Eyewitness identification: Bayesian information gain, base-rate effect equivalency curves, and reasonable suspicion.

We provide a novel Bayesian treatment of the eyewitness identification problem as it relates to various system variables, such as instruction effects, lineup presentation format, lineup-filler similarity, lineup administrator influence, and show-ups versus lineups. We describe why eyewitness identification is a natural Bayesian problem and how numerous important observations require careful consideration of base rates. Moreover, we argue that the base rate in eyewitness identification should be construed as a system variable (under the control of the justice system). We then use prior-by-posterior curves and information-gain curves to examine data obtained from a large number of published experiments. Next, we show how information-gain curves are moderated by system variables and by witness confidence and we note how information-gain curves reveal that lineups are consistently more proficient at incriminating the guilty than they are at exonerating the innocent. We then introduce a new type of analysis that we developed called base rate effect-equivalency (BREE) curves. BREE curves display how much change in the base rate is required to match the impact of any given system variable. The results indicate that even relatively modest changes to the base rate can have more impact on the reliability of eyewitness identification evidence than do the traditional system variables that have received so much attention in the literature. We note how this Bayesian analysis of eyewitness identification has implications for the question of whether there ought to be a reasonable-suspicion criterion for placing a person into the jeopardy of an identification procedure.

我们对与各种系统变量相关的目击证人辨认问题提供了一种新颖的贝叶斯处理方法，这些系统变量包括指示效应、列队呈现形式、陪衬者相似性、列队管理员的影响以及当场辨认与列队辨认的对比。我们阐述了为什么目击证人辨认是一个天然的贝叶斯问题，以及众多重要的观察结果为何需要仔细考虑基础比率。此外，我们认为目击证人辨认中的基础比率应被视为一个系统变量（在司法系统的控制之下）。然后，我们使用先验 - 后验曲线和信息增益曲线来检查从大量已发表的实验中获得的数据。接下来，我们展示了信息增益曲线是如何受到系统变量以及证人信心的调节的，并且我们注意到信息增益曲线揭示出列队在给有罪者定罪方面始终比在为无辜者开脱方面更有效。然后我们引入了一种我们开发的新型分析方法，称为基础比率效应等效（BREE）曲线。BREE曲线显示基础比率需要多大的变化才能与任何给定系统变量的影响相匹配。结果表明，即使基础比率相对较小的变化对目击证人辨认证据的可靠性产生的影响，也可能比文献中受到大量关注的传统系统变量更大。我们指出这种对目击证人辨认的贝叶斯分析对于是否应该有一个合理怀疑标准来使一个人面临辨认程序的风险这一问题有何影响。