Abstract
The forensic science world contains a variety of disciplines that cover a wide range of sciences, from chemistry to physics to biology. Today, DNA is considered to be the “goldstandard” of forensics, due to the amount of information that can be collected. However, fingerprinting used to be the pinnacle of forensic science before DNA because of the uniqueness of each print and their unchanging nature. The different patterns, along with the smaller ridge details, allow examiners to categorize and differentiate between two similar fingerprints, using the standard method of ACE-V, adopted by all fingerprint examiners. Experts had believed that fingerprints were infallible and therefore could always be relied upon when used in court. This changed when the practice came under scrutiny due to various cases in which errors occurred within the fingerprint method. The process of fingerprinting is a subjective process that leaves room for potential bias to affect the examiner. The biases that can affect fingerprint examiners can be both conscious and subconscious, making them difficult to avoid. Cognitive neuroscientist Dr. Itiel Dror explains that bias is a part of the human experience and cannot be prevented, only lessened. In addition, there are many other shortcomings within the fingerprinting method that have been studied to determine how and why they occur. Through these studies, various solutions, including a blind-verification method, have been developed to solve these issues. The cases of the Madrid Bombing and Shirley McKie are two prime examples of the mistakes that can be made when bias is allowed to interfere.
Keywords
forensic science, fingerprinting, bias, cognitive bias, motivational bias
Document Type
Thesis
Year of Completion
2017
Major
Forensic Science
Advisor
Pasquale Buffolino, Ph.D.
Academic Department
Forensic Science
Recommended Citation
Kern, Jessica, "Fingerprinting: A Study in Cognitive Bias and its Effects on Latent Fingerprint Analysis" (2017). Undergraduate Honors College Theses 2016-. 32.
https://digitalcommons.liu.edu/post_honors_theses/32