[Paleopsych] Paul R. Ehrlich and Simon A. Levin: The Evolution of Norms

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Paul R. Ehrlich and Simon A. Levin: The Evolution of Norms

Paul R. Ehrlich is with the Department of Biological Sciences, Stanford
University (Stanford, California, United States of America). Simon A. Levin
is with the Department of Ecology and Evolutionary Biology, Princeton
University (Princeton, New Jersey, United States of America).
E-mail: slevin at princeton.edu
Published: June 14, 2005
DOI: 10.1371/journal.pbio.0030194

Citation: Ehrlich PR, Levin SA (2005) The Evolution of Norms. PLoS Biol 3(6):

Over the past century and a half, we have made enormous progress in assembling 
a coherent picture of genetic evolution.that is, changes in the pools of 
genetic information possessed by populations, the genetic differentiation of 
populations (speciation) (see summaries in [1,2]), and the application of that 
understanding to the physical evolution of Homo sapiens and its forebears ([3]; 
e.g., [4,5]). But human beings, in addition to being products of biological 
evolution, are.vastly more than any other organisms.also products of a process 
of .cultural evolution.. Cultural evolution consists of changes in the 
nongenetic information stored in brains, stories, songs, books, computer disks, 
and the like. Despite some important first steps, no integrated picture of the 
process of cultural evolution that has the explanatory power of the theory of 
genetic evolution has yet emerged.

Much of the effort to examine cultural evolution has focused on interactions of 
the genetic and cultural processes (e.g., [6], see also references in [7]). 
This focus, however, provides a sometimes misleading perspective, since most of 
the behavior of our species that is of interest to policy makers is a product 
of the portion of cultural evolution [8] that occurs so rapidly that genetic 
change is irrelevant. There is a long-recognized need both to understand the 
process of human cultural evolution per se and to find ways of altering its 
course (an operation in which institutions as diverse as schools, prisons, and 
governments have long been engaged). In a world threatened by weapons of mass 
destruction and escalating environmental deterioration, the need to change our 
behavior to avoid a global collapse [9] has become urgent. A clear 
understanding of how cultural changes interact with individual actions is 
central to informing democratically and humanely guided efforts to influence 
cultural evolution. While most of the effort to understand that evolution has 
come from the social sciences, biologists have also struggled with the issue 
(e.g., p. 285 of [10], [11.16], and p. 62 of [17]). We argue that biologists 
and social scientists need one another and must collectively direct more of 
their attention to understanding how social norms develop and change. 
Therefore, we offer this review of the challenge in order to emphasize its 
multidisciplinary dimensions and thereby to recruit a broader mixture of 
scientists into a more integrated effort to develop a theory of change in 
social norms.and, eventually, cultural evolution as a whole. What Are the 
Relevant Units of Culture?

Norms (within this paper understood to include conventions or customs) are 
representative or typical patterns and rules of behavior in a human group [18], 
often supported by legal or other sanctions. Those sanctions, norms in 
themselves, have been called .metanorms. when failure to enforce them is 
punished [17,19,20]. In our (liberal) usage, norms are standard or ideal 
behaviors .typical. of groups. Whether these indeed represent the average 
behaviors of individuals in the groups is an open question, and depends on 
levels of conformity. Conformity or nonconformity with these norms are 
attributes of individuals, and, of course, heterogeneity in those attributes is 
important to how norms evolve. Norms and metanorms provide a cultural 
.stickiness. (p. 10 of [21]) or viscosity that can help sustain adaptive 
behavior and retard detrimental changes, but that equally can inhibit the 
introduction and spread of beneficial ones. It is in altering normative 
attitudes that changes can be implemented.

Here, we review the daunting problem of understanding how norms change, discuss 
some basic issues, argue that progress will depend on the development of a 
comprehensive quantitative theory of the initiation and spread of norms (and 
ultimately all elements of culture), and introduce some preliminary models that 
examine the spread of norms in space or on social networks. Most models of 
complex systems are meant to extract signal from noise, suppressing extraneous 
detail and thereby allowing an examination of the influence of the dominant 
forces that drive the dynamics of pattern and process. To this end, models 
necessarily introduce some extreme simplifying assumptions.

Early attempts to model cultural evolution have searched for parallels of the 
population genetic models used to analyze genetic evolution. A popular analogy, 
both tempting and facile, has been that there are cultural analogues of genes, 
termed .memes. [22,23], which function as replicable cultural units. Memes can 
be ideas, behaviors, patterns, units of information, and so on. But the 
differences between genes and memes makes the analogy inappropriate, and 
.memetics. has not led to real understanding of cultural evolution. Genes are 
relatively stable, mutating rarely, and those changes that do occur usually 
result in nonfunctional products. In contrast, memes are extremely mutable, 
often transforming considerably with each transmission. Among humans, genes can 
only pass unidirectionally from one generation to the next (vertically), 
normally through intimate contact. But ideas (or .memes.) now regularly pass 
between individuals distant from each other in space and time, within 
generations, and even backwards through generations. Through mass media or the 
Internet, a single individual can influence millions of others within a very 
short period of time. Individuals have no choice in what genes they incorporate 
into their store of genetic information, and the storage is permanent. But we 
are constantly filtering what will be added to our stored cultural information, 
and our filters even differentiate according to the way the same idea is 
presented [24,25]. People often deliberately reduce the store of data (for 
example, when computer disks are erased, old books and reprints discarded, 
etc.), or do so involuntarily, as when unreinforced names or telephone numbers 
are dropped from memory. Such qualitative differences, among others, ensure 
that simple models of cultural evolution based on the analogy to genetic 
evolution will fail to capture a great deal of the relevant dynamics. A model 
framework addressed to the specific challenges of cultural evolution is needed.

In the models discussed below, the most basic assumption is that the spread (or 
not) of norms shares important characteristics with epidemic diseases. In 
particular, as with diseases, norms spread horizontally and obliquely [14], as 
well as vertically, through infectious transfer mediated by webs of contact and 
influence. As with infectious diseases, norms may wax and wane, just as the 
popularity of norms is subject to sudden transitions [3]. On the other hand, 
there are unique features of cultural transmission not adequately captured by 
disease models, in particular the issue of .self-constructed. knowledge, which 
has long been a source of interest, and the development of problem-solving 
models in psychology ([26, 27]; D. Prentice, personal communication). New 
syntheses are clearly required. Microscopic Dynamic

Substantial progress has been made toward the development of a mathematical 
theory of cultural transmission, most notably by Cavalli-Sforza and Feldman 
[14], and Boyd and Richerson [11]. Cavalli-Sforza and Feldman consider the 
interplay between heritable genetic change and cultural change. This is an 
important question, addressed to the longer time scale, with a view to 
understanding the genetic evolution of characteristics that predispose 
individuals to act in certain ways in specified situations. For many of the 
phenomena of interest, however, individual behaviors have not evolved 
specifically within the limited context of a single kind of challenge, but in 
response to a much more general class of problems. Efforts to provide genetic 
evolutionary explanations for human decisions today within the narrow contexts 
in which they occur may be frustrated because generalized responses to 
evolutionary forces in the distant past have lost optimality, or even adaptive 
value. Extant human behaviors for example may be the relics of adaptations to 
conditions in the distant past, when populations were smaller and technology 
less advanced. Attempts to understand them as adaptive in current contexts may 
therefore be futile. Thus, we prefer to take the genetic determinants of human 
behavior (that, for example, we react strongly to visual stimuli) as givens, 
and to ask rather how those initial conditions shape individual and social 
learning [3]. Similar efforts have been undertaken by others, such as Henrich 
and Boyd [28] and Kendal et al. [20].

The sorts of models put forth by Cavalli-Sforza and Feldman, Boyd and 
Richerson, and others are a beginning towards the examination of a colossal 
problem. To such approaches, we must add efforts to understand ideation (how an 
idea for a behavior that becomes a norm gets invented in first place), and 
filtering (which ideas are accepted and which are rejected). How many ideas 
just pop up in someone's brain like a mutation? How many are slowly assembled 
from diverse data in a single mind? How many are the result of group 
.brainstorming?. How, for example, did an idea like the existence of an 
afterlife first get generated? Why do ideas spread, and what facilitates or 
limits that spread? What determines which ideas make it through transmission 
filters? Why are broadly held norms, like religious observance, most often not 
universal (why, for instance, has atheism always existed [29,30])? Ideas may be 
simply stated, or argued for, but transmission does not necessarily entail the 
reception or adoption of behaviors based on the idea, e.g., [31]. What we 
accept, and what gets stored in long-term memory, is but a tiny sample of a 
bombardment of candidate ideas, and understanding the nature and origin of 
filters is obviously one key to understanding the life spans of ideas and 
associated behaviors once generated. The Emergence of Higher-Level Structure: 
Some Simple Models

Our filters usually are themselves products of cultural evolution, just as 
degrees of resistance of organisms to epidemics are products of genetic 
evolution. Filters include the perceived opinions of others, especially those 
viewed as members of the same self-defined social group, which collectively 
attempt to limit deviance [32.34]. .Conformist transmission,. defined as the 
tendency to imitate the most frequent behavior in the population, can help 
stabilize norms [28] and indeed can be the principal mechanism underlying the 
endogenous emergence of norms. The robustness of norms can arise either from 
the slow time scales on which group norms shift, or from the inherent 
resistance of individuals to changing their opinions. In the simplest 
exploration of this, Durrett and Levin (unpublished data) have examined the 
dynamics of the .threshold. voter model, in which individuals change their 
views if the proportion of neighbors with a different opinion exceeds a 
specified threshold. Where the threshold is low, individuals are continually 
changing their opinions, and groups cannot form (Figure 1A). In contrast, at 
high thresholds, stickiness is high.opinions rarely change.and the system 
quickly becomes frozen (Figure 1B). Again, groups cannot form. In between, 
however, at intermediate thresholds (pure conformist transmission), groups form 
and persist (Figure 1C). In the simplest such models in two dimensions, 
unanimity of opinions will eventually occur, but only over much longer time 
periods than those of group formation (see also [20]). When the possibility of 
innovation (mutation) is introduced in a model that considers linkages among 
traits and group labels, and where individuals can shift groups when their 
views deviate from group norms sufficiently, multiple opinions and multiple 
groups can persist, essentially, indefinitely (Figure 1D). Figure 1.

(A) Long-term patterning in the dynamics of two opinions for the threshold 
voter model with a low threshold.

(B) Long-term patterning in the dynamics of two opinions for the threshold 
voter model with a high threshold. Note the existence of small, frozen 

(C) Long-term patterning in the dynamics of two opinions for the threshold 
voter model with an intermediate threshold. Note the clear emergence of group 

(D) Long-term patterning in a model of social group formation, in which 
individuals imitate the opinions of others in their (two) groups, and others of 
similar opinions, and may switch groups when their views deviate from group 

The formation of groups is the first step in the emergence of normative 
behavior; the work of Durrett and Levin shows that this can occur endogenously, 
caused by no more than a combination of ideation and imitation. The existence 
of a threshold helps to stabilize these groups, and to increase stickiness; 
furthermore, if threshold variation is permitted within populations, these 
thresholds can coevolve with group dynamics. What will the consequences be for 
the size distribution of groups, and for their persistence? Will group 
stability increase, while average size shrinks? What will be the consequences 
of allowing different individuals to have different thresholds, or of allowing 
everyone's thresholds to change with the size of the group? When payoffs reward 
individuals who adhere to group norms, and when individuals have different 
thresholds, will those thresholds evolve? The answers to such questions could 
provide deep insights into the mechanisms underlying the robustness of norms, 
and are ripe for investigation through such simple and transparent mathematical 

Modeling may also shed light on why some norms (like fashions) change so 
easily, while others (like foot binding in imperial China) persist over 
centuries, and more generally on how tastes and practices evolve in societies. 
Norms in art and music change rapidly and with little apparent effort at 
persuasion or coercion. But three-quarters of a century of communism barely 
dented the religious beliefs of many Russians, despite draconian attempts to 
suppress them [35], and several centuries of science have apparently not 
affected the belief of a large number of Americans in angels and creationism 
(e.g., [36,37]). Then there are the near-universal norms, such as the rules 
against most types of physical assault or theft within groups that, although 
they vary in their specifics, are interpreted as necessary to preserve 
functional societies. Group-selection explanations for such phenomena (e.g., 
[12]) are, we argue, neither justified nor necessary (see also pp. 221.225 of 
[38], [39]). Such behaviors can emerge from individual-based models, simply 
involving rewards to individuals who belong to groups.

There are degrees: the evolution of cooperation is facilitated by tight 
interactions, for example when individuals interact primarily with their 
nearest neighbors [40,41], and the payoffs that come to individuals from such 
cooperation can enhance the tightness of interactions and the formation of 
groups. This easily explains why mutually destructive behaviors, like murder, 
are almost universally proscribed. Group benefits can emerge, and can enhance 
these effects, but it is neither necessary nor likely that group selection 
among groups for these behaviors overrides individual selection within groups 
when these groups are not composed of closely related individuals [42].

Simple models could address such things as the role of contagion in cultural 
evolution, recognized in one of the first works on psychology [43] in the 
context of religious revivals and belief, as what has been described as .pious 
contagion. (p. 10 of [30]). But models must also address issues such as the 
roles of authority or moral entrepreneurs (individuals engaged in changing a 
norm) [32], to say nothing of the impacts of advertising and the norm-changing 
efforts of the entertainment and other industries. In reality, we are 
intentioned agents who act with purpose. In maturing, we master the norms that 
have been evolved over a long period, but to which we may adapt in different 
ways and even (in the case of moral entrepreneurs) strive to change.

For a moral entrepreneur, a group that is too small may have little influence 
and be not worth joining. But large groups may be too difficult to influence, 
so also may not be worth joining. For such individuals, there is likely an 
optimal group size, depending on the change the individual wants to effect. 
Groups also introduce ancillary benefits of membership that change the 
equation. Such considerations influence decisions such as whether to join a 
third party effort in a political campaign; understanding the interplay between 
individual decisions and the dynamics of party sizes is a deeply important and 
fascinating question, with strong ecological analogies. Groups, collectively, 
must also wrestle with the costs and benefits of increasing membership, thereby 
enhancing influence while potentially diminishing consensus and hence the 
perceived benefits to members. Innovation and Conservatism

Cultural evolution, like biological evolution, contains what we like to call 
the .paradox of viscosity.. Evolving organisms must balance the need to change 
at an appropriate rate in response to varying environmental conditions against 
the need to maintain a functioning phenome. This trade-off between conservatism 
and adaptability, between stability and exploration, is one of the central 
problems in evolutionary theory. For example, how much change can there be in 
the genes required to maintain adaptation in a caterpillar without lethally 
affecting the structure and functioning of the butterfly (p. 303 of [44])? 
Conservatism in religion might be explained by the lack of empirical tests of 
religious ideas. But even in military technology and tactics, where empirical 
tests are superabundant, changes are slower than might be expected. For 
example, the British high command in World War I did not react rapidly to the 
realities of barbed wire, massed artillery, and machine guns [45]. Even so, the 
conservatism of the generals may be overrated [46]. Macroscopic Dynamics

We have thus far examined the evolution of norms in isolation.as how the views 
of individuals (and thus the constituents of a pool of nongenetic information) 
change through time. But everywhere in common discourse and technical 
literature, it is assumed that norms are bundled into more or less discrete 
packages we call cultures, and that those packages themselves evolve. Recall 
that everyday notions such as that American culture of the 1990s was very 
different from that of the 1960s, that Islamic culture did not undergo the sort 
of reformation that convulsed Christian culture (for example, [47]), and that 
Alexander the Great carried Greek culture throughout the Mediterranean and as 
far east as Persia. The problem of defining .cultures. in cultural evolution 
seems analogous to that of defining .species. (or other categories) in genetic 
evolution. There has been a long and largely fruitless argument among 
taxonomists over the latter [48], and an equally fruitless debate in 
anthropology (and biology) on the definition of culture [39, 49.57].

Again, we suggest that the parsing of the various influences that create and 
sustain norms and cultures are ripe for theoretical modeling, but it must begin 
to incorporate the full richness on multiple scales of space, time, and 
complexity. Durrett and Levin [3] develop a model integrating the dynamics of 
clusters of linked opinions and group membership; appropriate extensions would 
allow group characteristics to evolve as well, but on slower time scales. The 
oversimplicity of models of symmetric imitation on regular grids, as 
represented in our simple models, must give way to those that incorporate 
fitnesses and feedbacks, as well as asymmetries and power brokers, on more 
complex networks of interaction [58]. Challenges and Hypotheses

One of the major challenges for those interested in the evolution of norms is, 
at the most elementary level, defining a norm. This is related to another 
general problem of defining exactly what is changing in cultural 
evolution.which we might call the .meme dilemma. in honor of Dawkins' 
regrettably infertile notion. A second major challenge is discovering the 
mechanism(s) by which truly novel ideas and behaviors are generated and spread. 
A third is discovering the most effective ways of changing norms.

We've got a long way to go before being able to meet those challenges. One 
place to start is to begin formulating hypotheses about the evolution of norms 
that can be tested with historical data, modeling, or even (in some cases) 
experiments. Some hypotheses we believe worth testing (and some of which may 
well be rejected) are given in Box 1. Box 1. Sample Hypotheses about the 
Evolution of Norms

Hypothesis 1. Evolution of technological norms will generally be more rapid 
than that of ethical norms.

Technological changes are generally tested promptly against environmental 
conditions.a round wheel wins against a hexagonal one every time, and the 
advantages of adopting it are clear to all. Ethical systems, on the other hand 
cannot often be tested against one another, and the standards of success are 
not only generally undetermined, they often vary from observer to observer and 
are the subject of ongoing controversy among philosophers.

Hypothesis 2. In societies with nonreligious art, the evolution of norms in art 
will be more rapid than those in religion.

We hypothesize that art is less important to the average individual than his or 
her basic system of relating to the world, and conservatism in the latter would 
be culturally adaptive (leading to success within a culture).

Hypothesis 3. Military norms will change more in defeated nations than 
victorious ones.

Was the Maginot Line and the generally disastrous performance of the French 
army in 1940 an example of a more general rule? Does success generally breed 

Hypothesis 4. The spread of a norm is not independent of the spread of others, 
but depends on the spread of other norms (norm clusters).

Does, for example, empathy decrease with social stratification?

Hypothesis 5. Susceptibility to the spread of norms is negatively correlated 
with level of education.

Are the less educated generally more conformist, or does the spread of norms 
depend almost entirely on the character of the norm?

Hypothesis 6. Horizontal transmission will show less stickiness than vertical 

This conjecture is based on anecdotal observations that norms like using hula 
hoops come and go and are primarily horizontally transmitted, and religious 
values and other high-viscosity points of view are mostly vertically 
transmitted (p. 129 of [14], [59]).

In this essay we have tried to be provocative rather than exhaustive. There is 
a welter of issues we have not even attempted to address, including: (1) 
asymmetries of power in the spread of norms, (2) the role of networks, (3) the 
efficacy of persuasion as opposed to imitation, (4) the cause of thresholds in 
the change of norms, (5) the genesis of norms during child development, (6) the 
connection between attitudes and actions, (8) competition among norms from 
different cultures; and (9) the question, can norms exist .free of people. in 
institutions? Institutions certainly may emerge as independent structures, 
stabilized by laws and customs that are enforced to varying degrees through 
formal punishment or social pressure. Can such norms persist long even when 
adherence to them is disappearing? The interplay between the dynamics of 
individual behaviors and normative rules, operating on different time (and 
other) scales, may be the key, we argue, to understanding sudden phase 
transitions that can transform the cultural landscape.

We hope that, by being provocative, we can interest more evolutionists, 
behavioral biologists, and ecologists in tackling the daunting but crucial 
problems of cultural evolution. Few issues in science would seem to be more 
pressing if civilization is to survive. Acknowledgments

We have received helpful critical comments from Kenneth Arrow, John Bonner, 
Samuel Bowles, Kai Chan, Gretchen Daily, Partha Dasgupta, Adrian deFroment, 
Anne Ehrlich, Marcus Feldman, Michelle Girvan, Ann Kinzig, Deborah Prentice, 
and Will Provine. Amy Bordvik provided invaluable assistance in preparing the 
manuscript for publication.

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