• 中国科学学与科技政策研究会
  • 中国科学院科技战略咨询研究院
  • 清华大学科学技术与社会研究中心
ISSN 1003-2053 CN 11-1805/G3

科学学研究 ›› 2026, Vol. 44 ›› Issue (7): 1384-1392.

• 热点议题 • 上一篇    下一篇

如何化解科技伦理争议? ———阿西洛马会议的伦理共识经验

和鸿鹏1,高旖蔚2   

  1. 1. 北京航空航天大学人文与社会科学高等研究院
    2. 中国科学院科技战略咨询研究院
  • 收稿日期:2025-05-28 修回日期:2026-01-14 出版日期:2026-07-15 发布日期:2026-07-15
  • 通讯作者: 和鸿鹏

How to Resolve Ethical Controversies in S&T?——Lessons from the Ethical Consensus of the Asilomar Conference

  • Received:2025-05-28 Revised:2026-01-14 Online:2026-07-15 Published:2026-07-15

摘要: 风险性新兴科技的伦理治理极具挑战,我国虽已出台《关于加强科技伦理治理的意见》等政策,但这些规范多适用于共识形成后的治理阶段,无法有效解决争议阶段的伦理问题。20世纪70年代的阿西洛马会议被认为是化解科技伦理争议的范例,已有研究主要将其成功归因于专家预警模式,忽视了背后的共识形成过程。在分析三种经典的共识模式及局限的基础上,指出了形成共识的难题在于应对不确定性和谁来主导共识过程。通过分析阿西洛马会议伦理共识达成的过程,研究发现,科技伦理共识的形成应由具备反思性的“猫头鹰”科学家专家主导且多方参与,制度约束有利于达成共识,最终的共识方案应具体灵活性。

关键词: 科技伦理, 阿西洛马会议, 专家预警, 共识机制

Abstract: The ethical governance of risky emerging technologies poses significant challenges. Although China has introduced policies such as the Opinions on Strengthening the Governance of Science and Technology Ethics, these norms primarily apply to post-consensus governance stages and fail to effectively address ethical issues during the controversy phase. The Asilomar Conference in the 1970s is regarded as a model for resolving ethical disputes in technology. Existing research mainly attributes its success to the expert warning model, overlooking the underlying consensus-building process.By analyzing three classic consensus models and their limitations, this study identifies the key challenges in forming consensus: addressing uncertainty and determining who should lead and coordinate the process. Through an examination of the Asilomar Conference's consensus-reaching process, the research finds that ethical consensus in technology should be expert-led yet involve multiple stakeholders. Experts should be reflective "owl" scientists, institutional constraints facilitate consensus formation, and the final consensus solution must maintain flexibility.

Key words: ethics of S&T,, Asilomar Conference,, expert warning model,, consensus mechanism

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