Artificial Intelligence in Law Enforcement Surveillance: Citizen Perspectives, Resistance and Counterstrategies

Artificial Intelligence (AI) has rapidly become a key component in the realm of security and law enforcement, offering unprecedented capabilities for enhancing safety, operational efficiency and crime prevention. However, the integration of AI into these fields has raised significant concerns among citizens, particularly around privacy, ethical oversight, and the potential for misuse. As AI-driven surveillance becomes more pervasive, it is crucial to understand the varied perspectives of citizens and the strategies they employ to navigate and resist these technologies. Citizens' voices are essential in shaping ethical and responsible AI policies, as they reflect the concerns, values, and lived experiences of those directly affected by surveillance practices. Including these perspectives ensures that AI deployment aligns with public expectations, enhances transparency, and fosters greater trust between law enforcement agencies and the communities they serve. This thesis explores citizens' reactions to the use of AI in law enforcement, focusing on their responses, resistance, and counterstrategies. This research achieves its aims and objectives through three studies, independently designed by embedding innovative mixed methods ranging from in-depth interviews to online experiments and privacy walks, this research provides new empirical insights by exploring the nuanced ways in which citizens engage with AI surveillance, articulate their concerns, and develop strategies to navigate or resist its impact. The findings reveal a nuanced landscape of citizen perspectives: while some participants recognize the potential benefits of AI in enhancing security, many express deep concerns about the implications for privacy, data ownership, and the broader social impact of AI surveillance. The study identifies a range of viewpoints, from cautious acceptance to active resistance, highlighting the specific counterstrategies that citizens adopt to protect themselves from what they perceive as intrusive surveillance practices. Briefly said, this thesis offers both theoretical insights and practical recommendations aimed at bridging the gap between citizens, law enforcement, and technology developers. It emphasizes the importance of transparency, the need for robust ethical frameworks, and the value of ongoing dialogue to ensure that AI technologies are deployed in ways that respect public trust and protect civil liberties, while still enhancing security.