Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
More Capable, Less Benevolent: Trust Perceptions of AI Systems across Societal Contexts
40
Zitationen
4
Autoren
2024
Jahr
Abstract
Modern AI applications have caused broad societal implications across key public domains. While previous research primarily focuses on individual user perspectives regarding AI systems, this study expands our understanding to encompass general public perceptions. Through a survey (N = 1506), we examined public trust across various tasks within education, healthcare, and creative arts domains. The results show that participants vary in their trust across domains. Notably, AI systems’ abilities were evaluated higher than their benevolence across all domains. Demographic traits had less influence on trust in AI abilities and benevolence compared to technology-related factors. Specifically, participants with greater technological competence, AI familiarity, and knowledge viewed AI as more capable in all domains. These participants also perceived greater systems’ benevolence in healthcare and creative arts but not in education. We discuss the importance of considering public trust and its determinants in AI adoption.
Ähnliche Arbeiten
The global landscape of AI ethics guidelines
2019 · 4.725 Zit.
The Limitations of Deep Learning in Adversarial Settings
2016 · 3.886 Zit.
Trust in Automation: Designing for Appropriate Reliance
2004 · 3.512 Zit.
Fairness through awareness
2012 · 3.302 Zit.
AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations
2018 · 3.202 Zit.