你能闻到人工智能的建议吗? 人类,机器或两者兼而有之:对金融咨询进行比较实验研究
Saurav Sathish Kumta1, Niyaz Panakaje2, S M Riha Parvin2
1Yenepoya Research Centre for Finance and Entrepreneurship Development (YEN-REFINED), YIASCM, Yenepoya (Deemed to be University), Mangalore, 575018, Karnataka, India.
Acta psychologica
|February 24, 2026
概括
人工智能和混合模型的财务建议导致投资组合的成功率高于人类顾问. 对人工智能的信任是通过交互质量建立的,而不是立即的关系,将信任从个人属性转移到过程中.
科学领域:
- 行为经济学是一种行为经济学.
- 金融技术 (金融科技)
- 人与计算机的交互
背景情况:
- 长期投资组合结果的最佳财务咨询来源 (人类,人工智能或混合) 仍在调查中.
- 了解不同类型的顾问信任和建议接受的动态对于财务规划至关重要.
- 社会交换理论和人际相互依赖框架提供了理论镜头来检查双层顾问-客户互动.
研究的目的:
- 为了比较人,人工智能和人-人工智能混合金融咨询对长期投资组合业绩的影响.
- 探索信任和建议的接受如何受到财务指导来源的影响.
- 研究人类与人工智能金融咨询背景下的信任形成的心理机制.
主要方法:
- 一个准实验性设计,涉及93名参与者,评估来自人类,人工智能和混合来源的财务建议.
- 长期金融投资组合结果的客观测量.
- 基于社会交流理论,对建立信任和接受建议的过程进行定性探索.
主要成果:
- 所有顾问类型都改善了投资组合结果,人工智能和混合型号的成功率高于仅有人类咨询.
- 绝对信任水平没有显著差异,但信任的基础有所不同:人工智能信任是通过交互质量发展的,而人类信任则依赖于声誉和个人属性.
- 与人工智能顾问相比,参与者最初对人类顾问的信任程度较低.
- 人工智能不会削弱信任,而是将其基础从个人关系转移到基于过程的互动.
结论:
- 人工智能和混合型财务咨询模式提供优越的长期投资组合结果,而不是只与人类咨询相比.
- 对人工智能的信任是通过交互质量和流程建立的,与人类信任的情感和声誉基础不同.
- 混合模型提供了一个可行的策略,平衡人工智能性能与人类监督,并使对金融服务的信任得到校准.
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