## 1 Introduction  
The proliferation of artificial intelligence (AI) in the public and private sectors, particularly in the domain of law enforcement, has generated substantial controversy based on ethical concerns and media attention [1; 2; 3; 4; 5]. Specifically, law enforcement agencies in the United States use AI technologies for predictive policing, surveillance, and automation. Yet, despite the considerable growth of research examining the contributions of AI technologies to societal development and sustainability [6], no United States-based studies to date have explored police officer perspectives on the application of AI in the domain of law enforcement and its ethical considerations (see Appendix A for additional details on the literature search for studies). Moreover, law enforcement professionals and citizens hold distinctly different views about the role of police in American society and legitimacy of practices used by police to carry out their mandate [7; 8]. However, to create consensus and improve democratic accountability, there is a need to holistically evaluate police officer perspectives on the role of AI technology and its increasing deployment in policing. The traditional role of law enforcement in the 21 st century United States has been one of crime control and order maintenance [9]. Additionally, the United States Bureau of Justice Statistics expands on this description of law enforcement by stating that its agencies and employees are responsible for enforcing laws, maintaining public order, and managing public safety. To carry out their responsibilities, police officers must have the ability to uphold every aspect of their profession to promote public safety and maintain the rule of law. Doing so requires a sense of ethics and the ability to use moral decision-making to navigate the grey areas of law enforcement and complex situations involving life and death. In addition, certain ideals and character traits enable police officers to act in ways to promote public safety and uphold the rule of law. Nevertheless, as technology advances, AI can increasingly enhance and, in some instances, replace various human elements of policing processes, procedures, and operations in real-world situations [10; 11]. Police increasingly apply advances in AI technologies to enhance their capacities and capabilities to control crime and maintain order [4]. In particular, law enforcement agencies in the United States use AI-enabled algorithms and machine learning for predictive policing, surveillance, and automation of certain tasks (e.g., reading license plates). Moreover, predictive policing and big data surveillance are not novel forms of police work. Instead, from a historical context, they are simply a sociotechnical extension of what has been long practiced [10]. Unfortunately, this technology also has the potential to do considerable harm, creating an additional, albeit distinct, set of societal and moral implications for 21 st century policing. For instance, can predictive policing applications offer a more impartial approach to reducing crime than their human counterparts? These programs claim to be impersonal and objective in their application, yet they rely on humans to create the computer algorithms and train machine learning systems that underpin their function [5; 10]. Furthermore, the data driven models used in these systems may be incomplete, biased, and may potentially target underrepresented populations [10]. The lack of transparency and explainability in the operation and decision-making processes of AI technologies employed in law enforcement is also problematic [12]. How can law enforcement professionals be held accountable when experts even struggle to explain the decision-making processes that AI technologies use, compounding and creating ancillary trust issues between police and the public they serve. Additional implications that stem from the risks of incorporating AI technologies into policing include privacy and fairness concerns and accountability challenges [10; 13].