Public's views of risk assessment algorithms and pretrial decision making

Abstract

Risk assessment algorithms are increasingly-and controversially-being used to inform whether criminal defendants are released or held in custody prior to their adjudications. A representative sample of Californians (n = 420)-the most recent state to consider eliminating cash bail and adopt an algorithmic approach to pretrial detention-was used to assess public knowledge and general support for the new law. The sample evidenced limited awareness of bail reform, was mixed in support of change to the existing system, and believed that an algorithm would augment rather than decrease racial and socioeconomic disparities in the criminal justice system. In terms of actually implementing a risk assessment algorithm for the purpose of pretrial decision making, it is ultimately a human decision maker who must apply a decision threshold and determine whether a given risk level is sufficient to occasion a particular course of action (e.g., deny pretrial release). The sample was also queried about their pretrial decision thresholds. The average respondent's decision threshold for "low risk" (or pretrial release) was 33%, indicating a 33% or less likelihood of failing to reappear or committing a new crime was tolerable, and 60% for "high risk" (or confinement), indicating a likelihood of 60% or greater of failing to reappear or committing a new crime was acceptable to deny a defendant release. Incorporating the public's values into the decision-making process is likely to promote the legitimacy of the use of risk assessment algorithms in the criminal justice system.