Skip to content

Shining a Light on Black Box Studies

Primary Author: Kori Khan
Secondary Authors: Alicia Carriquiry
Type: Webinar

This CSAFE webinar was held on April 22, 2022.

Presenters:
Dr. Kori Khan
Iowa State University

Dr. Alicia Carriquiry
Iowa State University

Presentation Description:
The American criminal justice system heavily relies on conclusions reached by the forensic science community. In the last ten years, there has been an increased interest in assessing the validity of the methods used to reach such conclusions. For pattern comparison disciplines, however, this can be difficult because the methods employed rely on visual examinations and subjective determinations. Recently, “black box studies” have been put forward as the gold standard for estimating the rate of errors a discipline makes to assist judges in assessing the validity and admissibility of the analysis of forensic evidence. These studies have since been conducted for various disciplines and their findings are used by judges across the country to justify the admission of forensic evidence testimony. These black box studies suffer from flawed experimental designs and inappropriate statistical analyses. We show that these limitations likely underestimate error rates and preclude researchers from making conclusions about a discipline’s error rates. With a view to future studies, we propose minimal statistical criteria for black box studies and describe some of the data that need to be available to plan and implement such studies.

Webinar Recording:

Read more about the study in this post

Related Resources

Is it a True Match? Top k correlations in a database search

Is it a True Match? Top k correlations in a database search

This presentation is from the 76th Annual Conference of the American Academy of Forensic Sciences (AAFS), Denver, Colorado, February 19-24, 2024.
Graph-Theoretic Techniques for Forensic Image Comparisons

Graph-Theoretic Techniques for Forensic Image Comparisons

This presentation is from the 76th Annual Conference of the American Academy of Forensic Sciences (AAFS), Denver, Colorado, February 19-24, 2024.
Presumption of Innocence, Probable Cause, and Prior Probability—Bayes Meets Due Process

Presumption of Innocence, Probable Cause, and Prior Probability—Bayes Meets Due Process

This presentation is from the 76th Annual Conference of the American Academy of Forensic Sciences (AAFS), Denver, Colorado, February 19-24, 2024.
Demonstrative Evidence and the Use of Algorithms in Jury Trials

Demonstrative Evidence and the Use of Algorithms in Jury Trials

We investigate how the use of bullet comparison algorithms and demonstrative evidence may affect juror perceptions of reliability, credibility, and understanding of expert witnesses and presented evidence. The use of…