The DOI matches its Crossref record, with a small difference in title or year; 1 of the 1 references it cites were found in a registry or an index.
“I Don't Know Exactly but I Know a Little”: Exploring Better Responses of Conversational Agents with Insufficient Information
Abstract
Despite the increasing presence of conversational agents (CAs) in our daily lives, the lack of information and technology behind them prevents CAs from answering many questions. One of the most typical problems facing conversational user interfaces today is that they often disappoint people by giving the same answer (e.g., “I don't know”). In this work, we focused on situations in which CAs do not provide a proper answer because of a lack of information. Under these situations, we aimed to find more effective answer strategies for CAs to provide people better user experiences. We tested four different response strategies using different degrees of inferences and information as ground. We found differences in usability and user experience depending on how CAs respond. Our results will help designers understand how people feel about the way CAs respond and create better CA responses in situations where it is difficult to provide accurate answers.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“negatively impacting user experience and damaging the overall effectiveness of SDS performance [5, 18, 41, 44].”
From System and User Strategies to Repair Conversational Breakdowns of Spoken Dialogue Systems: A Scoping Review (2024) · cites this paper as [41]
Citations
Cites
Assessing the Utility of the System Usability Scale for Evaluating Voice-based User Interfaces
Ghosh, D., Foong, P. S., Zhang, S., & Zhao, S. (2018) · Proceedings of the Sixth International Symposium of Chinese CHI · doi:10.1145/3202667.3204844 · Cited by 36
Research works printed but not linked: 14
- Bangor A. Kortum P.T. and Miller J.T. 2008. An empirical evaluation of the system usability scale. Intl. Journal of Human–Computer Interaction 24.6 (2008) 574-594. · DOI · Paper page
- 10.1145/3264901 · DOI · Paper page
- 10.1007/978-1-4020-6821-8_6 · DOI
- 10.1145/3322276.3322332 · DOI · Paper page
- Dahlbäck N. Jönsson A. and Ahrenberg L. Wizard of Oz studies—why and how. Knowledge- based systems 6.4 (1993): 258-266. https://dx.doi.org/10.1016/0950-7051(93)90017-N · DOI · Paper page
- Engelhardt P.E. Bailey K.G.D. and Ferreira F. 2006. Do speakers and listeners observe the Gricean Maxim of Quantity?. Journal of Memory and Language 54.4(2006) 554-573. · DOI
- 10.1145/2858036.2858288 · DOI · Paper page
- Hirst G. McRoy S. Heeman P. Edmonds P. and Horton D. 1994. Repairing conversational misunderstandings and non-understandings. Speech communication 15.3-4: 213-229. https://doi.org/10.1016/0167-6393(94)90073-6 · DOI
- 10.1007/978-3-7091-2670-7_44 · DOI
- 10.1007/978-3-319-20916-6_27 · DOI
- 10.1145/3342775.3342795 · DOI
- Paek, T., and Horvitz, E. 2000. Conversation as action under uncertainty. In Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence (UAI’00). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 455–464.
- Sanders, G.A., Le, A.N., and Garofolo, J.S. 2002. Effects of word error rate in the DARPA Communicator data during 2000 and 2001. Seventh International Conference on Spoken Language Processing.
- 10.1145/3173574.3173782 · DOI · Paper page
Cited by
Sorted by citations
Kuang, E., Soure, E. J., Fan, M., Zhao, J., & Shinohara, K. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581247 · Cited by 56
“Although participants in this study liked that the AI assistant admitted knowledge gaps, responses that only contain “I don’t know” may lead to negative perceptions of its usability [47].”
BackgroundWhat's The Talk on VUI Guidelines? A Meta-Analysis of Guidelines for Voice User Interface Design
Murad, C., Candello, H., & Munteanu, C. (2023) · Proceedings of the 5th International Conference on Conversational User Interfaces · doi:10.1145/3571884.3597129 · Cited by 36
“Numerous usability challenges are still encountered [26], including difficulties recalling information [88], system feedback [26, 59, 62], recognition”
BackgroundAlghamdi, E., Halvey, M., & Nicol, E. (2024) · ACM Conversational User Interfaces 2024 · doi:10.1145/3640794.3665558 · Cited by 36
“Furthermore, they often prevent users from completing tasks, leading to task aban-donment [5], negatively impacting user experience and damaging the overall effectiveness of SDS performance [5, 18, 41, 44].”
BackgroundAlloatti, F., Grasso, F., Ferrod, R., Siragusa, G., Di, L., & Cena, F. (2024) · Computer Speech & Language · doi:10.1016/j.csl.2023.101603 · Cited by 9
“…dialogue systems, whereas CAs should help humans attain a task (Seeger and Heinzl, 2021; Følstad and Brandtzaeg, 2020; Ashktorab et al., 2019). e CAs often fail at the understanding level, that is, when they are not capable of correctly parsing an input in natural language (Lee and Lee, 2021).”
BackgroundFrom Human-to-Human to Human-to-Bot Conversations in Software Engineering
Khojah, R., Neto, F. G. D. O., & Leitner, P. (2024) · ACM International Conference on AI-Powered Software (AIware) · doi:10.1145/3664646.3664761 · Cited by 2
“To evaluate the effectiveness of chatbots and how they can support software engineers, current research focuses on the quality [3], usability [7], and helpfulness [8] of the chatbot’s outcome.”
Background
Metadata
- Authors
- Lee, M., & Lee, S.
- Affiliations
- Korea Advanced Institute of Science and Technology (KR)
- Venue
- Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2021-05-08
- Pages
- 1-5
- OpenAlex
- W3160374727
- Cited by
- 5
- References
- 16
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 2
- FWCI
- 0.46
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- chatbots, insufficient information, answer strategies, response strategies, inference, user experience, usability, conversational interfaces
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
