The
redistribution of the payoffs that emerge from these different
strategies, and thus reducing inequalities in outcomes, is a
key factor to resolve the paradox of diversity.
In tolerating failures, societies face the trade-off between
the costs of bankruptcies and social safety nets, and collective
benefits from the risks entrepreneurs take. For this to work,
directly or indirectly, the rewards from innovation must be
redistributed and greater than the cost borne by the society
for the many failures. This redistribution may be direct, for
example, through taxes, or indirect, for example, by increasing
efficiency or improving payoffs for other companies and the
people who benefit from them. Ironically, however, although
tight societies discourage diversity, that intolerance of diversity
can create polarization and a kind of ‘cultural speciation’.
(d) Cultural evolvability can prevent polarization and
cultural speciation
Cultural evolvability interacts with the strength of norm
enforcement. Tighter societies are associated with greater
intolerance for deviation from social norms. But ironically, as
Michaeli & Spiro [126,127] theoretically and empirically
demonstrate, harsh punishments for minor deviations can
increase extremism and polarization. We argue that this polar-
ization in turn may create new cultural groups with more
culturally distant cultural traits; a kind of cultural speciation.
The logic of Michaeli and Spiro’s main model is as
follows: assume a given society holds a social norm that
ascribes a behaviour or expressed belief to be correct in a par-
ticular domain: for example, all must attend weekly religious
services. In a diverse society, some individuals will have
desired behaviours and hold personal beliefs that deviate
from such a social norm—for example, some may prefer to
attend religious services less frequently or not at all. The
strength of enforcement of the social norm incentivises indi-
viduals to adjust their behaviour and expressed beliefs to
different degrees. Societies may vary in the strength of the
sanctions (for example, weak sanctions may include with-
holding help, strong sanctions may include violence) and in
the relationship between the strength of the sanctions and
the size of the deviation. Both the magnitude of the social
sanctions (e.g. lack of approval or punishment) for deviation
and the curvature of the function that defines the relationship
between sanctions and deviation play an important role in
the evolution of diversity in society.
As an illustration, Muscat, Oman is very strict in sanction-
ing even small deviations from many social norms including
religious observance (based on the World Values Survey).
We would expect a small difference in the size of the sanction
between a small and a large deviation. By contrast,
Melbourne, Australia is more liberal and we may expect
small sanctions for small norm violations, but has larger
sanctions for large deviations. We stylistically illustrate
these contrasts in figure 3.
Michaeli and Spiro’s model predicts that large sanctions
for even small deviations (e.g. Muscat) will create an all or
nothing mentality in which individuals either fully conform,
or do not conform at all. A person with weakly held private
desired behaviours or non-conforming beliefs will conform.
A person with more strongly held private desired behaviours
or non-conforming beliefs will not conform since there is little
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7

incentive for compromise if even small deviations elicit a
similarly large sanction. By contrast, more tolerance for
some deviation (e.g. Melbourne) creates a ‘compromise men-
tality’in which individuals conform closer to the norm to a
greater extent.
The authors test their predictions using data from the
World Values Survey [128] using religious practices and reli-
gious norms. Societies with stronger religious norms (e.g.
measured by the item ‘the only acceptable religion is my reli-
gion’) are associated with polarized religious practice. That is,
in societies with stronger religious norms, a larger share of
the society either fully follows the norm (e.g. praying five
times a day) or deviates strongly (e.g. does not pray at all).
The model and results also have implications for debates
on freedom of speech, predicting that large sanctions for
small deviations may encourage polarization of opinion.
Michaeli and Spiro did not model the evolutionary dynamics
of the next generation learning from a polarized rather than
evenly distributed more moderate range of cultural traits,
but intuitively, this may create the conditions for cultural spe-
ciation, where some individuals follow one set of norms and
others follow a different set of norms.
Thus, looser societies that tolerate a multicultural diversity
of opinions and cultural traits may prevent polarization,
and help to reduce the coordination costs of cultural trait
diversity. A comparably loose approach to norm enforcement
and acculturation may also prevent averse dynamics
that play out between communities. For example, native
Germans are more likely to enforce social norms on ethnic
minorities who do not follow local norms [129]. This clustering
of culture complicates a straightforward understanding of
cultural evolvability.
(e) Cultural evolvability depends on cultural clustering
Cultural evolvability depends on how traits are distributed.
For example, the same diversity (in terms of frequency of cul-
tural traits) can be maximally diffuse such that individuals
themselves possess a great diversity of traits [54,57,130]. Or
they can be regionally or ethnically diffuse, such that sampling
from different ethnicities or regions looks similar—i.e. the
cultural distance between ethnicities or regions are small. Or
at the other extreme, the same diversity can be highly clustered
within groups and regions (consider the smaller regional
distances in the USA compared to Europe [42]).
Cultural groups, defined as clustered cultural traits, may
be created by many different processes. For example, confor-
mist learning and learning from common sources [131–133],
norm enforcement [134,135], symbolic markers of in-group
membership [136], collective memories [137,138], and the
forces of cultural-group selection. These forces of cultural-
group selection [20,139,140] include:
1. Assortative migration: biases in where people with
particular traits move—e.g. more individualist people
moving to more individualist countries.
2. Demographic growth: some traits spreading due to their
effect on the fertility of those who possess them—e.g.
norms that encourage fertility, or their correlation with
these traits.
3. Differential survival—some traits helping those who pos-
sess them to survive better—e.g. norms that encourage
caring for ingroup members or norms that lead to success
during the intergroup conflict.
4. Prestige-biased group selection—copying the traits of suc-
cessful groups—e.g. the spread of American culture
through Hollywood.
Competition between internally cooperative, culturally dis-
tant, cultural groups can create corruption and undermine
democratic decision-making [20–22]. For example, favouring
one’s kin group or tribe can undermine governmental insti-
tutions manifesting as nepotism [41,141]. Similarly, when
there is agreement on goals, groups can coordinate on pick-
ing the best person or political party to implement those
shared goals. But a greater difference in goals encourages
supporting the person in your cultural group rather than
the best person.
There are several convergent lines of evidence that reveal
the challenge of clustered diversity. For example, Africa’s colo-
nial history left many nations with arbitrarily drawn national
borders that do not reflect traditional or ethnic boundaries.
Countries containing different ethnic groups or ethnic fractio-
nalization have more civil conflicts [142,143]. Moreover,
within both corporations [144] and countries [143,145,146],
moderate, clustered diversity is associated with greaterconflict.
In highly homogenous groups, people tend to agree on funda-
mental issues, and in highly diverse groups, each group does
not have a sufficiently large critical mass to outcompete other
groups with differing interests. Between these extremes lies a
zone of cultural-group conflict.
Schnell et al. [147] model the competition between coop-
erative groups at different scales, revealing the importance
of resource availability to cooperation and competition.
People cooperate to access resources that they would not be
able to access by themselves or in a smaller group. The opti-
mal payoff is at the group size that maximizes the per person
payoff. The model looks at how transitions between scales of
cooperation can occur. As resources are accessed through
cooperation, the effective carrying capacity increases, allow-
ing the society to access more resources more efficiently
with more people and better technology (e.g. a small group
of hunter–gatherers would have trouble exploiting an oil
field even with the necessary technology and know-how).
sanction
deviation from the norm
Muscat
Melbourne
Figure 3. Illustrative example of relationship between deviation from the norm
and size of the sanctions based on public goods game experimental data as illus-
trated in Fig. 1 in Michaeli & Spiro [126]. In cities such as Muscat, small deviations
from the norm are punished followed by decreasing marginal sanctions. In cities
such as Melbourne the opposite occurs, as they do not punish small deviations, but
increasingly punish larger deviations . Thus, sanctioning can be both harsh and
concave (Muscat), or harsh and convex (Melbourne). (Online version in colour.)
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8

Transitions are easier when the cooperation-unlocked energy
and resources create a carrying capacity that overlaps with
the minimum number of people required to unlock a larger,
but more difficult to access resource. It is difficult to directly
transition from wood-fired steam to solar panels.
The model implies that the cost of clustered diversity may
be low when resources per person are plentiful or where
there is alignment between the incentives of different cultural
groups. But the same level of clustered diversity is a potential
source of conflict under limited resource availability or
even the perception of limited resources. As a stylized
example, consider a competitor (or competing group) open-
ing a pizza shop. When resources are plentiful, the market
is large, the economy is growing, this can be predictive of
your success. It is a signal that the pizza business is booming
and you could open a pizza shop and do well by copying the
cultural traits associated with a successful pizza business.
This incentivises productive competition: working harder to
have the best pizza in town. With a large enough market,
you could expand into a pizza franchise chain.
By contrast, when resources are limited, the market is
small, the economy is zero-sum, someone else’s success is
predictive of your relative loss. They have taken a piece of
the pizza market that you would struggle to get back. This
incentivises destructive competition: competing by harming
others (e.g. negative reviews for competitors). When the
market is large, concerns about tax incentives (inequality con-
cerns) or some groups hiring only ingroup members
(intergroup competition), remain mumblings and grum-
blings. As long as there is a sufficient market for you to
also start a successful business. But when this is not the
case, those mumblings and grumblings can break out into
something more: destructive competition [148].
The ‘Joy of Destruction’economic game has been used to
measure the tendency to engage in destructive competition.
In the Joy of Destruction game, two participants are given
an endowment. One participant is offered the opportunity
to destroy another participant’s endowment at some effi-
ciency. For example, the destroyer might pay $2 to take $4
from the other participant [149,150]. There is no in-game
incentive to engage in destruction and thus any destruction
is a function of out-of-game factors. Levels of destruction
are higher in places where resources are more limited. For
example, rates of destruction in the Joy of Destruction game
are higher in Namibia than Ukraine [149] and higher in low
rainfall regions within Namibia than in high rainfall regions
[151]. Prediger et al. [151] use rainfall as an instrumental vari-
able to causally identify the effect of resource availability on
rates of destruction.
In the light of cultural evolvability and these lines of evi-
dence, let us consider the research, methodological tools, and
policies that may help resolve the paradox of diversity.
4. Resolving the paradox of diversity
Cultural evolvability offers a framework for thinking about the
trade-off between recombination and coordination: the para-
dox of diversity. It also offers paths towards resolution—
reaping the benefits of diversity by reducing costs.
Diversity has been central to the success of all complex
life on earth. Diversity provides the new traits needed to
make life evolvable. Until around 1.2 billion years ago the
source of that diversity was mutation—genetic innovation
through serendipity and incremental improvement alone.
Single cells reproducing by simple replication. The evolution
of sexual reproduction unlocked the recombinatorial power
of diversity, increasing evolvability and the speed of evol-
ution [152]. Sexually reproducing organisms recombine
diverse genetic material to empower genetic evolution.
Today, diverse societies recombine diverse cultural traits to
empower cultural evolution. For example, large, novel leaps
in innovations can emerge through intellectual arbitrage
[153]—taking a perspective or solution from one place or dis-
cipline and applying it to another. But there are many
barriers to cultural traits meeting and recombining.
(a) Reaping diversity’s benefits by reducing costs
We live in an increasingly interconnected and multicultural
world [154]. Migration has been a constant feature of the
human story [155], but since the late nineteenth century’s
Age of Mass Migration [156], more people from more cultu-
rally distant societies increasingly live side by side. And at
a global level, their culturally distant countries of origin are
forced to coordinate on global issues as never before.
On a local scale, organizations are now forced to navigate
the benefits and challenges of diversity. For example, corpor-
ate cultural differences between firms may be a cause of the
large rate of failure in business mergers and acquisitions
[75,91]. Recent analyses reveal just how much human poten-
tial is lost through unequal access to information and
adaptive cultural traits [114,157]. The goal of any society
or organization should be to reap the benefits of diversity
and minimize the costs, thereby maximizing human poten-
tial. Drawing on insights from cultural evolution, the
collective brain and cultural evolvability, we discuss
challenges and insights.
(i) Measuring diversity
As a first step to resolving the paradox of diversity, we need
robust scientific methods to measure cultural trait diversity
and its effect. As we discussed, the definitions and measure-
ment of cultural trait diversity vary between papers and
between fields. Muthukrishna et al. [42] argue that a cultural
fixation index (CFst) offers a robust, theoretically derived
measure of cultural distance grounded in cultural evolution.
Just as a genetic fixation index (Fst) is theoretically mean-
ingful within population genetics, because it measures how
genotype frequencies between subpopulations differ from
expectations if there were random mating over the entire
population, a cultural fixation index (CFst) measures how
cultural trait frequencies between subpopulations differ
from expectations if there were broad social learning across
the entire population and no selection, migration, and
between-group differentiation between subpopulations. As
such, CFst allows us to measure cultural distance in a fine-
grained and direct manner.
Using CFst, we can thus identify the degree of diversity
between any groups, identifying the degree to which they
represent different cultural groups. For example, Handley &
Mathew [158] show that larger cultural distance, as measured
by CFst, predicts lower intergroup cooperation in four
pastoralist ethnic groups in Kenya. This is consistent with
theoretical work on the evolution of ethnic markers to dis-
tinguish group identities to decide who to cooperate with
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9

[136,159,160]. Muthukrishna et al. [42] focus on cultural dis-
tance between regions and countries. White et al. [79] focus
on cultural distance between religions. Handley and
Mathew focus on cultural distance between pastoralist
ethnic groups. New, larger datasets, such as those derived
from social media [161], will allow for cultural distance to
be studied on a much larger and finer scale. These
approaches may be able to re-examine past findings on the
U-shaped relationship between cultural clustering and trust
[145] and cultural clustering and conflict [143,146].
However, as discussed, cultural distance alone is not
necessarily a problem. But under resource scarcity or even per-
ceived resource scarcity, it can be. Thus, managing resource
availability and perceptions of resource availability are critical
to managing the paradox of diversity’s pernicious effects.
(ii) Resource competition and zero-sum perceptions
Resource competition shapes the effect of diversity. When
the perception and reality of competition between cultural
groups are positive-sum or resources are perceived to be
plentiful, clustered diversity can be a source of strength as separate
cultural groups coordinate, productively compete, and cooperate
to mutual benefit, unlocking more resources. Clustered diversity
may be optimal for avoiding homogeneity through conformity;
dividing a problem to solve it [14]. By contrast, when the percep-
tion or reality of competition is zero-sum or resources are
perceived to be limited, people cooperate at the scale needed to
best access those limited resources, creating conflict and destruc-
tive competition [147]. This insight has policy implications.
Within organizations, the local context of competition is
often under management’s control. A case study in the
creation of zero-sum competition is Enron and then CEO
Jeffrey Skilling’s‘rank and yank’policy [162]. Employees
were ranked on relative performance scoring and the
lowest-ranked lost their job. That is, regardless of absolute
performance, if you were relatively worse than other
colleagues under a predefined threshold, you would be fired
[163]. Such a strategy creates zero-sum competition among
employees, reducing the scale of cooperation, the willingness
to share recombinable knowledge, and facilitates unethical
behaviour for personal benefit [164].
Within countries, a review by Baldassarri & Abascal [165]
reveals the importance of economic conditions and
economic interdependence between groups. Prosocial attitudes
aregreaterundermorefavorableeconomic conditions and greater
economic interdependence. Consistent with zero-sum percep-
tions, a review by Craig et al. [166] reveals that the relationship
between intergroup contact and intergroup relations between
majority whites and minorities is moderated by zero-sum percep-
tions of demographic growth. That is, the majority is threatened
by minorities growing relative to the majority. But the context
of competition is sometimes under our control. For example,
investment in public infrastructure (e.g. schools, hospitals) that
matches levels of immigration can mitigate intergroup hostility.
Finally, at a global level, the rhetoric on climate change
policy has evolved from zero-sum framing in terms of
limits on growth to a more positive-sum focus on sustainable
growth and private and collective benefits, reducing
perceived inter-country competition [167].
To summarize, under conditions of plentiful resources,
clustered diversity is not necessarily an issue and may be
helpful as different groups align incentives, specialize and
exploit comparative advantages [10,14,168], increasing
cultural evolvability.
(iii) Bridging the cultural gap
Another obvious key to resolving the paradox of diversity
is finding common ground between cultural groups.
There are many strategies to achieve this common ground.
A basic requirement is communication across diverse
groups and common sources of information.
Language is probably the most obvious dimension that
affects communication—native language proficiency increases
employment probability and earnings [169]; beyond coordi-
nation, earning differences may result from discrimination
based on accents [170]. Investment in language programmes
can help close this earnings gap [171,172]. But other cultural
traits can also impede communication and coordination and
increase discrimination, reinforcing intergroup inequality. An
optimal strategy would involve identifying which cultural
traits and cultural dimensions policies may target to ensure
the best outcomes for both migrants and locals. For example,
individuals and groups can act as translators and bridges—
dual language speakers, individuals trained in multiple disci-
plines, or communities who have a cultural overlap between
two other communities. The development of real-time trans-
lation software shows that technology offers further potential
to help bridge the cultural gap.
More generally, formal education serves as a means by
which a cultural package is efficiently transmitted between
generations. Thus, unequal access to education, between and
within societies, creates a cultural gap that is difficult to close
without increasing access to shared education sources.
Indeed, the cultural distance between those with higher
education in different societies is likely to be smaller than
the cultural distance between those with lower education.
Moreover, given the importance of education as a means of
cultural transmission, the cultural distance between societies
may also reflect educational and economic differences that
equally affect the cultural gap.
The specifics of cultural traits matter and may be incompa-
tible. Such traits may range from which side of the road one
drives on, to whether your marriage practices include bride
prices, dowries, or no material transfer from either side to
power distances and equality between sexes, to different
world views created by different amounts and types of edu-
cation. These are important, but difficult challenges, especially
since cultural traits are not independent, but connected to one
another in ‘cultural complexes’of mutually interdependent
cultural traits, analogous to gene complexes [173].
Migration is a boon to economic development [174], but
these overall results differ by cultural, economic and edu-
cational distance. As one example, first-generation European
migrants to the UK make a greater fiscal contribution relative
to their cost to the social welfare system than do non-European
migrants (who are similar to locals in their contribution to cost
ratio) [175]. In an analysis including the UK, France and
Germany, and both first- and second-generation migrants,
Algan et al. [176] show similar differences between culturally
close and culturally distant ethnic groups. Between gener-
ations, the education and language gap closes in most cases.
The employment gap decreases, but does not close.
There are many caveats to interpreting these studies. In
the second generation, it is more difficult to identify ethnicity
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10

and immigration status creating possible sampling biases. But
even in the first generation, discrimination and other barriers
faced by more culturally distant migrants likely contribute to
these differences. However, a straightforward application of
this empirical literature to policy would preference more
culturally close migrants. By contrast, from a cultural evolva-
bility perspective, it is more culturally distant migrants who
offer more radically different cultural traits for recombina-
tion. Thus, from this perspective policies that target the
challenges faced by new migrants, particularly those from
more culturally distant places of origin, and particularly
those that target cultural traits that harm communication
and coordination, are likely to reap benefits. The key in this
case and others is reducing communication and coordination
costs to unlock the benefits of diversity for all members of
society. There are many ways for this to be achieved.
Within organizations, Cremer et al. [177] show that man-
agers can serve as translators, supporting between-unit
coordination where units lack a common technical language.
Groups can also negotiate a middle ground through
increased perspective-taking, which is associated with
higher team creativity [178].
Within countries, where diversity is less clustered, people
may be forced to find common ways of communicating. For
example, people from countries with a long history of
migration use more universally recognizable facial emotional
expressions [179,180]—for example, Americans are known
for their broad smiles and unambiguous displays of emotion.
In contrast, in a more homogenous country like Japan, other
Japanese may understand emotion based on context without
the need for explicit expression. But if your neighbour comes
from a very different place and does not speak the same
language, you need to be explicit in your emotional expression.
Research on contact theory reveals that a collaborative
rather than adversarial contact—consistent with positive
rather than zero-sum conditions—decreases intergroup
differences and hostility [181]. But the dimensions of cultural
difference matter and results on contact theory do not necess-
arily generalize. For example, in a field experiment, Mousa
[182] increased contact between Christians and Muslims in
football teams, raising tolerance, but not overall social cohe-
sion. Because the specifics of cultural trait diversity matter,
directly measuring cultural distance, trait and dimension
differences, and considering time scale and cohort are impor-
tant aspects of resolving the paradox of diversity. Time is
particularly important; many studies show fleeting or ambig-
uous effects of contact [183]. Groups need time to find ways
to communicate and coordinate [184]. Moreover, small inter-
ventions over short time periods (such as short-term bias
training; for review see [185]) are unlikely to remove the
underlying causes of barriers to communication and coordi-
nation nor the different levels of discrimination that
different groups face.
Finally, an important future area of research is how new
forms of communication, such as the Internet and social
media, and new forms of meeting and networking, such as
social media and dating apps affect the paradox of diversity.
5. Conclusion
Humans are a deeply cooperative species. Our greatest
achievements and our worst atrocities are both cooperative
acts. The scale of our cooperation has increased over time,
but still varies considerably between groups [20,48]. Through
large-scale cooperation, we share ideas and allow our societies’
collective brains to innovate solutions to problems we all face.
That innovation is empowered by diversity, but that diversity
also by definition divides groups into smaller cooperative
groups with lower levels of trust and the ability to communi-
cate, coordinate and work together for mutual benefit. The
challenge is greater in a world in which more culturally distant
people live side by side and in which more culturally distant
societies must coordinate on global challenges. But while the
challenge is greater, so too are the potential gains.
Cultural evolvability offers a framework for understanding
the importance and impact of diversity and how to reap its
benefits and reduce its costs. By resolving the paradox of diver-
sity, we bring more perspectives to bear on our common
problems, encourage recombination of the best solutions
from different societies and disciplines, and unlock human
potential by creating conditions conducive to ever larger
scales of cooperation and ever greater levels of innovation.
Data accessibility. Code is submitted as electronic supplementary
material.
Authors’contributions. R.S., L.R., E.S. and M.M. all contributed to the
writing of the paper. R.S. wrote the first draft. L.R. assisted with
the literature review. E.S. built the model.
Competing interests. We declare we have no competing interests.
Funding. M.M. acknowledges support from the Canadian Institute for
Advanced Research (CIFAR) grant no. CP22-005 and Templeton
World Charity Foundation grant TWCF0612. R.S. acknowledges sup-
port from the Swiss National Science Foundation (grant no.
100018_185417/1).
Acknowledgements. We would like to thank Christopher French for his
feedback on an earlier version of this paper and Veronika Plant for
illustrating figure 1.
Endnotes
1
Analogous to the concept of effective population size in population
genetics, here a function of the effective number of models for
learning.
2
Some insights from machine learning are particularly interesting. For
example, getting stuck in local optima is sometimes considered a pro-
blem. However, in a sufficiently high-dimensional space there are
effectively no local optima, only saddle points with some dimension
that allows escape. Given the large dimensionality of biological and
cultural systems, there may be no true evolutionary stable equilibria.
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