In AI We Trust? Factors That Influence Trustworthiness of AI-infused Decision-Making Processes

By Maryam Ashoori, Justin D. Weisz. 2019

71 citations recorded by the source corpus.

Many decision-making processes have begun to incorporate an AI element, including prison sentence recommendations, college admissions, hiring, and mortgage approval. In all of these cases, AI models are being trained to help human decision makers reach accurate and fair judgments, but little is known about what factors influence the extent to which people consider an AI-infused decision-making process to be trustworthy. We aim to understand how different factors about a decision-making process, and an AI model that supports that process, influences peoples' perceptions of the trustworthiness of that process. We report on our evaluation of how seven different factors -- decision stakes, decision authority, model trainer, model interpretability, social transparency, and model confidence -- influence ratings of trust in a scenario-based study.

Subfields: Artificial Intelligence, Safety Research, Social Psychology, AI Ethics, Fairness & Society, Human-Computer Interaction

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Citations in the corpus

Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges (2021, background): “It is universally agreed that interpretability is a key element of trust for AI models (Wagstaff, 2012; Rudin and Wagstaff, 2014; Lo Piano, 2020; Ashoori and Weisz, 2019; Thiebes et al., 2020; Spiegelhalter, 2020; Brundage et al., 2020).”
A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective (2022, background): “These complex characteristics can pose a challenge to address user trust in AI-enabled systems and risk a trust gap between users and the systems (Ashoori & Weisz, 2019).”
Design Principles for Generative AI Applications (2024, background): “Capture the user’s expectations, behaviors, and preferences to improve the AI system’s interactions with them.”
Trust in AI: progress, challenges, and future directions (2024, unknown): “…about the lack of empathy in an AI decision where some may see it as a positive aspect that increases trust in the process by keeping human emotions in check, while others think of AI ’ s lack of empathy and morality disqualify it for making higher-stakes decisions (Ashoori and Weisz, 2019).”