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Uncertainty

Uncertainty or Incertitude refers to epistemic situations involving imperfect or unknown information. It applies to predictions of future events, to physical measurements that are already made, or to the unknown. Uncertainty arises in partially observable or stochastic environments, as well as due to ignorance, indolence, or both.[1] It arises in any number of fields, including insurance, philosophy, physics, statistics, economics, finance, medicine, psychology, sociology, engineering, metrology, meteorology, ecology and information science.

For the film of the same name, see Uncertainty (film).

Type A, those evaluated by methods

statistical

Type B, those evaluated by other means, e.g., by assigning a

probability distribution

In the media[edit]

Uncertainty in science, and science in general, may be interpreted differently in the public sphere than in the scientific community.[21] This is due in part to the diversity of the public audience, and the tendency for scientists to misunderstand lay audiences and therefore not communicate ideas clearly and effectively.[21] One example is explained by the information deficit model. Also, in the public realm, there are often many scientific voices giving input on a single topic.[21] For example, depending on how an issue is reported in the public sphere, discrepancies between outcomes of multiple scientific studies due to methodological differences could be interpreted by the public as a lack of consensus in a situation where a consensus does in fact exist.[21] This interpretation may have even been intentionally promoted, as scientific uncertainty may be managed to reach certain goals. For example, climate change deniers took the advice of Frank Luntz to frame global warming as an issue of scientific uncertainty, which was a precursor to the conflict frame used by journalists when reporting the issue.[22]


"Indeterminacy can be loosely said to apply to situations in which not all the parameters of the system and their interactions are fully known, whereas ignorance refers to situations in which it is not known what is not known."[23] These unknowns, indeterminacy and ignorance, that exist in science are often "transformed" into uncertainty when reported to the public in order to make issues more manageable, since scientific indeterminacy and ignorance are difficult concepts for scientists to convey without losing credibility.[21] Conversely, uncertainty is often interpreted by the public as ignorance.[24] The transformation of indeterminacy and ignorance into uncertainty may be related to the public's misinterpretation of uncertainty as ignorance.


Journalists may inflate uncertainty (making the science seem more uncertain than it really is) or downplay uncertainty (making the science seem more certain than it really is).[25] One way that journalists inflate uncertainty is by describing new research that contradicts past research without providing context for the change.[25] Journalists may give scientists with minority views equal weight as scientists with majority views, without adequately describing or explaining the state of scientific consensus on the issue.[25] In the same vein, journalists may give non-scientists the same amount of attention and importance as scientists.[25]


Journalists may downplay uncertainty by eliminating "scientists' carefully chosen tentative wording, and by losing these caveats the information is skewed and presented as more certain and conclusive than it really is".[25] Also, stories with a single source or without any context of previous research mean that the subject at hand is presented as more definitive and certain than it is in reality.[25] There is often a "product over process" approach to science journalism that aids, too, in the downplaying of uncertainty.[25] Finally, and most notably for this investigation, when science is framed by journalists as a triumphant quest, uncertainty is erroneously framed as "reducible and resolvable".[25]


Some media routines and organizational factors affect the overstatement of uncertainty; other media routines and organizational factors help inflate the certainty of an issue. Because the general public (in the United States) generally trusts scientists, when science stories are covered without alarm-raising cues from special interest organizations (religious groups, environmental organizations, political factions, etc.) they are often covered in a business related sense, in an economic-development frame or a social progress frame.[26] The nature of these frames is to downplay or eliminate uncertainty, so when economic and scientific promise are focused on early in the issue cycle, as has happened with coverage of plant biotechnology and nanotechnology in the United States, the matter in question seems more definitive and certain.[26]


Sometimes, stockholders, owners, or advertising will pressure a media organization to promote the business aspects of a scientific issue, and therefore any uncertainty claims which may compromise the business interests are downplayed or eliminated.[25]

Uncertainty is designed into , most notably in gambling, where chance is central to play.

games

In , in which the prediction of future events should be understood to have a range of expected values

scientific modelling

In , and in particular data management, uncertain data is commonplace and can be modeled and stored within an uncertain database

computer science

In , uncertainty permits one to describe situations where the user does not have full control on the outcome of the optimization procedure, see scenario optimization and stochastic optimization.

optimization

In , it is now commonplace to include data on the degree of uncertainty in a weather forecast.

weather forecasting

Uncertainty or is used in science and engineering notation. Numerical values should only have to be expressed in those digits that are physically meaningful, which are referred to as significant figures. Uncertainty is involved in every measurement, such as measuring a distance, a temperature, etc., the degree depending upon the instrument or technique used to make the measurement. Similarly, uncertainty is propagated through calculations so that the calculated value has some degree of uncertainty depending upon the uncertainties of the measured values and the equation used in the calculation.[27]

error

In , the Heisenberg uncertainty principle forms the basis of modern quantum mechanics.[17]

physics

In , measurement uncertainty is a central concept quantifying the dispersion one may reasonably attribute to a measurement result. Such an uncertainty can also be referred to as a measurement error.

metrology

In daily life, measurement uncertainty is often implicit ("He is 6 feet tall" give or take a few inches), while for any serious use an explicit statement of the measurement uncertainty is necessary. The expected measurement uncertainty of many (scales, oscilloscopes, force gages, rulers, thermometers, etc.) is often stated in the manufacturers' specifications.

measuring instruments

In , uncertainty can be used in the context of validation and verification of material modeling.[28]

engineering

Uncertainty has been a common theme in art, both as a thematic device (see, for example, the indecision of ), and as a quandary for the artist (such as Martin Creed's difficulty with deciding what artworks to make).

Hamlet

Uncertainty is an important factor in . According to economist Frank Knight, it is different from risk, where there is a specific probability assigned to each outcome (as when flipping a fair coin). Knightian uncertainty involves a situation that has unknown probabilities.[12]

economics

Investing in such as the stock market involves Knightian uncertainty when the probability of a rare but catastrophic event is unknown.[12]

financial markets

(2006-09-11). Understanding Uncertainty. Wiley-Interscience. ISBN 978-0-470-04383-7.

Lindley, Dennis V.

(2009). Theory of Decision under Uncertainty. Cambridge: Cambridge University Press. ISBN 9780521517324.

Gilboa, Itzhak

(2005-09-01). Reasoning about Uncertainty. MIT Press. ISBN 9780521517324.

Halpern, Joseph

(1989). Ignorance and Uncertainty. New York: Springer-Verlag. ISBN 978-0-387-96945-9.

Smithson, Michael

"Treading Thin Air: Geoff Mann on Uncertainty and Climate Change", , vol. 45, no. 17 (7 September 2023), pp. 17–19. "[W]e are in desperate need of a politics that looks [the] catastrophic uncertainty [of global warming and climate change] square in the face. That would mean taking much bigger and more transformative steps: all but eliminating fossil fuels... and prioritizing democratic institutions over markets. The burden of this effort must fall almost entirely on the richest people and richest parts of the world, because it is they who continue to gamble with everyone else's fate." (p. 19.)

London Review of Books

Archived 2007-12-15 at the Wayback Machine

Measurement Uncertainties in Science and Technology, Springer 2005

Proposal for a New Error Calculus

Archived 2008-05-27 at the Wayback Machine

Estimation of Measurement Uncertainties — an Alternative to the ISO Guide

Bibliography of Papers Regarding Measurement Uncertainty

Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results

Strategic Engineering: Designing Systems and Products under Uncertainty (MIT Research Group)

from Cambridge's Winton programme

Understanding Uncertainty site

Bowley, Roger (2009). . Sixty Symbols. Brady Haran for the University of Nottingham.

"∆ – Uncertainty"