欧洲专家通过德尔菲法探讨AI治理未来，发现落地执行比技术细节更重要
Governing rapid technological change: Policy Delphi on the future of European AI governance
- 用两轮德尔菲法收集政策制定者、研究者等专家意见
- 共识：监管实效依赖执行而非条款细节，且理想政策难落地
- 适合关注政策设计与技术演进关系的研究者和决策者
人工智能的快速进步给政策制定者带来独特挑战。本文采用两轮政策德尔菲法，于2024年中对欧洲政策制定者、研究人员及非政府组织展开调查，旨在分析欧洲AI治理中的关键矛盾，并评估德尔菲法在前瞻性科技治理中的作用。研究揭示了多方视角下的治理分歧，达成共识：未来具有韧性的AI监管更依赖实际执行与执法能力，而非技术细节或覆盖范围。此外，研究识别出‘理想性-可行性’差距：如公民广泛参与等理想政策方向虽被普遍认可，但被认为实现概率较低。这凸显了理想监管愿景与技术快速迭代下监管滞后之间的张力。
原文摘要 · Abstract (English)
The rapid advancements in artificial intelligence (AI) present unique challenges for policymakers that seek to govern the technology. In this context, the Delphi method has become an established way to identify consensus and disagreement on emerging technological issues among experts in the field of futures studies and foresight. The aim of this article is twofold: first, it examines key tensions experts see in the development of AI governance in Europe, and second, it reflects on the Delphi method's capacity to inform anticipatory governance of emerging technologies like AI based on these insights. The analysis is based on the results of a two-round Policy Delphi study on the future of AI governance with European policymakers, researchers and NGOs, conducted in mid-2024. The Policy Delphi proved useful in revealing diverse perspectives on European AI governance, drawing out a consensus that future-proof AI regulation will likely depend more on practical implementation and enforcement of legislation than on its technical specifics or scope. Furthermore, the study identified a desirability-probability gap in AI governance: desirable policy directions, like greater citizen participation, were perceived as less probable and feasible. This highlights a tension between desirable regulatory oversight and the practical difficulty for regulation to keep up with technological change.
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