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Add to Preferred Sources The AI-headset HoloLens was used to investigate how AI and mixed reality can support police decision-making in real time. Credit: Jenny Karlsson How can AI provide police officers with better support in complex situations? In an interdisciplinary collaboration, researchers in police research and computing science at Umeå University have explored the opportunities and risks associated with using AI-based interactive systems in police work.
The results show significant potential for integrating AI support into police interventions, but the researchers emphasize that human autonomy and ethical considerations must remain in focus.
The work is published in the Journal of Artificial Intelligence Research.
The research project is based on a close collaboration between police research and computing science. The project began when Juan-Carlos Nieves, a researcher at the Department of Computing Science, contacted Jonas Hansson and Anders Schogster at the Unit of Police Work.
The study used Microsoft HoloLens to investigate how trustworthy AI and mixed reality can support police decision-making in real time. The headset makes it possible to project digital information directly into the police officer's field of view. The technology can be controlled through eye movements and voice commands and can, for example, be used to identify objects and potential risks.
The researchers emphasize that collaboration between the two units has been crucial for exploring responsible AI solutions for police work while also understanding the real needs of police officers. The researchers in computing science have contributed expertise in AI, mixed reality and ethical assessment frameworks, while researchers in police work and practicing police officers have contributed operational experience and tactical knowledge.
"We are not always aware of the possibilities offered by computing science, and computing scientists are not always aware of the needs within police work. The collaboration has been a very important part of the project. You need to understand police work in order to implement change," says Hansson, a researcher at the Unit of Police Work.
A multistage study was conducted in collaboration with police education programs and law enforcement agencies in Sweden and Catalonia. Before the practical tests, participants took part in two workshops. The first workshop introduced fundamental principles of trustworthy AI, while the second workshop gave the participants hands-on experience with mixed reality and HoloLens.
A total of 39 police officers and instructors participated in the study. During a tactical exercise, the participants carried out a high-risk vehicle stop using HoloLens as a support tool. The results showed that the police officers had a very positive attitude toward the system's usefulness, ease of use and trustworthiness.
"The results were better than I expected. The police officers were very interested in the technology and saw many possibilities," says Schogster, a police officer and teacher at the Unit of Police Work.
The technology offers considerable opportunities for improved decision support and increased safety during police interventions, but it also raises ethical questions. Nieves highlights the importance of ensuring that the systems are trustworthy, transparent and ethically designed so they can be used responsibly. Potential risks include issues related to privacy, data storage and transparency, as well as the risk of algorithmic bias.
The researchers analyzed the functions according to three risk levels, ranging from low to high. The study showed that as the system becomes more automated, the ethical risks related to privacy, transparency and algorithmic bias increase. A key conclusion is that the technology must never take over the police officer's own decision-making.
"It's important that this does not become fully autonomous. It should support police officers in their decision-making, but the decisions must ultimately be made by humans," says Hansson.
The researchers also conclude that simply introducing new technology is not enough. Police officers must be trained to critically assess its implications as well.
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The researchers are now working on new project applications to continue exploring responsible AI, the relationship between digital and physical crime, and how future AI systems can be introduced into police operations.
In the long term, the researchers see a need to develop tools that can help decision-makers and the police assess risks when AI systems are procured and implemented. AI-based interactive systems for policing require carefully defined requirements to ensure that they can be used effectively while also adhering to the principle of ethics by design.
Hansson points out that traditional police work relies heavily on what police officers see, hear, feel and perceive in a given situation. The challenge is to find ways for digital information to complement these impressions without taking over.
The researchers see considerable potential for integrating this type of technology directly into basic police training, allowing future police officers to learn at an early stage how to navigate both the opportunities and vulnerabilities associated with AI tools.
Andreas Brännström et al, Trustworthy AI and Mixed Reality in Police Interventions: Challenges and Opportunities, Journal of Artificial Intelligence Research (2026). DOI: 10.1613/jair.1.19461
Swati Mestri holds a bachelor's degree in Electronics Engineering and has worked as a content editor since 2019. She has experience editing research documents across technology, health care, and materials science, and has a particular interest in technology and space. Full profile
Master's in physics with research experience. Long-time science news enthusiast. Plays key role in Science X's editorial success. Full profile
In a simulated high-risk vehicle stop, 39 police officers and instructors rated AI-supported mixed reality positively for usefulness, ease of use and trustworthiness. Greater automation increased ethical risks involving privacy, transparency and bias. Such systems should support, not replace, human decisions, with training in critical assessment.
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