Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/179679
Title: | Human, AI vs. synergy agency: how agency framing affects perceived uncertainty, controllability, and trust in AI in autonomous vehicles | Authors: | Liu, Xinyi | Keywords: | Social Sciences | Issue Date: | 2024 | Publisher: | Nanyang Technological University | Source: | Liu, X. (2024). Human, AI vs. synergy agency: how agency framing affects perceived uncertainty, controllability, and trust in AI in autonomous vehicles. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/179679 | Project: | #021175-00001 AISG3-GV-2021-007 |
Abstract: | Media often depicts artificial intelligence (AI) as autonomous entities that outperform human operators in the realm of automation. However, policymakers and industrial stakeholders are increasingly seeing AI as a form of assistance that can coexist with human involvement across a range of automation scenarios. How do the contrasting frames regarding AI, human agency, and synergy agency in automation affect public perception and trust toward these emerging technologies? This study examined agency framing in the communication of AI-automated technologies, delving into whether accentuating AI agency in replacing human drivers or highlighting human agency involvement in driving affects audience perception of technologies. The findings reveal that compared with synergy agency framing and human agency framing, AI agency framing significantly decrease perceived controllability and increase perceived uncertainty. When it comes to enhancing trust in AI and autonomous vehicles, synergy agency framing, which emphasizes collaborative interaction between human and AI, significantly increased trust through increased perceptions of controllability and reduced uncertainty, suggesting it is the most effective strategy for enhancing trust in AI systems and autonomous vehicles. These outcomes contribute to the discourse on how strategic communication can influence the acceptance of AI technologies, offering significant implications for media representation and policy-making in the era of advanced automation. | URI: | https://hdl.handle.net/10356/179679 | DOI: | 10.32657/10356/179679 | Schools: | Wee Kim Wee School of Communication and Information | Rights: | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | WKWSCI Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
0815_xinyiliu_thesis.pdf | 781.06 kB | Adobe PDF | View/Open |
Page view(s)
134
Updated on Oct 3, 2024
Download(s) 50
77
Updated on Oct 3, 2024
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.