The use of artificial intelligence in criminal justice systems could be surpassing governments\u2019 pace of establishing adequate policies and guardrails to ensure the tech is implemented accurately and responsibly, a recent report says.\u00a0<\/p>\n
As the gap grows between the deployment and regulation of AI solutions in state and local courts, police departments, correctional facilities and other services, there is a critical need for policymakers and officials to better reign in applications that could significantly impact residents\u2019 lives and liberties, according to a report<\/a> released last month from the Council on Criminal Justice and RAND.\u00a0<\/p>\n \u201cThe main thing is that governance is required immediately \u2026 but yet people are adopting these technologies faster than the conversations have developed,\u201d said Kristin Warren, an engineer at RAND who researches national security and equitable policies. In doing so, she said, policymakers must consider, \u201cWhat are the real human costs here?\u201d\u00a0<\/p>\n Such costs have become reality for people like Angela Lipps, now 50, who was jailed last year for a crime in a state she\u2019d never visited. Lipps, of Elizabethton, Tennessee, was arrested<\/a> last July after a facial recognition system incorrectly identified her as the suspect behind bank fraud in Fargo, North Dakota.\u00a0<\/p>\n Lipps was arrested by the United States Marshals at her home and served jail time in Tennessee and North Dakota until December, losing her rental home, Social Security income, health insurance and coverage, her pet dog and other personal affects, according to Lipps\u2019s GoFundMe webpage<\/a>. The charges against her were eventually dropped when evidence showed she was in Tennessee at the time of the crime.\u00a0<\/p>\n Lipps is pursuing civil litigation for her wrongful arrest, according to A&E<\/a>. Reports of other issues that disrupt criminal justice proceedings due to AI have emerged in recent years, including legal citations increasingly containing hallucinations<\/a> or other errors.\u00a0<\/p>\n For policymakers and decision-makers, \u201cthe primary opportunity here lies in constructing accountability infrastructure. This could include developing audit frameworks, establishing transparency requirements and creating mechanisms for challenge and redress,\u201d the report states.\u00a0<\/p>\n Researchers also found that, based on academic literature, policy documents, practitioner reports and other sources, AI adoption in the criminal justice setting has largely concentrated around more high-stakes use cases, such as pretrial, sentencing and law enforcement decisions. Those findings present \u201can under-explored opportunity of repurposing AI capabilities to strengthen oversight and accountability, rather than expand decision-making systems,\u201d the report reads.\u00a0<\/p>\n Indeed, one of several recommendations from the report for criminal justice leaders is to develop and establish specific rules and standards for using AI in criminal justice proceedings, Warren said. \u00a0<\/p>\n \u201cPolicymakers should establish explicit governance protections prohibiting algorithmic determinations of guilt, sentencing, prosecutorial charging and other liberty deprivations,\u201d the report states. \u201cCourts should be required to disclose in judicial findings when AI recommendations inform outcomes, and defense counsel should have access to information about all AI tools used in their clients\u2019 cases.\u201d<\/p>\n For example, California lawmakers this year are considering a bill <\/a>that, if passed, would establish guardrails that aim to protect confidential information from being used in AI systems, make cite-checking a nondelegable task and prevent arbitrators from delegating decision-related tasks to AI.\u00a0\u00a0<\/p>\n The Indiana Supreme Court AI Governance Committee developed guidance<\/a> for courts to navigate the adoption and implementation of the technology late last year. The guidance<\/a> suggests that judges in the state consider how to transparently use AI tools in court processes, how to ensure any AI tool has a human verification step and how to hold vendors accountable to their AI services and solutions.\u00a0<\/p>\n