Modeling Evaluation Methods for Eyewitness Identification

Board Of Regents, Nshe, Obo University Of Nevada, Reno, Reno NV

Investigators

Abstract

Eyewitness identification plays an important role in administering justice in the criminal justice system. Yet, eyewitnesses make mistakes that can lead to grave legal consequences, with innocent suspects who are wrongfully convicted and guilty suspects who escape punishment and continue to harm society. Because of the complexity of eyewitness responses and associated legal consequences, it is critical to develop effective methods for evaluating eyewitness performance. This project will incorporate a modeling approach to develop effective evaluation methods for eyewitness identification. Employing a mathematical modeling approach, this project will advance and apply an expected cost model to integrate police investigation practices before, during, and after conducting an eyewitness identification. By incorporating meta-analytical data and mathematical modeling, the project’s expected cost model will provide an integrative framework for rigorously analyzing eyewitness performance and for making useful predictions under a broad range of circumstances. This research will analyze the implications of the evaluation methods commonly used in eyewitness research in order to build toward scientific consensus for analyzing eyewitness data and assessing identification procedures. This project will also develop computational and visualization tools to enhance proper use of the expected cost model and other evaluation methods. Findings will improve understanding of eyewitness performance, produce scientific evidence for optimal legal practices, and promote the scientific use of mathematical modeling approaches in eyewitness research. All of these outcomes are crucial in developing scientific understanding of eyewitness identification and improving identification practices to advance justice. This project is jointly funded by the Law and Science Program in the Directorate for Social, Behavioral & Economic Sciences (SBE) and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.