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

Gavin Farrell, Eleni Adamidi+28 more|ArXiv.org|May 22, 2025

Biomedical and Engineering Education被引用 3

一句话总结

本观点分析生命科学领域的AI在信任、可重复性和可持续性方面的挑战，并提出300多个与组件对齐的OS AI建议，以指导政策和实践。

ABSTRACT

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.

研究动机与目标

• 评估快速AI应用对生命科学领域信任、重用、可重复性和环境可持续性的影响。
• 识别AI生态系统中的碎片化现象以及对开放、可持续开发实践的需求。
• 提出一套实用的Open and Sustainable AI (OSAI)建议，映射到数百个AI生态系统组件，以指导研究人员和政策制定。

提出的方法

• 呈现一组结构化的OSAI建议。
• 将建议映射到AI生态系统的300多个组件。
• 使产出与生命科学社区共识及现有努力对齐，以支持政策与路径发展。

实验结果

研究问题

• RQ1 在AI支持的生命科学中，哪些挑战削弱了信任、可重用性、可重复性和环境可持续性？
• RQ2 哪些可操作的OSAI建议可以映射到AI生态系统，以提高可持续性、开放性和透明度？
• RQ3 这些建议如何为生命科学中的AI实施提供政策与结构化路径的指引？

主要发现

• 生命科学领域的AI因可重用性和可重复性差而信任度下降。
• 这些问题对与生命科学AI部署相关的环境可持续性有影响。
• 本文提供了一组直接映射到AI生态系统300多个组件的实用OSAI建议。
• 这些建议具有可操作性、开放性与可持续性，有助于未来的政策和路径开发。
• 本工作将研究人员与AI资源连接起来，实现可持续、可重用且透明的AI实现。