Towards socially-competent and culturally-adaptive artificial agents
Expressive order, interactional disruptions and recovery strategies
The development of artificial agents for social interaction pushes to enrich robots with social skills and
knowledge about (local) social norms. One possibility is to distinguish the expressive and the functional orders during a
human-robot interaction. The overarching aim of this work is to set a framework to make the artificial agent socially-competent
beyond dyadic interaction – interaction in varying multi-party social situations – and beyond individual-based user personalization,
thereby enlarging the current conception of “culturally-adaptive”. The core idea is to provide the artificial agent with the
capability to handle different kinds of interactional disruptions, and associated recovery strategies, in microsociology. The
result is obtained by classifying functional and social disruptions, and by investigating the requirements a robot’s architecture
should satisfy to exploit such knowledge. The paper also highlights how this level of competence is achieved by focusing on just
three dimensions: (i) social capability, (ii) relational role, and (iii) proximity, leaving aside the further complexity of
full-fledged human-human interactions. Without going into technical aspects, End-to-end Data-driven Architectures and Modular
Architectures are discussed to evaluate the degree to which they can exploit this new set of social and cultural knowledge.
Finally, a list of general requirements for such agents is proposed.
Article outline
- 1.Introduction
- 2.Guiding scenario: The (artificial) bartender
- 3.The expressive order of interaction
- 4.Disruptions and their recovery
- 5.Agent Architecture
- 6.Discussion
- 7.Conclusions
- Acknowledgement
- Notes
-
References
References (64)
References
Andriella, A., Torras, C., & Alenyà, G. (2020). Short-Term Human–Robot Interaction Adaptability in Real-World Environments. International Journal of Social Robotics,
12
1, 639–657.
Baraka, K., Alves-Oliveira, P., & Ribeiro, T. (2020). An extended framework for characterizing social robots. In C. Jost, B. Le Pévédic, T. Belpaeme, C. Bethel, D. Chrysostomou, N. Crook, et al. (Eds.), Human-Robot Interaction (p. 21–64). Springer Series on Bio- and Neurosystems, vol 12. Springer.
Bassetti, C., & Liberman, K. (2021). Making talk together: Simultaneity and rhythm in mundane Italian conversation. Language and Communication,
80
1, 95–113.
Benner, D., Elshan, E., Schöbel, S., & Janson, A. (2021). What do you mean? A review on recovery strategies to overcome conversational breakdowns of conversational agents. Paper presented at the International Conference on Information Systems (ICIS), Austin. Available at [URL]
Borgo, S., & Blanzieri, E. (2019). Trait-based module for culturally-competent robots. International Journal of Humanoid Robotics,
16
(6), 1950028.
Brown, P., & Levinson, S. (1978). Universals in language usage: Politeness phenomena. In: E. N. Goody (Ed.), Questions and Politeness: Strategies in Social Interaction (pp. 56–311). Cambridge University Press.
Bruno, B., Recchiuto, C. T., Papadopoulos, I., Saffiotti, A., Koulouglioti, C., Menicatti, R., Mastrogiovanni, F., Zaccaria, R., & Sgorbissa, A. (2019). Knowledge representation for culturally competent personal robots: requirements, design principles, implementation, and assessment. International Journal of Social Robotics,
11
(3), 515–538.
Buolamwini, J., & Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, in Proceedings of Machine Learning Research,
81
1, 77–91. Available from [URL]
Cain, A. (1983). A Study of Pets in the Family System. In A. Katcher, & A. Beck (Eds.), New perspectives on our lives with companion animals (pp. 71–81). University of Pennsylvania Press.
Carlucci, F. M., Nardi, L., Iocchi, L., & Nardi, D. (2015). Explicit representation of social norms for social robots. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4191–4196). IEEE.
Collins, R. (2004). Interaction ritual chains. Princeton University Press.
Cortellessa, G., Scopelliti, M., Tiberio, L., Svedberg, G. K., Loutfi, A., & Pecora, F. (2008). A cross-cultural evaluation of domestic assistive robots. In AAAI fall symposium: : Technical Report, v FS-08-02 (pp. 24–31). Retrieved from: [URL]
Crenshaw, K. (1991). Mapping the Margins: Intersectionality, Identity Politics, and Violence against Women of Color. Stanford Law Review,
43
(6), 1241–1299.
Deriu, J., Rodrigo, A., Otegi, A., Echegoyen, G., Rosset, S., Agirre, E., & Cieliebak, M. (2021). Survey on evaluation methods for dialogue systems. Artificial Intelligence Review,
54
(1), 755–810.
Drew, P., Heritage, J., Lerner, G., & Pomerantz, A. (Eds.) (2015). Talking about troubles in conversation. Oxford University Press.
Eresha, G., Haring, M., Endrass, B., Andre, E., & Obaid, M. (2013). Investigating the influence of culture on proxemic behaviors for humanoid robots. IEEE Ro-Man, 430–435.
Evers, V., Maldonado, H., Brodecki, T. L., & Hinds, P. J. (2008). Relational vs. group self-construal: Untangling the role of national culture in HRI. In Proceedings of the third ACM/IEEE International Conference on Human-Robot Interaction (pp. 255–262). Association for Computing Machinery.
Fitzgerald, R., & Housley, W. (Eds.) (2015). Advances in Membership categorization Analysis. Sage.
Foster, M. E., Gaschler, A., Giuliani, M., Isard, A., Pateraki, M., & Petrick, R. P. (2012). Two people walk into a bar: Dynamic multi-party social interaction with a robot agent. In Proceedings of the 14th ACM international conference on Multimodal interaction (pp. 3–10).
Gallo, D., Shreepriya, S., Colombino, T., Grasso, M. A., & Boulard, C. (2021). Considerations about Social Norms Compliance in a Shared Elevator Scenario. In RO-MAN 2021 Workshop on Robot Behavior Adaptation to Human Social Norms (TSAR).
Garfinkel, H. (1963). A conception of and experiments with ‘trust’ as a condition of concerted actions. In O. J. Harvey (Ed.), Motivation and Social Interaction: Cognitive Approaches (pp. 187–238). Ronald Press.
Garfinkel, H. (1967). Studies in Ethnomethodology. Prentice–Hall.
Garfinkel, H. (2002). Ethnomethodology’s program: working out Durkheim’s aphorism. Rowman & Littlefield Publishers.
Giuliani, M., Petrick, R. P. A., Foster, M. E., Gaschler, A., Isard, A., Pateraki, M., & Sigalas, M. (2013). Comparing task-based and socially intelligent behaviour in a robot bartender. In Proceedings of the 15th international conference on Multimodal interaction (pp. 263–270).
Goffman, E. (1959). The presentation of self in everyday life. Anchor Books.
Goffman, E. (1961). Encounters: two studies in the sociology of interaction. Bobbs–Merrill.
Goffman, E. (1967). Interaction ritual: essays on face-to-face behavior. Aldine Publishing.
Goffman, E. (1974). Frame analysis: an essay on the organization of experience. Harper & Row.
Goffman, E. (1981). Forms of talk. University of Pennsylvania Press.
Goffman, E. (1983). The interaction order. American Sociological Review,
48
(1), 1–17.
Goodwin, C., & Heritage, J. (1990). Conversation Analysis. Annual Review of Anthropology,
19
(1), 283–307.
Guye-Vuilleme, A., & Thalmann, D. A. (2000). High-level architecture for believable social agents. Virtual Reality
5
(2), 95–106.
hooks, B. (2014). Feminist Theory: from margin to center (3rd ed.). Routledge.
Horodeck, R. (1981). Excuses and Apologies: Discovering How They Work with the Game Excuses and Challenges. The Journal of the Association of Teachers of Japanese,
16
(2), 119–139.
Joosse, M., Poppe, R., Lohse, M., & Evers, V. (2014). Cultural differences in how an engagement-seeking robot should approach a group of people. In Proceedings of the 5th ACM international conference on Collaboration across boundaries: culture, distance & technology (pp. 121–130).
Katz, Y. (2020). Artificial Whiteness: Politics and Ideology in Artificial Intelligence. Columbia University Press.
Kendon, A. Goffman’s approach to face-to-face interaction. In: Drew, P., Wootton, A., editors. Erving Goffman: exploring the interaction order. Cambridge: Polity Press; 1988. p. 14–40.
Khaliq, A. A., Köckemann, U., Pecora, F., Saffiotti, A., Bruno, B., Recchiuto, C. T., Sgorbissa, A., Bui, H.-D., & Chong, N.-Y. (2018). Culturally aware Planning and Execution of Robot Actions. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 326–332).
Liberman, K. (2013). More Studies in Ethnomethodology. State University of New York Press.
Lim, V., Rooksby, M., & Cross, E. S. (2021). Social Robots on a Global Stage: Establishing a Role for Culture During Human–Robot Interaction. International Journal of Social Robotics,
13
1, 1307–1333.
Marge, M., & Rudnicky, A. I. (2019). Miscommunication Detection and Recovery in Situated Human–Robot Dialogue. ACM Transactions on Interactive Intelligent Systems,
9
(1), Article 3 (pp. 1–40).
Mascarenhas, S., Dias, J., Alfonso, N., Enz, S., & Paiva, A. (2009). Using rituals to express cultural differences in synthetic characters. In Proceedings of The 8th International Joint Conference on Autonomous Agents and Multiagent Systems – Volume 1 (pp. 305–312).
Mascarenhas, S., Prada, R., Paiva, A., & Hofstede, G. J. (2013a). Social Importance Dynamics: A Model for Culturally-Adaptive Agents. In R. Aylett, B. Krenn, C. Pelachaud, & H. Shimodaira (Eds.), Intelligent Virtual Agents (IVA 2013), LNCS 8108. Springer.
Mascarenhas, S., Silva, A., Paiva, A., Aylett, R., Kistler, F., André, E., Degens, N., Hofstede, G. J., & Kappas, A. (2013b). Traveller: an intercultural training system with intelligent agents. In Proceedings of the 2013 International Conference on Autonomous Agents and Multi-Agent Systems (pp. 1387–1388).
Miller, C. A., Wu, P., Vakili, V., Ott, T., & Smith, K. (2009). Culture, Politeness and Directive Compliance. In C. Stephanidis (Ed.), Universal Access in HCI, Part 1, HCII 2009 (pp. 568–577). Springer.
Moore, R., & Arar, R. (2019). Conversational UX Design: A Practitioner’s Guide to the Natural Conversation Framework. Association for Computing Machinery.
Nomura, T., Suzuki, T., Kanda, T., Han, J., Shin, N., Burke, J. L., & Kato, K. (2008). What People Assume about Humanoid and Animal-Type Robots: Cross-Cultural Analysis between Japan, Korea, and the United States. International Journal of Humanoid Robotics,
5
(1), 25–46.
Oh, C. S., Bailenson, J. N., & Welch, G. F. (2018). A Systematic Review of Social Presence: Definition, Antecedents, and Implications. Frontiers in Robotics and AI,
5
1, 114.
Onyeulo, E. B., & Gandhi, V. (2020). What makes a social robot good at interacting with humans?. Information,
11
1, 43.
Honig, S., & Oron-Gilad, T. (2018). Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development. Frontiers in Psychology,
9
1, 861.
Petrick, R., & Foster, M. E. (2013). Planning for Social Interaction in a Robot Bartender Domain. Proceedings of the International Conference on Automated Planning and Scheduling,
23
(1), 389–397. Retrieved from [URL].
Pitsch, K. (2016). Limits and opportunities for mathematizing communicational conduct for social robotics in the real world? Toward enabling a robot to make use of the human’s competences. AI & Society,
31
1, 587–593.
Pomerantz, A. (1984). Agreeing and disagreeing with assessments: some features of preferred/dispreferred turn shapes. In J. M. Atkinson, & J. C. Heritage (Eds.), Structures of Social Action: Studies in Conversation Analysis (pp. 57–101). Cambridge University Press.
Pustejovsky, J., & Krishnaswamy, N. (2021). Embodied human computer interaction. KI-Künstliche Intelligenz,
35
(3), 307–327.
Raymond, G., Hayashi, M., & Sidnell, J. (Eds.) (2013). Conversational Repair and Human Understanding. Cambridge University Press.
Rehm, M. (2010). Developing Enculturated Agents: Pitfalls and Strategies. In E. Blanchard, & D. Allard (Eds.), Handbook of Research on Culturally-Aware Information Technology: Perspectives and Models (pp. 362–386). Idea Group Publishing.
Sacks, H. (1992). Lectures on conversation. Blackwell.
Schegloff, E. A., Jefferson, G., & Sacks, H. (1977). The Preference for Self-Correction in the Organization of Repair in Conversation. Language,
53
(2), 361–382.
Tavory, I., & Fine, G. A. (2020). Disruption and the theory of the interaction order. Theory and Society,
49
1, 365–385.
Thomas, W. I. (1923). The Unadjusted Girl: With Cases and Standpoint for Behavior Analysis. Little, Brown.
Torta, E., Werner, F., Johnson, D. O., Juola, J. F., Cuijpers, R. H., Bazzani, M., & Bregman, J. (2014). Evaluation of a small socially-assistive humanoid robot in intelligent homes for the care of the elderly. Journal of Intelligent & Robotic Systems
76
(1), 57–71.
Turowetz, J., & Rawls, A. W. (2021). The development of Garfinkel’s ‘Trust’ argument from 1947 to 1967: Demonstrating how inequality disrupts sense and self-making. Journal of Classical Sociology,
21
(1), 3–37.
Wang, Y., & Kosinski, M. (2018). Deep neural networks are more accurate than humans at detecting sexual orientation from facial images. Journal of Personality and Social Psychology,
114
(2), 246–257.
Watson, D. R. (1978). Categorization, Authorization and Blame-Negotiation in Conversation. Sociology,
12
1, 105–113.
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