research-article

Hey Google, Can I Ask You Something in Private?

Author:

Eugene ChoAuthors Info & Claims

CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Paper No.: 258, Pages 1 - 9

https://doi.org/10.1145/3290605.3300488

Published: 02 May 2019 Publication History

Abstract

MModern day voice-activated virtual assistants allow users to share and ask for information that could be considered as personal through different input modalities and devices. Using Google Assistant, this study examined if the differences in modality (i.e., voice vs. text) and device (i.e., smartphone vs. smart home device) affect user perceptions when users attempt to retrieve sensitive health information from voice assistants. Major findings from this study suggest that voice (vs. text) interaction significantly enhanced perceived social presence of the voice assistant, but only when the users solicited less sensitive health-related information. Furthermore, when individuals reported less privacy concerns, voice (vs. text) interaction elicited positive attitudes toward the voice assistant via increased social presence, but only in the low (vs. high) information sensitivity condition. Contrary to modality, the device difference did not exert any significant impact on the attitudes toward the voice assistant regardless of the sensitivity level of the health information being asked or the level of individuals' privacy concerns.

References

[1]

Adrian Aguilera and Clara Berridge. 2014. Qualitative feedback from a text messaging intervention for depression: benefits, drawbacks, and cultural differences. JMIR Mental Uhealth 2, 4: e46.

[2]

Gaurav Bansal, Fatemeh M. Zahedi, and David Gefen. 2010. The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support System 49, 2: 138--150.

Digital Library

[3]

Gary Bente, Sabine Rüggenberg, Nicole C. Krämer, and Felix Eschenburg. 2008. Avatar-mediated networking: Increasing social presence and interpersonal trust in net-based collaborations. Human Communication Research 34, 2: 287--318.

[4]

Dianne C. Berry, Laurie T. Butler, and Fiorella de Rosis. 2005. Evaluating a realistic agent in an advice-giving task. Itnl Journal of Human-Computer Studies 63, 3: 304--327.

Digital Library

[5]

Tamera Dinev and Paul Hart. 2005. Internet privacy concerns and social awareness as determinants of intention to transact. Itnl Journal of Electronic Commerce 10, 2: 7--29.

Digital Library

[6]

Aaron C. Elkins and Douglas C. Derrick. 2013. The sound of trust: Voice as a measurement of trust during interactions with embodied conversational agents. Group Decision and Negotiation 22, 5: 897913.

[7]

Julia Fink. 2012. Anthropomorphism and human likeness in the design of robots and humanrobot interaction. In Social Robotics. ICSR 2012. Lecture Notes in Computer Science, vol 7621, Shuzhi S. Ge, Oussama Khatib, John-John Cabibihan, Reid Simmons, MaryAnne Williams (eds.). Springer, Berlin, Heidelberg, 199--208.

Digital Library

[8]

David Gefen and Detmar S. Straub. 2003. Managing user trust in B2B e-services. e-Service Journal 2, 2: 7--24.

Digital Library

[9]

Jonathan Gratch, Jeff Rickel, Elisabeth Andre, Justine Cassell, Eric Petajan, and Norman Badler. 2002. Creating interactive virtual humans: some assembly required. IEEE Intelligent Systems 17, 4: 54--63

Digital Library

[10]

Andrew F. Hayes. 2013. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York, NY: The Guilford Press.

[11]

Sriram Kalyanaraman and Shyam S. Sundar. 2006. The psychological appeal of personalized online content in Web portals: Does customization affect attitudes and behavior? Journal of Communication 56, 1: 110--132.

[12]

Kwan Min Lee and Clifford Nass. 2003. Designing social presence of social actors in human computer interaction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '03). 289--296.

Digital Library

[13]

Kwan Min Lee, Wei Peng, Seung-A Jin, Chang Yan. 2006. Can robots manifest personality?: An empirical test of personality recognition, social responses, and social presence in Human--Robot interaction. Journal of Communication 56, 4: 754--772.

[14]

Rich Ling. 2004. The mobile connection: The cell phone's impact on society. San Francisco, CA: Morgan Kaufmann Publisher.

Digital Library

[15]

Syaheerah L. Lutz, Fernando Fernández-Martínez, Jaime LorenzoTrueba, Roberto Barra-Chicote, and Juan M. Montero. 2013. I feel you: The design and evaluation of a domotic a?ect-sensitive spoken conversational agent. Sensors 13, 8: 10519--10538.

[16]

Richard E. Mayer & Roxana Moreno. 2003. Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist 38, 1: 43--52

[17]

Adam S. Miner, Arnold Milstein, Stephen Schueller, Roshini Hegde, Christina Mangurian, and Elini Linos. 2016. Smartphone-based conversational agents and responses to questions about mental health, interpersonal violence, and physical health. JAMA Internal Medicine 176, 5: 619--625.

[18]

Youngme Moon. 2000. Intimate exchanges: Using computers to elicit self-disclosure from consumers. Journal of Consumer Research 26, 4: 323--339.

[19]

Youngme Moon and Clifford Nass. 1996. How "real" are computer personalities: Psychological responses to personality types in human-computer interaction. Communication Research 23, 6: 651674.

[20]

Aarthi E. Moorthy amd Kim-Phoung Vu. 2015. Privacy concerns for use of voice activated personal assistant in the public space. International Journal of Human--Computer Interaction 31, 4: 307335.

[21]

Christos N. Moridis amd Anastasios A. Economides. 2012. Affective learning: Empathetic agents with emotional facial and tone of voice expressions. IEEE Transactions on Affective Computing 3: 260--272.

Digital Library

[22]

Cli?ord Nass and Li Gong. 1999. Maximized modality or constrained consistency? In Proceedings of the AVSP 99 Conference. Retreived from http://www.iscaspeech.org/archive_open/avsp99/av99_001.html

[23]

Cli?ord Nass and Kwan Min Lee. 2000. Does computer-generated speech manifest personality? An experimental test of similarityattraction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '00), 329--336.

Digital Library

[24]

Clifford Nass and Youngme Moon. 2000. Machines and mindlessness: Social responses to computers. Journal of Social Issues 56, 1: 81--103.

[25]

Clifford Nass, Jonathan Steuer, Ellen R. Tauber. 1994. Computers are social actors. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '94), 72--78. https://dl.acm.org/citation.cfm?id=191703

Digital Library

[26]

Jay F. Nunamaker, Douglas C. Derrick, Aaron C. Elkins, Judee K. Burgoon, and Mark W. Patton. 2011. Embodied conversational agent-based kiosk for automated interviewing. Journal of Management Information Systems 28, 1: 17--48.

Digital Library

[27]

Joseph P. Olive. 1997. The talking computer: Text to speech synthesis. In Hal's legacy: 2001's computer as dream and reality, David G. Stork (ed.). The MIT Press, Cambridge, MA, 101--130.

[28]

Allan Paivio. 1986. Mental representations: A dual coding approach. Oxford, England: Oxford University Press.

[29]

Eun Kyung Park and S. Shyam Sundar. 2014. Can synchronicity and visual modality enhance social presence in mobile messaging? Computers in Human Behavior 45: 121--128.

Digital Library

[30]

Judith Potts. 2018. New technology is rapidly improving cancer care, and Alexa is at the vanguard. The Telegraph. Retrieved from: https://www.telegraph.co.uk/health-?tness/body/new-technologyrapidly-improving-cancer-care-alexa-vanguard/

[31]

Lingyun Qiu and Izak Benbasat. 2009. Evaluating anthropomorphic product recommendation agents: A social relationship perspective to designing information systems. Journal of Management Information Systems 25, 4: 145--182.

Digital Library

[32]

Tiago Reism, Marco de Sá, and Luís Carriço. 2008. Multimodal interaction: Real context studies on mobile digital artefacts. In Haptic and audio interaction design, Antti Pirhonen and Stephen Brewster (eds.), Springer, Berlin, Germany, 60--69.

Digital Library

[33]

Laura Stevens. 2017. 'Alexa, can you prevent suicide?' How Amazon trains its AI to handle the most personal questions imaginable. The Wall Street Journal. Retrieved from: https://www.wsj.com/articles/alexa-can-you-prevent-suicide1508762311?mod=e2fb

[34]

S. Shyam Sundar, Haiyan Jia, Franklin T. Waddell, and Yan Huang. 2015. Towards a theory of interactive media effects (TIME). In The handbook of the psychology of communication technology, S. Shyam Sundar (ed), John Wiley & Sons, Chichester, UK, 47--86.

[35]

S. Shyam Sundar, Qian Xu, Saraswathi Bellur, Jeeyun Oh, and Haiyan Jia. 2011. Beyond pointing and clicking: How do newer interaction modalities affect user engagement? In Proceedings of the 2011 Annual Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA'11), 1477--1482.

Digital Library

[36]

John Sweller. 1999. Instructional design in technical areas. Camberwell, Australia: ACER Press.

[37]

Pragati Verma. 2018. Why voice assistants are gaining traction in healthcare. Samsung NEXT. Retrieved from: http://samsungnext.com/whats-next/voice-assistants-aihealthcare/

[38]

Joseph B. Walther. 1992. Interpersonal effects in computermediated interaction: A relational perspective. Communication Research 19, 1: 52--90.

[39]

Tyler Watson, Scot Simpson, and Christine Hughes. 2016. Text messaging interventions for individuals with mental health disorders including substance use: A systematic review. Psychiatry Research 243, 30: 255--262

[40]

Julie R. Williamson. 2012. User experience, performance, and social acceptability: usable multimodal mobile interaction. Ph.D Dissertation. University of Glasgow, Glasgow, Scotland.

Cited By

Schulz AYoussef YBeruscha FHornecker E(2024)User Perceptions and Experiences with Smart Homes - The Smart Home as an Obedient Guard Dog, Disinterested Cat, Ambitious Octopus or Busy BeehiveProceedings of Mensch und Computer 202410.1145/3670653.3670659(171-183)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1145/3670653.3670659
Chin JDesai SLin SMejia S(2024)Like My Aunt Dorothy: Effects of Conversational Styles on Perceptions, Acceptance and Metaphorical Descriptions of Voice Assistants during Later AdulthoodProceedings of the ACM on Human-Computer Interaction10.1145/36373658:CSCW1(1-21)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637365
Zhan XAbdi NSeymour WSuch J(2024)Healthcare Voice AI Assistants: Factors Influencing Trust and Intention to UseProceedings of the ACM on Human-Computer Interaction10.1145/36373398:CSCW1(1-37)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637339
Show More Cited By

Index Terms

Hey Google, Can I Ask You Something in Private?
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction devices
      1. Sound-based input / output

Recommendations

Someone or Something to Play With?: An Empirical Study on how Parents Evaluate the Social Appropriateness of Interactions Between Children and Differently Embodied Artificial Interaction Partners
IVA '21: Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents

Children are raised with technologies that are able to respond to them in natural language. This not only makes it easy to communicate but also to connect with them socially. While communication abilities might have benefits (e.g., for learning), it ...
‘Okay google, what about my privacy?’: User's privacy perceptions and acceptance of voice based digital assistants
Abstract
Conversational Artificial Intelligence (AI) backed Alexa, Siri and Google Assistants are examples of Voice-based digital assistants (VBDA) that are ubiquitously occupying our living spaces. While they gather an enormous amount of ...
Highlights
- Voice-based digital assistants (VBDC) pose the biggest concern for the privacy.
OK Google, Let's Learn: Using Voice User Interfaces for Informal Self-Regulated Learning of Health Topics among Younger and Older Adults
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

In this paper, we present Health Buddy, a voice agent integrated into commercially available Voice User Interfaces (VUIs) to support informal self-regulated learning (SRL) of health-related topics through multiple learning strategies and examine the ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

May 2019

9077 pages

ISBN:9781450359702

DOI:10.1145/3290605

General Chairs:
Stephen Brewster
University of Glasgow, Scotland, UK
,
Geraldine Fitzpatrick
TU Wien, Austria
,
Program Chairs:
Anna Cox
University College London, UK
,
Vassilis Kostakos
University of Melbourne, Australia

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 May 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

CHI '19

Sponsor:

SIGCHI

CHI '19: CHI Conference on Human Factors in Computing Systems

May 4 - 9, 2019

Glasgow, Scotland Uk

Acceptance Rates

CHI '19 Paper Acceptance Rate 703 of 2,958 submissions, 24%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Upcoming Conference

CHI '25

Sponsor:
sigchi

CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

62
Total Citations
View Citations
1,561
Total Downloads

Downloads (Last 12 months)130
Downloads (Last 6 weeks)25

Reflects downloads up to 25 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Schulz AYoussef YBeruscha FHornecker E(2024)User Perceptions and Experiences with Smart Homes - The Smart Home as an Obedient Guard Dog, Disinterested Cat, Ambitious Octopus or Busy BeehiveProceedings of Mensch und Computer 202410.1145/3670653.3670659(171-183)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1145/3670653.3670659
Chin JDesai SLin SMejia S(2024)Like My Aunt Dorothy: Effects of Conversational Styles on Perceptions, Acceptance and Metaphorical Descriptions of Voice Assistants during Later AdulthoodProceedings of the ACM on Human-Computer Interaction10.1145/36373658:CSCW1(1-21)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637365
Zhan XAbdi NSeymour WSuch J(2024)Healthcare Voice AI Assistants: Factors Influencing Trust and Intention to UseProceedings of the ACM on Human-Computer Interaction10.1145/36373398:CSCW1(1-37)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637339
Zhan LXiong TZhang HGuo SChen XGong JLin JQin Y(2024)TouchEditorProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314547:4(1-29)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631454
Desai SWei CSin JDubiel MZargham NAhire SPorcheron MKuzminykh ALee MCandello HFischer JMunteanu CCowan B(2024)CUI@CHI 2024: Building Trust in CUIs—From Design to DeploymentExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3636287(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3636287
Liu ZLi HChen AZhang RLee Y(2024)Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural AnalysisProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642840(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642840
Kim DSong H(2024)Designing an age-friendly conversational AI agent for mobile bankingInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2024.103262187:COnline publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1016/j.ijhcs.2024.103262
Leschanowsky ARech SPopp BBäckström T(2024)Evaluating privacy, security, and trust perceptions in conversational AIComputers in Human Behavior10.1016/j.chb.2024.108344159:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.chb.2024.108344
Sam SMohamed Jasim K(2024)Hybridization of metaheuristics and NLP approach to examine public opinion towards virtual voice assistantsAnnals of Operations Research10.1007/s10479-024-06105-2Online publication date: 25-Jun-2024
https://doi.org/10.1007/s10479-024-06105-2
Suhas DRana OLannon SPerera C(2024)Talking Buildings: Interactive Human-Building Smart-Bot for Smart BuildingsWeb Information Systems Engineering – WISE 202410.1007/978-981-96-0579-8_28(399-415)Online publication date: 29-Nov-2024
https://doi.org/10.1007/978-981-96-0579-8_28
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Table of Contents