{"title":"动态决策环境中的不确定性信息传递","authors":"Gala Gulacsik, S. Joslyn, J. Robinson, Chao Qin","doi":"10.1175/wcas-d-21-0186.1","DOIUrl":null,"url":null,"abstract":"\nThe likelihood of threatening events is often simplified for members of the public and presented as risk categories such as the “watches” and “warnings” currently issued by National Weather Service in the United States. However, research (e.g., Joslyn and LeClerc) suggests that explicit numeric uncertainty information—for example, 30%—improves people’s understanding as well as their decisions. Whether this benefit extends to dynamic situations in which users must process multiple forecast updates is as yet unknown. It may be that other likelihood expressions, such as color coding, are required under those circumstances. The experimental study reported here compared the effect of the categorical expressions “watches” and “warnings” with both color-coded and numeric percent chance expressions of the likelihood of a tornado in a situation with multiple updates. Participants decided whether and when to take shelter to protect themselves from a tornado on each of 40 trials, each with seven updated tornado forecasts. Understanding, decision quality, and trust were highest in conditions that provided percent chance information. Color-coded likelihood information inspired the least trust and led to the greatest overestimation of likelihood and confusion with severity information of all expressions.","PeriodicalId":48971,"journal":{"name":"Weather Climate and Society","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Communicating Uncertainty Information in a Dynamic Decision Environment\",\"authors\":\"Gala Gulacsik, S. Joslyn, J. Robinson, Chao Qin\",\"doi\":\"10.1175/wcas-d-21-0186.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nThe likelihood of threatening events is often simplified for members of the public and presented as risk categories such as the “watches” and “warnings” currently issued by National Weather Service in the United States. However, research (e.g., Joslyn and LeClerc) suggests that explicit numeric uncertainty information—for example, 30%—improves people’s understanding as well as their decisions. Whether this benefit extends to dynamic situations in which users must process multiple forecast updates is as yet unknown. It may be that other likelihood expressions, such as color coding, are required under those circumstances. The experimental study reported here compared the effect of the categorical expressions “watches” and “warnings” with both color-coded and numeric percent chance expressions of the likelihood of a tornado in a situation with multiple updates. Participants decided whether and when to take shelter to protect themselves from a tornado on each of 40 trials, each with seven updated tornado forecasts. Understanding, decision quality, and trust were highest in conditions that provided percent chance information. Color-coded likelihood information inspired the least trust and led to the greatest overestimation of likelihood and confusion with severity information of all expressions.\",\"PeriodicalId\":48971,\"journal\":{\"name\":\"Weather Climate and Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2022-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Weather Climate and Society\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1175/wcas-d-21-0186.1\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Weather Climate and Society","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/wcas-d-21-0186.1","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
Communicating Uncertainty Information in a Dynamic Decision Environment
The likelihood of threatening events is often simplified for members of the public and presented as risk categories such as the “watches” and “warnings” currently issued by National Weather Service in the United States. However, research (e.g., Joslyn and LeClerc) suggests that explicit numeric uncertainty information—for example, 30%—improves people’s understanding as well as their decisions. Whether this benefit extends to dynamic situations in which users must process multiple forecast updates is as yet unknown. It may be that other likelihood expressions, such as color coding, are required under those circumstances. The experimental study reported here compared the effect of the categorical expressions “watches” and “warnings” with both color-coded and numeric percent chance expressions of the likelihood of a tornado in a situation with multiple updates. Participants decided whether and when to take shelter to protect themselves from a tornado on each of 40 trials, each with seven updated tornado forecasts. Understanding, decision quality, and trust were highest in conditions that provided percent chance information. Color-coded likelihood information inspired the least trust and led to the greatest overestimation of likelihood and confusion with severity information of all expressions.
期刊介绍:
Weather, Climate, and Society (WCAS) publishes research that encompasses economics, policy analysis, political science, history, and institutional, social, and behavioral scholarship relating to weather and climate, including climate change. Contributions must include original social science research, evidence-based analysis, and relevance to the interactions of weather and climate with society.