Harnessing AI for Forensics

The project aims to create a framework of actionable guidelines for agency decision-makers to evaluate and administer AI effectively and responsibly in their agencies. Although AI holds promise for improving communication, increasing investigative capacity, and streamlining administrative tasks in forensic investigations, potential risks such as data privacy concerns, analysis errors, and bias must be carefully considered. Through workshop presentations, publications and other research dissemination, RTI and NIST seek to address these challenges and promote responsible AI deployment in forensic investigations.

In March, RTI and NIST plan to host a workshop in order to communicate the state of artificial intelligence, identify the unique technical challenges in forensic science and outline specific forensic science problems that can benefit from AI technology. RTI and NIST will engage with the community including experts in the use and deployment of artificial intelligence driven technologies and representatives from across the criminal justice system including FSSPs, LEAs, and the legal community. Support for this event was provided, in part, by National Institute of Standards and Technology financial assistance award 70NANB24H237. If you would like to receive updates, please sign up here!

Artificial Intelligence (AI) in Forensic Science Use Case Explorer

Using the Special Programs Office’s broad forensic science experience and the ITL’s deep expertise in AI/ML, the AI in Forensics
project team is cataloging and characterizing specific challenges facing forensic science service providers that AI-enabled systems
may solve. The catalog of use cases will describe complex real-world tasks and problems and transformative AI opportunities relevant to forensic science practitioners and researchers.

Each Use Case Comprises:
1) a user story, 2) a description of current state without AI, and 3) the opportunities that AI has to transform the current state.

Each Use Case Can:
– Spark innovation in developers of AI-enabled solutions.
– Match with AI-enabled tools currently available in the marketplace.
– Provide the context needed to develop the standards, testing, and evaluation frameworks that are necessary for responsible adoption and use.