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Trust Dynamics in Financial Decision Making: Behavioral Responses to AI and Human Expert Advice Following Structural Breaks

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Date 2024 Oct 26
PMID 39457836
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Abstract

This study explores the trust dynamics in financial forecasting by comparing how individuals perceive the credibility of AI and human experts during significant structural market changes. We specifically examine the impact of two types of structural breaks on trust: Additive Outliers, which represent a single yet significant anomaly, and Level Shifts, which indicate a sustained change in data patterns. Grounded in theoretical frameworks such as attribution theory, algorithm aversion, and the Technology Acceptance Model (TAM), this research investigates psychological responses to AI and human advice under uncertainty. This experiment involved 157 participants, recruited via Amazon Mechanical Turk (MTurk), who were asked to forecast stock prices under different structural break scenarios. Participants were randomly assigned to either the AI or human expert treatment group, and the experiment was conducted online. Through this controlled experiment, we find that, while initial trust levels in AI and human experts are comparable, the credibility of advice is more severely compromised following a structural break in the Level Shift condition, compared to the Additive Outlier condition. Moreover, the decline in trust is more pronounced for human experts than for AI. These findings highlight the psychological factors influencing decision making under uncertainty and offer insights into the behavioral responses to AI and human expert systems during structural market changes.

References
1.
Goodell J . COVID-19 and finance: Agendas for future research. Financ Res Lett. 2020; 35:101512. PMC: 7152896. DOI: 10.1016/j.frl.2020.101512. View

2.
Bostrom A, Demuth J, Wirz C, Cains M, Schumacher A, Madlambayan D . Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences. Risk Anal. 2023; 44(6):1498-1513. DOI: 10.1111/risa.14245. View

3.
Dietvorst B, Bharti S . People Reject Algorithms in Uncertain Decision Domains Because They Have Diminishing Sensitivity to Forecasting Error. Psychol Sci. 2020; 31(10):1302-1314. DOI: 10.1177/0956797620948841. View

4.
Sharan N, Romano D . The effects of personality and locus of control on trust in humans versus artificial intelligence. Heliyon. 2020; 6(8):e04572. PMC: 7475230. DOI: 10.1016/j.heliyon.2020.e04572. View

5.
Dietvorst B, Simmons J, Massey C . Algorithm aversion: people erroneously avoid algorithms after seeing them err. J Exp Psychol Gen. 2014; 144(1):114-26. DOI: 10.1037/xge0000033. View