arXiv:2505.16619cs.AIq-bio.OT2025-05被引 9

推动生命科学AI开源可持续发展,解决可复现性与生态碎片化问题

Open and Sustainable AI: challenges, opportunities and the road ahead in the life sciences (October 2025 -- Version 2)

  • 提出面向生命科学的开源可持续AI实践框架
  • 关联300多个AI组件,构建可落地的实施路径
  • 适合科研人员、政策制定者及跨领域协作团队参考

人工智能在生命科学领域取得突破性进展,显著提升生物信息解析能力,应用与成果不断涌现。为最大化对AI研究投入的回报并加速发展,亟需应对因快速采用AI方法而加剧的长期科研挑战。本文分析了当前AI研究成果可信度下降的问题,主要源于可复用性差与可重现性不足,并揭示其对环境可持续性的负面影响。同时指出,当前AI生态系统存在组件分散、缺乏指导路径等问题。为此,本观点提出一套直接映射超过300个生态组件的开源可持续AI(OSAI)实践建议,连接研究者与相关资源,助力实现可重复、可透明、可持续的AI应用。基于生命科学界共识并与现有工作协同,该成果旨在支持未来政策制定和结构化实施路径的建立。

原文摘要 · Abstract (English)

Artificial intelligence (AI) has recently seen transformative breakthroughs in the life sciences, expanding possibilities for researchers to interpret biological information at an unprecedented capacity, with novel applications and advances being made almost daily. In order to maximise return on the growing investments in AI-based life science research and accelerate this progress, it has become urgent to address the exacerbation of long-standing research challenges arising from the rapid adoption of AI methods. We review the increased erosion of trust in AI research outputs, driven by the issues of poor reusability and reproducibility, and highlight their consequent impact on environmental sustainability. Furthermore, we discuss the fragmented components of the AI ecosystem and lack of guiding pathways to best support Open and Sustainable AI (OSAI) model development. In response, this perspective introduces a practical set of OSAI recommendations directly mapped to over 300 components of the AI ecosystem. Our work connects researchers with relevant AI resources, facilitating the implementation of sustainable, reusable and transparent AI. Built upon life science community consensus and aligned to existing efforts, the outputs of this perspective are designed to aid the future development of policy and structured pathways for guiding AI implementation.

AI伦理开源科学生命科学可持续计算

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