评估ChatGPT-4的历史准确性:关于SWOT分析起源的案例研究
Richard W Puyt1, Dag Øivind Madsen2
1Industrial Engineering and Business Information Systems (IEBIS), Faculty of Behavioural, Management and Social Sciences (BMS), University of Twente, Enschede, Netherlands.
Frontiers in artificial intelligence
|May 20, 2024
概括
这项研究对ChatGPT-4进行了评估.
科学领域:
- 人工智能的人工智能
- 商业战略 商业战略
- 信息科学 信息科学 信息科学
背景情况:
- SWOT分析是全球普遍存在的战略规划工具.
- 评估AI在历史业务概念中的准确性至关重要.
- 像ChatGPT-4这样的大型语言模型 (LLM) 越来越多地用于信息检索.
研究的目的:
- 评估ChatGPT-4关于SWOT分析的起源和演变的准确性.
- 在ChatGPT-4的响应中识别事实错误和幻觉的实例.
- 了解在各种数据源上训练的LLM的局限性.
主要方法:
- 使用Python脚本来提示ChatGPT-4 API使用结构化问题.
- 输入问题来源于一个Excel文件.
- 响应被记录在一个Excel文件中,并以二进制级别对准确度进行评分.
主要成果:
- 聊天GPT-4准确地描述了SWOT分析的一般概念.
- 在有关SWOT分析起源和演变的细节中发现了显著的差异和幻觉.
- 一些自发的,历史准确的事实是由ChatGPT-4生成的.
结论:
- 聊天GPT-4的知识库似乎受到易于获得的网页内容的严重影响.
- 访问学术出版物,特别是那些在付费墙后的出版物,其培训数据可能受到限制.
- 需要进一步的研究来提高专业历史和学术主题的法学士准确性.
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