OBJECTIVE: We conducted 2 experiments using machine learning to better understand which lineup looking behaviors postdict suspect guilt., Hypotheses: We hypothesized that (a) lineups with guilty suspects would be subject to shorter viewing duration o...
Health system data incompletely capture the social risk factors for drug overdose. This study aimed to improve the accuracy of a machine-learning algorithm to predict opioid overdose risk by integrating human services and criminal justice data with h...
Journal of environmental and public health
35685862
Environmental problem is an international problem that transcends national boundaries and develops into regional and global environmental pollution and ecological problems. Facing the increasing environmental pollution, the international community ha...
Erroneous eyewitness identification evidence is likely the leading cause of wrongful convictions. To minimize this error, scientists recommend collecting confidence. Research shows that eyewitness confidence and accuracy are strongly related when an ...
BACKGROUND: Artificial intelligence (AI) is anticipated to play a significant role in criminal trials involving citizen jurors. Prior studies have suggested that AI is not widely preferred in ethical decision-making contexts, but little research has ...
Proceedings of the National Academy of Sciences of the United States of America
40388624
Mistaken eyewitness identification is one of the leading causes of false convictions. Improving law enforcement's ability to identify correct identifications could have profound implications for criminal justice. Across two experiments, we show that ...