Challenges in Shaping AI Governance in Europe: A Multi-Stakeholder Approach

Abstract

Rapid digital transformation has resulted in a paradigm shift, creating the need for shaping effective AI (artificial intelligence) governance. AI governance encompasses laws, policies, frameworks, and practices at global, regional, national, and organizational levels. Evaluating the impact of AI requires addressing ethical considerations. The need for appropriate AI governance has been highlighted by the United Nations (UN), which has access to existing normative and policy instruments, such as international standards. Global efforts in the UN system regarding AI governance are grounded in international law.AI governance takes a pragmatic approach and is delivered through an ecosystem that includes research, development, coordination, monitoring, evaluation, capacity building, and stakeholder engagement. Effective AI governance is essential in shaping the future of AI. At the European Union (EU) level, significant progress has been made, particularly with the AI Act, which is the first-ever regulation specifically on AI. The AI Act follows a risk-based approach and categorizes AI systems into four risk levels. It applies not only to EU-based providers but also to those outside the EU, particularly when their AI inputs are used within the EU.As Europe’s geopolitical influence remains crucial, particularly in light of recent developments, AI governance must be addressed from a multi-stakeholder perspective. The aim of this paper is to identify the current challenges in shaping AI governance in Europe through this approach. The study employs a qualitative, case-study methodology, analyzing the roles and needs of key stakeholders, including governments, regulatory bodies, international institutions, AI engineers, ethicists, industry associations, and end-users.