Algorithms, human decision-making and predictive policing

Given their technical sophistication, it is easy to overlook the human choices that underpin predictive policing algorithms and, importantly, the basic structures of decision theory that it embeds. To make a problem amenable to algorithmic computation, the problem must be transformed, often metaphorically, and the problem space delineated. Problem space delineation is one pathway through which human decision-making processes may enter and shape algorithm design, construction, and application. We use decision theory, including behavioural economics, to highlight the choices embedded within this problem space delineation and raise awareness as to the potential effect of these choices on the outcomes of applications of predictive policing algorithms. We highlight the importance of balancing the technical-formal evolution of predictive policing algorithms with lockstep advancement in awareness and application of decision theory. Such awareness may help to mitigate some of the recognised weaknesses with this emerging technology and, also, help to identify those aspects of human decision-making that can be augmented positively by algorithms