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Article published In: Socially Acceptable Robot Behavior: Approaches for Learning, Adaptation and Evaluation
Edited by Oliver Roesler, Elahe Bagheri, Amir Aly, Silvia Rossi and Rachid Alami
[Interaction Studies 23:3] 2022
► pp. 469–512

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Towards socially-competent and culturally-adaptive artificial agents

Expressive order, interactional disruptions and recovery strategies

ORCiD logo with link | University of Trento | Italian National Research Council (CNR)
ORCiD logo with link | University of Trento
ORCiD logo with link | Italian National Research Council (CNR)
 | University of Trento
Published online: 21 April 2023
DOI logo with link
https://doi.org/10.1075/is.22021.bas
Abstract
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, 121, 639–657. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
Bassetti, C., & Liberman, K. (2021). Making talk together: Simultaneity and rhythm in mundane Italian conversation. Language and Communication, 801, 95–113. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
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.Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
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, 811, 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.Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
Collins, R. (2004). Interaction ritual chains. Princeton University Press. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
Drew, P., Heritage, J., Lerner, G., & Pomerantz, A. (Eds.) (2015). Talking about troubles in conversation. Oxford University Press. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
Fitzgerald, R., & Housley, W. (Eds.) (2015). Advances in Membership categorization Analysis. Sage. Google Scholar logo with link to Google Scholar
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). Google Scholar logo with link to Google Scholar
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).Google Scholar logo with link to Google Scholar
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.Google Scholar logo with link to Google Scholar
(1967). Studies in Ethnomethodology. Prentice–Hall.Google Scholar logo with link to Google Scholar
(2002). Ethnomethodology’s program: working out Durkheim’s aphorism. Rowman & Littlefield Publishers.Google Scholar logo with link to Google Scholar
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). Google Scholar logo with link to Google Scholar
Goffman, E. (1959). The presentation of self in everyday life. Anchor Books.Google Scholar logo with link to Google Scholar
(1961). Encounters: two studies in the sociology of interaction. Bobbs–Merrill.Google Scholar logo with link to Google Scholar
(1967). Interaction ritual: essays on face-to-face behavior. Aldine Publishing.Google Scholar logo with link to Google Scholar
(1974). Frame analysis: an essay on the organization of experience. Harper & Row.Google Scholar logo with link to Google Scholar
(1981). Forms of talk. University of Pennsylvania Press.Google Scholar logo with link to Google Scholar
(1983). The interaction order. American Sociological Review, 48(1), 1–17. Google Scholar logo with link to Google Scholar
Goodwin, C., & Heritage, J. (1990). Conversation Analysis. Annual Review of Anthropology, 19(1), 283–307. Google Scholar logo with link to Google Scholar
Guye-Vuilleme, A., & Thalmann, D. A. (2000). High-level architecture for believable social agents. Virtual Reality 5(2), 95–106. Google Scholar logo with link to Google Scholar
hooks, B. (2014). Feminist Theory: from margin to center (3rd ed.). Routledge. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
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). Google Scholar logo with link to Google Scholar
Katz, Y. (2020). Artificial Whiteness: Politics and Ideology in Artificial Intelligence. Columbia University Press. Google Scholar logo with link to Google Scholar
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.Google Scholar logo with link to Google Scholar
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). Google Scholar logo with link to Google Scholar
Liberman, K. (2013). More Studies in Ethnomethodology. State University of New York Press.Google Scholar logo with link to Google Scholar
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, 131, 1307–1333. Google Scholar logo with link to Google Scholar
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). Google Scholar logo with link to Google Scholar
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).Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
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).Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
Moore, R., & Arar, R. (2019). Conversational UX Design: A Practitioner’s Guide to the Natural Conversation Framework. Association for Computing Machinery. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
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, 51, 114. Google Scholar logo with link to Google Scholar
Onyeulo, E. B., & Gandhi, V. (2020). What makes a social robot good at interacting with humans?. Information, 111, 43. Google Scholar logo with link to Google Scholar
Honig, S., & Oron-Gilad, T. (2018). Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development. Frontiers in Psychology, 91, 861. Google Scholar logo with link to Google Scholar
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, 311, 587–593. Google Scholar logo with link to Google Scholar
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.Google Scholar logo with link to Google Scholar
Pustejovsky, J., & Krishnaswamy, N. (2021). Embodied human computer interaction. KI-Künstliche Intelligenz, 35(3), 307–327. Google Scholar logo with link to Google Scholar
Raymond, G., Hayashi, M., & Sidnell, J. (Eds.) (2013). Conversational Repair and Human Understanding. Cambridge University Press. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
Sacks, H. (1992). Lectures on conversation. Blackwell.Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
Tavory, I., & Fine, G. A. (2020). Disruption and the theory of the interaction order. Theory and Society, 491, 365–385. Google Scholar logo with link to Google Scholar
Thomas, W. I. (1923). The Unadjusted Girl: With Cases and Standpoint for Behavior Analysis. Little, Brown.Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
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. Google Scholar logo with link to Google Scholar
Watson, D. R. (1978). Categorization, Authorization and Blame-Negotiation in Conversation. Sociology, 121, 105–113. Google Scholar logo with link to Google Scholar
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