AI for Science中的机器幻觉:生成逻辑、伦理隐忧与治理模式OACHSSCD

The domain of artificial intelligence-driven scientific research,otherwise termed AI for Science,is emerging as a significant application domain for artificial intelligence.A plethora of significant scientific discoveries pertaining to AI for Science have been made on a global scale.These discoveries have demonstrated the ability of AI to accelerate scientific progress and its immense developmental potential.However,machine hallucinations within AI for Science are emerging as a critical constraint affecting the realization of its immense potential and sustainable development.These hallucinations possess inherent generative logic,including cognitive illusions embedded with data biases,structural fallacies solidified by feedback mechanisms,and vulnerabilities in reasoning equilibrium.Concurrently,machine hallucinations in AI for Science give rise to numerous ethical concerns,including the distortion of scientific research conclusions,the deconstruction of scientific rigour,and the entrenchment of theoretical inertia.In order to align AI for Science with human values and ensure it better serves scientific research,the exploration of collaborative governance models for machine illusions in AI for Science is now required.The following three-pronged approach is proposed,The establishment of logical consistency verification mechanisms to advance technical de-illusioning;The reshaping of verifiable AI scientific systems to build trustworthy institutional frameworks;The development of ethical mechanisms for scientific innovation to clarify societal responsibility;The construction of co-governance institutions to promote scientific autonomy within a global perspective.