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Hemmatian and Sloman
Please cite as: Hemmatian, B., & Sloman, S.A. (in press). Two systems for thinking with a
community: outsourcing versus collaboration. In S. Elqayam (Ed.), Festschrift for David Over.
New York, NY: Psychology Press.
© 2019, Psychology Press. This chapter is not the copy of record and may not exactly
replicate the final, authoritative version to be published in the book. Please do not copy
without authors permission. The final version will be available, upon publication.
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Hemmatian and Sloman
Two Systems for Thinking with a Community: Outsourcing versus Collaboration
Babak Hemmatian and Steven Sloman
Brown University
Abstract
Evans and Over (1996) made a seminal contribution to the cognitive sciences by describing two
different routes humans take to reason toward their goals, one associated with intuition, the other
with deliberation. We show how knowledge provided by our communities influences both
routes. Many methods of outsourcing cognitive effort– taking advantage of information that one
does not know but assumes that someone else can supply—show the hallmarks of intuitive
reasoning. Effective outsourcing requires fast and efficient ways of identifying what must be
outsourced, and which individual or group of people is most likely to have the relevant expertise.
Research has identified several fallible heuristics like the degree of entrenchment of a term in a
community of use that help people figure out what needs to be outsourced (content heuristics),
and a different group of heuristics that allow us to find experts, for instance, through associations
with certain environments and disciplines (expertise heuristics). In contrast, deliberation is
primarily concerned with facilitating intentional collaboration with others toward joint goals,
often using natural language. This division of labor between two interacting but distinct systems
allows humans to leverage the representational and computational capacities of their
communities to achieve ever more sophisticated goals.
Word count (excluding title, abstract, table, acknowledgments and references): 4891
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David Over has been a key player in the psychology of reasoning since the field was
born. One of his seminal contributions was to ally different conceptions of rationality with each
of two systems of thought, deliberation pursuing the god of truth and intuition pursuing
individual goals (Evans & Over, 1996). This characterization had some support, including the
fact that individuals understand and use conditional logic better when it is framed in terms of
permissibility of social actions, rather than represented as abstract symbols (Manktelow & Over,
1991). Since those heady days, there has been some consensus that all reasoning depends on
goals, that each system can be involved in the pursuit of truth, and that the rationality of both
systems can only be evaluated in relation to some goal (Evans & Stanovich, 2013; Sloman,
1996).
How do we reconcile the dual systems view of thought with another change in how we
think about the mind? On the strength of arguments and observations found across psychology
and the social sciences, and in the study of organizations, we have come around to the view that
reasoning is a social affair, that the great advances made by human thought towards personal and
collective goals come from individuals working together (Mercier & Sperber, 2017; Sloman &
Fernbach, 2017).
When our goals are individually determined, the world’s complexity prompts us to turn to
our conspecifics for help due to our brains’ limited capacity for representing and manipulating
information (Hardwig, 1985). Individuals are largely ignorant about most things, including how
everyday objects work (Landauer, 1986; Rozenblit & Keil, 2002), and are quick to forget
important facts (Fisher & Keil, 2016). By relying on a division of linguistic and cognitive labor,
whereby each person focuses on learning and reasoning about certain aspects of the world and
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relies on communication with others to act as a team, humans can overcome their individual
ignorance (Putnam, 1979).
Our dependence on conspecifics goes beyond filling the gaps in our knowledge. Many of
our goals are shared with others and best achieved through collaboration (Kitcher, 2003). This
capacity for joint cognition and joint action has propelled humans to wondrous feats, from
building colossal pyramids to creating Hadron Colliders. While not all mental faculties are
strongly dependent on other individuals, there is an increasing recognition within the cognitive
sciences of the important role our communities play in everyday reasoning.
Based on this understanding of intelligence, we investigate how dual systems relate to the
community of knowledge. In particular, we propose that dual systems provide two means of
accessing the community: Intuitions may be prompted in the course of collaboration, but the
structure of intuitions generally includes outsourced data, information that one does not know
oneself but assumes that someone else (whose identity may be unknown) can supply.
Deliberation generally accesses the community through collaboration, the intentional creation
and use of information by a group.
Thinking within a community of knowledge means depending on others for reference,
inference, and understanding. To illustrate, stereotypes are a critical form of intuition that help us
organize our social worlds. They are often informative (Jussim et al., 2009) but can also be
biased, like all intuitions. Stereotypes are shaped by social norms; they are not creations of mere
individuals. As such, their use is a form of outsourcing: We rely on the community to provide
information about other people because we are not capable of providing it all on our own. Not all
intuitions depend on outsourced knowledge. But we will see that many methods of outsourcing
show the hallmarks of intuitive thought.
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Deliberating can take advantage of outsourcing, but it is primarily a means of
collaboration. Deliberation usually involves more than one individual together constructing
symbolic forms via one or more symbol systems, often natural language. Collaboration is more
than outsourcing because it involves striving toward shared intentionality. It involves pursuing
goals together, not separately, and it requires an effort toward joint knowledge that agents are
pursuing goals together (Tomasello & Carpenter, 2007).
Intuition and deliberation are, thus, forms of individual thought that each provide access
to the community of knowledge, and they may do so in different and complementary ways.
Before discussing the evidence for these interactions, we briefly review the hallmarks of these
two systems of reasoning.
Two Systems
The notion of two interacting, but distinct systems has proven useful for characterizing
higher-level human cognition (Sloman, 1996; Stanovich & West, 2000). Evans and colleagues
(Evans & Over, 1996; Evans, 2007) characterize the two systems as “default-interventionist,”the
deliberative system acting as a filter on intuition. Most of the discussion in this volume takes this
view. We will adopt a “parallel-competitive” view in the remainder of this chapter. We assume
intuition and deliberation operate in parallel, generally co-operating to determine the eventual
outcome of reasoning (Sloman, 2002).
While different terms have been used to refer to the two systems, there is some consensus
regarding their general properties (Evans & Stanovich, 2013). The intuitive system uses pattern
recognition, affective and bodily responses, and sometimes simple heuristics to guide effective
cognition and action (Sloman, 1996, 2002). The intuitions this system produces are often general
in purpose, and processing is done in parallel and is therefore quick. Intuitions arise without
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effort and without conscious awareness of the processes that produce them. Machine learning
through spreading of activation in a distributed neural network provides a useful metaphor for
this form of reasoning (Rumelhart & McClelland, 1986).
The deliberative system, on the other hand, is dependent on slow, sequential
manipulations of abstract and symbolic representations. The procedures associated with this
system are often more specialized and model the rich logical and causal relations in the
environment. Individuals are generally conscious of the processes that lead to their deliberative
responses and are capable of communicating them. Performing a difficult mathematical
calculation on a piece of paper involves the kind of step-by-step sequencing of thoughts and
perceived cognitive effort that generally characterizes this system.
Where is the Knowledge: Intuition and Outsourcing
How do the two systems of reasoning relate to the task of outsourcing cognitive effort to
our communities? Effective division of cognitive labor requires, among other things, determining
the best dimensions of knowledge to outsource and the best groups or individuals to outsource to.
The ubiquity of our epistemic dependence on others means that there is an ever-present need to
quickly and efficiently create and employ representations of both.
Intuitive thinking can provide us with computationally cheap and informationally
efficient answers to these problems. It is especially helpful when no powerful deliberative
procedure has been established: Deliberation is computationally expensive and guaranteed to fail
in the absence of any factor constraining the set of considered options (Wolpert & MacReady,
1997). The slow and effortful nature of deliberation, in contrast with intuitive thought, makes
intuition a better candidate to restrict the options to be investigated. It is therefore not surprising
that mechanisms for cognitive outsourcing are generally intuitive in nature. For instance,
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physicians’ titles can guide us to experts who are most likely to know the cause of our pain,
while the number of people waiting in the clinics to meet with each physician may help us gauge
the quality of each expert. Such rules of thumb can be applied quickly and effortlessly to
outsource knowledge. These particular heuristics apply to any situation where experts are
distinguishable using public titles and individuals are free to choose from various service
providers, a generality of purpose often found in intuitive heuristics.
Heuristics for Outsourcing
Research has identified many mechanisms for outsourcing knowledge that we illustrate
here (see Table 1 for a summary). These are essentially heuristics that take advantage of
knowledge carried by other people. The table provides a sample of outsourcing heuristics, rather
than an exhaustive taxonomy of the many ways in which humans locate knowledge in their
communities.
_______________
Table 1 around here (appended to the end of manuscript)
_______________
Outsourcing Content
Several heuristics take advantage of cues to confirm the presence and accessibility of
communal knowledge. The goal of many of these heuristics is to determine the entrenchment of
a concept or idea in a generally reliable, valid, and easy-to-use way: the degree to which it is
accepted and commonly used by the community. Entrenchment can index the community’s
experience with a certain phenomenon and its efforts to understand it, thereby serving as a
helpful indicator of communal knowledge. For the purposes of these heuristics, the community
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can be conceived in a broad manner, with little need to uniquely identify individuals or groups
most associated with relevant knowledge.
The most obvious way of outsourcing cognitive effort to one’s community is through the
use of default options (Johnson & Goldstein, 2003). Many decisions have uncertain options and
outcomes, making it difficult to determine the best course of action. The default heuristic
replaces this under-determined problem with one about what is commonly done in similar
situations. We register to vote if that is the default and visit our employer’s default health care
provider, provided that we have no strong reasons not to. In all these decisions we are heavily
influenced by social norms (Cialdini, 2009): Our culture provides us with a preferred set of
dishes to consume, presumably perfected over many generations, that we often adopt as our
default choice. Our colleagues go to a certain healthcare provider and they seem healthy enough,
so we contact that provider for our own maladies. The assumption behind a preference for
default options is that a process of selection – for us as individuals or for our communities as a
whole – has resulted in the persistence and spread of the most adaptive behaviors. Boyd and
Richerson (2005) use simulations and historical data to show that in stable environments where
this assumption is valid, intuitive adherence to the usual way of doing things is more likely to be
adaptive.
A similar logic applies to imitation in new settings where we have little background
knowledge about what to do. A natural tendency in such situations might be to observe and
imitate the most common behavior around us. Note that both imitation and preference for default
options do not require collaboration: Intentions are not necessarily coordinated or shared with
others, and therefore there is no joint action towards joint goals.
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Many situations call for a more nuanced form of outsourcing than defaults or imitation:
To determine who is an expert on which topic requires up-to-date knowledge of which categories
are among the community’s shared concepts and thereby determining how the division of
cognitive labor is conducted. Language use within a community can provide strong cues to this
collective conceptual structure. For instance, the statement that “reverse racism is not a thing” is
an explicit statement about what someone believes a basic conceptual commitment should be in
their community, and therefore information about which concepts should be sought from other
members.
In the same vein, Hemmatian and Sloman (2018) provide evidence for a label
entrenchment heuristic, whereby the degree to which a label is used in a community imbues that
label with perceived explanatory power, regardless of any actual information it provides. For
instance, participants were told that a combination of symptoms has been called Ganser’s
syndrome. They were informed that the label is only a shorthand for the symptoms and nothing
else is known about this category, even whether it is well-formed. In conditions with no label
entrenchment, they were told that only a small group of foremost experts use this label. In other
conditions, the label was commonly used by members of the broader community. In both cases,
participants were asked to rate the comprehensiveness of a categorical explanation for the
symptoms, namely that an individual displays those symptoms because they suffer from
Ganser’s syndrome. Despite the clear circularity of the explanation in all conditions, participants
rated the explanatory value of entrenched labels significantly higher than unentrenched labels. A
similar result was observed across experiments for various basic- and subordinate-level
categories spanning domains involving social, natural, and biological entities. This result can be
explained by observing that a label’s entrenchment identifies the associated category as a
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building block in a community’s representation of the world --a piece of information that is
useful for social agents regardless of whether the category itself is well-formed and its
informativity justified.
Entrenched communal knowledge is sometimes not only explicitly communicated, but
also codified, institutionalized, and enforced. Legal codes are examples of this kind of
knowledge, often passed down through generations and shaped by culture. This highly accessible
and environmentally prominent knowledge structure provides an opportunity for outsourcing
cognitive effort: In unfamiliar situations where it is difficult (or impossible) to determine the
morality of an action, individuals may substitute legality for moral status (Kahneman &
Frederick, 2002). Amit and colleagues (submitted) provide experimental evidence suggesting
that individuals use this heuristic when making judgments regarding the morality of knowingly
producing a harmful drug. The strength of the resulting intuition is such that it may override
provided information about the severity of the drug’s negative side effects.
The communal source of our moral intuitions is not always as easy to recognize. There is
accumulating evidence that cultural information can be integrated into immediate emotional
reactions (Shweder & Haidt, 1993a). Haidt and colleagues (Haidt, Koller & Dias, 1993; Haidt,
Bjorklund & Murphy, 2000) have shown that these reactions are spontaneously used as
substitutes for moral judgments of certain actions. They asked individuals to provide
justifications for their judgments of intuitively wrong actions (e.g. incest) in settings where no
harm or infringement on rights could easily be inferred. Despite participants’ confidence in their
responses, they were often surprised by how little justification they had for their beliefs, a
phenomenon called moral dumbfounding.
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Part of the utility of these heuristics arises from their potential to be combined. For
instance, in many situations one may use both emotional reactions and information about legality
to hone in on the appropriate moral judgment. But outsourcing heuristics can be misused, as we
illustrated above in the case of circular arguments due to entrenched labels. One explanation for
such unwarranted evaluations is that frequently employing heuristics runs the risk of habitual
reliance on the intuitions they provide, even when explicit knowledge contradicts the answers
derived from them.
The force of habit is not the only cause of inappropriate use of outsourcing heuristics.
Our knowledge and activities are intertwined with other human beings in a way that makes it
difficult (sometimes impossible) to determine the source of information. This entanglement and
the ensuing misattribution of the source provides an explanation for several findings in the
literature. Sloman and Rabb (2016) show that simply stating that scientists have found an
explanation for some phenomenon elevates participants’ perceived personal understanding of the
phenomenon, provided that there is potential access to that knowledge. Fisher, Goddu, and Keil
(2015) show that controlling for the contribution of information, knowing that one has access to
the internet can similarly enhance perceived understanding. The fact that these effects depend on
access suggests that our sense of understanding tracks the availability of information in our
communities rather than what is in our brains.
The illusory intuitive sense of understanding can potentially be punctured. Rozenblit and
Keil (2002) have provided empirical evidence for such a phenomenon by asking about these
intuitions and then forcing respondents to provide deliberative answers: Participants were asked
to rate their understanding of the principles behind the workings of various everyday devices and
natural events. They were then asked to describe these principles in as much causal detail as
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they could. The attempt to explain made most participants realize they did not know as much
about the topic as they thought they did, thus lowering their re-ratings of own understanding
compared to the baseline. Fernbach, Rogers, Fox and Sloman (2013) have extended this finding
to abstract policy decisions.
Outsourcing Expertise
A successful division of cognitive labor often depends not only on a determination of the
knowledge to be outsourced, but also on an estimate of what individuals or groups of people may
know. Each person’s knowledge base is the result of information gained from their community,
adjusted, and complemented by idiosyncratic personal experiences (Nickerson, 1999). Effective
outsourcing may depend on knowing what groups are likely to know, while also keeping track of
knowledge that individuals have. For instance, while experts are generally expected to know
about the topic of their expertise, we may come to the conclusion that a certain unhelpful
“expert” is likely to lead us astray. We may also need an understanding of the other person’s
mental state to determine if they would be willing to share their knowledge, or if they have a
conflicting interest.
To determine likely knowledge at the group level, the division of labor in societies can
come to the reasoner’s aid: We learn to look for pediatricians when our children get sick and ask
our hairdressers about the quality of hair products. How do reasoners identify what a pediatrician
or any other expert is likely to know? Keil (2005) suggests that a category association heuristic
is one easy way to find an answer: Expertise can be naively understood as being the best
accessible source for information normally associated with a category. A hairdresser is expected
to know most things about hair, while a cook serves as a resource for all culinary matters. The
features that determine the coherence of the category that is the object of expertise can differ
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depending on the reasoner’s goals. For instance, they can represent activities, parts of objects,
etc. Keil (2005) traces the origin of this heuristic to a motivational hypothesis: Individuals will
strive to learn the details of something that is the focus of their job or interest.
People also assume others have knowledge by virtue of their access to and experience
with specific environments, regardless of goals and motivations. Individuals often
subconsciously integrate access-based information into their representations of what others may
know (e.g. Hollingshead, 1998). For instance, a native of a certain country is assumed to have
expertise about that country and may often serve as the go-to person for knowledge about their
homeland.
Many of the examples discussed so far (such as hairdressing or a specific nationality)
involve categories at the basic level of categorization or below. Basic-level categories are “those
which carry the most information... and are... the most differentiated from one another”
compared with more specific or more abstract ones (Rosch, Mervis, Gray, Johnson & Boyes-
Braem, 1976). The abundance of basic-level nouns in natural language facilitates recognition of
the associations between individuals, groups and categories at an intermediate level of
abstraction using the discussed heuristics, aiding the process of outsourcing.
Another prominent example of explicit communication of communal knowledge involves
categories at the superordinate level: The set of accepted and communicated disciplines can
guide the way an individual breaks the world up into ontological domains and consequently who
they turn to for epistemic assistance. Thon and Jucks (2017) provide evidence that individuals
pervasively and effortlessly take advantage of this source of information: Simply mentioning the
name of a discipline can conjure up strong intuitions regarding the scope of an individual’s
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knowledge. Hopkins, Weisberg and Taylor (2016) demonstrate that such domain-specific
intuitions affect judgments even if irrelevant to the task at hand.
Information from any of these heuristics may be used to inform the use and interpretation
of other heuristics. Disciplines are associated with often clearly-stated goals, imply access to
certain environments, and suggest knowledge of specific categories (Kuhn, 2012). Extensive
knowledge about a category can also imply association with the relevant discipline. There is
evidence that children as young as five have awareness of these relations (Keil, Stein, Webb,
Billings & Rozenblit, 2008).
Despite the sophisticated nature of heuristics for recognizing expertise, they need not
reflect deliberation; they are usually the result of intuitive pattern recognition. Indeed, although
the level of detail and confidence in these intuitions may improve over time, even adults have
difficulty explaining the rationale behind them, a lack of awareness of process that is
characteristic of intuitive thinking (Keil et al., 2008).
Outsourcing Dynamics
Outsourcing heuristics seem to be mostly deployed intuitively. People would not report a
greater sense of understanding when others understand (Sloman & Rabb, 2016; Zeveney &
Marsh, 2016) if they were consciously aware that they were appealing to others. In some cases,
people have trouble providing deliberate justifications for their judgments (Fernbach et al., 2013;
Haidt, et al., 1993; Rozenblit & Keil, 2002; Keil et al., 2008). The heuristics are often employed
across domains automatically with little adjustment and usually without verbalizable awareness
(e.g. Hemmatian & Sloman, 2018). The initial responses to questions are fast and effortless, with
slower deliberative answers occasionally overriding them (e.g. Haidt et al., 2000). Nevertheless,
deliberation may affect the downstream behavior guided by these intuitions. For instance, a voter
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who makes an explicit effort to list the pros and cons of electing a certain representative may
combine deliberation with intuitions to determine who to outsource important communal
decisions to.
We have seen that the outsourcing heuristics can be applied in rigid and inappropriate
ways, for example resulting in endorsement of circular explanations. Despite such shortcomings,
there is evidence that people are remarkably sensitive to the domain they are operating in when
they apply heuristics. They are also sensitive to properties of the sources they are outsourcing to
and to the environment they are operating in. Heuristic use needs to be constantly tuned in a
complex and dynamic world to ensure its effectiveness.
For instance, Buchsbaum, Gopnik, Griffiths and Shafto (2011) discuss how prior causal
information can impact choices of who and what to imitate, even in novel situations. Subtle
information about category membership, such as the number of observed features in an instance,
can interact with the effect of label entrenchment on judgments of explanatory value
(Hemmatian & Sloman, 2018). In the moral domain, Amit and colleagues (submitted) have
shown that increasing personal significance of induced harm can mitigate the effect of legality on
moral judgments, presumably by enhancing the relevance of the action’s consequences.
Heuristics used to determine who to outsource to are also modulated. Keil and colleagues
(2008) show that a category’s level of abstraction can determine the amount of knowledge
attributed to an expert specializing in that category: The more abstract the category, the lower the
fraction of relevant knowledge the expert is assumed to have. Their evidence also suggests that
feature centrality is spontaneously taken into account in judgments of what individuals in a
discipline or subdiscipline may know, meaning rich causal structures can be used to adjust the
downstream outcomes of intuitive reasoning. Such adjustments themselves are modulated by
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beliefs about the general properties of knowledge in each discipline (e.g. its breadth, depth, and
proximity to physical causes; Weisberg, Keil, Goodstein, Rawson & Gray, 2008). Access-based
and goal-based heuristics are similarly impacted by causal and discipline-based information. For
example, the goal of curing cancer can imply in-depth knowledge of the physiology of cancer, an
association made using causal beliefs regarding disorders.
Deliberation and Collaboration
We substitute deliberation with intuition to reduce cognitive load and combine the
insights intuition provides with deliberation to adjust the downstream behaviors. Another relation
between intuition and deliberation is that some deliberative processes may be intuitively
outsourced as a means of reducing complexity. We can avoid understanding and deliberating
about complex structured knowledge by outsourcing it. For instance, if your car won’t start, you
can avoid deliberating about what’s wrong by outsourcing the problem to a mechanic. This is an
intuitive act inasmuch as the outsourcing is done automatically. It allows the reasoner to avoid
much of the complex reasoning that would be required to solve the problem by themselves.
This isn’t the only way that people appeal to the community of knowledge when they
face the prospect of deliberating though. Humans not only outsource cognitive effort, but also
communicate with one another and collaborate on joint projects. Our intuitions have therefore
developed to facilitate collaboration too. Even preschool children adjust various aspects of their
speech such as speed, complexity and content based on the observed properties of their listeners
in an effortless, spontaneous and automatic manner, even though they fail to verbalizable an
awareness of the interlocutor’s perspective (Shatz & Gelman, 1973; Asher, 1979).
Despite the usefulness of intuitive heuristics, deliberation is better suited to support
collaboration. It allows us to develop informative shared representational frameworks for novel
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problems and to inhibit intuitive responses when the need arises (Frederick, 2005; Stanovich,
2009). Furthermore, deliberation aids us in fluently communicating with others about the content
and processes of our thought, a capacity that is instrumental to human collaboration. And,
conversely, collaboration aids deliberation. The time and effort required of deliberation
compared with the application of simple intuitive rules-of-thumb can mean that problems
requiring deliberation are often well-served by joint effort.
The importance of the latter function cannot be overstated. The human capacity for
shared intentionality might be what sets us apart from other animals and led to human dominance
in nature (Tomasello & Carpenter, 2007). We have developed impressive skills for
understanding other minds (Nickerson, 1999), and for using this understanding to efficiently
perform joint tasks.
Complicated collaborative enterprises require careful, step-by-step reasoning and clear
communication of content. Collaborators often need to identify joint goals and clarify the criteria
for success (e.g., Van Ginkel & van Knippenberg, 2009). Any non-trivial collaborative project
includes many steps requiring joint decisions and combining problem-solving skills of various
members in response to expected and unexpected hurdles. At every step, members may need to
negotiate and renegotiate their shared goals and strategies. It might therefore not be a
coincidence that the term deliberation in English has come to represent both careful, analytic
individual thought and considered discussion by a group.
The division of knowledge in human societies in general (Hardwig, 1985), and within
professions and disciplines in particular (Kitcher, 2003), is a testament to the sophistication of
human collaborative skills. On a smaller scale, Wegner (1987) discusses how members of a
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closely interacting group deliberate in a sophisticated way about aspects of one another’s goals,
knowledge and skills in order to divide the cognitive burden imposed by joint tasks.
The success of these collaborations depends heavily on our use of language, itself a
collaborative endeavor. Wittgenstein (2010) argues that utterances whose terms of use are not
determined by a community of speakers are all but meaningless. Putnam (1979) posits a division
of linguistic labor, whereby the semantic content of linguistic terms is determined in
collaboration with one’s community: Each individual has detailed knowledge of only a few
terms. But through communication with other members of the society she can fruitfully use
concepts outside her areas of expertise.
Language allows us to develop collective narratives, convenient simplifications of shared
causal beliefs used to describe actual and imagined events that can have rich symbolic structures.
For instance, the goals political parties set for themselves and the strategies they use in the
pursuit of those goals can be strongly influenced by shared narratives about the course of a
nation’s history, which can in turn impact individual members’ beliefs and behaviors. As aspects
of a collective identity, such narratives arise through collaborative efforts of group members
(Bruner, 2004).
Given the importance of collaboration to human activities, some theorists have suggested
the main force behind the evolution of explicit, deliberative reasoning is to provide convincing
arguments and therefore facilitate social dynamics (Mercier & Sperber, 2017). For the
facilitation to be informed by deliberation, one’s position need not have stemmed from
deliberative thought. Shweder and Haidt (1993b) propose a model of moral reasoning in which
judgments arise from intuitions partly received from one’s community, but the deliberative
system acts as a “press secretary” that develops justifications for them to be presented to others.
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While we maintain that the contribution of deliberation to human thinking goes beyond
argumentation (see Sloman & Fernbach, 2018), any complete account of human reasoning will
need to consider the profound interconnections between intuition and deliberation.
The advent of advanced communicative technologies has provided an opportunity to
overcome some of the biological and physical constraints on collaborative deliberation (Ward,
2013). Storing, manipulating and relaying information between collaborators has never been
easier and the limitations induced by temporal or physical distance have never been weaker. We
therefore predict that the importance of deliberative collaboration to human cognition will only
increase in the foreseeable future.
Summary and Conclusion
One of David Over’s seminal contributions to the cognitive sciences was highlighting the
impressive capacity of humans to reason towards their goals (Evans & Over, 1996). Knowledge
provided by our communities has a strong impact on both intuition and deliberation in service of
such goals. We argued that intuition is primarily associated with outsourcing cognitive effort to
our conspecifics. Effective outsourcing requires identifying the knowledge dimension to be
outsourced, as well as determining which individual or group of people is most likely to have
detailed knowledge about that dimension. Content heuristics help us hone in on important
dimensions of communal knowledge relevant to the task at hand, while a different group of
heuristics allow us to find others with relevant expertise. In contrast with intuition, we argued,
deliberation is primarily concerned with facilitating collaboration with others. Through this
division of labor between two interacting, but distinct systems of reasoning, humans leverage the
representational and computational capacities of their communities to achieve ever more
sophisticated goals.
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Acknowledgements
This publication was made possible through a grant from the Intellectual Humility in
Public Discourse Project at the University of Connecticut and the John Templeton Foundation.
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How Cognitive Systems Access the Community of Knowledge
●Intuitive System: Relies on outsourcing to the community
•Uses heuristics
■For outsourcing content
●Entrenchment heuristics
•Default heuristic
•Imitation
•Label entrenchment
•Legality as morality
●Affective cuing
■For outsourcing expertise
●Category association
●Goal-based
●Access-based
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●Discipline-based
●Deliberative system: Relies on collaboration
•Tools
■Language and other symbolic systems
■Sharing intentionality
•Functions
■Transactive memory systems
■Joint goal-setting
■Joint decision-making
■Joint problem solving
■Narration
■Argumentation
■Negotiation
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Table 1. A non-exhaustive taxonomy of the ways in which intuition and deliberation interact with
the community of knowledge
