范式转变:探索AI对定性调查和分析的影响
1Teesside University International Business School, TU Online, Teesside University, Middlesbrough, United Kingdom.
Frontiers in research metrics and analytics
|December 20, 2024
概括
人工智能 (AI) 提供更快的定性数据分析,但可能与解释主义相冲突. 由于人工智能,人类研究人员应该保留最终的解释.
科学领域:
- 社会科学 社会科学 社会科学
- 计算机科学 计算机科学
背景情况:
- 在定性研究中,技术的整合是很常见的.
- 在定性数据分析中的人工智能 (AI) 对解释主义提出了挑战.
研究的目的:
- 探索人工智能技术的使用,如自然语言处理 (NLP) 在定性数据分析.
- 检查人工智能驱动分析与解释主义假设之间的潜在冲突.
- 讨论研究范式和人类研究人员的角色的影响.
主要方法:
- 探索AI在定性研究中的应用,特别是用于数据分析的NLP.
- 讨论围绕自动定性分析的有效性和伦理性的辩论.
- 在解释主义框架内保留人类监督解释的论点.
主要成果:
- 人工智能,包括NLP,越来越多地用于定性数据分析,提供速度.
- 由于其基于规则的性质,人们对AI与解释主义假设的结合存在担忧.
- 人工智能可能会忽视人类沟通中的细微差别,这对于定性解释至关重要.
结论:
- 人类研究人员应在定性研究中保持上下文理解和最终解释.
- 使用人工智能的部分自动化可以提高定性研究的严谨性和效率.
- 人工智能的兴起可能需要新的研究范式,例如数字研究人员的"计算"范式.
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