Cited by 84Innovative Human-Technology InteractionAI in Service InteractionsSpeech and dialogue systems

Understanding Circumstances for Desirable Proactive Behaviour of Voice Assistants: The Proactivity Dilemma

Zargham, Nima, Reicherts, Leon, Bonfert, Michael, Voelkel, Sarah Theres, Schoening, Johannes, Malaka, Rainer, Rogers, Yvonne·2022·Proceedings of the 4th Conference on Conversational User Interfaces

Abstract

The next major evolutionary stage for voice assistants will be their capability to initiate interactions by themselves. However, to design proactive interactions, it is crucial to understand whether and when this behaviour is considered useful and how desirable it is perceived for different social contexts or ongoing activities. To investigate people’s perspectives on proactivity and appropriate circumstances for it, we designed a set of storyboards depicting a variety of proactive actions in everyday situations and social settings and presented them to 15 participants in interactive interviews. Our findings suggest that, although many participants see benefits in agent proactivity, such as for urgent or critical issues, there are concerns about interference with social activities in multi-party settings, potential loss of agency, and intrusiveness. We discuss our implications for designing voice assistants with desirable proactive features.

Integrity signals

Registry

Crossref · 10.1145/3543829.3543834

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Participants co-writing with an LLM found that seeing the LLM's suggestions was helpful even when they did not implement them.

    “For example, participants co-writing with an LLM found that seeing the LLM's suggestions was helpful even when they did not implement them [207].”

    From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [207]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Zargham, N., Reicherts, L., Bonfert, M., Voelkel, S. T., Schoening, J., Malaka, R., & Rogers, Y.
Affiliations
  • University of Bremen (DE)
  • University College London (GB)
  • LMU Munich, Germany
  • University of St.Gallen (CH)
Venue
Proceedings of the 4th Conference on Conversational User Interfaces
Publisher
ACM
Published
2022-07-26
Pages
1-14
OpenAlex
W4295955444
Cited by
84
References
6
Citations by year
2026: 20 · 2025: 15 · 2024: 31 · 2023: 18
FWCI
12.80
Type
conference paper
Language
en
Open access
closed
Locations
  • ACM Conference on Conversational User Interfaces (CUI) (publishedVersion)
  • Alexandria (UniSG) (University of St.Gallen) (acceptedVersion)
  • Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
Keywords
voice assistants, proactive behavior, user perception, social environment, intrusiveness, loss of agency, storyboards, human-agent interaction

About these checks

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review