Mapping Perceptions of Humanness in Intelligent Personal Assistant Interaction
Open accessAbstract
Humanness is core to speech interface design. Yet little is known about how users conceptualise perceptions of humanness and how people define their interaction with speech interfaces through this. To map these perceptions n=21 participants held dialogues with a human and two speech interface based intelligent personal assistants, and then reflected and compared their experiences using the repertory grid technique. Analysis of the constructs show that perceptions of humanness are multidimensional, focusing on eight key themes: partner knowledge set, interpersonal connection, linguistic content, partner performance and capabilities, conversational interaction, partner identity and role, vocal qualities and behavioral affordances. Through these themes, it is clear that users define the capabilities of speech interfaces differently to humans, seeing them as more formal, fact based, impersonal and less authentic. Based on the findings, we discuss how the themes help to scaffold, categorise and target research and design efforts, considering the appropriateness of emulating humanness.
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The study's data demonstrate that older adults adopt human dialogue as a metaphor for interaction with VAs.
“Our data demonstrate that older adults adopt human dialogue as a metaphor for interaction with VAs [14, 18]”
From Situated Understanding of Errors in Older Adults' Interactions with Voice Assistants: A Month-Long, In-Home Study (2026) · cites this paper as [18]
The Discussion (p. 8) describes human dialogue as a metaphor for speech-interface interaction, and the background section (p. 2) reports that users may initially use that metaphor. But the study did not demonstrate this for older adults: its Method (p. 3) reports 21 participants with a mean age of 23.1 years. The specific metaphor finding on p. 2 is attributed to prior qualitative work, not presented as a result of this study's data. (LLM, conf=0.88)
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Wei, C. Z., Kim, Y.-H., & Kuzminykh, A. (2023) · Proceedings of the 5th International Conference on Conversational User Interfaces · doi:10.1145/3571884.3597139 · Cited by 14 · see citing works
Designing AI Personalities: Enhancing Human-Agent Interaction Through Thoughtful Persona Design
Zargham, N., Dubiel, M., Desai, S., Mildner, T., & Belz, H.-J. (2024) · International Conference on Mobile and Ubiquitous Multimedia (MUM) · doi:10.1145/3701571.3701608 · Cited by 15 · see citing works
Audience design and egocentrism in reference production during human-computer dialogue
Peña, P. R., Doyle, P. R., Edwards, J., Garaialde, D., Rough, D. J., Bleakley, A., Clark, L., Tobar-Henríquez, A., Branigan, H. P., Gessinger, I., et al. (2023) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2023.103058 · Cited by 15 · see citing works
Self-citation“You, Move There!”: Investigating the Impact of Feedback on Voice Control in Virtual Environments
Baxter, M., Bleakley, A., Edwards, J., Clark, L., Cowan, B. R., & Williamson, J. (2021) · International Conference on Conversational User Interfaces · doi:10.1145/3469595.3469609 · Cited by 16 · see citing works
Self-citationUser speech rates and preferences for system speech rates
Dowding, S., Gutwin, C. A., & Cockburn, A. (2024) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2024.103222 · Cited by 13 · see citing works
Ferguson, S. A., Aoyagui, P. A., Rizvi, R., Kim, Y., & Kuzminykh, A. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3687056 · Cited by 15 · see citing works
Li, Z., Zhu, Z., Gui, X.-N., & Luo, Y. (2025) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2025.103555 · Cited by 23 · see citing works
From C-3PO to HAL: Opening The Discourse About The Dark Side of Multi-Modal Social Agents
Avanesi, V., Rockstroh, J., Mildner, T., Zargham, N., Reicherts, L., Friehs, M. A., Kontogiorgos, D., Wenig, N., & Malaka, R. (2023) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3571884.3597441 · Cited by 12 · see citing works
Wu, Y., Porcheron, M., Doyle, P. R., Edwards, J., Rough, D., Cooney, O., Bleakley, A., Clark, L., & Cowan, B. R. (2022) · International Conference on Conversational User Interfaces · doi:10.1145/3543829.3543839 · Cited by 12 · see citing works
Self-citationRapp, A. (2023) · Oxford Research Encyclopedia of Psychology · doi:10.1093/acrefore/9780190236557.013.47 · Cited by 10 · see citing works
Nuñez, T. R., Jakobowsky, C., Prynda, K., Bergmann, K., & Pütten, A. M. R.-V. D. (2023) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2023.103093 · Cited by 10 · see citing works
Tickling Proactivity: Exploring the Use of Humor in Proactive Voice Assistants
Zargham, N., Reicherts, L., Avanesi, V., Rogers, Y., & Malaka, R. (2023) · International Conference on Mobile and Ubiquitous Multimedia (MUM) · doi:10.1145/3626705.3627777 · Cited by 9 · see citing works
Cross-Cultural Validation of Partner Models for Voice User Interfaces
Seaborn, K., Gessinger, I., Yoshida, S., Cowan, B. R., & Doyle, P. R. (2024) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3640794.3665537 · Cited by 9 · see citing works
Self-citationUnderstanding Task Differences to Leverage the Usability and Adoption of Voice Assistants (VAs)
Motta, I., & Quaresma, M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-78227-6_35 · Cited by 9 · see citing works
ReflectPal: Exploring Self-Reflection on Collaborative Activities Using Voice Assistants
Papachristos, E., Meldgaard, D. P., Thomsen, I. R., & Skov, M. B. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-85610-6_12 · Cited by 8 · see citing works
Perception of Power and Distance in Human-Human and Human-Robot Role-Based Relations
Lumer, E., & Buschmeier, H. (2022) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1109/hri53351.2022.9889308 · Cited by 8 · see citing works
Bucher, A. M., Dolata, M., Eckhardt, S., Staehelin, D., & Schwabe, G. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3633072 · Cited by 7 · see citing works
LGBTQ-AI? Exploring Expressions of Gender and Sexual Orientation in Chatbots
Edwards, J., Clark, L., & Perrone, A. (2021) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3469595.3469597 · Cited by 7 · see citing works
Self-citationMahmood, A., Wang, J., & Huang, C.-M. (2026) · ACM Transactions on Accessible Computing · doi:10.1145/3796236 · Cited by 6 · see citing works
“Our data demonstrate that older adults adopt human dialogue as a metaphor for interaction with VAs [16, 20], which can be attributed to two factors: 1) speech interfaces are increasingly designed and marketed to emulate the nuances of human speech [23, 26] and 2) speech alone as interaction…”
Give and Take: Perceptions of a Conversational Coach Agent in Fitness Trackers MHCI014
Loerakker, M. B., Stefanidi, E., Niess, J., Mildner, T., & Woźniak, P. W. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3743718 · Cited by 6 · see citing works
Exploring the Effects of Self-Mockery to Improve Task-Oriented Chatbot’s Social Intelligence
Liu, C., Zhou, S., Zhang, Y., Liu, D., Peng, Z., & Ma, X. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533461 · Cited by 6 · see citing works
Understanding User Preferences of Voice Assistant Answer Structures for Personal Health Data Queries
Rey, B., Sakamoto, Y., Sin, J., & Irani, P. (2024) · International Conference on Conversational User Interfaces · doi:10.1145/3640794.3665552 · Cited by 7 · see citing works
Seaborn, K., Altmeyer, M., Li, G., Ku, B., Kobuki, S., & Urakami, J. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103576 · Cited by 7 · see citing works
Human Speakers Help Machine Listeners To account For Visual Asymmetries in Dialogue
Peña, P. R., Doyle, P. R., Garaialde, D., Wu, Y., McDonnell, R., & Cowan, B. R. (2023) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3571884.3597124 · Cited by 5 · see citing works
Self-citationUsing Playful Metaphors to Conceptualize Practical Use of ChatGPT : An Autoethnography
Desai, S., & Twidale, M. B. (2023) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.816 · Cited by 5 · see citing works
Barzilai, G., & Rampino, L. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-49760-6_2 · Cited by 5 · see citing works
Beyond the Illusion: LLMs and the Case for Pragmatic Cues in Conversation
Spillner, L., Rockstroh, J., Peña, P. R., Wenig, N., Zargham, N., & Cowan, B. R. (2025) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3719160.3737614 · Cited by 4 · see citing works
Self-citationSteeds, M., Claudy, M., Cowan, B. R., & Suri, A. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103683 · Cited by 4 · see citing works
Self-citationRapp, A., Lodovico, C. D., & Di, L. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2632156 · Cited by 4 · see citing works
Are you sure you want to order that?
Dubiel, M., Bongard-Blanchy, K., Leiva, L. A., & Sergeeva, A. (2023) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3571884.3604312 · Cited by 4 · see citing works
"Let's Face It": Investigating User Preferences for Virtual Humanoid Home Assistants
Zargham, N., Alexandrovsky, D., Mildner, T., Porzel, R., & Malaka, R. (2023) · International Conference on Human-Agent Interaction (HAI) · doi:10.1145/3623809.3623821 · Cited by 4 · see citing works
Climbing the Ladder: How Agents Reach Counterfactual Thinking
Moruzzi, C. (2022) · International Conference on Agents and Artificial Intelligence (ICAART) · doi:10.5220/0010857900003116 · Cited by 4 · see citing works
Understanding Online Discussion Experiences of Blind Screen Reader Users
Ferdous, M. J., Nayak, A. K., Prakash, Y., Venkatraman, N., Jayarathna, S., Lee, H.-N., & Ashok, V. G. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2589865 · Cited by 3 · see citing works
Li, S., Yuan, X., Zhao, X., & Yang, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-35678-0_9 · Cited by 3 · see citing works
Devising Scrutable User Models for Time Management Assistants
Jeromela, J., & Conlan, O. (2024) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3631700.3665182 · Cited by 3 · see citing works
Oh, J., Im, H., & Lee, S. (2024) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3640794.3665880 · Cited by 3 · see citing works
Villa, L., Hervás, R., Cabañero, L., Fontecha, J., López, G., & Favela, J. (2025) · Behaviour and Information Technology · doi:10.1080/0144929x.2025.2546976 · Cited by 3 · see citing works
Will the Assistant Become the Driver, and the Driver Become the Assistant?
Meck, A.-M., Sardone, M., & Cullmann, J. (2023) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3571884.3603753 · Cited by 3 · see citing works
Mathur, M., Mandhyana, Y., & Chaudhuri, M. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-50518-8_2 · Cited by 3 · see citing works
Kaate, I., Salminen, J. O., Jung, S., Xuan, T. T. T., Azem, J. Y., Santos, J. M., & Jansen, B. J. J. (2025) · Designing Interactive Systems Conference · doi:10.1145/3715336.3735676 · Cited by 3 · see citing works
Beyond Subservience: Using Joint Commitment to Enable Proactive CUIs for Mood Logging
Bowman, R., Cowan, B. R., Thieme, A., & Doherty, G. J. (2022) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3543829.3544512 · Cited by 3 · see citing works
Self-citationComparing Perceptions of Static and Adaptive Proactive Speech Agents
Edwards, J., Doyle, P. R., Branigan, H. P., & Cowan, B. R. (2024) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3640794.3665548 · Cited by 2 · see citing works
Self-citationThe Importance of Timing—An Expert Evaluation on Latencies for Voice Assistants
Sogemeier, D., Forster, Y., Naujoks, F., Krems, J. F., & Keinath, A. (2024) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/10711813241260290 · Cited by 2 · see citing works
Oh, J., Choi, Y. J., & Lee, S.-S. (2025) · Conference on Designing Interactive Systems · doi:10.1145/3715336.3735763 · Cited by 2 · see citing works
VoxVista: Enhancing Screen Reading Experience for Online User Comments
Prakash, Y., Nayak, A. K., Alyaan, S. M., Jayarathna, S., Lee, H.-N., & Ashok, V. G. (2026) · Conference on Human Information Interaction and Retrieval · doi:10.1145/3786304.3788850 · Cited by 1 · see citing works
Liao, Q., Zhang, S., Wang, M., Li, J., Wang, X., & Deng, X. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-49062-1_14 · Cited by 1 · see citing works
Embrace your incompetence! Designing appropriate CUI communication through an ecological approach
Becker, S., Doyle, P. R., & Edwards, J. (2022) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3543829.3544531 · Cited by 1 · see citing works
Self-citationHarth, J. (2024) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2024.100063 · Cited by 1 · see citing works
Virtual Personal Assistant Design Effects on Memory Encoding
Chesser, A. F., Bramlett, K. N., Atchley, A., Gray, C. E., & Tenhundfeld, N. L. (2022) · Systems and Information Engineering Design Symposium · doi:10.1109/sieds55548.2022.9799387
Exploring users' mental models of conversational agents: a systematic review
Cena, F., & Grasso, F. (2025) · Behaviour and Information Technology · doi:10.1080/0144929x.2025.2573436
Is ChatGPT Gender-Neutral? Implicit Stereotyping Persists Over Time and With Experience
Steeds, M., Seaborn, K., Fujii, T., Cooney, O., & Gessinger, I. (2026) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3816046.3816201
Wang, Z.-R. (2026) · SHS Web of Conferences · doi:10.1051/shsconf/202623602010
- Authors
- Doyle, P. R., Edwards, J., Dumbleton, O., Clark, L., & Cowan, B. R.
- Affiliations
- University College Dublin (IE)
- Venue
- Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services
- Publisher
- ACM
- Published
- 2019-10
- Pages
- 1-12
- OpenAlex
- W2965031209
- Cited by
- 100
- References
- 34
- Citations by year
- 2026: 5 · 2025: 14 · 2024: 22 · 2023: 18 · 2022: 16 · 2021: 17 · 2020: 8
- FWCI
- 3.92
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Voysis ltd (EBP/2017/513)
- Irish Research Council for the Humanities and Social Sciences (EBP/2017/513)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- humanness, virtual assistants, speech interfaces, user perception, human-computer interaction, repertory grid technique, human connection, voice quality, partner identity, conversation
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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