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NCJRS Abstract

The document referenced below is part of the NCJRS Library collection. To conduct further searches of the collection, visit the NCJRS Abstracts Database. See the Obtain Documents page for direction on how to access resources online, via mail, through interlibrary loans, or in a local library.

 
  NCJ Number: NCJ 240830     Find in a Library
  Title: Impact of Human–Technology Cooperation and Distributed Cognition in Forensic Science: Biasing Effects of AFIS Contextual Information on Human Experts
  Document URL: HTML 
  Author(s): Itiel E. Dror, Ph.D. ; Kasey Wertheim, M.B.A. ; Peter Fraser-Mackenzie, Ph.D. ; Jeff Walajtys, B.A.
  Journal: Journal of Forensic Sciences  Volume:57  Issue:2  Dated:March 2012  Pages:343 to 352
  Date Published: 03/2012
  Page Count: 10
  Annotation: In this paper, the researchers investigated the impact of using Automated Fingerprint Identification Systems (AFIS) on human decisionmakers.
  Abstract: Experts play a critical role in forensic decisionmaking, even when cognition is offloaded and distributed between human and machine. In this paper, the researchers investigated the impact of using Automated Fingerprint Identification Systems (AFIS) on human decisionmakers. The researchers provided 3680 AFIS lists (a total of 55,200 comparisons) to 23 latent fingerprint examiners as part of their normal casework. The researchers manipulated the position of the matching print in the AFIS list. The data showed that latent fingerprint examiners were affected by the position of the matching print in terms of false exclusions and false inconclusives. Furthermore, the data showed that false identification errors were more likely at the top of the list and that such errors occurred even when the correct match was present further down the list. These effects need to be studied and considered carefully, so as to optimize human decisionmaking when using technologies such as AFIS. Abstract published by arrangement with John Wiley & Sons.
  Main Term(s): Forensics/Forensic Sciences
  Index Term(s): Automated fingerprint processing ; Decisionmaking ; Science and Technology ; Statistical bias ; Technical experts ; NIJ grant-related documents
  Sponsoring Agency: National Institute of Justice (NIJ)
US Department of Justice
Office of Justice Programs
United States of America
  Grant Number: 2009-DN-BX-K224
  Type: Research (Applied/Empirical)
  Country: United States of America
  Language: English
   
  To cite this abstract, use the following link:
https://www.ncjrs.gov/App/Publications/abstract.aspx?ID=262911

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