大型语言模型的进步应该如何影响科学实践?
Marcel Binz1,2, Stephan Alaniz2,3,4, Adina Roskies5
1Max Planck Institute for Biological Cybernetics, Tübingen, Baden-Württemberg 72076, Germany.
概括
大型语言模型 (LLM) 正在改变科学工作流程,引发了关于其整合的辩论. 科学家们对负责任的LLM使用,协作和在研究中保持人类监督提供了不同的观点.
科学领域:
- *跨学科的科学研究和方法.
- *人工智能和机器学习在科学中的应用.
- * 伦理学和科学哲学.
背景情况:
- * 越来越多地将大型语言模型 (LLM) 集成到科学工作流中.
- *关于LLM采用对科学实践的全部影响的不确定性.
- * 需要在整个社区讨论LLMs的影响.
研究的目的:
- 探索大型语言模型 (LLM) 对科学实践的多方面的影响.
- 为科学家们提供关于LLM整合的不同观点的辩论.
- 突出关于LLM采用学术界的关键考虑.
主要方法:
- 一篇论文形式,介绍了四个不同的科学家群体的观点.
- 通过对每个观点的互补回应,促进辩论.
- 综合各种关于LLM实用性,局限性和道德考虑的论点.
主要成果:
- 舒尔茨等人. 舒尔茨等人. 假设LLM的协作与人类的协作相似.
- 班德尔和其他人. 警LLM的作,倡导专门的工具.
- 马雷利等人. 马雷利等人. 强调透明的归因和负责任的LLM使用.
- 博特维尼克和格尔什曼强调人类对科学路线图的控制.
结论:
- 将法学士纳入科学中需要仔细考虑其能力和局限性.
- 负责任的采用需要明确的指导方针关于归因,透明度和人类监督.
- 持续的对话对于在科学研究中驾人工智能的不断变化的环境至关重要.
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