AI and Law Enforcement: The Archetypical Scenario Methodology
AI and Law Enforcement: The Archetypical Scenario Methodology
The Archetypical Scenarios Methodology, developed by CBRNE Ltd Team in the ALIGNER project, offers a robust framework for simulating and analysing real-world applications of Artificial Intelligence (AI) in law enforcement. Designed to address operational, ethical, and legal challenges, this methodology supports law enforcement agencies (LEAs) in ensuring that AI tools comply with fundamental rights and societal values. By using detailed scenario-based models, it enables LEAs to anticipate risks, enhance decision-making, and mitigate potential issues arising from AI deployment.
This methodology is particularly relevant for high-risk AI systems as defined by the EU AI Act. It focuses on understanding the interaction between AI technologies and diverse environments, providing critical insights into their practical use, potential misuse, and societal impact. The scenarios integrate multi-disciplinary expertise, combining ethical, legal, and technical considerations to create actionable and comprehensive tools for law enforcement.
At its core, the methodology employs archetypical scenarios tailored to specific law enforcement contexts, such as predictive policing, facial recognition, and surveillance. These scenarios help identify the impact of AI on privacy, non-discrimination, accountability, and other fundamental rights. The methodology also evaluates how AI systems may affect vulnerable populations and provides tools to operationalise ethical principles in daily law enforcement activities.
Key features of the methodology include the identification of ethical and legal challenges, evaluation of societal and operational implications, and support for developing governance frameworks aligned with EU regulations like GDPR and the AI Act. It provides structured mechanisms to document, assess, and refine AI practices based on real-world feedback, ensuring compliance and accountability. Its outcomes, including templates and governance models, are publicly available for adaptation and use.
More information
The methodology and supporting materials can be accessed on the ALIGNER website: ALIGNER Deliverables
