[科学的叙事对象:从工业化到解释经验的化]
1Doctor in Collective Health. Professor-researcher, Institute of Collective Health, Universidad Nacional de Lanús, Buenos Aires, Argentina. vivianamartinovich@gmail.com.
Salud colectiva
|January 9, 2026
概括
科学的工业化和"cobotization",使用生成的人工智能,风险侵蚀科学社区和知识的社会意义. 恢复人类的解释对于真正的科学验证至关重要.
科学领域:
- 科学哲学的科学哲学
- 科学社会学科学社会学
- 科学与技术研究 研究科学与技术研究
背景情况:
- 科学实践日益受到工业化和自动化的影响.
- 生成型人工智能 (AI) 正在融入知识生产和验证中.
- 现有的框架可能无法完全解决人工智能对科学沟通和共识的影响.
研究的目的:
- 批判性地研究科学实践的工业化和"化".
- 分析人工智能对科学知识的生产,验证和社会意义的影响.
- 建议恢复解释经验和以人为中心的验证过程.
主要方法:
- 借鉴批判理论和哲学解释学.
- 分析科学的叙事对象作为共识构建设备.
- 在科学解释和验证中,研究从工业化转向科博化.
主要成果:
- 工业化和科博化可能会侵蚀科学语言社区和科学文本的社会意义.
- 生成性AI的整合"技术化"了科学中的沟通行动.
- 当前的过程使得科学界建立共识的传统方法失效.
结论:
- 越来越多的人工智能在科学中的依赖,需要重新评估验证环境.
- 恢复内在人类的解释经验对于真正的科学交流至关重要.
- 恢复科学话语的关系性,定位性和反射性是必不可少的.
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