What is it about?
Imagine you are making an investment. The financial algorithm gives you one recommendation, but a seasoned human expert tells you the exact opposite. Whom do you listen to? This study simulated this exact conflict with over 800 participants to see what drives their final decision. We looked at three big factors: how much the person inherently likes/dislikes algorithms, how much they trust human experts, and their personal willingness to take risks. Unsurprisingly, people who favor AI follow the AI, and people who favor humans follow the human. However, we discovered that a person's appetite for risk changes the entire equation.
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Why is it important?
Most research looks at how people react to AI advice or human advice in isolation. But in the real world, these two sources constantly clash. Set in the context of investment decision-making, this paper provides a behavioral blueprint for predicting user behavior during an "expert contradiction." For developers building robo-advisors, wealth-tech apps, or decision-support software, this research proves that you cannot just look at whether a user has "algorithm aversion." You must profile the user's risk tolerance. By understanding a user's psychological risk profile, fintech platforms can better design their interfaces and frame their data to prevent users from making erratic choices when automated systems and human insights collide.
Read the Original
This page is a summary of: When algorithms and human experts contradict, whom do users follow?, Behaviour and Information Technology, July 2025, Taylor & Francis,
DOI: 10.1080/0144929x.2025.2525306.
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