Preparing Society for Automated Vehicles: Perceptions of the Importance and Urgency of Emerging Issues of Governance, Regulations, and Wider Impacts
Open accessAbstract
This study explores the overall picture of how people perceive the importance level and urgency level regarding issues associated with automated vehicles, by sorting out ten issues, developing a questionnaire with 66 measurement items, and investigating how Artificial Intelligence (AI) experts and Computer Science (CS)/Electrical Engineering (EE) majors assessed these issues. The findings suggest that AI experts in Taiwan believed that the top five issues for preparing a society for autonomous vehicles (AVs) should include (1) data privacy and cybersecurity, (2) regulation considerations, (3) infrastructure, (4) governance, and (5) public acceptance. On the other hand, for their student counterparts, the results (1) demonstrate a somewhat different order from the third to the fifth place, (2) show an attention-focused profile on the issue of cybersecurity and data privacy, and (3) indicate that gender and a few wider-impact variables (technology innovation, infrastructure) are significant predictors for the assessment on the importance level of AVs, while some wider-impact variables (technology innovation, governance, economic benefits, infrastructure), which are positively associated, as well as concerns variables (cybersecurity and data privacy, regulations), which are negatively associated, could be predictors for the urgency level of AVs. Suggestions for future research and policymakers are provided.
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The ethical risks of AI include privacy, security, trust, bias, unfairness, lack of transparency, and social inequality.
“They include privacy, security, trust, bias, unfairness, lack of transparency, and social inequality (Ahmad et al. 2020; Chen et al. 2020; Hoffmann 2019; Larsson and Heintz 2020; Yigitcanlar et al. 2020).”
From Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review (2023) · cites this paper as Chen et al. 2020
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- Authors
- Chen, S.-Y., Kuo, H.-Y., & Lee, C.
- Affiliations
- National Tsing Hua University (TW)
- Corresponding author
- Chen, Su-Yen
- Venue
- Sustainability
- Publisher
- MDPI AG
- Published
- 2020-09-23
- Volume
- 12
- Issue
- 19
- Pages
- 7844
- ISSN
- 2071-1050 (ISSN-L)
- OpenAlex
- W3089226300
- Cited by
- 26
- References
- 20
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 8 · 2023: 6 · 2022: 2 · 2021: 3 · 2020: 1
- FWCI
- 1.11
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sustainability (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Ministry of Science and Technology of the Republic of China (MOST 109-2634-F-007 -011)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Keywords
- autonomous vehicles, public perception, societal preparedness, governance, regulation, data privacy, cybersecurity, public acceptance, infrastructure, university students, gender differences, technological innovation, economic benefits
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