Stay back, clever thing! Linking situational control and human uniqueness concerns to the aversion against autonomous technology. (June 2019)
- Record Type:
- Journal Article
- Title:
- Stay back, clever thing! Linking situational control and human uniqueness concerns to the aversion against autonomous technology. (June 2019)
- Main Title:
- Stay back, clever thing! Linking situational control and human uniqueness concerns to the aversion against autonomous technology
- Authors:
- Stein, Jan-Philipp
Liebold, Benny
Ohler, Peter - Abstract:
- Abstract: As artificial intelligence advances towards unprecedented levels of competence, people's acceptance of autonomous technology has become a hot topic among psychology and HCI scholars. Previous studies suggest that threat perceptions—regarding observers' immediate physical safety (proximal) as well as their more abstract concepts of human uniqueness (distal)—impede the positive reception of self-controlled digital systems. Developing a Model of Autonomous Technology Threat, we propose both of these threat forms as common antecedents of users' general threat experience, which ultimately predicts reduced technology acceptance. In a laboratory study, 125 participants were invited to interact with a virtual reality agent, assuming it to be the embodiment of a fully autonomous personality assessment system. In a path analysis, we found correlational support for the proposed model, as both situational control and human uniqueness attitudes predicted threat experience, which in turn connected to stronger aversion against the presented system. Other potential state and trait influences are discussed. Highlights: Autonomous technology can seem threatening to users in various ways. Proximal and distal threat cues are juxtaposed in a newly developed model. Participants interact with the VR embodiment of an allegedly autonomous system. Both situational and attitudinal factors increase the threat evoked by the AI system. Ultimately, situational factors emerge as more relevantAbstract: As artificial intelligence advances towards unprecedented levels of competence, people's acceptance of autonomous technology has become a hot topic among psychology and HCI scholars. Previous studies suggest that threat perceptions—regarding observers' immediate physical safety (proximal) as well as their more abstract concepts of human uniqueness (distal)—impede the positive reception of self-controlled digital systems. Developing a Model of Autonomous Technology Threat, we propose both of these threat forms as common antecedents of users' general threat experience, which ultimately predicts reduced technology acceptance. In a laboratory study, 125 participants were invited to interact with a virtual reality agent, assuming it to be the embodiment of a fully autonomous personality assessment system. In a path analysis, we found correlational support for the proposed model, as both situational control and human uniqueness attitudes predicted threat experience, which in turn connected to stronger aversion against the presented system. Other potential state and trait influences are discussed. Highlights: Autonomous technology can seem threatening to users in various ways. Proximal and distal threat cues are juxtaposed in a newly developed model. Participants interact with the VR embodiment of an allegedly autonomous system. Both situational and attitudinal factors increase the threat evoked by the AI system. Ultimately, situational factors emerge as more relevant than overarching attitudes. … (more)
- Is Part Of:
- Computers in human behavior. Volume 95(2019)
- Journal:
- Computers in human behavior
- Issue:
- Volume 95(2019)
- Issue Display:
- Volume 95, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 95
- Issue:
- 2019
- Issue Sort Value:
- 2019-0095-2019-0000
- Page Start:
- 73
- Page End:
- 82
- Publication Date:
- 2019-06
- Subjects:
- Autonomous technology -- Artificial intelligence -- Threat -- Control -- Human uniqueness -- Virtual reality
Interactive computer systems -- Periodicals
Man-machine systems -- Periodicals
004.019 - Journal URLs:
- http://www.sciencedirect.com/science/journal/07475632 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.chb.2019.01.021 ↗
- Languages:
- English
- ISSNs:
- 0747-5632
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.921600
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16373.xml