金融决策中的信任动态:在结构性断裂之后,对人工智能和人类专家建议的行为反应
Hyo Young Kim1, Young Soo Park2
1Department of Artificial Intelligence, Tech University of Korea, 237 Sangidaehak-ro, Siheung-si 15073, Republic of Korea.
Behavioral sciences (Basel, Switzerland)
|October 26, 2024
概括
在市场结构性崩后,对财务预测的人工智能和人类专家的信任下降. 水平变化影响信任比异常值更大,人类专家的下降比人工智能系统更大.
科学领域:
- 行为经济学是一种行为经济学.
- 人工智能伦理学 人工智能伦理学
- 金融市场 金融市场
背景情况:
- 了解对人工智能与人类专家的信任对于决策至关重要.
- 市场结构性崩带来不确定性,挑战现有的信任动态.
- 诸如归因理论和算法厌恶等理论框架为心理反应提供了信息.
研究的目的:
- 在市场结构变化下进行财务预测时,比较对人工智能和人类专家的信任.
- 调查增值异常值和水平转移对信任的差异影响.
- 在不确定性中分析对人工智能和人类建议的心理反应.
主要方法:
- 一个受控的在线实验,通过亚马逊机械土耳其 (MTurk) 招募了157名参与者.
- 参与者预测股票价格,随机分配到人工智能或人类专家条件.
- 暴露于不同的结构性崩场景 (附加异常值与水平转移).
主要成果:
- 人工智能和人类专家的初始信任水平是可比的.
- 建议的可信度更严重地受到水平转移的影响,而不是附加的异常值.
- 与人工智能相比,对人类专家来说,信任的下降在结构性崩后更为明显.
结论:
- 市场结构性崩显著影响对预测咨询的信任.
- 水平的变化会比单一的异常更破坏信任,尤其是对人类专家来说.
- 研究结果提供了对不确定的金融环境中人工智能和人类系统的行为反应的见解.
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