Communicating uncertainty using words and numbers
Authors: Mandeep K. Dhami, David R. Mandel
Journal: Trends in Cognitive Sciences (2022)

The (positive and negative) directionality of verbal probabilities enables them to convey more than uncertainty. Probability terms can communicate uncertainty in a face-saving manner and implicitly shape receivers' cognitions and behavior.Verbal probabilities preclude fine-grained uncertainty communication. Assigning numeric probability ranges to words does not eliminate their imprecise and variable meaning, but can have unintended effects on judgment and decision-making.Senders are misplaced in their belief that verbal expressions of uncertainty are especially helpful for those with lower numeracy and in thinking that these individuals cannot benefit from numeric probability information.The benefits of precise numeric expressions of uncertainty, coupled with receivers' preference for numeric information when it really matters, suggests that senders ought to embrace numeric precision over vague words if they wish to communicate uncertainty clearly. Life in an increasingly information-rich but highly uncertain world calls for an effective means of communicating uncertainty to a range of audiences. Senders prefer to convey uncertainty using verbal (e.g., likely) rather than numeric (e.g., 75% chance) probabilities, even in consequential domains, such as climate science. However, verbal probabilities can convey something other than uncertainty, and senders may exploit this. For instance, senders can maintain credibility after making erroneous predictions. While verbal probabilities afford ease of expression, they can be easily misunderstood, and the potential for miscommunication is not effectively mitigated by assigning (imprecise) numeric probabilities to words. When making consequential decisions, recipients prefer (precise) numeric probabilities. Life in an increasingly information-rich but highly uncertain world calls for an effective means of communicating uncertainty to a range of audiences. Senders prefer to convey uncertainty using verbal (e.g., likely) rather than numeric (e.g., 75% chance) probabilities, even in consequential domains, such as climate science. However, verbal probabilities can convey something other than uncertainty, and senders may exploit this. For instance, senders can maintain credibility after making erroneous predictions. While verbal probabilities afford ease of expression, they can be easily misunderstood, and the potential for miscommunication is not effectively mitigated by assigning (imprecise) numeric probabilities to words. When making consequential decisions, recipients prefer (precise) numeric probabilities. Citizens and policymakers alike depend on information characterized by uncertainty to be informed and make decisions (Box 1). Many pressing problems facing humanity, from climate change to global pandemics, are characterized by deep uncertainties about the nature of the problem and the efficacy of proposed solutions [1.Kay J.A. King M.A. Radical Uncertainty: Decision-Making for an Unknowable Future. Bridge Street Press, 2020Google Scholar]. The format in which these uncertainties are communicated, numerically or non-numerically (e.g., verbally), can affect how well they are understood and how they influence cognition and behavior. Numeric representations of uncertainty include percentages, decimals, ratios, and fractions. Numeric information can be expressed precisely (e.g., 75% chance), imprecisely (e.g., 65–85%), or with features of both (e.g., 75 ±10%). Common non-numeric representations include probability terms (e.g., likely) as well as words such as slight hope [2.Wallsten T.S. Budescu D.V. A review of human linguistic probability processing: general principles and empirical evidence.Knowl. Eng. Rev. 1995; 10: 43-62Crossref Scopus (106) Google Scholar]. These natural language expressions may be used with modifiers (e.g., very) and hedges (e.g., almost) [3.Ferson S. et al.Natural language of uncertainty: numeric hedge words.Int. J. Approx. Reason. 2015; 57: 19-39Crossref Scopus (19) Google Scholar,4.Strekalova Y. James V.S. Language of uncertainty: the expression of decisional conflict related to skin cancer prevention recommendations.J. Cancer Educ. 2016; 32: 532-536Crossref Scopus (4) Google Scholar].Box 1Defining uncertaintyRecent reviews focus on applied domains [87.Dhami M.K. Mandel D.R. Words or numbers? Communicating probability in intelligence analysis.Am. Psychol. 2021; 76: 549-560Crossref PubMed Scopus (9) Google Scholar,89.Andreadis K. et al.Imprecision and preferences in interpretation of verbal probabilities in health: a systematic review.J. Gen. Intern. Med. 2021; 36: 3820-3829Crossref PubMed Scopus (3) Google Scholar, 90.Bansback N. et al.Communicating uncertainty in benefits and harms: a review of patient decision support interventions.Patient. 2016; 10: 311-319Crossref Scopus (14) Google Scholar, 91.Bostrom A. et al.Methods for communicating the complexity and uncertainty of oil spill response actions and tradeoffs.Hum. Ecol. Risk. Assess. 2015; 21: 631-645Crossref Scopus (14) Google Scholar, 92.Raftery A.E. Use and communication of probabilistic forecasts.Stat. Anal. Data Min. 2014; 9: 397-410Crossref Scopus (24) Google Scholar, 93.Simpkin A.L. Armstrong K.A. Communicating uncertainty: a narrative review and framework for future research.J. Gen. Intern. Med. 2019; 34: 2586-2591Crossref PubMed Scopus (36) Google Scholar] or specific readerships [94.Spiegelhalter D. Risk and uncertainty communication.Annu. Rev. Stat. 2017; 4: 31-60Crossref Scopus (75) Google Scholar], while others consider the context of communication [95.van der Bles A.M. et al.Communicating uncertainty about facts, numbers and science.R. Soc. Open Sci. 2019; 6181870Crossref PubMed Scopus (124) Google Scholar]. Researchers use the terms uncertainty, risk, and probability interchangeably (e.g., [19.Jenkins S.C. Harris A.J.L. Maintaining credibility when communicating uncertainty: the role of directionality.Think. Reason. 2020; 27: 97-123Crossref Scopus (3) Google Scholar,72.McDowell M. Kause A. Communicating uncertainties about the effects of medical interventions using different display formats.Risk Anal. 2021; 41: 2220-2239Crossref PubMed Scopus (1) Google Scholar]) and so do previous reviews (e.g., [21.Collins P.J. Hahn U. Communicating and reasoning with verbal probability expressions.Psychol. Learn. Motiv. 2018; 69: 67-75Crossref Scopus (8) Google Scholar]). In Boolean logic, propositions can be either true or false and there is no place for uncertainty. Past, present, and future events can all have uncertainty associated with them. Prominent examples of uncertainty around past events include criminal case investigations and prosecutions, uncertainty around present events includes medical diagnoses, and around future events includes climate change and national security threats.Formally, extensions to three-valued logics included uncertainty such that possible states could be true, false, or unsure [96.Baratgin J. et al.The psychology of uncertainty and three-valued truth tables.Front. Psychol. 2018; 9: 1479Crossref PubMed Scopus (19) Google Scholar]. Probability allows degrees of certainty in the truth or falsity of a proposition to be scaled (from 0 to 1), adding the ability to quantify degrees of uncertainty. Knight made an important distinction between risk and uncertainty: situations in which the probabilities of propositions (often possible gains or losses) were specifiable were referred to as risk and situations in which the probabilities were not specifiable were called uncertainty [97.Knight F.H. Risk, Uncertainty, and Profit. Houghton Mifflin, 1921Google Scholar]. Since risk has other connotations associated with it, such as possible loss, and because it can be conceived as the quantifiable subset of uncertainty, we use the term uncertainty to refer to any situation in which degrees of unsureness are communicated. However, we restrict the scope of our review to what traditionally falls under the category of Knightian risk; namely, the communication of probabilities that are assumed to be translatable into quantitative equivalents, even if communicated in nonquantitative formats (e.g., with words). These non-numeric equivalents can be assumed to be precise (e.g., translatable to 70% chance) or imprecise (e.g., translatable to 60–80% chance), but they are nonetheless assumed to be quantifiable (see Figure 1 in the main text).Within this scope, the bases for quantifiable probability communications are varied. Such communication might originate in objective or external sources, such as a base rate of event occurrence. Alternatively, it might originate in subjective or internal sources, such as an individual's feeling of sureness (or confidence) that they answered a question correctly [98.Galesic M. et al.A sampling framework for uncertainty in individual environmental decisions.Top. Cogn. Sci. 2016; 8: 242-258Crossref PubMed Scopus (13) Google Scholar,99.Ulkumen G. et al.Two dimensions of subjective uncertainty: clues from natural language.J. Exp. Psychol. 2016; 145: 1280-1297Crossref Scopus (39) Google Scholar]. Internal uncertainty tends to be conveyed in first-person (e.g., 'I am X% certain…'), whereas external uncertainty is conveyed in third-person ('there is an X% chance…') [100.Løhre E. Teigen K.H. There is a 60% probability, but I am 70% certain: communicative consequences of external and internal expressions of uncertainty.Think. Reason. 2016; 22: 369-396Crossref Scopus (17) Google Scholar]. Although we acknowledge these and other distinctions [63.Janzwood S. Confident, likely, or both? The implementation of the uncertainty language framework in IPCC special reports.Clim. Chang. 2020; 162: 1655-1675Crossref Scopus (7) Google Scholar], our review of the literature cuts across them. Additionally, we focus on the communication of different levels of uncertainty, rather than simply on the communication of certain (deterministic) outcomes versus uncertain ones (e.g., [101.Gaertig C. Simmons J.P. Do people inherently dislike uncertain advice?.Psychol. Sci. 2018; 29: 504-520Crossref PubMed Scopus (15) Google Scholar, 102.Joslyn S.L. LeClerc J.E. Climate projections and uncertainty communication.Top. Cogn. Sci. 2016; 8: 222-241Crossref PubMed Scopus (23) Google Scholar, 103.Wiedeman et al.Effects of communicating uncertainty descriptions in hazard identification, risk characterization, and risk protection.PLoS ONE. 2021; 16e0253762Crossref PubMed Scopus (3) Google Scholar]). Recent reviews focus on applied domains [87.Dhami M.K. Mandel D.R. Words or numbers? Communicating probability in intelligence analysis.Am. Psychol. 2021; 76: 549-560Crossref PubMed Scopus (9) Google Scholar,89.Andreadis K. et al.Imprecision and preferences in interpretation of verbal probabilities in health: a systematic review.J. Gen. Intern. Med. 2021; 36: 3820-3829Crossref PubMed Scopus (3) Google Scholar, 90.Bansback N. et al.Communicating uncertainty in benefits and harms: a review of patient decision support interventions.Patient. 2016; 10: 311-319Crossref Scopus (14) Google Scholar, 91.Bostrom A. et al.Methods for communicating the complexity and uncertainty of oil spill response actions and tradeoffs.Hum. Ecol. Risk. Assess. 2015; 21: 631-645Crossref Scopus (14) Google Scholar, 92.Raftery A.E. Use and communication of probabilistic forecasts.Stat. Anal. Data Min. 2014; 9: 397-410Crossref Scopus (24) Google Scholar, 93.Simpkin A.L. Armstrong K.A. Communicating uncertainty: a narrative review and framework for future research.J. Gen. Intern. Med. 2019; 34: 2586-2591Crossref PubMed Scopus (36) Google Scholar] or specific readerships [94.Spiegelhalter D. Risk and uncertainty communication.Annu. Rev. Stat. 2017; 4: 31-60Crossref Scopus (75) Google Scholar], while others consider the context of communication [95.van der Bles A.M. et al.Communicating uncertainty about facts, numbers and science.R. Soc. Open Sci. 2019; 6181870Crossref PubMed Scopus (124) Google Scholar]. Researchers use the terms uncertainty, risk, and probability interchangeably (e.g., [19.Jenkins S.C. Harris A.J.L. Maintaining credibility when communicating uncertainty: the role of directionality.Think. Reason. 2020; 27: 97-123Crossref Scopus (3) Google Scholar,72.McDowell M. Kause A. Communicating uncertainties about the effects of medical interventions using different display formats.Risk Anal. 2021; 41: 2220-2239Crossref PubMed Scopus (1) Google Scholar]) and so do previous reviews (e.g., [21.Collins P.J. Hahn U. Communicating and reasoning with verbal probability expressions.Psychol. Learn. Motiv. 2018; 69: 67-75Crossref Scopus (8) Google Scholar]). In Boolean logic, propositions can be either true or false and there is no place for uncertainty. Past, present, and future events can all have uncertainty associated with them. Prominent examples of uncertainty around past events include criminal case investigations and prosecutions, uncertainty around present events includes medical diagnoses, and around future events includes climate change and national security threats. Formally, extensions to three-valued logics included uncertainty such that possible states could be true, false, or unsure [96.Baratgin J. et al.The psychology of uncertainty and three-valued truth tables.Front. Psychol. 2018; 9: 1479Crossref PubMed Scopus (19) Google Scholar]. Probability allows degrees of certainty in the truth or falsity of a proposition to be scaled (from 0 to 1), adding the ability to quantify degrees of uncertainty. Knight made an important distinction between risk and uncertainty: situations in which the probabilities of propositions (often possible gains or losses) were specifiable were referred to as risk and situations in which the probabilities were not specifiable were called uncertainty [97.Knight F.H. Risk, Uncertainty, and Profit. Houghton Mifflin, 1921Google Scholar]. Since risk has other connotations associated with it, such as possible loss, and because it can be conceived as the quantifiable subset of uncertainty, we use the term uncertainty to refer to any situation in which degrees of unsureness are communicated. However, we restrict the scope of our review to what traditionally falls under the category of Knightian risk; namely, the communication of probabilities that are assumed to be translatable into quantitative equivalents, even if communicated in nonquantitative formats (e.g., with words). These non-numeric equivalents can be assumed to be precise (e.g., translatable to 70% chance) or imprecise (e.g., translatable to 60–80% chance), but they are nonetheless assumed to be quantifiable (see Figure 1 in the main text). Within this scope, the bases for quantifiable probability communications are varied. Such communication might originate in objective or external sources, such as a base rate of event occurrence. Alternatively, it might originate in subjective or internal sources, such as an individual's feeling of sureness (or confidence) that they answered a question correctly [98.Galesic M. et al.A sampling framework for uncertainty in individual environmental decisions.Top. Cogn. Sci. 2016; 8: 242-258Crossref PubMed Scopus (13) Google Scholar,99.Ulkumen G. et al.Two dimensions of subjective uncertainty: clues from natural language.J. Exp. Psychol. 2016; 145: 1280-1297Crossref Scopus (39) Google Scholar]. Internal uncertainty tends to be conveyed in first-person (e.g., 'I am X% certain…'), whereas external uncertainty is conveyed in third-person ('there is an X% chance…') [100.Løhre E. Teigen K.H. There is a 60% probability, but I am 70% certain: communicative consequences of external and internal expressions of uncertainty.Think. Reason. 2016; 22: 369-396Crossref Scopus (17) Google Scholar]. Although we acknowledge these and other distinctions [63.Janzwood S. Confident, likely, or both? The implementation of the uncertainty language framework in IPCC special reports.Clim. Chang. 2020; 162: 1655-1675Crossref Scopus (7) Google Scholar], our review of the literature cuts across them. Additionally, we focus on the communication of different levels of uncertainty, rather than simply on the communication of certain (deterministic) outcomes versus uncertain ones (e.g., [101.Gaertig C. Simmons J.P. Do people inherently dislike uncertain advice?.Psychol. Sci. 2018; 29: 504-520Crossref PubMed Scopus (15) Google Scholar, 102.Joslyn S.L. LeClerc J.E. Climate projections and uncertainty communication.Top. Cogn. Sci. 2016; 8: 222-241Crossref PubMed Scopus (23) Google Scholar, 103.Wiedeman et al.Effects of communicating uncertainty descriptions in hazard identification, risk characterization, and risk protection.PLoS ONE. 2021; 16e0253762Crossref PubMed Scopus (3) Google Scholar]). Senders often prefer to communicate uncertainty verbally [5.Wallsten T.S. et al.Preferences and reasons for communicating probabilistic information in numeric or verbal terms.Psychon. Bull. Rev. 1993; 31: 135-138Crossref Scopus (157) Google Scholar] (Box 2). Indeed, people find it easier and more natural to use words than numbers [6.Zimmer A.C. Verbal vs. numerical processing of subjective probabilities.Adv. Psychol. 1983; 16: 159-182Crossref Scopus (57) Google Scholar]. The language system is learned earlier than the numeric system during individual development, and words are a more dominant mode of human communication than are numbers. However, research suggests that verbal probabilities do not fare well in expressing uncertainty unambiguously [7.Budescu D.V. et al.The interpretation of IPCC probabilistic statements around the world.Nat. Clim. Chang. 2014; 4: 508-512Crossref Scopus (132) Google Scholar, 8.Brun W. Teigen K.H. Verbal probabilities: ambiguous, context-dependent, or both?.Organ. Behav. Hum. Decis. Process. 1988; 41: 390-404Crossref Scopus (204) Google Scholar, 9.Wallsten T.S. et al.Base-rate effects on the interpretations of probability and frequency expressions.J. Mem. Lang. 1986; 25: 571-587Crossref Scopus (136) Google Scholar]. Additionally, terms may communicate information that goes beyond strict degrees of probability [10.Teigen K.H. Brun W. Yes, but it is uncertain: direction and communicative intention of verbal probabilistic terms.Acta Psychol. 1995; 88: 233-258Crossref Scopus (87) Google Scholar, 11.Teigen K.H. Brun W. The directionality of verbal probability expressions: effects on decisions, predictions, and probabilistic reasoning.Organ. Behav. Hum. Decis. Process. 1999; 80: 155-190Crossref PubMed Scopus (124) Google Scholar, 12.Teigen K.H. et al.Verbal probabilities: an alternative approach.Q. J. Exp. Psychol. 2014; 67: 124-146Crossref Scopus (19) Google Scholar], raising concerns for their use in uncertainty communication. Senders and receivers may be unaware of miscommunication, given that their judgments of communicative success are unrelated to actual communicative success [13.Holtgraves T. Understanding miscommunication: speech act recognition in digital contexts.Cogn. Sci. 2021; 45e13023Crossref PubMed Scopus (1) Google Scholar].Box 2Communication mode preference paradoxAn individual's role in the communication process (i.e., sender/receiver) influences their preferred format for communicating uncertainty. Early research revealed a 'preference paradox', namely that, while most senders prefer to convey uncertainty verbally, most recipients prefer numeric uncertainty information [5.Wallsten T.S. et al.Preferences and reasons for communicating probabilistic information in numeric or verbal terms.Psychon. Bull. Rev. 1993; 31: 135-138Crossref Scopus (157) Google Scholar,104.Erev I. Cohen B.L. Verbal versus numerical probabilities: efficiency, biases, and the preference paradox.Organ. Behav. Hum. Decis. Process. 1990; 45: 1-18Crossref Scopus (188) Google Scholar].Although recent research demonstrates senders' preferences for verbal probabilities in domains such as medicine [105.Juanchich M. Sirota M. Most family physicians report communicating the risks of adverse drug reactions in words (vs. numbers).Appl. Cogn. Psychol. 2020; 34: 526-534Crossref Scopus (2) Google Scholar], extreme weather forecasting [33.Rosen Z.M.J. et al.Communicating probability information in hurricane forecasts: Assessing statements that forecasters use on social media and implications for public assessments of reliability.J. Operational Meteor. 2021; 9 (89–10)Google Scholar], and intelligence analysis [106.Barnes A. Making intelligence analysis more intelligent: using numeric probabilities.Intell. Natl. Secur. 2016; 31: 327-344Crossref Scopus (37) Google Scholar, 107.Marchio J. 'If the weatherman can...': The intelligence community's struggle to express analytic uncertainty in the 1970s.Stud. Intell. 2014; 58: 31-42Google Scholar, 108.Friedman J.A. Zeckhauser R. Assessing uncertainty in intelligence.Intell. Natl. Secur. 2012; 27: 824-847Crossref Scopus (34) Google Scholar], such preferences depend on specific factors. One is the nature of the uncertainty being communicated (e.g., lack of knowledge versus variation in the outcome being predicted). Epistemic and dispositional uncertainty are more likely to be conveyed using words, whereas distributional (aleatory) uncertainty is more likely to be expressed numerically [31.Juanchich M. Sirota M. Do people really prefer verbal probabilities?.Psychol. Res. 2020; 84: 2325-2338Crossref PubMed Scopus (7) Google Scholar]. Another influential factor is the severity of the predicted outcome. For instance, physicians' preference for communicating uncertainty using verbal probabilities over the numeric 1-in-X representation is reduced when conveying the more severe adverse effects of a drug than its less severe effects [105.Juanchich M. Sirota M. Most family physicians report communicating the risks of adverse drug reactions in words (vs. numbers).Appl. Cogn. Psychol. 2020; 34: 526-534Crossref Scopus (2) Google Scholar]. Thus, the qualitative–quantitative nature of the uncertainty matches senders' preference for a qualitative versus quantitative communication format, and the potential consequence of a decision (i.e., to take a drug) leads senders to increasingly favor the numeric format.In recent years, research on the receiver side has branched out to other evaluative measures, and these do not suggest a superiority of words over numbers. For instance, there was no difference in receivers' initial perceptions of the credibility (i.e., knowledge and trustworthiness) of senders who used verbal probabilities or precise or imprecise numeric values to express uncertainty [19.Jenkins S.C. Harris A.J.L. Maintaining credibility when communicating uncertainty: the role of directionality.Think. Reason. 2020; 27: 97-123Crossref Scopus (3) Google Scholar,20.Jenkins S.C. et al.When unlikely outcomes occur: the role of communication format in maintaining communicator credibility.J. Risk Res. 2019; 22: 537-554Crossref Scopus (18) Google Scholar]. One study suggests that the public perceives verbal hurricane forecasts as more reliable if they are combined with numeric probability information [33.Rosen Z.M.J. et al.Communicating probability information in hurricane forecasts: Assessing statements that forecasters use on social media and implications for public assessments of reliability.J. Operational Meteor. 2021; 9 (89–10)Google Scholar]. Similarly, receivers said they 'like' information about low-probability, high-impact industry-related environmental risks less when they are expressed using words alone than when the words are combined with point numeric values [79.Knoblauch et al.Communicating low-probability high-consequence risk, uncertainty, and expert confidence: Induced seismicity of deep geothermal energy and shale gas.Risk Anal. 2018; 38: 694-709Crossref PubMed Scopus (26) Google Scholar].Indeed, recent research shows that receivers prefer either a combination of numbers with words [33.Rosen Z.M.J. et al.Communicating probability information in hurricane forecasts: Assessing statements that forecasters use on social media and implications for public assessments of reliability.J. Operational Meteor. 2021; 9 (89–10)Google Scholar,54.Carey M. et al.Exploring health literacy and preferences for risk communication among medical oncology patients.PLoS ONE. 2018; 13e0203988Crossref Scopus (10) Google Scholar] or (numeric) precision [89.Andreadis K. et al.Imprecision and preferences in interpretation of verbal probabilities in health: a systematic review.J. Gen. Intern. Med. 2021; 36: 3820-3829Crossref PubMed Scopus (3) Google Scholar]. Receivers' preference for numbers over words is reflected in their preference for precise over imprecise numbers. For instance, when receiving information about food safety risk, people prefer numeric point values over numeric ranges [74.Lofstedt R. et al.Uncertainty analysis: results from an empirical pilot study. A research note.J. Risk Res. 2017; 24: 606-616Crossref Scopus (8) Google Scholar]. Examples of policymakers requesting uncertainty information to be provided as point numeric values rather than ranges have also been documented [109.Manski C.F. Communicating uncertainty in policy analysis.Proc. Natl. Acad. Sci. U. S. A. 2019; 116: 7634-7641Crossref PubMed Scopus (26) Google Scholar]. Together, these findings suggest that, when it really matters, both senders and receivers prefer the (precise) numeric expression of uncertainty. An individual's role in the communication process (i.e., sender/receiver) influences their preferred format for communicating uncertainty. Early research revealed a 'preference paradox', namely that, while most senders prefer to convey uncertainty verbally, most recipients prefer numeric uncertainty information [5.Wallsten T.S. et al.Preferences and reasons for communicating probabilistic information in numeric or verbal terms.Psychon. Bull. Rev. 1993; 31: 135-138Crossref Scopus (157) Google Scholar,104.Erev I. Cohen B.L. Verbal versus numerical probabilities: efficiency, biases, and the preference paradox.Organ. Behav. Hum. Decis. Process. 1990; 45: 1-18Crossref Scopus (188) Google Scholar]. Although recent research demonstrates senders' preferences for verbal probabilities in domains such as medicine [105.Juanchich M. Sirota M. Most family physicians report communicating the risks of adverse drug reactions in words (vs. numbers).Appl. Cogn. Psychol. 2020; 34: 526-534Crossref Scopus (2) Google Scholar], extreme weather forecasting [33.Rosen Z.M.J. et al.Communicating probability information in hurricane forecasts: Assessing statements that forecasters use on social media and implications for public assessments of reliability.J. Operational Meteor. 2021; 9 (89–10)Google Scholar], and intelligence analysis [106.Barnes A. Making intelligence analysis more intelligent: using numeric probabilities.Intell. Natl. Secur. 2016; 31: 327-344Crossref Scopus (37) Google Scholar, 107.Marchio J. 'If the weatherman can...': The intelligence community's struggle to express analytic uncertainty in the 1970s.Stud. Intell. 2014; 58: 31-42Google Scholar, 108.Friedman J.A. Zeckhauser R. Assessing uncertainty in intelligence.Intell. Natl. Secur. 2012; 27: 824-847Crossref Scopus (34) Google Scholar], such preferences depend on specific factors. One is the nature of the uncertainty being communicated (e.g., lack of knowledge versus variation in the outcome being predicted). Epistemic and dispositional uncertainty are more likely to be conveyed using words, whereas distributional (aleatory) uncertainty is more likely to be expressed numerically [31.Juanchich M. Sirota M. Do people really prefer verbal probabilities?.Psychol. Res. 2020; 84: 2325-2338Crossref PubMed Scopus (7) Google Scholar]. Another influential factor is the severity of the predicted outcome. For instance, physicians' preference for communicating uncertainty using verbal probabilities over the numeric 1-in-X representation is reduced when conveying the more severe adverse effects of a drug than its less severe effects [105.Juanchich M. Sirota M. Most family physicians report communicating the risks of adverse drug reactions in words (vs. numbers).Appl. Cogn. Psychol. 2020; 34: 526-534Crossref Scopus (2) Google Scholar]. Thus, the qualitative–quantitative nature of the uncertainty matches senders' preference for a qualitative versus quantitative communication format, and the potential consequence of a decision (i.e., to take a drug) leads senders to increasingly favor the numeric format. In recent years, research on the receiver side has branched out to other evaluative measures, and these do not suggest a superiority of words over numbers. For instance, there was no difference in receivers' initial perceptions of the credibility (i.e., knowledge and trustworthiness) of senders who used verbal probabilities or precise or imprecise numeric values to express uncertainty [19.Jenkins S.C. Harris A.J.L. Maintaining credibility when communicating uncertainty: the role of directionality.Think. Reason. 2020; 27: 97-123Crossref Scopus (3) Google Scholar,20.Jenkins S.C. et al.When unlikely outcomes occur: the role of communication format in maintaining communicator credibility.J. Risk Res. 2019; 22: 537-554Crossref Scopus (18) Google Scholar]. One study suggests that the public perceives verbal hurricane forecasts as more reliable if they are combined with numeric probability information [33.Rosen Z.M.J. et al.Communicating probability information in hurricane forecasts: Assessing statements that forecasters use on social media and implications for public assessments of reliability.J. Operational Meteor. 2021; 9 (89–10)Google Scholar]. Similarly, receivers said they 'like' information about low-probability, high-impact industry-related environmental risks less when they are expressed using words alone than when the words are combined with point numeric values [79.Knoblauch et al.Communicating low-probability high-co