Designing Artificial Intelligence (AI)-based interactive systems for law enforcement poses unique socio-technical and ethical challenges, particularly when such systems must support real-time decision-making in dynamic, high-stakes environments. Despite their potential, AI-supported interactive systems in policing require carefully elicited domain-specific requirements to ensure effective use while being Ethical by Design. However, methods for such requirement elicitation remain limited. This paper presents a participatory approach for identifying the requirements of AI-driven Mixed Reality (MR) systems in law enforcement contexts. The introduced methodology builds on two of our previous EU projects: the Erasmus+ project "Trustworthy AI", which provided educational material to teach key principles of Trustworthy AI, and AI4EU, which developed an abbreviated assessment tool for evaluating AI systems. In collaboration with police education units and law enforcement agencies in Sweden and Catalonia, we conducted a multi-phase study involving two preparatory workshops—one focused on educating participants in Trustworthy AI, and another involving hands-on MR use in standard police training scenarios. This reflects the view that it is not enough to simply ask people about new technologies—they must also be educated to critically assess their implications. After the workshops, we collected structured feedback using quantitative and qualitative methods. To analyze risk levels of the elicited requirements, we applied the AI4EU-based assessment tool. Our findings highlight key challenges and opportunities for designing AI-based systems with MR interfaces that enhance decision-making in real-time police operations while ensuring transparency, safety, and human oversight.