Artificial intelligence and emerging technologies in public safety
- Submission status
- Open
- Submission deadline
Artificial intelligence (AI) is reshaping public safety by equipping law enforcement with tools for crime prevention, investigation, control and resource management. Technologies such as predictive policing algorithms, sensor networks and data analytics enhance surveillance, streamline emergency response and improve operational efficiency.
This Collection invites contributions on the application and impact of AI—including machine learning, data mining, robotics and autonomous systems—in public safety. Key areas of interest include predictive policing, sensor integration, crime pattern detection and emergency response optimisation. Submissions should explore how institutions and policymakers can anticipate and respond to the socio-legal, ethical and practical challenges posed by quantum-enabled AI.
Topics of interest include (but are not limited to):
- AI in crime prediction and prevention: Applications of machine learning for predictive policing, crime mapping, offender risk assessment and resource allocation.
- Surveillance, analytics and big data in policing: AI-driven systems such as drones, CCTV analytics, licence plate readers and integrated sensor technologies, and their role in crime detection. Use of data mining on large datasets (e.g. social media, communications) for investigative insights.
- Legal and ethical governance: Development of laws, policies and ethical frameworks for AI in law enforcement and criminal justice. Topics include human oversight, ethics boards, community consultation and international governance principles.
- Quantum computing and public safety: Implications of quantum computing for cybersecurity, encryption protocols and law enforcement capabilities. Exploration of quantum algorithms for complex problem-solving and the associated ethical considerations.
- Interdisciplinary approaches and case studies: Evaluations of pilot programmes, governance models and comparative studies across jurisdictions (e.g. EU, US, China) on AI regulation in public safety.
- Public trust and community engagement: Societal impacts of AI on trust in justice institutions. Public perceptions of algorithmic policing and strategies for transparency and accountability, such as citizen review boards and media oversight.
We invite interdisciplinary research on AI applications in public safety, including areas such as predictive policing, crime forecasting, law enforcement and governance. In the spirit of exploration, we particularly welcome empirical submissions that bridge disciplinary boundaries. These should foster collaboration across criminology, sociology, computer science, law and criminal justice policy, and address diverse analytical levels and empirical contexts.
Please note: theoretical contributions from computer science will be considered out of scope.
