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The use of statistical learning methods has recently increased within the risk assessment literature. They have primarily been used to increase accuracy and the area under the curve (AUC, i.e., discrimination). Processing approaches applied to statistical learning methods have also emerged to increase cross-cultural fairness. However, these approaches are rarely trialed in the forensic psychology discipline nor have they been trialed as an approach to increase fairness in Australia. The study included 380 Aboriginal and Torres Strait Islander and non-Aboriginal and Torres Strait Islander males assessed with the Level of Service/Risk Needs Responsivity (LS/RNR). Discrimination was assessed through the AUC, and fairness was assessed through the cross area under the curve (xAUC), error rate balance, calibration, predictive parity, and statistical parity. Logistic regression, penalized logistic regression, random forest, stochastic gradient boosting, and support vector machine algorithms using the LS/RNR risk factors were used to compare performance against the LS/RNR total risk score. The algorithms were then subjected to pre- and postprocessing approaches to see if fairness could be improved. Statistical learning methods were found to produce comparable or marginally improved AUC values. Processing approaches increased several fairness definitions (namely xAUC, error rate balance, and statistical parity) between Aboriginal and Torres Strait Islanders and non-Aboriginal and Torres Strait Islanders. The findings demonstrate that statistical learning methods may be a useful approach to increasing the discrimination and cross-cultural fairness of risk assessment instruments. However, both fairness and the use of statistical learning methods encompass significant trade-offs that need to be considered. Public Significance Statement: The purpose of this study is to investigate the use of algorithms in increasing fairness between cultural groups by utilizing a commonly used instrument that assesses the risk of reoffending. Although this preliminary study demonstrated positive findings in increasing cross-cultural fairness, various trade-offs emerged, including among different forms of fairness, that require thoughtful deliberation. [ABSTRACT FROM AUTHOR]

Police killings of Black civilians have brought unprecedented attention to racial and ethnic discrimination in the criminal justice and legal systems. However, these topics have been underexamined in the field of law-psychology, both in research and forensic-clinical practice. We discuss how a racial justice framework can provide guidance for advancing psycholegal research and forensic-clinical practice related to race, ethnicity, culture, and their intersections. A racial justice framework centers the goal of increasing fair and responsive treatment and just outcomes for the most vulnerable populations involved with the criminal justice, legal, and carceral systems and ending existing disparities. We argue that the framework should include the use of transparent nonobjectivity, in which racial justice is an explicit and acknowledged goal of research and practice that exists alongside a commitment to open and rigorous science and evidence-based practice. We then use the racial justice framework as a backdrop for discussing the articles and broader themes that appear in the special issue, which include racial biases in policing, public views of the police and use of force, expanding research on racial bias in lay judgments, understanding disparities in sentencing and corrections, and improving forensic practice. Finally, we look to the future, discussing practices and perspectives that can facilitate a racial justice approach in psycholegal research and forensic-clinical practice. Our recommendations include engaging in reflexivity and addressing positionality; expanding research questions and methods, especially qualitative and community-based participatory action research; centering and engaging with communities of color; greater emphasis on intersectionality; shifting toward structural and adaptive interventions; and greater integration of work from other fields. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Objective: Cross-cultural research into risk assessment instruments has often identified comparable levels of discrimination. However, cross-cultural fairness is rarely addressed. Therefore, this study explored the discrimination and fairness of the Level of Service/Risk, Need, Responsivity (LS/RNR) within a sample of Aboriginal and Torres Strait Islander and non-Aboriginal and Torres Strait Islander males., Hypotheses: We hypothesized that discrimination would not be significantly different for Aboriginal and Torres Strait Islander individuals and non-Aboriginal and Torres Strait Islander individuals. We further hypothesized that some fairness definitions would be unsatisfied., Method: The study included 380 males (Aboriginal and Torres Strait Islander, n = 180) from Australia. Discrimination was assessed with the area under the curve (AUC) and cross AUC (xAUC). To determine fairness, error rate balance, calibration, predictive parity, and statistical parity were used., Results: The discrimination of the LS/RNR was not statistically different (p = .61) between groups. The xAUC identified disparities (p < .001), with the LS/RNR being unable to discriminate between Aboriginal and Torres Strait Islander nonreoffenders and non-Aboriginal and Torres Strait Islander reoffenders (xAUC = .46, 95% CI [.35, .57]). Disparities among certain fairness definitions were identified, with Aboriginal and Torres Strait Islander individuals scoring higher on the LS/RNR (d = 0.52) and nonreoffenders being classified as high risk more often., Conclusions: The findings suggest that the LS/RNR may not be a cross-culturally fair risk assessment instrument for Australian individuals, and standard discrimination indices with comparable levels do not imply that a risk assessment instrument is cross-culturally fair. (PsycInfo Database Record (c) 2022 APA, all rights reserved).