AI Forensics vs. Traditional Digital Forensics: Examining AI Systems in Litigation

Joe Sremack | CBIZ Forensic Consulting Group, LLC

Joe Sremack is an advisory partner and leader for the Forensic Data Analytics team. He has over 20 years of experience providing technology, forensics, and data analytics services to assess and advise on large-scale data, software, and enterprise systems issues.

Joe’s practice focuses on delivering advisory services relating to complex data analysis, system and business process analysis, complex data identification and management, data-intensive business process failure and underperformance issues, internal and government investigations, litigation, and regulatory compliance implementation and response. Joe develops software and assesses source code in numerous programming languages and performs data extraction and analysis involving virtually every major enterprise data system, including various ERPs and cloud-based data services. His focus on complex system and data issues includes biometric data, geospatial/GIS data, and cloud-based systems controls. Joe also routinely serves as a litigation expert witness and a regulatory fact witness on behalf of clients. He has experience working across jurisdictions and before numerous financial and trade regulatory bodies. His experience spans jurisdictions across the U.S. and in over fifty countries.

Joe provides corporate IT, finance, and legal departments and law firms with the analysis and strategies necessary to address litigation, compliance, and business risks. He advises on issues including internal investigations, FCPA and anti-corruption enforcement, OFAC and U.S. Department of Commerce sanctions, CMS compliance, class-action litigation, intellectual property litigation, labor and employment litigation, and compliance implementation and assessment, among others.

Joe is the author of Big Data Forensics and a frequent contributor to professional and academic organizations. He is consistently listed as one of the top data and technology experts by “Who’s Who Legal.” He is an active member of the Association of Certified Fraud Examiners (ACFE), Information Systems Audit and Control Association (ISACA), and the IEEE Biometrics Council.

Paul Starrett | Starrett Consulting

Paul Starrett is a seasoned expert in complex investigations and technology-focused matters, specializing in AI forensics. He founded Starrett Consulting in 1996, offering full-service investigative solutions for high-stakes cases, and Starrett Law and Advisory in 2001, where he provides legal and advisory services on AI governance and cyber risk. His firms often work together to tackle intricate challenges at the intersection of law and technology.

With 15 years of experience in investigations, Paul has handled hundreds of complex cases and spent eight years specializing in electronic discovery and information management. He is a former certified computer forensics examiner (EnCE: 2011-2024), a Certified Fraud Examiner (CFE), and has five years of experience as a software engineer in information security. His deep technical expertise, combined with his legal background, enables him to effectively address digital challenges.

Paul contributes to academia as an adjunct lecturer at Santa Clara University School of Law, teaching AI Governance in Law, Business, and Engineering, and as an adjunct professor at the University of the Pacific in their Masters in Data Science program.

He is also active in the AI Governance Certification (IAPP AIG) program and served as founding chair of the American Bar Association’s Big Data Committee from 2013 to 2020.

Paul holds a Master of Science in Predictive Analytics from Northwestern University and a Master of Laws (LL.M.) in Taxation. He is an active member of the ACFE, IAPP, and ISACA, staying at the forefront of discussions on emerging technologies and their legal implications.

I. Types of litigation involving AI and the common types of AI | 1:00pm – 1:30pm

II. AI forensics vs. traditional digital forensics | 1:30pm – 2:00pm

Break | 2:00pm – 2:10pm

III. Ethical considerations and potential bias in AI-derived evidence | 2:10pm – 2:30pm

IV. Strategies for presenting complex AI-related evidence in civil and criminal cases | 2:30pm – 2:40pm