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Voice Activated Virtual Assistants Personality Perceptions and Desires: Comparing Personality Evaluation Frameworks

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Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

Human Computer Interaction Conference

4 - 6 July 2018

Personality, Artificial Intelligence, Voice Activated Virtual Assistant

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      Abstract

      Currently, Voice Activated Virtual Assistants and Artificial Intelligence technologies are not just about performance or the functionalities they can carry out, it is also about the associated personality. This empirical multi-country study explores the personality perceptions of current VAVA users regarding these technologies. Since this is a rather unexplored territory for research, this study has identified two well-established personality evaluation methodologies, Aaker’s traits approach and Jung’s archetypes, to investigate current perceived personality and future desired personality of the four main Voice Activated Virtual Assistants: Siri, Google Assistant, Cortana and Alexa. Following are a summary of results by each methodology, and an analysis of the commonalities found between the two methodologies.

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            Author and article information

            Affiliations
            [1 ] Telefonica R&D

            Madrid, Spain
            [2 ] Telefonica Digital

            Madrid, Spain
            Contributors
            Conference
            July 2018
            July 2018
            : 1-10
            10.14236/ewic/HCI2018.40
            © Garcia et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Proceedings of the 32nd International BCS Human Computer Interaction Conference
            HCI
            32
            Belfast, UK
            4 - 6 July 2018
            Electronic Workshops in Computing (eWiC)
            Human Computer Interaction Conference
            Product
            Product Information: 1477-9358 BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

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