The ideological divide in public perceptions of self-driving cars

Peng, Yilang

doi:10.1177/0963662520917339

Cited by 30 publications

(21 citation statements)

References 42 publications

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“…To measure public perceptions of AI about perceived benefits, risks, and trust, we developed constructs by following the lead of the academic literature on AI, public perceptions, and government decision automation (e.g. Fraszczyk and Mulley 2017 ; Araujo et al 2020 ; Peng 2020 ; Stai et al 2020 ; Cui and Wu 2021 ; Dennis et al 2021 ; Kassens-Noor et al 2021 ; Selwyn and Gallo Cordoba 2021 ). All items were measured on a 7-point Likert scale ranging from “disagree” to “agree” for perceived benefits and risks, and “distrust” to “trust” for the trust construct.…”

Section: Methodsmentioning

confidence: 99%

Drivers behind the public perception of artificial intelligence: insights from major Australian cities

2022

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Artificial intelligence (AI) is not only disrupting industries and businesses, particularly the ones have fallen behind the adoption, but also significantly impacting public life as well. This calls for government authorities pay attention to public opinions and sentiments towards AI. Nonetheless, there is limited knowledge on what the drivers behind the public perception of AI are. Bridging this gap is the rationale of this paper. As the methodological approach, the study conducts an online public perception survey with the residents of Sydney, Melbourne, and Brisbane, and explores the collected survey data through statistical analysis. The analysis reveals that: (a) the public is concerned of AI invading their privacy, but not much concerned of AI becoming more intelligent than humans; (b) the public trusts AI in their lifestyle, but the trust is lower for companies and government deploying AI; (c) the public appreciates the benefits of AI in urban services and disaster management; (d) depending on the local context, public perceptions vary; and (e) the drivers behind the public perception include gender, age, AI knowledge, and AI experience. The findings inform authorities in developing policies to minimise public concerns and maximise AI awareness.

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Section: Methodsmentioning

confidence: 99%

Drivers behind the public perception of artificial intelligence: insights from major Australian cities

2022

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“…A parallel between fully autonomous versus semiautonomous approaches has been seen in the automobile industry over the past several decades. Companies such as Google and Tesla have made significant strides in the development of fully autonomous cars (25)(26)(27)(28), but due to the significant technical and ethical requirements needed (29)(30)(31), fully autonomous driving is not yet commercially implemented. On the other hand, semi-autonomous driving features such as lane-assist, or initiation of braking for collision avoidance have more quietly become standard in the automotive industry over the past decade.…”

Section: Discussionmentioning

confidence: 99%

Volumetric Accuracy Analysis of Virtual Safety Barriers for Cooperative-Control Robotic Mastoidectomy

Ding

Capostagno²,

Razavi

et al. 2021

Otology &Amp; Neurotology

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Hypothesis: Virtual fixtures can be enforced in cooperativecontrol robotic mastoidectomies with submillimeter accuracy. Background: Otologic procedures are well-suited for robotic assistance due to consistent osseous landmarks. We have previously demonstrated the feasibility of cooperative-control robots (CCRs) for mastoidectomy. CCRs manipulate instruments simultaneously with the surgeon, allowing the surgeon to control instruments with robotic augmentation of motion. CCRs can also enforce virtual fixtures, which are safety barriers that prevent motion into undesired locations. Previous studies have validated the ability of CCRs to allow a novice surgeon to safely complete a cortical mastoidectomy. This study provides objective accuracy data for CCRimposed safety barriers in cortical mastoidectomies. Methods: Temporal bone phantoms were registered to a CCR using preoperative computed tomography (CT) imaging. Virtual fixtures were created using 3D Slicer, with 2D planes placed along the external auditory canal, tegmen, and sigmoid, converging on the antrum. Five mastoidectomies were performed by a novice surgeon, moving the drill to the limit of the barriers. Postoperative CT scans were obtained, and Dice coefficients and Hausdorff distances were calculated. Results: The average modified Hausdorff distance between d r i l l e d b o n e a n d t h e p r e p l a n n e d v o l u m e w a s 0.351 AE 0.093 mm. Compared with the preplanned volume of 0.947 cm 3 , the mean volume of bone removed was 1.045 cm 3 (difference of 0.0982 cm 3 or 10.36%), with an average Dice coefficient of 0.741 (range, 0.665-0.802). Conclusions: CCR virtual fixtures can be enforced with a high degree of accuracy. Future studies will focus on improving accuracy and developing 3D fixtures around relevant surgical anatomy.

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“…A recent study on the role of ideology on attitudes toward driverless cars found an ideological divide in public reactions to the subject. Compared to liberals, conservatives expressed more concern about autonomous vehicles and more support for regulating driverless cars (Peng, 2020).…”

Section: Political Ideology and Acceptance Of Technologymentioning

confidence: 99%

The Acceptance of Driverless Cars: The Roles of Perceived Outcomes and Technology Usefulness

Mesch

Dodel

2022

American Behavioral Scientist

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The accelerating development of autonomous vehicles is expected to have important effects on society such as reducing the number of traffic accidents, preventing the disabilities and deaths attributed to car accidents, and reducing pollution. However, their adoption depends on the willingness of the population to accept this innovation and incorporate it in their everyday activities. This study investigated the association between socio-demographic factors, political ideology, and attitudes toward technology and its perceived potential impact on society on support for driverless cars. We conducted a secondary analysis of a large sample of employees in the United States ( n = 2,470). Based on conceptual frameworks relevant to the study of technology adoption such as the self-interest hypothesis, the usefulness of the technology, ideological orientation, and socio-demographic gaps in attitudes toward technology, our results indicate that perceived social outcomes of driverless cars are strongly associated with their support. Age and gender are negatively associated with support for autonomous vehicles. In contrast, perceived positive outcomes of the introduction of technology in the workplace are positively associated with them. Individuals with a consistently conservative ideology are also less likely to be supporters of autonomous vehicles. Our findings indicate that the centrality of the expected societal impact of autonomous vehicles implies the need to provide the public with accurate facts about their expected effect. Doing so is critical to increasing the public’s willingness to adopt the technology and support its production. People must also be reassured that regulations and product designs will be created to ensure their safety.

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The ideological divide in public perceptions of self-driving cars

Cited by 30 publications

References 42 publications

Drivers behind the public perception of artificial intelligence: insights from major Australian cities

Drivers behind the public perception of artificial intelligence: insights from major Australian cities

Volumetric Accuracy Analysis of Virtual Safety Barriers for Cooperative-Control Robotic Mastoidectomy

The Acceptance of Driverless Cars: The Roles of Perceived Outcomes and Technology Usefulness

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