ABSTRACT
Conversational systems are inherently disadvantaged when indicating either what capabilities they have or the state they are in. The notion of habitability, the appropriate balancing in design between the language people use and the language a system can accept, emerged out of these early difficulties with conversational systems. This literature review aims to summarize progress in habitability research and explore implications for the design of current AI-enabled conversational systems. We found that i) the definitions of habitability focus mostly on matching between user expectations and system capabilities by employing well-balanced restrictions on language use; ii) there are two comprehensive design perspectives on different domains of habitability; iii) there is one standardized questionnaire with a sub-scale to measure habitability in a limited way. The review has allowed us to propose a working definition of habitability and some design implications that may prove useful for guiding future research and practice in this field.
- Lars Ahrenberg. 1996. Customizing Interaction for Natural Language Interfaces. Computer Information Science 1, 1.Google Scholar
- Matthew Chalmers and Areti Galani. 2004. Seamful Interweaving: Heterogeneity in the Theory and Design of Interactive Systems. In Proceedings of Proceedings of the 5th conference on Designing interactive systems: processes, practices, methods, and techniques. ACM, Cambridge, MA, USA, 243--252.Google ScholarDigital Library
- Herbert H. Clark and Susan E. Brennan. 1991. Grounding in Communication. In Perspectives on Socially Shared Cognition., American Psychological Association, Washington, DC, US, 127--149.Google Scholar
- Leigh Clark, Nadia Pantidi, Orla Cooney, Philip Doyle, Diego Garaialde, Justin Edwards, Brendan Spillane, Emer Gilmartin, Christine Murad, Cosmin Munteanu, Vincent Wade and Benjamin R. Cowan. 2019. What Makes a Good Conversation?: Challenges in Designing Truly Conversational Agents. In Proceedings of Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, Glasgow, Scotland UK, 1--12.Google Scholar
- E. Coiera. 2000. When Conversation Is Better Than Computation. Journal of the American Medical Informatics Association : JAMIA 7, 3, 277--286.Google ScholarCross Ref
- Benjamin R. Cowan, Nadia Pantidi, David Coyle, Kellie Morrissey, Peter Clarke, Sara Al-Shehri, David Earley and Natasha Bandeira. 2017. "What Can I Help You With?": Infrequent Users' Experiences of Intelligent Personal Assistants. In Proceedings of Proceedings of the 19th International Conference on HumanComputer Interaction with Mobile Devices and Services. ACM, Vienna, Austria, 1--12.Google ScholarDigital Library
- Danica Damljanovic, Milan Agatonovic, Hamish Cunningham and Kalina Bontcheva. 2013. Improving Habitability of Natural Language Interfaces for Querying Ontologies with Feedback and Clarification Dialogues. Journal of Web Semantics 19, 1--21.Google ScholarCross Ref
- Paul Dourish and Graham Button. 1998. On "Technomethodology": Foundational Relationships between Ethnomethodology and System Design. Human-computer interaction 13, 4, 395--432.Google Scholar
- Susan L. Epstein, Joshua Gordon, Rebecca Passonneau and Tiziana Ligorio. 2010. Toward Spoken Dialogue as Mutual Agreement. In Proceedings of Proceedings of the 4th AAAI Conference on Metacognition for Robust Social Systems. AAAI Press, 14--21.Google Scholar
- Randy Goebel, Ajay Chander, Katharina Holzinger, Freddy Lecue, Zeynep Akata, Simone Stumpf, Peter Kieseberg and Andreas Holzinger. 2018. Explainable Ai: The New 42? In Proceedings of Machine Learning and Knowledge Extraction. Springer International Publishing, 295--303.Google Scholar
- Randy Allen Harris. 2004. Voice Interaction Design: Crafting the New Conversational Speech Systems. Elsevier,Google Scholar
- J. Hecht. 2018. Managing Expectations of Artificial Intelligence. Nature 563, 7733, S141-s143.Google Scholar
- Kate S Hone and Chris Baber. 2001. Designing Habitable Dialogues for Speech-Based Interaction with Computers. International Journal of Human-Computer Studies 54, 4, 637--662.Google ScholarDigital Library
- Kate S Hone and Robert Graham. 2000. Towards a Tool for the Subjective Assessment of Speech System Interfaces (SASSI). Natural Language Engineering 6, 3--4, 287--303.Google ScholarDigital Library
- Kate S Hone and Robert Graham. 2001. Subjective Assessment of Speech-System Interface Usability. In Proceedings of Seventh European Conference on Speech Communication and Technology.Google ScholarCross Ref
- Arne Jönsson. 1997. A Model for Habitable and Efficient Dialogue Management for Natural Language Interaction. Nat. Lang. Eng. 3, 2, 103--122.Google ScholarDigital Library
- Evangelos Karapanos, Jean-Bernard Martens and Marc Hassenzahl. 2012. Reconstructing Experiences with Iscale. International Journal of Human-Computer Studies 70, 11, 849--865.Google ScholarDigital Library
- Ahmet Baki Kocaballi, S Berkovsky, JC Quiroz, L Laranjo, HL Tong, D Rezazadegan, A Briatore and E Coiera. 2019. Personalization of Conversational Agents in Healthcare: A Systematic Review. Journal of Medical Internet Research, 21(11), e15360.Google ScholarCross Ref
- Rafal Kocielnik, Saleema Amershi and Paul N. Bennett. 2019. Will You Accept an Imperfect Ai?: Exploring Designs for Adjusting End-User Expectations of Ai Systems. In Proceedings of Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, Glasgow, Scotland Uk, 1--14.Google Scholar
- Ewa Luger and Abigail Sellen. 2016. Like Having a Really Bad Pa: The Gulf between User Expectation and Experience of Conversational Agents. In Proceedings of Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 5286--5297.Google ScholarDigital Library
- Michael McTear, Zoraida Callejas and David Griol. 2016. The Conversational Interface: Talking to Smart Devices. Springer,Google Scholar
- Robert J. Moore and Raphael Arar. 2019. Conversational UX Design: A Practitioner's Guide to the Natural Conversation Framework. ACM,Google Scholar
- Roger K Moore. 2017. Is Spoken Language All-orNothing? Implications for Future Speech-Based Human-Machine Interaction. In Dialogues with Social Robots, Springer, 281--291.Google Scholar
- Philippe Morin and Jean-Claude Junqua. 1993. Habitable Interaction in Goal-Oriented Multimodal Dialogue Systems. In Proceedings of Third European Conference on Speech Communication and Technology.Google ScholarCross Ref
- Jakob Nielsen. 1993. Usability Engineering. Morgan Kaufmann Publishers Inc.,Google ScholarDigital Library
- William C Ogden and Philip Bernick. 1997. Using Natural Language Interfaces. In Handbook of Human-Computer Interaction, Elsevier, 137--161.Google Scholar
- William Ogden, James Mcdonald, Philip Bernick and Roger Chadwick. 2008. Habitability in Question Answering Systems. In Advances in Open Domain Question Answering, Springer, 457--473.Google Scholar
- Martin Porcheron, Joel E Fischer, Stuart Reeves and Sarah Sharples. 2018. Voice Interfaces in Everyday Life. In Proceedings of Proceedings of CHI Conference on Human Factors in Computing Systems. ACM, 640.Google ScholarDigital Library
- Stuart Reeves, Martin Porcheron and Joel Fischer. 2018. 'This Is Not What We Wanted': Designing for Conversation with Voice Interfaces. Interactions 26, 1, 46--51.Google Scholar
- Harald Trost, Wolfgang Heinz, Johannes Matiasek and Ernst Buchberger. 1992. Datenbank-Dialog and the Relevance of Habitability. In Proceedings of Proceedings of the third conference on Applied natural language processing. Association for Computational Linguistics, Trento, Italy, 241--242.Google ScholarDigital Library
- William Watt. 1968. Habitability. American Documentation 19, 3, 338--351.Google ScholarCross Ref
- S. J. Young and C. E. Proctor. 1989. The Design and Implementation of Dialogue Control in Voice Operated Database Inquiry Systems. Computer Speech & Language 3, 4, 329--353.Google ScholarCross Ref
Index Terms
- Revisiting Habitability in Conversational Systems
Recommendations
Conversational Agents: Acting on the Wave of Research and Development
CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing SystemsIn the last five years, work on software that interacts with people via typed or spoken natural language, called chatbots, intelligent assistants, social bots, virtual companions, non-human players, and so on, increased dramatically. Chatbots burst into ...
How do you Converse with an Analytical Chatbot? Revisiting Gricean Maxims for Designing Analytical Conversational Behavior
CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing SystemsChatbots have garnered interest as conversational interfaces for a variety of tasks. While general design guidelines exist for chatbot interfaces, little work explores analytical chatbots that support conversing with data. We explore Gricean Maxims to ...
The Bot on Speaking Terms: The Effects of Conversation Architecture on Perceptions of Conversational Agents
CUI '23: Proceedings of the 5th International Conference on Conversational User InterfacesConversational agents mimic natural conversation to interact with users. Since the effectiveness of interactions strongly depends on users’ perception of agents, it is crucial to design agents’ behaviors to provide the intended user perceptions. ...
Comments