Abstract
Excerpted From: Jack Glaser, Implicit Bias, Science, and the Racial Justice Act, 29 Berkeley Journal of Criminal Law 17 (2024) (31 Footnotes) (Full Document)
In attempts to explain persistent racial disparities in important outcomes and conditions, including in the realm of criminal justice, much attention has been given to implicit bias. California's Racial Justice Act (RJA) explicitly references this phenomenon, explaining that “[i]mplicit bias, although often unintentional and unconscious, may inject racism and unfairness into proceedings similar to intentional bias.” The statute continues, “It is the intent of the Legislature to ensure that race plays no role at all in seeking or obtaining convictions or in sentencing.” As an expert on the relationship between implicit bias and criminal justice, I have been approached by defense attorneys and organizations asking about whether and how implicit bias can be incorporated in RJA claims.
In this Article, I will first provide a description of the science behind implicit bias to inform consideration of its applicability to RJA. Next, I arrive at the general conclusion that implicit bias, as defined and measured in the ample and rigorous body of psychological science, would be difficult and problematic to utilize in criminal defense. This is because its defining feature--implicitness--renders it unobservable in individual instances. No doubt, implicit bias is a cause of disparate treatment, but it is not an observable indicator of it. Nevertheless, there may be some hope for applying the science of implicit bias to individual RJA cases. By examining aggregate data on the ambient levels of implicit bias within specific jurisdictions, one can assess the likelihood of racially biased application of the law. Finally, I will comment on the use of “statistical significance” in the RJA; how the application of the standard as conventionally employed in science could undermine justice; and how further modification to the California Penal Code in AB 256, which extends the RJA retroactively, likely addresses the problem if employed effectually.
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The RJA presents opportunities to remedy the discriminatory impacts of group-based biases on criminal justice outcomes at least partially. This is, promisingly, a systemic response to a systemic problem--a problem at the heart of the American democratic experiment. References in the RJA to implicit bias rightly point to the challenges presented by racial stereotypes and prejudices that are deeply embedded in our collective culture and, consequently and recursively, in our individual nonconscious memory and information processing systems. However, as with any new law, the legislative intent will be the object of interpretation as criminal justice actors and stakeholders seek to implement the law. Attempts to bring evidence of the operation of implicit bias in any individual case will likely run into the problem that implicit bias is, by definition, unobservable even as its effects are very real. Scientific advances allowing for strong inferences of the presence, operation, and impact of implicit bias lead to the conclusion that it is pervasive, but individual level implicit bias scores are inherently noisy and therefore of limited reliability. Compounding this challenge is the reference to a standard of “significance,” which, if the careful corrective language of AB 256 is not heeded, could lead to the assumption of a standard of “statistical significance,” which is one that science has long set very high, leaving little room for error when applied correctly. Legal actors seeking to apply the RJA meaningfully, effectively, and fairly will do well to invoke implicit bias as an important contextual factor illustrating the prevalence of, in particular, race-crime stereotypes. In turn, this understanding of the ubiquity and uncontrollability of implicit biases should both motivate efforts to improve impartiality and inform understanding of ex ante probability that any given criminal justice decision or action is racially impartial.
Jack Glaser, PhD, is a social psychologist and a Professor at the Goldman School of Public Policy at the University of California, Berkeley.
