Public Perceptions on Law Enforcement Use of Investigative Genetic Genealogy (IGG): Results from a Choice Experiment
Friday, October 13, 2023
9:30 AM – 10:45 AM ET
Location: Essex AB (Fourth Floor)
Investigative genetic genealogy (IGG) is a technique used by law enforcement that involves uploading crime scene DNA to a commercial genetic genealogy database to identify a genetic relative of the perpetrator and build a family tree to help identify them. IGG was first used to identify the alleged Golden State Killer in 2018 and has since been used in hundreds of investigations. Initially, those investigations focused on decades-old cold cases, but IGG is increasingly being used in active investigations, including the recent murder of four University of Idaho students. As IGG becomes more integrated into police practice, questions regarding public support of IGG and its regulation have intensified. To date, however, few studies have examined public perceptions of the use of IGG in various circumstances.
This presentation will report findings from a choice experiment embedded within a survey administered to 1,000 members of the U.S. general population. The survey aimed to understand public preferences and privacy concerns relative to interests in promoting public safety and efficient resource use. The experiment assessed the level of concern regarding police access to and use of various types of personal information. The results of the experiment will be presented in the context of ongoing efforts to regulate the practice of IGG and will highlight unresolved ethical questions.
Norah Crossnohere – Division of General Internal Medicine – Ohio State University College of Medicine; Nicola Campoamor – Department of Biomedical Informatics – Ohio State University College of Medicine; Jill Robinson – Center for Medical Ethics and Health Policy – Baylor College of Medicine; Amy McGuire – Center for Medical Ethics and Health Policy – Baylor College of Medicine; Christi Guerrini – Center for Medical Ethics and Health Policy – Baylor College of Medicine; John FP Bridges – Department of Biomedical Informatics – The Ohio State University College of Medicine