负责任创新视域下人工智能赋能脑机接口的伦理治理

Ethical Governance of AI-Enabled Brain-Computer Interfaces from the Perspective of Responsible Innovation

摘要: 人工智能技术的嵌入显著提升了脑机接口在神经信号采集、解码、反馈与个体适配方面的能力，推动脑机接口由实验室研究加速走向临床康复、智能交互和人体功能修复等应用场景。然而，人工智能赋能并非单纯的技术增效过程，也使脑机接口风险呈现出复合化、隐蔽化和扩散化特征。算法黑箱可能导致神经信号误判，意识解析可能冲击主体能动性，神经数据处理可能引发隐私泄露与数据滥用，责任归属和权属边界也因“人脑–算法–设备”共同作用而趋于复杂。负责任创新理论强调在科技创新全过程中嵌入预测、反思、协商与回应机制，为人工智能赋能脑机接口的伦理治理提供了重要分析框架。基于此，应从前瞻性风险评估、算法透明与可审计、神经数据全生命周期保护、多主体协同审查和责任规则完善等方面构建治理体系，以推动人工智能赋能脑机接口技术安全、规范、可持续发展。

Abstract: The embedding of artificial intelligence technologies has significantly enhanced the capabilities of brain-computer interfaces (BCIs) in neural signal acquisition, decoding, feedback and individual adaptation, accelerating the transition of BCIs from laboratory-based research to application scenarios including clinical rehabilitation, intelligent interaction and human-body function restoration. Nevertheless, AI-enablement is not merely a process of technical efficiency improvement; it also renders risks associated with BCI compound, covert and diffuse. The algorithmic black box may give rise to misinterpretation of neural signals; consciousness decoding may challenge subject agency; neural data processing may trigger privacy breaches and data misuse. Furthermore, the attribution of responsibility and demarcation of ownership boundaries have grown complicated due to the joint interaction among the human brain, algorithms and devices. Emphasizing the integration of foresight-oriented prediction, reflection, deliberation and responsiveness throughout the whole process of scientific and technological innovation, the theory of Responsible Innovation provides a vital analytical framework for the ethical governance of AI-enabled brain-computer interfaces. Accordingly, a governance system should be constructed from the perspectives of proactive risk assessment, algorithmic transparency and auditability, full-life-cycle protection of neural data, multi-agent collaborative review and improvement of liability rules, so as to promote the safe, standardized and sustainable development of AI-enabled BCI technologies.