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Morgan, Phillip
Publications (3 of 3) Show all publications
Zhang, Q., Williams, C. & Morgan, P. L. (2024). Partial habituation to disruption by irrelevant emotive speech—evidence for duplex-mechanism account. Journal of Cognitive Psychology, 36(1), 42-60
Open this publication in new window or tab >>Partial habituation to disruption by irrelevant emotive speech—evidence for duplex-mechanism account
2024 (English)In: Journal of Cognitive Psychology, ISSN 2044-5911, E-ISSN 2044-592X, Vol. 36, no 1, p. 42-60Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Taylor & Francis, 2024
National Category
Applied Psychology
Research subject
Psychology
Identifiers
urn:nbn:se:ltu:diva-104620 (URN)10.1080/20445911.2024.2310881 (DOI)2-s2.0-85185680389 (Scopus ID)
Note

Validerad;2024;Nivå 2;2024-03-22 (joosat);

Available from: 2024-03-19 Created: 2024-03-19 Last updated: 2024-03-22Bibliographically approved
Zhang, Q., Wallbridge, C. D., Jones, D. M. & Morgan, P. (2024). Public perception of autonomous vehicle capability determines judgment of blame and trust in road traffic accidents. Transportation Research Part A: Policy and Practice, 179, Article ID 103887.
Open this publication in new window or tab >>Public perception of autonomous vehicle capability determines judgment of blame and trust in road traffic accidents
2024 (English)In: Transportation Research Part A: Policy and Practice, ISSN 0965-8564, E-ISSN 1879-2375, Vol. 179, article id 103887Article in journal (Refereed) Published
Abstract [en]

Road accidents involving autonomous vehicles (AVs) will not only introduce legal challenges over liability distribution but also generally diminish the public trust that may make itself manifested in slowing the initial adoption of the technology and call into question the continued adoption of the technology. Understanding the public’s reactions to such incidents, especially the way they differentiate from conventional vehicles, is vital for future policy-making and legislation, which will in turn shape the landscape of the autonomous vehicle industry. In this paper, intuitive judgments of blame and trust were investigated in simulated scenarios of road-traffic accidents involving either autonomous vehicles or human-driven vehicles. In an initial study, five of six scenarios showed more blame and less trust attributed to autonomous vehicles, despite the scenarios being identical in antecedents and consequences to those with a human driver. In one scenario this asymmetry was sharply reversed; an anomaly shown in a follow-up experiment to be dependent on the extent to which the incident was more likely to be foreseeable by the human driver. More generally these studies show—rather than being the result of a universal higher performance standard against autonomous vehicles—that blame and trust are shaped by stereotypical conceptions of the capabilities of machines versus humans applied in a context-specific way, which may or may not align with objectively derived state of affairs. These findings point to the necessity of regularly calibrating the public’s knowledge and expectation of autonomous vehicles through educational campaigns and legislative measures mandating user training and timely disclosure from car manufacturers/developers regarding their product capabilities.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Autonomous driving, Blame attribution, Liability, Trust in automation, Human-robot interaction, Artificial intelligence
National Category
Transport Systems and Logistics
Research subject
Psychology
Identifiers
urn:nbn:se:ltu:diva-102978 (URN)10.1016/j.tra.2023.103887 (DOI)001124080800001 ()2-s2.0-85183752021 (Scopus ID)
Note

Validerad;2023;Nivå 2;2023-12-12 (hanlid);

Funder: ESRC-JST project: Rule of Law in the Age of AI: Principles of Distributive Liability for Multi-Agent Societies;

Full text license: CC BY 

Available from: 2023-11-23 Created: 2023-11-23 Last updated: 2024-03-11Bibliographically approved
Marcinkiewicz, V. & Morgan, P. L. (2023). Trust and Blame in Self-driving Cars Following a Successful Cyber Attack. In: Abbas Moallem (Ed.), HCI for Cybersecurity, Privacy and Trust: . Paper presented at 5th International Conference on HCI for Cybersecurity, Privacy and Trust (HCI-CPT 2023), Copenhagen, Denmark, July 23-28, 2023 (pp. 323-337). Springer Nature
Open this publication in new window or tab >>Trust and Blame in Self-driving Cars Following a Successful Cyber Attack
2023 (English)In: HCI for Cybersecurity, Privacy and Trust / [ed] Abbas Moallem, Springer Nature, 2023, p. 323-337Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Springer Nature, 2023
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 14045
National Category
Computer and Information Sciences
Research subject
Psychology
Identifiers
urn:nbn:se:ltu:diva-103576 (URN)10.1007/978-3-031-35822-7_22 (DOI)2-s2.0-85171468046 (Scopus ID)
Conference
5th International Conference on HCI for Cybersecurity, Privacy and Trust (HCI-CPT 2023), Copenhagen, Denmark, July 23-28, 2023
Note

Funder: EPRSRC DTP Hub in Cyber Security Analytics awarded to Cardiff University;

ISBN for host publication: 978-3-031-35821-0 (print); 978-3-031-35822-7 (electronic)

Available from: 2024-01-12 Created: 2024-01-12 Last updated: 2024-03-11Bibliographically approved
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