Overcoming algorithm aversion: A comparison between process and outcome control

Authors: L Cheng, A Chouldechova

Published: 2024

Publication: Proceedings of the 2023 CHI Conference ..., 2023 - dl.acm.org

Giving users process control by selecting the training algorithm mitigates algorithm aversion, but not by changing input factors, while combined outcome and process control is not more effective than each individually.

Methods: Replication study on outcome control and novel process control conditions tested on MTurk and Prolific platforms.

Key Findings: Impact of outcome control, process control, and combined controls on algorithm aversion mitigation.

Limitations: Reproducibility challenges and lack of enhanced effectiveness from combining outcome and process control.

Institution: Carnegie Mellon University

Research Area: Human-Computer Interaction (HCI), Algorithm Aversion, Decision Science

Discipline: Human-Computer Interaction (HCI)

Citations: 41

DOI: https://doi.org/10.1145/3544548.3581253