{"title":"On the making of crystal balls: Five lessons about simulation modeling and the organization of work","authors":"Paul M. Leonardi , DaJung Woo , William C. Barley","doi":"10.1016/j.infoandorg.2021.100339","DOIUrl":null,"url":null,"abstract":"<div><p><span>Digital models that simulate the dynamics of a system are increasingly used to make predictions about the future. Although modeling has been central to decision-making under conditions of uncertainty across many industries for many years, the COVID-19 pandemic has made the role that models play in prediction and policymaking real for millions of people around the world. Despite the fact that modeling is a process through which experts use data and statistics to make sophisticated guesses, most consumers expect a model's predictions to be like crystal balls and provide perfect information about what the future will bring. Over the last decade, we have conducted a series of in-depth, </span>longitudinal studies<span> of digital modeling across several industries. From these studies, we share five lessons we have learned about modeling that demonstrate (1) why models are indeed not crystal balls and (2) why, despite their indeterminacy, people tend to treat them as crystal balls anyway. We discuss what each of these lessons can teach us about how to respond to the predictions made by COVID-19 models as well models of other stochastic processes and events about whose futures we wish to know today.</span></p></div>","PeriodicalId":47253,"journal":{"name":"Information and Organization","volume":"31 1","pages":"Article 100339"},"PeriodicalIF":5.7000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.infoandorg.2021.100339","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information and Organization","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1471772721000051","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 7
Abstract
Digital models that simulate the dynamics of a system are increasingly used to make predictions about the future. Although modeling has been central to decision-making under conditions of uncertainty across many industries for many years, the COVID-19 pandemic has made the role that models play in prediction and policymaking real for millions of people around the world. Despite the fact that modeling is a process through which experts use data and statistics to make sophisticated guesses, most consumers expect a model's predictions to be like crystal balls and provide perfect information about what the future will bring. Over the last decade, we have conducted a series of in-depth, longitudinal studies of digital modeling across several industries. From these studies, we share five lessons we have learned about modeling that demonstrate (1) why models are indeed not crystal balls and (2) why, despite their indeterminacy, people tend to treat them as crystal balls anyway. We discuss what each of these lessons can teach us about how to respond to the predictions made by COVID-19 models as well models of other stochastic processes and events about whose futures we wish to know today.
期刊介绍:
Advances in information and communication technologies are associated with a wide and increasing range of social consequences, which are experienced by individuals, work groups, organizations, interorganizational networks, and societies at large. Information technologies are implicated in all industries and in public as well as private enterprises. Understanding the relationships between information technologies and social organization is an increasingly important and urgent social and scholarly concern in many disciplinary fields.Information and Organization seeks to publish original scholarly articles on the relationships between information technologies and social organization. It seeks a scholarly understanding that is based on empirical research and relevant theory.