基于对大型语言模型的评估,为可持续的政策制定制定制定一个异性智能方法框架
Eva M Buitrago-Esquinas1,2, Miguel Puig-Cabrera1,2, José António C Santos1,2
1Faculty of Economics and Business Sciences, Universidad de Sevilla, Spain.
MethodsX
|April 23, 2024
概括
本研究介绍了一种组合人类和人工智能 (AI) 的异质智能框架,用于可持续的政策制定. 它突出了人工智能.
科学领域:
- 环境科学与政策
- 人工智能应用程序 人工智能应用程序
- 可持续发展研究 可持续发展研究
背景情况:
- 可持续性挑战日益复杂,需要先进的分析工具.
- 大型语言模型 (LLM) 显示出潜力,但在政策环境中存在局限性.
- 现有的框架缺乏一个结构化的方法来整合人类和人工智能在可持续发展.
研究的目的:
- 为可持续的政策制定提出和验证一个新的异性情报框架.
- 评估LLM在可持续发展规划中的能力和局限性.
- 为整合人工智能和人类智能提供可复制,基于经验的方法.
主要方法:
- 开发一个融合人类和人工智能的异质智能框架.
- 在政策制定中进行性能测试,比较人类智能和人工智能.
- 描述可持续性规划的七步可复制的方法.
主要成果:
- 在可持续政策任务中,LLM展示了特定的能力和局限性.
- 人类智能对于提高人工智能驱动系统的有效性至关重要.
- 拟议的框架提供了一个结构化的方法,用于无偏见的政策整合.
结论:
- 异性情报提供了一种有希望的方法来加强可持续的政策制定.
- 人类监督和人工智能的平衡整合对于有效的可持续发展解决方案至关重要.
- 提出的方法提供了实施AI在政策中的实用指南.
关键词:
聊天GPT 聊天 在GPT 聊天交谈式生成性AI是一种对话式AI.异型智能性能测试是指对异型智能性能进行的测试.人类智能 人类智能大型语言模型.可持续发展的规划和政策.可持续决策的异质情报方法框架.更多相关视频
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