关于大型人工智能模型的透明度
Wanying Wang1, Ge Wang2, Vukosi Marivate3
1Scientific Editor, Patterns.
Patterns (New York, N.Y.)
|July 31, 2023
概括
发表关于大型人工智能 (AI) 模型的研究对透明度和可重复性提出了独特的挑战. 这篇社论为研究人员提供了指导,帮助他们与期刊政策保持一致,并提高AI研究的开放性.
科学领域:
- 人工智能的人工智能
- 科学出版科学出版
- 科学中的可复制性
背景情况:
- 大型人工智能模型带来了独特的出版挑战.
- 确保人工智能研究的开放性和可重复性至关重要.
- 现有的出版规范可能无法充分解决AI特定的问题.
研究的目的:
- 为开发或使用大型AI模型的研究人员提供指导.
- 澄清有关AI研究提交的期刊政策.
- 促进人工智能科学出版物的透明度和可复制性.
主要方法:
- 编辑概述期刊政策的编辑.
- 讨论人工智能研究透明度的最佳实践.
- 准备可复制AI提交的指导.
主要成果:
- 研究人员在公开发布人工智能工作时面临着特定的障碍.
- 期刊正在调整政策,以适应人工智能研究需求.
- 更明确的指导方针可以提高人工智能研究的可复制性.
结论:
- 遵守期刊政策对于发表人工智能研究至关重要.
- 研究人员应该在他们的AI工作中优先考虑透明度和可重复性.
- 这篇社论旨在促进出版高质量,可复制的AI研究.
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