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This article explores the various understandings of the concept of uncertainty in the social sciences. First, it examines the idea of uncertainty and related concepts. Then, it explores the use of the concept in economics, psychology, and sociology.
Uncertainty: History of the Concept
Joshua Wakeham, University of Alabama, Tuscaloosa, AL, USA
Ó2015 Elsevier Ltd. All rights reserved.
This article explores the various understandings of the concept of uncertainty in the social sciences. First, it examines the idea
of uncertainty and related concepts. Then, it explores the use of the concept in economics, psychology, and sociology.
Within the social sciences, the concept of uncertainty has long
been of interest, particularly in areas concerned with decision-
making and knowledge. In very broad terms, uncertainty occurs
at the limits of knowledge. In those social sciences that take an
information-processing perspective on the problem of knowl-
edge and cognition, such as economics, organizational studies,
and some parts of psychology, some might describe uncertainty
as a fundamental problem, even in places where it is not
explicitly discussed. Uncertainty lurks in the background of any
seemingly rational decision that is of interest to social scien-
tists. A lack of certainty about the outcome of any action colors
the way individuals or groups evaluate the world and their
choices. Yet this is not the only understanding of the concept
of uncertainty. One can nd references to the problem of
uncertainty and related concepts scattered throughout
economics, psychology, sociology, anthropology, and related
subelds. Both across and within the social science disciplines,
there are differing understandings of the concept of uncer-
tainty, as well as differing interpretations of its signicance for
social behavior and social science.
In order to better illuminate the history of the concept of
uncertainty in the social sciences, this article sets out to do two
things. First, it provides some conceptual discussion of uncer-
tainty. Second, it provides historical overviews of the concept of
uncertainty in each of the social sciences.
Conceptual Considerations
The Dimensions of Uncertainty
Broadly speaking, uncertainty refers to an epistemic state at the
limits of knowledge. It concerns what is known or believed
without certainty. It also concerns what is not known. If being
certain means having clarity with regard to the truth, then being
uncertain means having an obscured view of the truth. The
problem of uncertainty points not only to the limits of what
any individual might know, but also to the ultimate limits of
what is knowable.
To put it another way, there are subjective and objective
dimensions to uncertainty (Tannert et al., 2007). First, there are
the subjective dimensions of uncertainty. An individual may
experience uncertainty with regard to his or her own knowledge
about some particular topic. Some experience or some piece of
evidence might challenge an individuals once rmly held
belief, causing them to have doubts about this belief. An
individual may experience uncertainty about the possible
outcome of some course of action. In important ways, this
subjective, phenomenological experience of uncertainty is both
cognitive and emotional. As such, it has obvious relevance to
social behavior. There are questions of not only how the
experience of uncertainty drives or inuences behavior, but
also how social context shapes the perception and experience of
this cognitive and emotional uncertainty.
Second, there are the objective dimensions of uncertainty,
which presume a world out there that is knowable only to
a degree. Uncertainty, in this sense, is not necessarily some-
thing felt, but rather a feature of living in a complex world. It is
useful to distinguish between epistemological and ontological
uncertainty (Van Asselt and Rotmans, 2002). In the case of
epistemological uncertainty, something that is potentially
knowable remains unknown. Further research or searching for
more information can reduce such uncertainty. In the case of
ontological uncertainty, something remains unknown because
it is ultimately unknowable. This may be due to the sheer
complexity of the problem, the stochastic nature of the situa-
tion, or because natural processes obscure access to the rele-
vant knowledge (such as time-obscuring access to historical
knowledge). Thinking about uncertainty as an objective
feature of the world is related to social scienticworkattwo
levels. At the rst level is the thinking about how other people
encounter and deal with the uncertainty of the world around
them. Problems of epistemological uncertainty, for example,
and the practical problem of distinguishing between episte-
mological and ontological uncertainty are directly relevant to
the social production of knowledge in the sciences, the law,
medicine, business, and other venues. More broadly, how
people manage ontological uncertainty, particularly as it
relates to the complex social, political, technological, and
economic systems that make up modernity, is of great interest
for the social sciences. At the second level is the thinking about
716 International Encyclopedia of the Social & Behavioral Sciences, 2nd edition, Volume 24
how the social sciences themselves encounter uncertainty as
a feature of the world. This has direct bearing on the limits of
proposed models of human behavior, particularly on their
predictive validity. Uncertainty, in this sense, is a technical
problem that social scientists must account for in their models
and explanations of human behavior.
Presumably, most of the time, the subjective experience of
uncertainty and the reality of an uncertain world line up, so
speaking of the uncertainty in the market or surrounding
a particular policy decision or about some organizational
strategy practically conates these two analytic dimensions.
Nonetheless, within the social sciences, researchers have
emphasized different aspects of uncertainty, depending on
their eld and their research subject. This expanded view of
uncertainty as having both subjective and objective dimen-
sions provides a sufciently broad framework for capturing the
various ways the social sciences have used the term. However,
it is also important to recognize that these different points of
conceptual emphasis result in research projects that do not
necessarily speak to one another.
Related Concepts
Within the social sciences, uncertainty is rarely considered on
its own. It is often paired with other ideas related to challenges
and problems in knowledge. This includes terms like risk,
ambiguity, and ignorance. A brief discussion of how uncer-
tainty has been associated with each of these terms is useful for
further conceptual clarity.
Risk and Uncertainty
Uncertainty has most commonly been paired with risk in the
social sciences. This is particularly true in economics, where it
goes back to Knights early work (1921), but it is also common
in the more recent sociological work on risk and organizations,
as well as work on the risk society(Douglas and Wildavsky,
1983;Beck, 1992,2009).
Risks are generally understood to be the known potential
negative outcomes of a course of action. Risks include things
like a loss on an investment, a nuclear plant having a melt-
down, or the environmental and human health impact of
widespread use of automobiles. A more technical under-
standing of risk typically includes some measure or guess of
the probability of that negative-outcome happening multi-
plied by some measure of the presumed cost of that nega-
tive outcome. As risks are known potential outcomes,
individuals or organizations presumably make efforts to
mitigate or manage them, and avoid risks with costs that are
too severe.
Uncertainty may be understood as the state of mind of
someone deciding on a course of action without a clear
outcome. In this subjective sense of the term, an uncertain
individual consider the benets and the risks, or potentially
negative outcomes, of any course of action. Perceptions of
costly risks are more likely to induce feelings of uncertainty
about a particular course of action. However, when paired with
risk, uncertainty has been more often understood in the more
objective sense of the term.
If risks are known potential negative outcomes, uncertainty,
in an objective sense, refers to the broader set of unknowns that
may affect the course of action and its outcome. Risks, in
theory, can be accounted for, but uncertainty cannot. A deeper
critique of theories of risk management (in business, in
management, or in other elds; or social sciences, such as
economics), is that in the real world, the real probabilities of
negative outcomes are never truly known, meaning that real
uncertainty is more pervasive than any models of risk reveal
(Taleb, 2010).
Anal distinction between risk and uncertainty worth
noting is the evaluative sense in which they are used. Risk bears
a distinctly negative connotation. Objective uncertainty, by
contrast, is neutral. Unknown factors may have a positive or
negative effect on any course of action.
Ambiguity and Uncertainty
An ambiguous situation or problem is one that invites multiple
interpretations. There is a lack of clarity about what it really is.
Ambiguity has often been lumped together or even conated
with uncertainty. The amount of overlap between the two
concepts, of course, depends on what denition one gives
each idea.
Those who take information-processing approach to the
problems of knowledge and cognition tend to dene ambi-
guity, like uncertainty, more technically. Ambiguity, like
uncertainty, has to do with missing information that is relevant
to the outcome of an action (Galbraith, 1973;Frisch and
Baron, 1988). Some economists, building on Ellsbergs
paradox (Ellsberg, 1961), dene ambiguity as uncertainty
about the probability of possible outcomes rather than uncer-
tainty about the outcome itself (Camerer and Weber, 1992;
Dequech, 2000). Others in organizational studies (Schrader
et al., 1993) have argued that in an ambiguous situation, the
structure of the problem itself i.e., the relationship between
the potentially relevant variables is unknown or unsettled,
while in an uncertain situation, the structure of the problem is
settled, but the value of the relevant variables is not. In these
kinds of distinctions, one nds attempts to elucidate not just
how the experience of ambiguity differs from uncertainty, but
how dealing with ambiguity in order to solve a problem
requires different strategies than dealing with uncertainty.
Ambiguity, conceived as a subjective phenomenon, has
similarities with the experience of uncertainty. Encountering
ambiguity is a troubling cognitive and emotional experience
that pushes people to seek out clarity, even at an unconscious
level. From experiments on perception in cognitive psychology
(Hoffman, 1998) to sociological studies of culture (Zerubavel,
1993), social scientists have demonstrated how people, at the
individual or collective level, appear motivated to resolve
ambiguity, imposing a sense of clarity. Research using this
conception of ambiguity tends to focus on the cognitive and
social processes through which individuals and groups
perceive and dene problems and construct knowledge.
Interpretive approaches to social science, particularly in
anthropology and sociology, tend to focus on this kind of
ambiguity, often conating it with uncertainty. Arguably, the
focus on social and cognitive processes and the production of
knowledge rather than the outcomes of actions, where
uncertainty has greater practical salience, may account for this
emphasis on ambiguity and the underdeveloped sense of
uncertainty as a distinctive notion.
Uncertainty: History of the Concept 717
Ignorance and Uncertainty
Some social scientists have also been interested in the larger
problem of ignorance. Ignorance refers to the broad set of
unknowns. Ignorance is of interest not only because it points to
the limits of knowledge, but also because of its dynamic role in
human affairs, as both a productive and destructive force
(Gross, 2007). To that end, some have offered typologies that
make distinctions between different kinds of ignorance. Merton
(1987), for example, distinguishes between unrecognized and
specied ignorance within scientic communities. Unrecog-
nized ignorance refers to unknown unknowns(Kerwin, 1993)
or meta-ignorance(Smithson, 1989)ignorance of what one
does not know. Specied ignorance refers to the acknowledged
limitations of knowledge, which often drive the search for
knowledge (in science and in other elds). Several related terms
like Nichtwissen, nonknowledge, negative knowledge (Knorr-
Cetina, 1999), and nescience (Simmel, 1906) are used in
similar ways.
Smithsons taxonomy of ignorance (1989) makes multiple
levels of distinction. The rst level of distinction is between
irrelevance and error. Things that are irrelevant are those that
are deemed unworthy of further consideration. Error includes
both distortions of information (confusion and inaccuracy)
and incompleteness of information. Incompleteness is broken
down into absence (e.g., missing piece of information) and
uncertainty. Uncertainty includes vagueness, probability, and
ambiguity. In this typology, uncertainty is thus a subtype of
ignorance related to states where one has partial information.
Recent social scientic interest in the problem of ignorance
tends to frame the social production of ignorance as process
that is complementary to the production of knowledge
(Proctor and Schiebinger, 2008). Cultural norms and social
structures play a key role in placing and enforcing limits on
what people know about the world around them. Within this
framework, uncertainty is often treated as a political tool. For
example, politically motivated propagandists use the scientic
communitys provisional sense of the truth to instill a false
sense of uncertainty about the status of ofcial scientic claims
regarding things such as cigarette smoking or environmental
degradation (Oreskes and Conway, 2011).
Uncertainty in the Social Sciences
Uncertainty in Economics
Of all the social sciences, economics has given the most
attention to the concept of uncertainty. Given economics
interest in successfully modeling rational action, uncertainty
poses a real problem. Uncertainty, as either an objective or
subjective phenomenon, challenges many of the basic
assumptions of such modeling efforts. The history of the
concept of uncertainty in economics is very much one of
attempting to tame and domesticate uncertainty(Quiggin,
2009, p. 195).
For uncertainty in economics, 1921 was an important year.
Both British economist John Maynard Keynes and American
economist Frank M. Knight published books that dealt, in part,
with the problem of uncertainty. In his Treatise on Probability,
Keynes (1921) lays out an argument about demonstrating
logical relationships between two propositions based on both
a subjective probabilistic assessment of certainty in ones belief
and the accuracy of that belief. While some relationships
between two propositions can be established probabilistically,
there are some instances where no numerical relationship can
be established. Keynes considers these instances to reect
a kind of fundamental uncertainty about the world (Lawson,
1985;Dequech, 2000). KnightsRisk, Uncertainty, and Prot
(1921) offers a basic denitional distinction between risk and
uncertainty. Risk is measurable. The probabilities of the various
outcomes are known. Uncertainty refers to those unknowns
that cannot be quantied or measured. For both Keynes and
Knight, the looming uncertainty of the world also explains
some seemingly irrational social behavior (for Keynes, reliance
on conventional thinking in the face of long-term uncertainty;
for Knight, development of large, hierarchical organizations),
as such behaviors have formed to help deal with or manage it.
Keynes and Knights similar understandings of uncertainty had
inuence on the post-Keynesian and Austrian schools of
economics, respectively, but really failed to take hold in
mainstream economics despite being cited often (Kelsey and
Quiggin, 1992).
Uncertainty as an inescapable, objective feature of the world
cannot effectively accounted for in traditional economic
models, so most economists ignored or abandoned these
particular denitions of uncertainty, treating them as heterodox.
Instead, alternative understandings of uncertainty as a subjective
phenomenon became more prominent. Being able to incorpo-
rate subjective estimates of probability expressed or revealed
without regard to their accuracy (that is, essentially ignoring
whether these estimates reected objective features of the
world) into economic models was a key. This is where devel-
opment of expected utility theory comes in. Von Neumann and
Morgenstern (1944) demonstrated that people evaluate
outcomes by their expected utility and that expected utility
was subject to variation. This allowed economists to explain
why people were often risk averse under conditions of uncer-
tainty. This model inuenced several lines of work, including
game theory and several variations on the expected utility
model. This includes Savages (1954) work deriving subjective
probabilities and expected utility from peoples preferences, as
well as Arrow and Debreaus (1954) demonstration of suf-
cient conditions’–namely, market completeness, or a market in
which all future outcomes are accounted for by assuming
africtionlessmarket for all current goods –“for the existence of
general equilibrium .under conditions of uncertainty
(Quiggin, 2009, p. 196). In what would become the prevailing
microeconomic model, this meant that uncertainty, as it was
conceived, could be effectively accounted for. Much attention
turned to developing ways to better account for subjective
probabilities in the models, such as Bayesian approaches
(Hirshleifer and Riley, 1992), or variations on expected utility
theory like rank-dependent expected utility theory (Kelsey and
Quiggin, 1992).
Since the 1970s, a growing body of empirical ndings has
shown that people consistently violated the predictions of the
expected utility theory. In particular, the work of psychologists
Daniel Kahneman and Amos Tversky and their collaborators
(Kahneman and Tversky, 1979;Kahneman et al., 1982;Tversky
and Kahneman, 1992) demonstrated that under conditions of
risk and uncertainty, people violated the predictions of the
718 Uncertainty: History of the Concept
expected utility model, but in consistent ways. In place of
expected utility theory, they propose prospect theory, which
takes into account the psychological dimensions of decision
making. Prospect theory breaks choices down into two pha-
ses: editing/framing and evaluation. In the editing/framing
phrase, people simplify available options and outcomes
through a variety of heuristics, or cognitive shortcuts, which are
determined by the context or formulation of the problem. Such
editing or framing makes the evaluation phase easier. During
this phase, people evaluate the outcomes or prospects of
decision, following several psychological rules, such as using
ones starting position to judge gains or losses, overweighing
small probabilities or underweighing large probabilities
depending on the risks, and loss aversion. The key lesson from
all of this is that under conditions of uncertainty, peoples
behavior is not consistent with the rational actor model, but
they do behave in relatively predictable ways. Essentially,
peoples minds draw on even the imsiest pieces of evidence
from the context in order to impose a subjective sense of
certainty in a situation with objective uncertainty. At times, this
leads people to overestimate the potential costs and underes-
timate the benets (or vice versa) of such risky decisions. This
work, of course, contributed directly to the development of the
new elds, behavioral economics and behavioral nance.
These developments in the eld of economics, along with
the Great Recession of 2008, have led some (e.g., Taleb, 2010)
to question the wisdom of economics effectively bracketing off
the problem of objective uncertainty. However, the problem of
effectively modeling or theorizing about unforeseen events and
other exogenous shocks to economic markets still remains.
Uncertainty in Psychology
Uncertainty, usually as a subjective experience, often lingers
in the background of various theories in psychology.
Psychologists have connected uncertainty to the concepts of
personality, emotion, and cognition, and the problem of
decision making. Although work with these concepts often
interacts, they map roughly onto the three distinct normative
approaches to the problem of uncertainty that Smithson
(2009) identies.
The rst approach comes out of the politicized psychoana-
lytic tradition of the mid-twentieth century. Tolerance of
ambiguity and uncertainty are taken as signs of a positive,
well-adjusted personality type, whereas intolerance of such
epistemic conditions is often taken as signs of an authoritarian
personality (Adorno et al., 1950). While the politics of such an
approach have largely been toned down, interest in the concept
of personality and relationship to the psychological experience
of uncertainty have persisted. At the heart of this research is the
idea that there are measurable differences in how individuals
respond to uncertainty (Sorrentino et al., 1984;Sorrentino and
Short, 1986;Sorrentino and Roney, 2000). Freeston et al.
(1994) even developed an Intolerance for Uncertainty scale to
measure such individual variation. Differences in tolerance for
uncertainty are in turn measured against other psychometric
data, including now widely accepted big vemeasures of
personality openness, conscientiousness, extraversion, agree-
ableness, and neuroticism (Berenbaum et al., 2008). Even within
this more recent work, a lack of tolerance for uncertainty as an
inevitable fact of life is seen as potentially problematic from
the individual psychological point of view.
The second approach to uncertainty focuses the cognitive,
emotional, and physiological effects of uncertainty, unpre-
dictability, and uncontrollability(Smithson, 2009, p. 206).
Uncertainty, in this sense, is a generally experienced problem.
As such, it may even be a variable induced in laboratory
settings. In such research, psychologists typically assume that
uncertainty induces psychological distress or strain, including
anxiety and motivation to seek certainty. For example, Berger
and Calabrese (1975) put forth an uncertainty reduction
theoryof social interaction and communication, arguing that
in the initial stages of successful social interaction depends on
reducing uncertainty among participants. Social psychologists
have been interested in not only how uncertainty affects social
interaction and communication (Gao and Gudykunst, 1990),
but also social judgment and evaluation (van de Boss 2001,
2009). Recent work in neuroscience and cognitive psychology
suggests that the drive for certainty works even at an uncon-
scious level (Burton, 2008). The general lesson is that the
experience of uncertainty often drives people into behaviors
and beliefs that are potentially problematic because of an
underlying cognitive and/or emotional need for certainty.
Wilson et al. (2005) have challenged this largely negative
assessment of uncertainty, demonstrating that the drive for
certainty sometimes lessens the positive emotional experience
of a positive event and that uncertainty about a positive event
can lengthen the experience of positive emotions.
The third approach to uncertainty that Smithson identies
comes from research focused on decision making. This
approach takes an information-processing perspective on
cognition (Smithson, 1989). It is often found in cognitive
psychology, but it is also related to other approaches to decision-
making outside of psychology, including organizational
studies, economics, and behavioral economics. Kanheman
and Tverskys (1982) work is probably the best example of
this approach. Researchers taking this approach tend to treat
uncertainty like economists do, often conating it with notions
of probability or risk that can be accounted for in models of
decision-making. The central concern is understanding and
identifying cognitive biases and heuristics that people rely on
when making decisions under conditions of uncertainty.
Uncertainty in Sociology
Considerations of uncertainty gure less prominently within
the eld of sociology. There are some areas, however, where the
problem of uncertainty garners some explicit attention. In
particular, in the eld of organizational studies and in the
social theoretical work on risk culture and society.
Organizational Studies
Organizational sociologists, and others under the broader
umbrella of organizational studies, have long been interested
in how uncertainty drives organizational behavior. The
problem is, like in the other social sciences, the term uncer-
tainty has often been used to refer to slightly different things.
For example, of general interest is the uncertainty an organi-
zation faces in its task environment, yet environmental uncer-
tainty has been conceived of as a state or an objective feature of
Uncertainty: History of the Concept 719
the world, as largely a matter of the perception of organiza-
tional actors, or having to do with the unknown effects of an
action, or the unknown responses of the environment
(Milliken, 1987). Because of such differences in understanding
the concept, scholars have used the problem of uncertainty to
account for an array of organizational behaviors.
The Carnegie Schools early work on the cognitive-
behavioral approach to organizational decision making, for
example, focuses on the ways in which practical limits
constrain or bound rational behavior (March and Simon
[1958]1993). In the face of uncertainty, organizational actors
often rely on standardization of behavior and responses (Cyert
and March [1964]1992). Uncertainty thus contributes to the
kind of suboptimal, bounded rationality observed in organi-
zational decisions.
Uncertainty has also played a central role in the work on
organizational design (Thompson, 1967;Lawrence and Lorsch
1967;Galbraith, 1973). Organizations cannot have full
knowledge of their environment, so they must anticipate the
unforeseen. One of the goals in organizational design is not
necessarily to eliminate uncertainty (this is impossible), but to
cope with it. This means not only paying attention to various
sources of information (through the division of labor or
specialization), but also designing an organization that is
responsive to unanticipated information (through the
successful integration or coordination of the parts). Attempting
to cope with such uncertainty has been invoked to explain
macrolevel organizational behaviors from a wide array of
theoretical perspectives, including population ecology
(Hannan and Freeman, 1977), resource dependency theory
(Pfeffer and Salancik, 1978), and neoinstitutionalism
(DiMaggio and Powell, 1983). Uncertainty, as either an
objective feature of the environment or as a subjective
perception of key organizational actors, can thus possibly
explain differences in organizations across environment (more
or less certain), as well as seemingly irrational or inefcient
organizational behaviors and forms.
Beyond theories of organizations, the problem of uncertainty
also plays a central role in the practical considerations of the
literature on organizations operating in high-risk environments.
The complexity of both technologies and large organizations
make accurate assessment of the situations, actions, or conse-
quences more difcult, if not impossible. With the threat of
serious human and environmental costs for being wrong,
managing risks and uncertainty is paramount. In his normal
accident theory, Perrow ([1984]1999) argues that major disas-
ters are an inevitable by-product of working under such
epistemic conditions, so some high technological endeavors
should be abandoned. In contrast, drawing on cases of
successful organizational management of high-risk endeavors,
the high-reliability organization theory out of Berkeley (Weick,
1987;Roberts, 1989) proposes that uncertainties and risks can
be effectively managed with the right kind of management,
organizational culture, and approach to teamwork and organi-
zational learning and knowledge. Arguably, what separates these
two different approaches to risk management is an assessment
of the nature of uncertainty and our ability or inability to
anticipate problems. In the high-reliability approach and in the
broader literature on organizational risk management, one nds
an understandable focus on preventing foreseeable mistakes and
disasters. This places more focus on epistemological uncertainty.
Perrows more cautious approach places greater emphasis on the
idea of ontological uncertainty that is, there are things that are
going to happen that could not be predicted.
Risk Culture and Society
The other area within sociology where the concept of uncer-
tainty receives some explicit attention is in the social theoretical
work concerned with the role of risk in modernity. Within this
area of research, there has been emphasis on both the cultural
and structural elements related to problems of risk. Douglas
and Wildavskys (1983) work on the culture of risk explores
how perceptions of risk are tied to cultural ideals about what
constitutes a good society. Fears and concerns about certain
dangers do not necessarily reect real risks, but rather culturally
framed anxieties embedded within a particular social organi-
zation. More recently, Cerulo (2006) argues that culture plays
a role in preventing people from anticipating the worst possible
outcomes, skewing their perceptions to be overly optimistic.
While this work emphasizes the problem of risk perception, the
problem of uncertainty looms in the background. Culture
shapes what areas of uncertainty receive more attention within
a given social context, and thus, what areas of uncertainty
people may fail to see coming.
Beck (1992, 2009) argues that one of the hallmarks of the
postindustrial, globalized world is the unequal distribution of
risks and hazards. Scientic and technological advances have
brought with them the potential for untold human and envi-
ronmental costs; yet those costs are not born out equally,
especially in a globalized economy. This political dynamic, in
effect, means that the powerful are able to minimize negative
uncertainties in their lives, while those on the bottom have
lives exposed to even more uncertainty.
The concept of uncertainty has had a varied, if somewhat
inconsistent, history in the social sciences. At the heart of the
matter is a conceptual confusion. Is uncertainty a characteristic
of the knowledge itself or a characteristic of the knower? For
better or worse, the social sciences have treated it as both.
Uncertainty refers to an inevitable feature of the chaotic,
unpredictable world, yet it also refers to a psychological state or
phenomenological experience. How uncertainty has been
conceived of in the social sciences depends on the agenda,
methods, and theoretical assumptions of the researcher.
Economists, for example, turned away from the idea of
uncertainty as a kind of fundamental unpredictability because
it essentially stands outside of the models and thus, the basic
assumptions of economists. Uncertainty as a subjective expe-
rience holds greater sway in psychology and sociology because
it is seen as a fundamental driver for an array of seemingly
nonrational individual and collective behaviors. Yet this drive
for certainty in an uncertain world does not eliminate the
intrusion of unpredictable events in human affairs.
The lack of conceptual clarity and consistency does not
undermine the importance of this idea to the social sciences.
Rather it points to the challenges and the potential intellectual
richness of working at the limits of human knowledge.
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Uncertainty: History of the Concept 721
... Uncertainty was illuminated as meaningfully related to living with FS. Uncertainty is a broad concept but in a phenomenological sense it is both cognitive and emotional (Wakeham, 2015). In this respect it concerns not only the epistemological limit of knowledge about a given phenomenon, but also the ontological changes that may result from 'being uncertain.' ...
... In this respect it concerns not only the epistemological limit of knowledge about a given phenomenon, but also the ontological changes that may result from 'being uncertain.' There also appears to be a two-way interaction of the social situation on the individual's uncertainty and how the individual's uncertainty can change their social situation (Wakeham, 2015). The uncertainty of living with FS in this study is encapsulated by one participant's vivid description of living in "no-man's land." ...
Background: Frozen Shoulder (FS) is a painful debilitating condition that is a significant burden to those experiencing it and healthcare systems. Despite research investigating the pathogenesis and effective treatment for the condition, there is a paucity of research exploring how having frozen shoulder is lived through and meaningful to persons experiencing it. Objective: To explore how living with Frozen Shoulder is experienced and meaningful. Methods: A qualitative research study design using hermeneutic phenomenology methodology was used. In-depth unstructured interviews were conducted with six purposively recruited participants. Interpretive Phenomenological methods were used to analyze the data forming emergent, superordinate and master themes to qualitatively expose the meaningful aspects of living through FS. Findings: Five Master themes were identified: 1) "Dropping me to my knees," an incredible pain experience; 2) The struggle for normality; 3) An emotional change of self; 4) The challenges of the healthcare journey; and 5) Coping and adapting. The overarching 'binding theme' was Frozen Shoulder: Living with uncertainty and being in "no-man's land." Conclusions: This study illuminated the struggle to maintain a normal life while living with the significant pain, physical restriction, sleep loss and disability experienced by persons with Frozen Shoulder. Attempts to cope and adapt were impeded by the challenges of the healthcare journey. The uncertainty of these experiences was conveyed as being in "no man's land" an expression that reflected the existential crisis and impact on persons' sense of self.
... Lewis, Sycara & Walker (2018) states, the introduction of anthropomorphism poses serious risks, as humans may develop a higher level of trust in a robot than is warranted. Additionally, risks do not always reflect real dangers, but rather culturally framed anxieties originating from social organisation (Wakeham, 2015). Interestingly, research by Robinette et al. (2016) shows that in certain situations, a person may over-trust a robot while mitigating risks and disregarding the prior performance of the robot. ...
... However, another dimension of trust is uncertainty. According to Wakeham (2015), who described being uncertain as having an obscured view of the truth, with a limit on what an individual might know. Uncertainty can cause a restriction in the ability to trust; with uncertainty, you are unable to know all that can happen, resulting in trust becoming a leap of faith (Nooteboom, 2019). ...
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Background Human senses have evolved to recognise sensory cues. Beyond our perception, they play an integral role in our emotional processing, learning, and interpretation. They are what help us to sculpt our everyday experiences and can be triggered by aesthetics to form the foundations of our interactions with each other and our surroundings. In terms of Human-Robot Interaction (HRI), robots have the possibility to interact with both people and environments given their senses. They can offer the attributes of human characteristics, which in turn can make the interchange with technology a more appealing and admissible experience. However, for many reasons, people still do not seem to trust and accept robots. Trust is expressed as a person’s ability to accept the potential risks associated with participating alongside an entity such as a robot. Whilst trust is an important factor in building relationships with robots, the presence of uncertainties can add an additional dimension to the decision to trust a robot. In order to begin to understand how to build trust with robots and reverse the negative ideology, this paper examines the influences of aesthetic design techniques on the human ability to trust robots. Method This paper explores the potential that robots have unique opportunities to improve their facilities for empathy, emotion, and social awareness beyond their more cognitive functionalities. Through conducting an online questionnaire distributed globally, we explored participants ability and acceptance in trusting the Canbot U03 robot. Participants were presented with a range of visual questions which manipulated the robot’s facial screen and asked whether or not they would trust the robot. A selection of questions aimed at putting participants in situations where they were required to establish whether or not to trust a robot’s responses based solely on the visual appearance. We accomplished this by manipulating different design elements of the robots facial and chest screens, which influenced the human-robot interaction. Results We found that certain facial aesthetics seem to be more trustworthy than others, such as a cartoon face versus a human face, and that certain visual variables ( i.e., blur) afforded uncertainty more than others. Consequentially, this paper reports that participant’s uncertainties of the visualisations greatly influenced their willingness to accept and trust the robot. The results of introducing certain anthropomorphic characteristics emphasised the participants embrace of the uncanny valley theory, where pushing the degree of human likeness introduced a thin line between participants accepting robots and not. By understanding what manipulation of design elements created the aesthetic effect that triggered the affective processes, this paper further enriches our knowledge of how we might design for certain emotions, feelings, and ultimately more socially acceptable and trusting robotic experiences.
... In general characterization, uncertainty is a situation closely related to imperfect or unknown information and occurs at the limits of knowledge. In other words, uncertainty permeates several moments, not only in academic fields but also in daily life (WAKEHAM, 2015). It has a significant influence on our daily decisions, from choosing whether to take an umbrella on a cloudy day and invest or not in stocks on the stock exchange. ...
... Uncertainty is a relevant topic in several research fields (WAKEHAM, 2015). ...
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Futures studies have shown an accelerated growth since the post-World War II period, in which governments and private companies have been attentive to the importance of "forecasting" new trends, mainly technological ones, for their security as an institution. Such studies have gained a new panorama from the proliferation of data on massive scales and the increasing processing capacity, leading to new approaches, mainly in data-driven studies. Big Data and Machine Learning (BDML) has become powerful tools to extract and analyze data for future-oriented activities. The central question about using BDML tools is to understand the specific impacts of these mechanisms on futures studies' conceptual and methodological approaches. This work intends to respond to these questions by analyzing academic publications about futures studies supported by BDML and the opinions of 479 futures studies experts. The proposed methodology aims to comprehend how these tools are employed, the future benefits and limitations of BDML in foresight. The bibliometric results point to a reduced but increasing number of prospective studies supported by BDML published in the past decades. In general, these studies employ BDML techniques such as text and data mining in at least one part of the foresight process. Futures studies experts' opinions suggested that 1) analytical competencies are essential to deal with the complexity of the digital revolution, and 2) robust data analysis and automated tools support the transfer of study results to policy- and strategy-making. However, 3) the lack of data reliability and manipulation can play an uncertain role in this environment. The thesis concludes that BDML impact future-oriented activities in three dimensions: 1) Data reliance, 2) Data-Method integration, and 3) Decision-making. Data manipulation may increase the perception of substantive uncertainty in futures studies. However, integrating BDML techniques in foresight methodologies strongly decreases procedural uncertainty and will support effective decision-making. The limitation of this work is mainly two. First, non-academic futures studies publications were not collected in the bibliometric analysis. Second, the expert's population and sample characteristics were not compared due to a limitation of population data in survey analysis.
... Similarly to gestures, ambiguous situations invite more than one interpretation. Having found themselves in an ambiguous situation, participants tend to seek resolution sometimes unconsciously [19]. Non-verbal ambiguity (there is more to it than just the types described above, for instance, the ambiguity of facial expressions, body language, etc.) needs further transdisciplinary research. ...
... The recipient may not have sufficient background knowledge to resolve ambiguity or may make wrong inferences due to differences in the combination of cognitive, social, professional, value and gender attributes. It has long been known that ambiguities require much more time and effort to understand that unambiguous sentences or structures [18][19][20]. Psychological consequences of ambiguity result in its slower perception. Experiments demonstrate that it takes longer to process sentences with three meanings than those having two or one [1]. ...
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Here, we offer a reflection on ambiguity, its typology, production and effects as well as cognitive mechanisms of disambiguation. We approach ambiguity from the cognitivist viewpoint combined with elements of enactivism understood as embodied knowledge, interactivity and distributiveness. Without refuting the cognitivist paradigm or incurring into contradiction, we use these features as additional engines of our reflexing. Ambiguity is enacted by a network of heterogeneous participants (agents, subjects, objects) in various roles and with varying degrees of reflexive awareness and intentionality. Based on this we built a typology of ambiguity according to several criteria: the degree of awareness or intentionality, pragmatic effects achieved, language mechanisms, the volume of encoded conceptual information, the type of modality, and the number of events referred to. We hold that the process of disambiguation is triggered by cognitive context and conceptual primes over time, both in pre- and post-position.
... When we talk about uncertainty, we are referring to something objectively indefinite, related to the world order, and not to the limitations of our knowledge (Wakeham, 2015) [9]. When we talk about the objective, we only mean that we are talking about the structure of the world, regardless of how well we understand this device. ...
... When we talk about uncertainty, we are referring to something objectively indefinite, related to the world order, and not to the limitations of our knowledge (Wakeham, 2015) [9]. When we talk about the objective, we only mean that we are talking about the structure of the world, regardless of how well we understand this device. ...
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The article reveals the concept of “uncertainty” in the context of culture, science and practice. The notions of uncertainty in different schools and concepts in the field of philosophy and psychology are compared. The hypotheses of the uncertainty phenomenon are explained in detail. The article describes a clinical analysis of five types of subjective attitude to uncertainty, based on the research of scientists: M. K. Mamardashvili, T. E. Sokolova and other experts in the field of subjective attitude to uncertainty. At the end of the article, the data of the scientific interview is given. The article also presents research by modern scientists: Byrne, Peters, Willis, Phan, Worthy (2020), who demonstrated in their research the psychological States of respondents with high uncertainty. The article goes on to describe in more detail the types of research that demonstrate the concepts of acute and moderate stress, tolerance, and other important factors that influence attitudes to uncertainty. The following describes a study aimed at disaster risk reduction, researchers: Schueller, Booth, Fleming, Abad (2020), who developed a disaster risk reduction (DRR) recommendation for stakeholders, which is designed to assess how uncertainty affects the processing of early warning information and subsequent decision-making (for example, an evacuation order), embedded in fictitious geo-graphical, policy and practical conditions. This topic: "Uncertainty as an important determinant in psychological science and practice" is relevant in modern society. The conclusions reveal the content of the data obtained, the analysis of the attitude to uncertainty as a phenomenon of science and practice.
... The term uncertainty has often been used interchangeably with similar, albeit conceptually distinct, terms such as "ambiguity" and "risk" (Wakeham, 2015), contributing further to the instability of the concept. The likely cause for this complexity and diversity of definitions is in part due to the use of the term across a variety of disparate fields for different purposes, ranging from behavioural economics (Tversky & Kahneman, 1974) and communication studies (Afifi & Afifi, 2016), to mental health sciences (Grupe & Nitschke, 2013) and medical disciplines (Szulczewski et al., 2017). ...
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Background The current moment is characterised by deep-rooted uncertainties, such as climate change and COVID-19. Uncertainty has been reported to be associated with negative mental health outcomes, such as stress and anxiety. However, no comprehensive review on the association between uncertainty and mental health exists. Aim The aim of the current scoping review was to systematically explore and describe the literature on the link between uncertainty and mental health. Methods A scoping review was undertaken following guidelines by Arksey and O’Malley (2005). Results One hundred and one papers addressing the association between uncertainty and mental health were identified. Most were cross-sectional studies (67%) conducted in the fields of medicine or nursing (59%), in high-income countries, among adult populations (74%), and in medical settings. Substantial heterogeneity was identified in the measurements of uncertainty and mental health. Most studies (79%) reported a positive association between uncertainty and mental health problems. Conclusions Research is needed in more diverse contexts and populations. More robust designs are required to provide insight into the directionality and strength of the association between uncertainty and mental health. Few studies reported how individuals coped with uncertainty. Future studies should address the identified gaps and investigate interventions to address uncertainty and its determinants.
"The purpose of this study was to establish the relationship between the tolerance for uncertainty level and several psychophysiological and psychological qualities of military specialists for determining additional approaches to occupational selection. The study was conducted on a group of servicemen who performed special tasks and were capable of responding to terrorism – 49 men (main group) and 19 military doctors (control group) – men aged 25-34 years. Tolerance for uncertainty was studied based on the modified S. Badnder’s method. The level of manipulation score (MAC) was assessed by the adapted I.A. Romanova and O.O. Zhdanov questionnaire (estimated by the so-called ""MacScale""). Psycho-physiological parameters were determined using a special computer program. Statistical analysis of data was performed by descriptive and nonparametric statistics, as well as a cluster, stepwise discriminant, and correlation analysis. A personality trait “tolerance for uncertainty” was valuable for the occupational activity of servicemen performing special tasks. The such feature had 63.3% of servicemen in the studied group. The specificity of the occupational activity of military doctors was the quality of manipulation of people. Moreover, those who were the most tolerant of uncertainty had an inverse relationship with Machiavellianism, which indicates the existence of compensatory psychological mechanisms balancing and harmonizing service and personal relationships among micro-teams of servicemen. Servicemen with a lower level of tolerance for uncertainty had positive relationships with several psychophysiological functions (strength and mobility of nervous processes, quality of dynamic memorization), which confirms the idea of psychophysiological mechanisms to enhance tolerance for uncertainty by increasing the working capacity of these people. Such personal quality as tolerance for uncertainty is a valuable occupationally important feature that allows performing the selection of servicemen who are more efficient and reliable in the performance of official duties tasks. "
This article offers a conceptual framework within a decision-making (DM) context in situations, when child protection workers have to decide to either remove a child from his or her parents care or leave him or her in a family. Based on the thematic analysis of data from the 33 interviews, we have developed the concept of DM context as a space of uncertainty which is multilayered and implies an inherent duality of each contextual element. The study contributed to the research on work in a private setting, by revealing the role of agency culture and public attitudes in child protection workers’ decisions.
Aim To analyze and examine the concept of uncertainty of the patient's illness among family caregivers. Background Promoting family caregivers’ health is significant in nursing. Family caregivers may experience uncertainty related to their loved ones’ illness. A lack of clarity exists regarding the uncertainty concept among family caregivers and its implications in nursing. Data Source A review of the literature that focused on family caregivers of adult patients using PubMed, CINAHL, and Scopus databases was completed. Methods The Walker and Avant framework was applied to identify the attributes, antecedents, and consequences of family caregivers’ uncertainty. Results Eight articles were analyzed. Attributes of family caregivers’ uncertainty included the patient's illness probability and family caregivers’ perception of the illness. Antecedents included the characteristics of the patient's illness, factors associated with the family caregivers’ perception of the illness, and family responsibilities of caregiving. The consequences included family caregivers’ emotional, psychological, and financial outcomes. Family caregivers’ uncertainty is defined as the perception of the inability to process information regarding the patient's illness trajectory when caring for significant others’ illness. Conclusions Individuals can perceive uncertainty differently as a patient-facing uncertainty in illness versus a family caregiver facing uncertainty of their loved ones’ illness.
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The speed of the Covid-19 pandemic has imparted an acceleration – a "variation of velocity in the time unity" – to multiple social processes: that of political decision making, that of science in search of medical protocols and treatments, that of the use of new technologies, that of political and biopolitical control techniques. But each of the different functional systems tackling the challenge of this global threat has its own rhythm and tempo, constrained by the nature of its own constitutive processes. How is this acceleration putting to test the extant social "time structures", and how is it altering the dynamics of their interactions? The conceptual tools developed by the critical theory of acceleration for interpreting the temporal paradoxes of late modernity may provide a key for reading the ongoing transformations, and help reasoning on the possible directions of this acceleration – in fact, as it is the case in physics, the direction of acceleration is not pregiven, it is rather the resultant of the directions and intensities of the forces which act upon a body.
This occasionally biographical paper deals with three cognitive and social patterns in the practice of science (not 'the scientific method’). The first, “establishing the phenomenon,” involves the doctrine (universally accepted in the abstract) that phenomena should of course be shown to exist or to occur before one explains why they exist or how they come to be; sources of departure in practice from this seemingly self-evident principle are examined. One parochial case of such a departure is considered in detail. The second pattern is the particular form of ignorance described as “specified ignorance”: the express recognition of what is not yet known but needs to be known in order to lay the foundation for still more knowledge. The substantial role of this practice in the sciences is identified and the case of successive specification of ignorance in the evolving sociological theory of deviant behavior by four thought-collectives is sketched out. Reference is made to the virtual institutionalization of specified ignorance in some sciences and the question is raised whether scientific disciplines differ in the extent of routinely specifying ignorance and how this affects the growth of knowledge. The two patterns of scientific practice are linked to a third: the use of “strategic research materials (SRMs)” i.e. strategic research sites, objects, or events that exhibit the phenomena to be explained or interpreted to such advantage and in such accessible form that they enable the fruitful investigation of previously stubborn problems and the discovery of new problems for further inquiry. The development of biology is taken as a self-exemplifying case since it provides innumerable SRMs for the sociological study of the selection and consequences of SRMs in science. The differing role of SRMs in the natural sciences and in the Geisteswissenschaften is identified and several cases of strategic research sites and events in sociology, explored.
In subjective expected utility (SEU), the decision weights people attach to events are their beliefs about the likelihood of events. Much empirical evidence, inspired by Ellsberg (1961) and others, shows that people prefer to bet on events they know more about, even when their beliefs are held constant. (They are averse to ambiguity, or uncertainty about probability.) We review evidence, recent theoretical explanations, and applications of research on ambiguity and SEU.