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

arXiv 2408.10905 ↗First posted 20 Aug 2024cs.HC cs.AI cs.ETcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 29 references that are in the map. First posted on arXiv 20 Aug 2024.

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References · 2

  1. 2022Trust in AI and Its Role in the Acceptance of AI Technologiescited by 29
  2. 2024From "AI" to Probabilistic Automation: How Does Anthropomorphization of Technical Systems Descriptions Influence Trust?cited by 18

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