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and the bifocal stance that allows flexible switching between both?
We think that light can be shed on this question through an inves-
tigation of how it may have emerged in our hominid ancestors.
Following Sterelny’s(2012) account of the evolution of human
cognition, which emphasizes feedback loops between learning,
environmental scaffolding, and cooperative foraging, we maintain
that the evolution of the bifocal stance should be understood in
the context of cooperative foraging. This type of social arrange-
ment creates unique pressures and opportunities that can support
the development of both types of cultural learning, as well as the
ability to move between them as appropriate.
Successful cooperative foraging can provide a surplus under
which investments into cultural learning can be sustained before
they inevitably have to pay off. Elsewhere, one of us has argued
that it is in this context that we can understand the evolution
of resolve as a means to enable interpersonal exchange (Veit &
Spurrett, 2021). Here too, the value of the instrumental stance
increases. With sharing and trading becoming a central feature
of the lives of our early hominid ancestors, there was a need to
evolve both motivation and attention towards keeping track of
the instrumental value of different actions, which could be scaf-
folded to promote a greater awareness of the instrumental value
of both behavioural innovations and other people’s actions.
With more complex foraging methods, the value of learning
and innovation also increases, further expanding the human for-
aging niche. However, importantly, this also has the potential to
have facilitated the development of the ritual stance. Human
societies are unique in the degree of reliance of individuals on the
community. Under these conditions, the risks from social ostracism
are much higher, as it would be near impossible for an individual to
survive in isolation. As the authors have demonstrated, the salience
or threat of social ostracism seems to lead into the ritual stance,
where copying fidelity increases. In general, as the rewards of social
cohesion increase, along with the costs of ostracism, we should
expect to see the elaboration of the ritual stance; and this is precisely
what occurs with the rise of cooperative foraging.
Cultural learning is far more complex in humans than any
other species, seemingly responsible for many of the features we
take to be unique about human cognition and societies.
Although other animals, particularly some nonhuman primates,
show some forms of social learning and cultural transmission,
right now it appears that only humans are capable of the high-
fidelity copying that arises from the ritual stance, and of moving
flexibly between the different types of learning as need suits. We
suggest that it is through the emergence of cooperative foraging,
and the unique selective environment thus created, that the bifo-
cal stance will have truly come into its own, creating feedback
loops that have led to its current form.
Financial support. WV’s research was supported under Australian Research
Council’s Discovery Projects funding scheme (project number FL170100160).
Conflict of interest. None.
References
Dennett, D. C. (1987). The intentional stance. MIT Press.
Horner, V., & Whiten, A. (2005). Causal knowledge and imitation/emulation switching in
chimpanzees (Pan troglodytes) and children (Homo sapiens). Animal Cognition,8(3),
164–181.
Sterelny, K. (2012). The evolved apprentice. MIT Press.
Veit, W., Dewhurst, J., Dołega, K., Jones, M., Stanley, S., Frankish, K., & Dennett, D. C.
(2019). The rationale of rationalization. Behavioral and Brain Sciences,43, e53. https://
doi.org/10.1017/S0140525X19002164
Veit, W., & Spurrett, D. (2021). Evolving resolve. Behavioral and Brain Sciences,44, E56.
https://doi.org/10.1017/S0140525X20001041
Whiten, A. (2019). Cultural evolution in animals. Annual Review of Ecology, Evolution,
and Systematics,50, 27–48.
Representational exchange in social
learning: Blurring the lines between
the ritual and instrumental
Natalia Véleza, Charley M. Wuband Fiery
A. Cushmana
a
Department of Psychology, Harvard University, Cambridge, MA 02138, USA and
b
Human and Machine Cognition Lab, University of Tübingen, 72076 Tübingen,
Germany
nvelez@fas.harvard.edu,charley.wu@uni-tuebingen.de,cushman@fas.harvard.edu
nataliavelez.org,hmc-lab.com,cushmanlab.fas.harvard.edu
doi:10.1017/S0140525X22001339, e271
Abstract
We propose that human social learning is subject to a trade-off
between the cost of performing a computation and the flexibility
of its outputs. Viewing social learning through this lens sheds
light on cases that seem to violate bifocal stance theory (BST)
–such as high-fidelity imitation in instrumental action –and
provides a mechanism by which causal insight can be boot-
strapped from imitation of cultural practices.
According to bifocal stance theory (BST), how faithfully someone
imitates depends on their goals. We copy actions faithfully to affil-
iate with others or to highlight our membership in a group (the
“ritual stance”), but selectively copy only what is necessary to
achieve instrumental goals (the “instrumental stance”). We
agree that social learning can serve both affiliative and instrumen-
tal ends. However, we disagree that high-fidelity copying is neces-
sarily triggered by non-instrumental goals. Humans can perform
a variety of computations to learn from others, from faithfully
copying others’actions to inferring the values and beliefs that
caused them. Collectively, these computations trade off the cost
of performing the computation against the flexibility and compo-
sitionality of its outputs. Understanding social learning through
the lens of this trade-off can guide theorizing about when high-
fidelity imitation and mentalizing may be deployed toward the
same goal, and provides a mechanism by which causal insight
can be bootstrapped from faithfully transmitted cultural practices.
A general principle of intelligent behavior is to use simple
methods whenever possible and more complex strategies when
necessary. An emerging framework has framed the arbitration
between simple and complex strategies as a resource-rational
trade-off (Lieder & Griffiths, 2020). Much like a thrifty shopper
or an efficient long-distance runner, adaptive organisms should
not only maximize rewards, but also account for the cognitive
costs of different strategies. While resource-rational adaptations
have been widely studied in the context of individual decision
making (Kool, Gershman, & Cushman, 2018; Shenhav et al.,
2017), we propose that a similar trade-off exists in social learning
(Wu, Vélez, & Cushman, 2022).
48 Commentary/Jagiello et al.: Tradition and invention
To illustrate this trade-off, suppose you are watching your
friend bake baguettes. As she pops the loaves into the oven, she
pours boiling water into a skillet on the bottom rack. There are
several ways that you could learn from this observation. First,
you could directly imitate this action the next time you bake
baguettes. This may quickly improve your technique, at the cost
of flexibility: You may continue copying this action even
when it is unnecessary or maladaptive. Alternatively, you could
try to infer why she performed that action. For example, you
could infer she used the boiling water to create steam, because
steam gives bread a crunchy crust. Inferring the goals and beliefs
driving your friend’s actions is more costly than simply copying
her, but it affords increased flexibility. The next time you bake
bread yourself, you could use this insight to find alternative solutions
to the same goal (e.g., by spraying water on the loaves) and to skip it
when it is not needed (e.g., when baking soft, chewy breads).
What distinguishes these possibilities is not the observer’sgoal,but
whether the benefits outweigh the computational costs. This trade-off
helps identify cases where high-fidelity imitation is not only possible,
but even preferable to mentalizing in instrumental contexts. If you
are baking bread for the first time, or operating a complex and
expensive MRI machine, you will likely maximize your rewards
(and avoid catastrophic costs) by strictly following procedure.
Just as high-fidelity imitation can sometimes be beneficial to
instrumental action, this computational trade-off can also guide
theorizing about contexts where strategic innovation may be
deployed in ritual. For example, medieval charms often required
certain words to be invoked verbatim, but allowed ingredient sub-
stitutions (Luft, 2020). One charm for curing rabid dogs involved
buttering a slice of barley bread (“or if you cannot get that [type of
bread], take another”) and writing ritual words on it before feed-
ing it to the dog (Leach, 2022). It is possible these deviations from
ritual were guided by intuitive theories about which aspects were
causally relevant –perhaps the charm depends on the words, but
not on the type of bread on which they are written. Indeed, recent
work suggests that modern adults’judgments about magic, such as
the difficulty of a charm, are governed by intuitive theories of how
the real world works (Lewry, Curtis, Vasilyeva, Xu, & Griffiths,
2021; McCoy & Ullman, 2019). While we agree that rituals serve
an important affiliative function, these examples raise the possibility
that rituals have their own causal logic and may allow a greater
degree of behavioral flexibility than accounted for in BST.
So far, we have identified cases where observers may use high-
fidelity imitation or mentalizing in the service of the same goal.
This flexibility also provides a mechanism by which causal insights
can be bootstrapped from faithfully transmitted cultural practices,
thus blurring the lines between ritual and instrumental actions.
Returning to the baking example above, you may assume that
your friend’s technique is the result of rational planning –that is,
that she understands why each step in the recipe works and has
arrived at her technique through deliberate utility maximization.
But this is often not the case. The chemical reactions involved in
bread-baking are sufficiently opaque that even a seasoned baker
may faithfully copy a technique out of habit or conformity to cul-
tural norms, without understanding why it works. If an observer
were to then impute beliefs and rational planning to the demonstra-
tor where there were none, they would be constructing a fiction –a
“rationalization”of the demonstrator’s behavior (Cushman, 2020).
This fiction can be quite useful. Technologies are often
adopted and refined long before we discover why they work
(Henrich, 2015). For example, the bark of the cinchona tree was
used to treat malaria for centuries before its active ingredient,
quinine, was first isolated and its pharmacological mechanism
understood (Achan et al., 2011). Rationalization provides a means
of representational exchange across different forms of social learn-
ing, enabling observers to extract generalizable, causal insights
from cultural practices. This exchange may enable observers to
innovate by design, by re-examining and refining long-held prac-
tices using their current internal models of the world.
In sum, beyond faithful copying, humans have access to a vari-
ety of cognitive capacities that enable us to learn from others.
These capacities can be flexibly deployed and can support one
another through representational exchange. Viewing social learn-
ing through the lens of computational trade-offs paints a more
dynamic, agentic picture of how humans build culture.
Acknowledgments. We are grateful to Ashley Thomas, Dorsa Amir, and
Katherine Leach for insightful comments.
Financial support. NV is supported by an award from the National
Institutes of Health (award number K00MH125856). CMW is supported by
the German Federal Ministry of Education and Research (BMBF): Tübingen
AI Center, FKZ: 01IS18039A and funded by the Deutsche
Forschungsgemeinschaft (DFG, German Research Foundation) under
Germany’s Excellence Strategy –EXC2064/1-390727645. FAC was supported
by grant N00014-19-1-2025 from the Office of Naval Research.
Conflict of interest. None.
References
Achan, J., Talisuna, A. O., Erhart, A., Yeka, A., Tibenderana, J. K., Baliraine, F. N., …
D’Alessandro, U. (2011). Quinine, an old anti-malarial drug in a modern world:
Role in the treatment of malaria. Malaria Journal,10, 144.
Cushman, F. (2020). Rationalization is rational. The Behavioral and Brain Sciences,43, e28.
Henrich, J. (2015). The secret of our success. Princeton University Press.
Kool, W., Gershman, S. J., & Cushman, F. A. (2018). Planning complexity registers as a
cost in metacontrol. Journal of Cognitive Neuroscience,30(10), 1391–1404.
Leach, K. (2022). Unpublished doctoral thesis. Harvard University.
Lewry, C., Curtis, K., Vasilyeva, N., Xu, F., & Griffiths, T. L. (2021). Intuitions about
magic track the development of intuitive physics. Cognition,214, 104762.
Lieder, F., & Griffiths, T. L. (2020). Resource-rational analysis: Understanding human
cognition as the optimal use of limited computational resources. Behavioral and
Brain Sciences,43, e1.
Luft, D. (2020). Medieval Welsh medical texts: Volume one: The recipes. University of
Wales Press.
McCoy, J., & Ullman, T. (2019). Judgments of effort for magical violations of intuitive
physics. PLoS ONE,14(5), e0217513.
Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T. L., Cohen, J. D., & Botvinick,
M. M. (2017). Toward a rational and mechanistic account of mental effort. Annual
Review of Neuroscience,40, 99–124.
Wu, C. M., Vélez, N., & Cushman, F. A. (2022). Representational exchange in human
social learning: Balancing efficiency and flexibility. In I. C. Dezza, E. Schulz, &
C. M. Wu (Eds.), The drive for knowledge: The science of human information-seeking
(pp. 169–192). Cambridge University Press.
Tradition–invention dichotomy and
optimization in the field of science
Mukta Watve and Milind Watve
Independent Researchers, Pune 411052, India
mukta.watve05@gmail.com
Milind.watve@gmail.com
https://milindwatve.in/
doi:10.1017/S0140525X22001236, e272
Commentary/Jagiello et al.: Tradition and invention 49
