Eyewitness Identification: Debiasing the Effects of Composites and Surveillance Images

目击者识别：消除合成和监控图像的影响

• 批准号: 0211711
• 负责人: Gary Wells
• 金额: $ 33万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-15 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0211711&HistoricalAwards=false
• 关键词: Eyewitness; Identification; Debiasing; Effects; Composites

The advent of forensic DNA testing has helped establish the fact that mistaken eyewitness identification is the largest factor contributing to jury convictions of innocent people. As a result, the system-variable approach to eyewitness identification research, which is designed to reduce mistaken identifications without harming accurate identification rates, has started to have considerable impact in the legal system. In spite of considerable progress in recent years, little is known about how the "paths" through which innocent people become suspects in lineups can bias identifications toward the suspect and how to debias these situations (reduce mistaken identifications) without lowering the chances that the witnesses will identify the actual culprit. Two important "paths" through which innocent people become suspects are the use of composite drawings and the use of surveillance images. Both paths guarantee some propensity for eyewitnesses to identify an innocent suspect if that person became a suspect based in part on the image. It is hypothesized that the dominant recommendation of eyewitness researchers for selecting lineup fillers is not sufficient to debias lineups when either the image-similarity or the composite-similarity paths are operating. This research will test various debiasing techniques. The methodology will use films depicting a terrorist event (12 versions involving 12 different culprits) that will be shown to over 2000 people individually who will then be asked to identify the terrorist from a lineup and state their certainty. Innocent suspects will substitute for the terrorist in half of the lineups. Innocent suspects will be selected based on verbal descriptions, composite drawings, or surveillance images. Debiasing techniques will include methods of selecting lineup fillers, the use of the sequential lineup, and the use of a new technique called the phantom lineup. In addition to traditional analyses, Bayesian information-gain analyses, which assess both the incriminating and exonerating value of a give lineup procedure, will be used to assess the effectiveness of the debiasing procedures. The results of this work will help clarify eyewitness scientists' basic understanding of the processes of false recognition and false certainty. In addition, the results will inform law enforcement about procedures that can be used to create unbiased and informative lineups under conditions in which surveillance images and composite drawings could otherwise bias those results.

法医DNA检测的出现帮助证实了这样一个事实：错误的目击者身份是导致陪审团对无辜者定罪的最大因素。因此，旨在减少错误识别而不损害准确识别率的目击者识别研究的系统变量方法已开始在法律体系中产生相当大的影响。尽管近年来取得了相当大的进展，但人们对无辜者在队列中成为嫌疑人的“路径”如何使对嫌疑人的识别产生偏见以及如何在不降低目击者识别真正罪犯的机会的情况下消除这些情况（减少错误识别）知之甚少。无辜者成为嫌疑人的两个重要“途径”是使用合成绘图和使用监控图像。这两条路径都保证了目击者在一定程度上根据图像识别无辜嫌疑人的倾向，如果该人成为嫌疑人的话。据推测，当图像相似性或复合相似性路径运行时，目击者研究人员对于选择阵容填充物的主要建议不足以消除阵容偏差。这项研究将测试各种去偏技术。该方法将使用描述恐怖事件的电影（12 个版本涉及 12 名不同的罪犯），这些电影将分别向 2000 多人放映，然后要求他们从阵容中识别出恐怖分子并陈述他们的确定性。无辜嫌疑人将取代恐怖分子占据一半的阵容。将根据口头描述、合成图画或监控图像来选择无辜嫌疑人。去偏技术将包括选择阵容填充物的方法、顺序阵容的使用以及称为幻影阵容的新技术的使用。除了传统分析之外，贝叶斯信息增益分析（评估给定阵容程序的有罪和无罪价值）将用于评估去偏程序的有效性。这项工作的结果将有助于澄清目击科学家对错误识别和错误确定过程的基本理解。此外，结果还将告知执法部门有关程序，这些程序可用于在监视图像和合成绘图可能使这些结果产生偏差的情况下创建公正且信息丰富的阵容。