Exploring and Understanding Law enforcement Applications of Artificial Intelligence
2024 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE credits
Student thesis
Abstract [en]
The purpose of this study is to explore how artificial intelligence technology is applied by law enforcement. Five law enforcement employees from Alaska and Washington, the United States, participated in semi-structured expert interviews about their professional experiences with technology based on artificial intelligence. The audio recordings of the interviews were transcribed using automatic transcription software. The transcripts were analyzed using thematic analysis which resulted in three distinct themes: (1) public perception, (2) civil rights and (3) productivity.
The theme of public perception shows that the types and amount of AI based technology they use, e.g. face recognition, is significantly dependent on the political pressure from both the public and politicians. However, the criticism seem to be mostly unwarranted as the risks and concerns that have been pointed out is at least equally problematic when a human is performing the same tasks manually.
The theme of civil rights shows that AI can potentially infringe on the civil rights of citizens. On the other hand, AI is also used to process huge amounts of internal surveillance data in order to discover officer misconducts. In the long run, this would potentially protect the civil rights of citizens by opening up new possibilities for internal investigators to hold police officers responsible for their actions.
The theme of productivity shows that application of AI have many uses that improves the effectiveness of the police officer on duty. However, AI assistance also have limitations that needs more awareness. Depending on the data that is fed to the AI, it can be more or less biased in it's results.
Place, publisher, year, edition, pages
2024.
Keywords [en]
artificial intelligence, law enforcement, expert interview, semi-structured
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:su:diva-242715OAI: oai:DiVA.org:su-242715DiVA, id: diva2:1955647
2025-04-302025-04-30