Misinformation, Information Theory, and Implications

Abstract

Misinformation has become an increasingly important topic, as concerning as sexism, racism, terrorism or climate change (Mitchell et al., 2019; Altay et al 2023). Typically defined in reference to falsehoods or misinterpretation, misinformation is blamed for political tribalization, social media misuse, fake news, and poor decision making (Hameleers 2022; Vraga, Bode & Tully 2022). More recently, the use of AI to identify and eliminate misinformation on social media and the potential for AI and Large Language Models to create misinformation has increased the urgency to better understand misinformation.

We suggest a clearer understanding of information will help improve our understanding of misinformation. Research on information in IS has progressed in recent years (Boell 2017; McKinney & Yoos 2010; McKinney & Boell 2022); yet is not well cited by misinformation studies. In addition to providing theoretical clarity, we also examine several practical implications of a theoretical understanding of misinformation.

We first define misinformation and essential terms such as facts and truth. We then describe a framework that classifies theories of information into four stances and for each explain how misinformation occurs, potential research questions, and practical suggestions for reducing its impact. We consider how misinformation is used in common language, and the implications of information theory for these common uses of misinformation.

Bio

Dr McKinney have been on the faculty at Bowling Green State University for 22 years and is currently the chair of the Accounting and IS department. Prior to that, he taught at the United States Air Force Academy where he retired from active duty. His teaching responsibilities have included Introduction to IS, ERP/SAP, security, social media, information, database, and analytics. His interest in the broader context of the business curriculum is reflected in his research publications and by the Decision Science Institute’s National Instructional Innovation Award. He publishes a Pearson Introduction to IS textbook and does research on information theory and the ambiguity of data. His main consulting work is in aviation safety, where he works for the former head of the NTSB on contracts with British Petroleum, the U.S. Forest Service, and several Air Force agencies on human factors and aviation communication issues. His Masters degree is in Operations Research from Cornell and his PhD from the University of Texas in IS. He was a Fulbright Scholar in 2022 in Salzburg, Austria, studying and collecting data on awareness of ambiguity. He has also taught a number of classes in recent years at Tiangong University in Tianjin, China, on database and security.