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Artificial Intelligence in the Criminal Justice System.  Demystifying artificial intelligence, its applications, and potential risks 

By James Redden; Molly O'Donovan Dix

This technology brief is the first in a four-part series that explores artificial intelligence (AI) applications within the criminal justice system. This first brief frames AI, defines common AI terms, and offers a mental model for identifying AI use cases within the criminal justice system. While this brief provides examples of how AI might bring significant benefit to the criminal justice system, it also highlights risks that decision makers should consider when developing or deploying AI tools. Additional briefs provide greater consideration of AI in law enforcement, the criminal courts system, and corrections.   

  Key Takeaways ¡ AI will transform our personal, industrial, commercial, and civil realities in the years to come— enabling and challenging individuals involved in the justice system as well as in criminal activity. ¡ AI tools have the potential to improve efficiency, reduce costs, and expand capabilities across many criminal justice use cases; however, technical feasibility and operational realities need to be considered. ¡ AI systems carry inherent risk that decision makers need to understand. For example, AI technologies raise ethical and civil liberties questions that the criminal justice system and society at large will have to wrestle with in the years ahead. AI will bring changes to nearly every industry over the next decade. In fact, AI is already impacting our daily lives and is being built into the background of many of our daily activities—from facial recognition technologies that unlock our smartphones, to algorithms that recommend movies we might like, to virtual chatbots that handle our customer service inquiries. Forthe criminal justice system, AI presents opportunities along with significant risks. AI tools have the potential to improve efficiency, reduce costs, and expand capabilities across many criminal justice use cases. Yet many criminal justice leaders have misconceptions about the capabilities and the level of investment required to create or deploy AI solutions for specific use cases

Research Triangle Park, NC:RTI International.,   . 

2020. 10p.

Change to Federal Definition of Hemp and Implications for Federal Enforcement

By Lisa N. Sacco, Zachary T. Neuhofer, Hassan Z. Sheikh

Change to Federal Definition of Hemp and Implications for Federal Enforcement

December 3, 2025 (IN12620)

On November 12, 2025, Congress and President Trump enacted a full-year FY2026 Agriculture appropriations act (P.L. 119-37, Division B), which contained a provision that reimposes federal controls over certain hemp products.

Both marijuana and hemp are varieties of the cannabis plant, and until 2018, hemp was considered to be marijuana as defined under the Controlled Substances Act (CSA). From 1970 until 2018, the federal government's definition of marijuana included hemp and its derivatives, and widespread hemp production was generally prohibited. Under the Agriculture Improvement Act of 2018 (2018 farm bill; P.L. 115-334), Congress amended the CSA definition of marijuana to reflect the differences in the chemical and psychoactive properties between hemp and marijuana, but it referred only to the level of delta-9 tetrahydrocannabinol (THC) to distinguish between them and not the other cannabinoids found within the cannabis plant. Some interpreted this definition of marijuana and the new federal definition of hemp to mean that products containing less than 0.3% delta-9 THC in addition to other psychoactive compounds would not be considered marijuana and would legally be considered hemp—the so-called farm bill loophole

Washington, DC: Congressional Research Service, 2025. 3p.