标题： 推动科学和基于证据的人工智能政策 显示英文标题

标题： Advancing Science- and Evidence-based AI Policy

摘要： 人工智能政策应通过确保其潜在好处得到负责任的实现和广泛共享，从而促进人工智能创新。 为了实现这一目标，人工智能政策制定应重视证据：科学理解和系统分析应指导政策，政策应加速证据的生成。 但政策结果反映了制度限制、政治动态、选举压力、利益相关者利益、媒体环境、经济考虑、文化背景和领导层观点。 增加这种复杂性的是现实情况，即人工智能的广泛影响可能意味着证据和政策之间存在不一致：尽管一些证据和政策直接针对人工智能，但更多的则只是部分与人工智能相交。 设计良好的政策应整合反映科学理解而非炒作的证据。 越来越多的努力正在解决这个问题，通常是（i）为人工智能的风险及其有效缓解做出研究，或者（ii）倡导政策以应对这些风险。 本文探讨了如何优化证据与政策之间的关系，以应对日益强大的人工智能带来的机遇和挑战这一难题。 显示英文摘要

摘要： AI policy should advance AI innovation by ensuring that its potential benefits are responsibly realized and widely shared. To achieve this, AI policymaking should place a premium on evidence: Scientific understanding and systematic analysis should inform policy, and policy should accelerate evidence generation. But policy outcomes reflect institutional constraints, political dynamics, electoral pressures, stakeholder interests, media environment, economic considerations, cultural contexts, and leadership perspectives. Adding to this complexity is the reality that the broad reach of AI may mean that evidence and policy are misaligned: Although some evidence and policy squarely address AI, much more partially intersects with AI. Well-designed policy should integrate evidence that reflects scientific understanding rather than hype. An increasing number of efforts address this problem by often either (i) contributing research into the risks of AI and their effective mitigation or (ii) advocating for policy to address these risks. This paper tackles the hard problem of how to optimize the relationship between evidence and policy to address the opportunities and challenges of increasingly powerful AI.