Challenges currently being addressed by the Turing’s Public Policy Programme include: to use data science and artificial intelligence to inform policy-making and track impact; to improve the provision of public services; to build ethical foundations for the use of data science and AI in policy-making; to contribute to policy that governs the use of data science and AI.
Agent-based models of police resourcing and demand – Developing proof of concept models to unpick police supply and demand interactions
Understanding how police supply responds to changing demand is crucial with ever greater pressures on the police force. Computational models offer a potential means for replicating the highly complex interdependencies that exist in police supply. Led by Turing Fellow Dan Birks, this project generated a proof-of-concept method for simulating police demand on a day-by-day basis and an agent based model of police supply. Learn more.
Computational models of police demand dynamics – Exploring how advanced simulation techniques might be used to increase understanding of demand for, and supply of, policing resources
The 21st century has seen increasingly diverse and novel responsibilities imposed upon the police service, while funding has declined. Limited policing resource has proved to be an enduring reality. The need to do more with less makes an understanding of short-, medium- and long-term demand a key priority. Without an increased understanding of the factors that drive demand, optimising police responses will continue to be a challenge. Led by Turing Fellow Dan Birks, this project aims to map the demand challenges and explore the viability of technical solutions in the form of simulation models that could support evidence-based ethical decision making. Learn more.