在生成性AI时代,重新校准学术专业知识
Zhicheng Lin1,2, Aamir Sohail3,4
1Department of Psychology, Yonsei University, Seoul 03722, Republic of Korea.
Patterns (New York, N.Y.)
|January 26, 2026
概括
科学中的生成人工智能 (GenAI) 提高了生产力,但可能会阻碍技能发展. 培养人工智能超能力,如批判性辨别,对于研究人员来说至关重要,以保持智力自主性和有效地指导人工智能工具.
科学领域:
- 科学研究和学术工作流程.
- 科学领域的人工智能
- 研究人员的认知发展研究人员的认知发展
背景情况:
- 将生成性AI (GenAI) 整合到学术工作流中正在改变科学实践.
- 虽然GenAI提高了生产力,但它对认知技能发展构成风险,包括合成,实验设计和写作.
- 对GenAI的不批判依赖可能会导致研究人员的技能缩和自满.
研究的目的:
- 为研究人员提出一个基本人工智能元技能框架.
- 建立一种新的科学素养形式,将传统的批判性思维与人工智能能力相结合.
- 为培养这些元技能提供一个教学模型,确保智力自主.
主要方法:
- 制定一个框架,包括战略方向,批判性辨别和系统的校准.
- 使用特定领域的例子来说明元技能应用.
- 采用一种定位学习教学模式来培养技能.
主要成果:
- 拟议的AI元技能形成了一个新的科学素养,增强了传统的批判性思维.
- 基于定位学习的教学方法可以有效地培养这些基本的元技能.
- 实习研究人员可以通过故意的元技能发展来保持智力自主.
结论:
- 对研究人员,特别是实习生来说,刻意培养人工智能元技能是必不可少的.
- 如果未能发展这些元技能,就有可能使研究人员变得服从于人工智能工具.
- 一代新一代的科学家必须有能力战略地指导人工智能,而不仅仅是利用它.
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