The impact of labeling automotive AI as "trustworthy" or "reliable" on user evaluation and technology acceptance

TL;DR

This study investigates how labeling automotive AI as "trustworthy" or "reliable" affects user perceptions, showing that such labels can enhance perceived ease of use and human-like trust, thereby influencing acceptance.

Contribution

It provides empirical evidence on the influence of specific AI labels on user perceptions and acceptance in automotive contexts, highlighting the importance of language in technology adoption.

Findings

Labeling as "trustworthy" increased perceived ease of use.

Labeling as "trustworthy" enhanced human-like trust, especially benevolence.

Labels influenced attitudes but not scenario judgments.

Abstract

This study explores whether labeling AI as "trustworthy" or "reliable" influences user perceptions and acceptance of automotive AI technologies. Using a one-way between-subjects design, the research involved 478 online participants who were presented with guidelines for either trustworthy or reliable AI. Participants then evaluated three vignette scenarios and completed a modified version of the Technology Acceptance Model, which included variables such as perceived ease of use, human-like trust, and overall attitude. Although labeling AI as "trustworthy" did not significantly influence judgments on specific scenarios, it increased perceived ease of use and human-like trust, particularly benevolence. This suggests a positive impact on usability and an anthropomorphic effect on user perceptions. The study provides insights into how specific labels can influence attitudes toward AI technology.