Why Are Conversational Assistants Still Black Boxes? The Case For Transparency
Article No.: 52, Pages 1 - 5
Abstract
Much has been written about privacy in the context of conversational and voice assistants. Yet, there have been remarkably few developments in terms of the actual privacy offered by these devices. But how much of this is due to the technical and design limitations of speech as an interaction modality? In this paper, we set out to reframe the discussion on why commercial conversational assistants do not offer meaningful privacy and transparency by demonstrating how they could. By instrumenting the open-source voice assistant Mycroft to capture audit trails for data access, we demonstrate how such functionality could be integrated into big players in the sector like Alexa and Google Assistant. We show that this problem can be solved with existing technology and open standards and is thus fundamentally a business decision rather than a technical limitation.
References
[1]
Noura Abdi, Kopo M Ramokapane, and Jose M Such. 2019. More than Smart Speakers: Security and Privacy Perceptions of Smart Home Personal Assistants. In SOUPS@ USENIX Security Symposium.
[2]
Noura Abdi, Xiao Zhan, Kopo M. Ramokapane, and Jose Such. 2021. Privacy Norms for Smart Home Personal Assistants. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 558, 14 pages. https://doi.org/10.1145/3411764.3445122
[3]
Marc Serramia Amoros, William Seymour, Natalia Criado, and Michael Luck. 2023. Predicting Privacy Preferences for Smart Devices as Norms. In The 22nd International Conference on Autonomous Agents and Multiagent Systems. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).
[4]
Jide Edu, Xavier Ferrer-Aran, Jose Such, and Guillermo Suarez-Tangil. 2022. Measuring Alexa Skill Privacy Practices across Three Years. In Proceedings of the Web Conference (WWW).
[5]
Nathaniel Fruchter and Ilaria Liccardi. 2018. Consumer Attitudes Towards Privacy and Security in Home Assistants. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI EA ’18). Association for Computing Machinery, New York, NY, USA, 1–6. https://doi.org/10.1145/3170427.3188448
[6]
Nina Gerber, Paul Gerber, Hannah Drews, Elisa Kirchner, Noah Schlegel, Tim Schmidt, and Lena Scholz. 2018. FoxIT: Enhancing Mobile Users’ Privacy Behavior by Increasing Knowledge and Awareness. In Proceedings of the 7th Workshop on Socio-Technical Aspects in Security and Trust (Orlando, Florida, USA) (STAST ’17). Association for Computing Machinery, New York, NY, USA, 53–63. https://doi.org/10.1145/3167996.3167999
[7]
Yolanda Gil and Simon Miles. 2013. PROV Model Primer. Technical Report. World Wide Web Consortium. http://www.w3.org/TR/2013/NOTE-prov-primer-20130430/ W3C Note.
[8]
Yue Huang, Borke Obada-Obieh, and Konstantin (Kosta) Beznosov. 2020. Amazon vs. My Brother: How Users of Shared Smart Speakers Perceive and Cope with Privacy Risks(CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376529
[9]
Trung Dong Huynh, Niko Tsakalakis, Ayah Helal, Sophie Stalla-Bourdillon, and Luc Moreau. 2023. A Methodology and Software Architecture to Support Explainability-by-Design. arxiv:2206.06251 [cs.SE]
[10]
Josephine Lau, Benjamin Zimmerman, and Florian Schaub. 2018. Alexa, Are You Listening? Privacy Perceptions, Concerns and Privacy-Seeking Behaviors with Smart Speakers. 2, CSCW, Article 102 (nov 2018), 31 pages. https://doi.org/10.1145/3274371
[11]
Ewa Luger, Stuart Moran, and Tom Rodden. 2013. Consent for All: Revealing the Hidden Complexity of Terms and Conditions(CHI ’13). Association for Computing Machinery, New York, NY, USA, 2687–2696. https://doi.org/10.1145/2470654.2481371
[12]
Luc Moreau, Belfrit Victor Batlajery, Trung Dong Huynh, Danius Michaelides, and Heather Packer. 2018. A Templating System to Generate Provenance. IEEE Transactions on Software Engineering 44, 2 (2018), 103–121. https://doi.org/10.1109/TSE.2017.2659745
[13]
Luc Moreau and Paolo Missier. 2013. PROV-DM: The PROV Data Model. Technical Report. World Wide Web Consortium. http://www.w3.org/TR/2013/REC-prov-dm-20130430/ W3C Recommendation.
[14]
Helen Nissenbaum. 2009. Privacy in context. In Privacy in Context. Stanford University Press.
[15]
Leon Reicherts, Nima Zargham, Michael Bonfert, Yvonne Rogers, and Rainer Malaka. 2021. May I Interrupt? Diverging Opinions On Proactive Smart Speakers(CUI ’21). Association for Computing Machinery, New York, NY, USA, Article 34, 10 pages. https://doi.org/10.1145/3469595.3469629
[16]
William Seymour, Mark Cote, and Jose Such. 2022. When It’s Not Worth the Paper It’s Written On: A Provocation on the Certification of Skills in the Alexa and Google Assistant Ecosystems. In Proceedings of the 4th Conference on Conversational User Interfaces (Glasgow, United Kingdom) (CUI ’22). Association for Computing Machinery, New York, NY, USA, Article 14, 5 pages. https://doi.org/10.1145/3543829.3544513
[17]
William Seymour, Martin J. Kraemer, Reuben Binns, and Max Van Kleek. 2020. Informing the Design of Privacy-Empowering Tools for the Connected Home. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–14. https://doi.org/10.1145/3313831.3376264
[18]
William Seymour and Jose Such. 2023. Ignorance is Bliss? The Effect of Explanations on Perceptions of Voice Assistants. Proc. ACM Hum.-Comput. Interact. 7, CSCW1, Article 64 (apr 2023), 24 pages. https://doi.org/10.1145/3579497
[19]
Irina Shklovski, Scott D. Mainwaring, Halla Hrund Skúladóttir, and Höskuldur Borgthorsson. 2014. Leakiness and Creepiness in App Space: Perceptions of Privacy and Mobile App Use. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Toronto, Ontario, Canada) (CHI ’14). Association for Computing Machinery, New York, NY, USA, 2347–2356. https://doi.org/10.1145/2556288.2557421
[20]
Max Van Kleek, Reuben Binns, Jun Zhao, Adam Slack, Sauyon Lee, Dean Ottewell, and Nigel Shadbolt. 2018. X-Ray Refine: Supporting the Exploration and Refinement of Information Exposure Resulting from Smartphone Apps. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI ’18). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3173574.3173967
[21]
Xiao Zhan, Stefan Sarkadi, Natalia Criado, and Jose Such. 2022. A Model for Governing Information Sharing in Smart Assistants. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (Oxford, United Kingdom) (AIES ’22). Association for Computing Machinery, New York, NY, USA, 845–855. https://doi.org/10.1145/3514094.3534129
Index Terms
- Why Are Conversational Assistants Still Black Boxes? The Case For Transparency
Recommendations
AI-Based Voice Assistants Technology Comparison in Term of Conversational and Response Time
Intelligent Human Computer InteractionAbstractWith the rapid development of artificial intelligence (AI) technology, the field of mobile phone technology is also developing in the direction of using artificial intelligence. Natural user interfaces are becoming popular. One of the most common ...
Collaboration with Conversational AI Assistants for UX Evaluation: Questions and How to Ask them (Voice vs. Text)
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing SystemsAI is promising in assisting UX evaluators with analyzing usability tests, but its judgments are typically presented as non-interactive visualizations. Evaluators may have questions about test recordings, but have no way of asking them. Interactive ...
Ok Google, What Am I Doing?: Acoustic Activity Recognition Bounded by Conversational Assistant Interactions
Conversational assistants in the form of stand-alone devices such as Amazon Echo and Google Home have become popular and embraced by millions of people. By serving as a natural interface to services ranging from home automation to media players, ...
Comments
Information & Contributors
Information
Published In
July 2023
504 pages
ISBN:9798400700149
DOI:10.1145/3571884
Copyright © 2023 Owner/Author.
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 19 July 2023
Check for updates
Author Tags
Qualifiers
- Work in progress
- Research
- Refereed limited
Conference
CUI '23
Sponsor:
Acceptance Rates
Overall Acceptance Rate 34 of 100 submissions, 34%
Upcoming Conference
CUI '25
- Sponsor:
- sigchi
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 70Total Downloads
- Downloads (Last 12 months)36
- Downloads (Last 6 weeks)1
Reflects downloads up to 31 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format