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科学领域:

  • 生物医学研究生物医学研究
  • 人工智能的人工智能
  • 科学合作科学合作

背景情况:

  • 大型语言模型 (LLM) 的快速发展正在对学术和研究环境产生重大影响.
  • 人工智能工具在科学工作流程中的整合正变得越来越普遍.
  • 由于这些技术转变,学生和主要研究人员 (PI) 面临着不断变化的角色.

研究的目的:

  • 检查LLMs在生物医学研究中的变革潜力.
  • 在研究过程中探索LLM作为合作伙伴,或"Co-PI".
  • 为科学中负责任和高效的人类-人工智能合作提出框架.

主要方法:

  • 在研究任务中对LLM能力的基于视角的分析.
  • 识别与LLM整合相关的机会和风险.
  • 在科学实验室中开发人工智能协作框架.

主要成果:

  • 法律学可以作为"Co-PI",用于包括文献审查和假设生成在内的任务.
  • 对研究人员来说,LLMs的整合既带来了重大机遇,也带来了潜在的风险.
  • 提出了一个结构化的框架,以指导负责任的LLM使用.

结论:

  • 士准备成为生物医学研究中不可分割的合作者.
  • 负责任和战略性地实施LLMs对于最大限度地提高效益至关重要.
  • 拟议的框架旨在促进科学中有效的AI-人类伙伴关系.