Location-based or geospatial or place-based crime predictions is based on the place or location of crime or the likelihood that in those areas a crime would be committed. In principle, such policing does not involve an assessment of a specific individual . They therefore fall outside the scope of the prohibition. Examples of location-based or geospatial predictive or place-based crime predictions
- AI-based predictive policing system provides a score of the likelihood of criminality in different areas in a city based on previous criminality rates by area and other supporting information such as street maps, to highlight elevated risk of specific types of criminalities e.g., burglaries, knife crime etc. and help law enforcement authorities determine where to deploy less or more police patrols/presence to carry out community policing to disrupt and deter criminal activity.
- A customs authority uses AI risk analytic tools to predict the likelihood of the location of narcotics or illicit goods, for example on the basis of known trafficking routes.
- A police department uses AI-driven systems to detect and locate gunshots in real time. The system employs acoustic sensors in urban areas to identify gunfire sounds and triangulate their location, providing officers with actionable data to aid detection and investigation of crimes.
It may , however, not always be evident how to distinguish location-based crime predictive systems from individual predictive systems assessing the risk of a person committing a crime . To the extent that an AI system carries out location-based predictive policing and then considers the risk score of the location as an aspect in the profiling of a person , that system should be considered person-based and in principle covered by Article 5(1) (d) AI Act , although it may f all outside the scope of the prohibition on other grounds. For example, if location-based or geospatial information or place-based information is linked to information relating to an individual ( e.g., the place of residences of a given person) and the AI system would assess the risk that that person is likely to commit crime based solely on profiling of the individual concerned, including based on his or her residence where crime is high, that system should be considered person-based.