Artificial intelligence governance, management and risk management - A look into EU AIA, standards and other frameworks from practical level - Reivo, Juho (2024)
This thesis explores the governance of artificial intelligence (AI) through various frameworks, emphasizing the necessity of comprehensive management beyond technical solutions in order to achieve effective and secure AI in a complex socio-technical world. The research posits that AI risks cannot be mitigated solely through technical means or managed through a singular strategy at a single level. The central hypothesis is that small organizations struggle to meet the demands of prominent AI frameworks, which often overlook the unique situation of these entities and particularly the challenges faced by small public sector organizations. The study highlights how practical level issues within these frameworks may threaten AI adoption. This research examines three key frameworks: the European Union Artificial Intelligence Act (EU AIA), ISO/IEC 42001:2023, and the National Institute of Standards and Technology AI Risk Management Framework (NIST RMF). The primary research question investigates practical risk management issues related to AI governance and human roles within these frameworks. Findings suggest that these frameworks are extensive and challenging for small organizations, particularly in the public sector, which often have limited IT and security resources. The study underscores the importance of selecting and calibrating governance frameworks appropriately, as inadequate frameworks render digital security efforts ineffective. Closer examination is also done in order to clarify structures of frameworks for effective governance and management of AI systems, risks and digital security aspects.