AI-Powered Digital Forensics

This course introduces law enforcement professionals to the dual role of Artificial Intelligence (AI) and Large Language Models (LLMs) as both investigative tools and emerging threats. It gives a comprehensive introduction to the rapidly evolving landscape of AI within modern policing environments. Participants will gain a foundational understanding of how AI works and get into its wide-ranging applications in the field of criminal justice. They will also explore how AI can enhance investigative efficiency, automate analysis, and support decision-making. Simultaneously, the course addresses how criminals exploit AI for scams, deepfakes, and other digital offenses. The course showcases practical AI tools that assist with evidence examination, pattern recognition, predictive policing, and even routine administrative functions—enabling agencies to achieve greater operational efficiency. Legal, ethical, and forensic considerations are built into each section to ensure responsible and lawful application.

Law enforcement investigators and digital forensic examiners who conduct investigations involving digital evidence. No prior AI or mathematical knowledge is required.

• Understand the foundations of artificial intelligence, including key concepts such as machine learning, deep learning, and natural language processing —without requiring technical expertise.
• Explore real-world applications of AI in law enforcement, from digital forensics and OSINT to surveillance and administrative workflows.
• Gain hands-on experience with AI tools like ChatGPT, Perplexity, Gemini, Claude and integrated AI features in existing digital forensics tools through simulated investigative exercises.
• Gain hands-on experience with AI assistants, local LLM systems, and Retrieval-Augmented Generation (RAG) systems designed for analyzing investigative datasets.
• Understand how AI agents can autonomously coordinate tasks, interact with software tools, and assist investigators in complex analytical workflows.
• Understand how AI is exploited for criminal purposes, including its use in scams, deepfakes, misinformation, and other emerging digital offenses.
• Critically assess the risks, failures, and societal impacts of AI misuse within policing contexts.
• Navigate legal and ethical considerations in AI deployment, with a focus on the practical application of the various AI compliance.
• Improve operational efficiency using AI-powered automation, low-code/no-code tools, and AI-driven document and report generation.
• Prepare for future trends in AI for law enforcement, including predictive policing, courtroom AI use, and autonomous technologies.

Upon successful completion of this course, participants will be able to:

• Define key AI concepts relevant to modern policing, including distinctions between machine learning models, data types, and AI agents
• Explain how AI systems learn and make decisions, using real-life analogies and examples accessible to non-technical professionals.
• Identify and evaluate AI tools used in investigations, such as facial recognition, automated crime mapping, and video analysis platforms.
• Use AI tools effectively for tasks like evidence analysis, translation, summarization, OSINT gathering, and workflow automation.
• Apply basic prompting techniques to generate accurate and reliable outputs from LLM-based tools (e.g., ChatGPT, Claude, DeepSeek).
• Recognize the ethical concerns and risks associated with AI in law enforcement, including algorithmic bias, privacy violations, and accountability gaps.
• Build and use simple RAG systems to analyze large investigative datasets such as case files, reports, and digital evidence collections.
• Understand the operation of AI agents capable of autonomous task planning, tool use, and multi-step reasoning in investigative environments.
• Interpret relevant sections of the EU AI Act and apply them to common investigative scenarios (e.g., lawful facial recognition use, surveillance restrictions).
• Assess the legality of AI applications in digital forensics and investigations through scenario-based learning and case study analysis.
• Utilize AI-powered office tools to automate documentation, enhance reporting, and support administrative duties efficiently.
• Collaborate on AI-assisted case resolution, demonstrating how AI can support real-time decision-making and teamwork in simulated investigations.

Participants should have experience in conducting investigations related to digital evidence and a good understanding of procedures, tools, and reporting practices. Familiarity with cybercrime cases and comfort using digital technologies is expected. While not mandatory, basic programming or scripting skills are beneficial for engaging with AI automation and workflow tools. No prior AI or mathematical knowledge is required, as all concepts are presented in an accessible, law enforcement-focused format.