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Emotions in Human-AI Collaboration

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Navigating Unpredictability: Collaborative Networks in Non-linear Worlds (PRO-VE 2024)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 726))

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Abstract

This exploratory paper addresses the role of emotions in the management of collaborative networks (CNs) amid the rise of hybrid teams consisting of humans and AI agents. Building on previous research that emphasizes the critical role of emotions in fostering trust and preventing conflicts within CNs, we propose expanding these emotional frameworks to accommodate hybrid collaborative networks. The paper reviews the significance of human-AI collaboration, highlighting the complementary strengths of both and identifying three research streams: affective/sentient AI agents, human emotions modelling, and collective hybrid network emotions. Emphasizing the underexplored area of collective emotions, we suggest leveraging these insights to enhance the management and sustainability of hybrid networks. A framework for emotions estimation in CNs is described. Our aim is to identify challenges and guide future research in the integration of emotional intelligence within human-AI collaborative environments.

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References

  1. Kapucu, N., Hu, Q.: Netw. Gover. Routl (2020). https://doi.org/10.4324/9781351056540

    Article  Google Scholar 

  2. Baek, J.S., Meroni, A., Manzini, E.: A socio-technical approach to design for community resilience: a framework for analysis and design goal forming. Des. Stud. 40, 60–84 (2015). https://doi.org/10.1016/j.destud.2015.06.004

    Article  Google Scholar 

  3. Paula Urze, A., Osório, L., Afsarmanesh, H., Camarinha-Matos, L.M.: A balanced sociotechnical framework for collaborative networks 4.0. In: Camarinha-Matos, L.M., Afsarmanesh, H., Ortiz, A. (eds.) Boosting Collaborative Networks 4.0. IAICT, vol. 598, pp. 485–498. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-62412-5_40

    Chapter  Google Scholar 

  4. Beckett, R.C., Jones, M.: Collaborative network success and the variable nature of trust. Prod. Plan. Control 23, 240–251 (2012). https://doi.org/10.1080/09537287.2011.627654

    Article  Google Scholar 

  5. Msanjila, S.S., Afsarmanesh, H.: On modelling evolution of trust in organisations towards mediating collaboration. Prod. Plan. Control 22, 518–537 (2011). https://doi.org/10.1080/09537287.2010.536623

    Article  Google Scholar 

  6. Ferrada, F., Camarinha-Matos, L.M.: A modelling framework for collaborative network emotions. Enterp. Inf. Syst. 13, 1164 (2019). https://doi.org/10.1080/17517575.2019.1633583

    Article  Google Scholar 

  7. Ferrada, F., Camarinha-Matos, L.M.: Simulation model to estimate emotions in collaborative networks. Appl. Sci. (Switzerland). 9, 5202 (2019). https://doi.org/10.3390/app9235202

    Article  Google Scholar 

  8. Peeters, M.M.M., et al.: Hybrid collective intelligence in a human–AI society. AI Soc. 36, 217–238 (2021). https://doi.org/10.1007/s00146-020-01005-y

    Article  Google Scholar 

  9. Hemmer, P., Schemmer, M., Vössing, M., Kühl, N.: Human-AI Complementarity in Hybrid Intelligence Systems: A Structured Literature Review (2021)

    Google Scholar 

  10. Bosch, K., Schoonderwoerd, T., Blankendaal, R., Neerincx, M.: Six challenges for human-AI co-learning. In: Sottilare, R.A., Schwarz, J. (eds.) Adaptive Instructional Systems. LNCS, vol. 11597, pp. 572–589. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22341-0_45

    Chapter  Google Scholar 

  11. Camarinha-Matos, L.M., Afsarmanesh, H.: The evolution path to collaborative networks 4.0. In: Goedicke, M., Neuhold, E., Rannenberg, K. (eds.) Advancing Research in Information and Communication Technology: IFIP’s Exciting First 60+ Years, Views from the Technical Committees and Working Groups. IFIPAICT, vol. 600, pp. 170–193. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-81701-5_7

    Chapter  Google Scholar 

  12. Watzek, V., Rehm, M., Mulder, R.H.: Exploring dynamics of emotional reactions in online collaboration of communities of learners and their relations with learning outcomes. Interact. Learn. Environ. 32, 90–101 (2024). https://doi.org/10.1080/10494820.2022.2078985

    Article  Google Scholar 

  13. van Kleef, G.A., Côté, S.: The social effects of emotions. Annu. Rev. Psychol. 73, 629–658 (2022). https://doi.org/10.1146/annurev-psych-020821-010855

    Article  Google Scholar 

  14. Zhang, G., Lu, D., Jia, X.: Emotional contagion in physical-cyber integrated networks: the phase transition perspective. IEEE Trans Cybern. 52, 7875–7888 (2022). https://doi.org/10.1109/TCYB.2021.3052766

    Article  Google Scholar 

  15. Block, P., Burnett Heyes, S.: Sharing the load: contagion and tolerance of mood in social networks. Emotion 22, 1193–1207 (2022). https://doi.org/10.1037/emo0000952

    Article  Google Scholar 

  16. de Sousa, R.: Emotion, http://plato.stanford.edu/entries/emotion/

  17. Behnke, M., Saganowski, S., Kaczmarek, Ł.D., Kazienko, P.: Emotions studied by computer scientists and psychologists—a complementary perspective. In: 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). pp. 206–211. IEEE (2023). https://doi.org/10.1109/PerComWorkshops56833.2023.10150393

  18. Lazarus, R.S.: Progress on a cognitive-motivational-relational theory of emotion. Am. Psychol. 46, 819–834 (1991). https://doi.org/10.1037/0003-066X.46.8.819

    Article  Google Scholar 

  19. Picard, R.W.: Affective computing: challenges. Int. J. Hum. Comput. Stud. 59, 55–64 (2003). https://doi.org/10.1016/S1071-5819(03)00052-1

    Article  Google Scholar 

  20. Perez-Aranda, J., Medina-Claros, S., Urrestarazu-Capellán, R.: Effects of a collaborative and gamified online learning methodology on class and test emotions. Educ. Inf. Technol (Dordr). 29, 1823–1855 (2024). https://doi.org/10.1007/s10639-023-11879-2

    Article  Google Scholar 

  21. Xu, W., Lou, Y.-F.: Changes in the socially shared regulation, academic emotions, and product performance in venue-based collaborative learning. Active Learn. Higher Edn. 146, 978–1167 (2023). https://doi.org/10.1177/14697874231167331

    Article  Google Scholar 

  22. Avry, S., Molinari, G., Bétrancourt, M., Chanel, G.: Sharing emotions contributes to regulating collaborative intentions in group problem-solving. Front. Psychol. 11, 1160 (2020). https://doi.org/10.3389/fpsyg.2020.01160

    Article  Google Scholar 

  23. Bin, S.: Social network emotional marketing influence model of consumers’ purchase behavior. Sustainability. 15, 5001 (2023). https://doi.org/10.3390/su15065001

    Article  Google Scholar 

  24. Lewenberg, Y., Bachrach, Y., Volkova, S.: Using emotions to predict user interest areas in online social networks. In: 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA). pp. 1–10. IEEE (2015). https://doi.org/10.1109/DSAA.2015.7344887

  25. Aguado, G., Julian, V., Garcia-Fornes, A.: Multi-agent system for privacy protection through user emotions in social networks. In: Bajo, J., et al. (eds.) Highlights of Practical Applications of Cyber-Physical Multi-Agent Systems, pp. 235–245. Springer International Publishing, Cham (2017)

    Chapter  Google Scholar 

  26. Russell, J.A.: A circumplex model of affect. J. Pers. Soc. Psychol. 39, 1161–1178 (1980). https://doi.org/10.1037/h0077714

    Article  Google Scholar 

  27. Velásquez, J.D.: Cathexis: A Computational Model for the Generation of Emotions and Their Influence in the Behavior of Autonomous Agents, (1996)

    Google Scholar 

  28. Becker-Asano, C., Wachsmuth, I.: WASABI as a Case Study of How Misattribution of Emotion Can Be Modelled Computationally. In: A Blueprint for Affective Computing: A Sourcebook and Manual. pp. 179–193. Oxford University Press (2010)

    Google Scholar 

  29. Breazeal, C.: Emotion and sociable humanoid robots. Int. J. Hum. Comput. Stud. 59, 119–155 (2003). https://doi.org/10.1016/S1071-5819(03)00018-1

    Article  Google Scholar 

  30. Wilson, J., Daugherty, P.R.: Collaborative Intelligence: Humans and AI Are Joining Forces. Harv Bus Rev. 114–123 (2018)

    Google Scholar 

  31. Gupta, P., Nguyen, T.N., Gonzalez, C., Woolley, A.W.: Fostering collective intelligence in human–AI collaboration: laying the groundwork for COHUMAIN. Top. Cogn. Sci. (2023). https://doi.org/10.1111/tops.12679

    Article  Google Scholar 

  32. Richter, S., Richter, A.: Human-AI Collaboration in the Metaverse – How to Research the Future of Work? In: Proceedings of ECIS 2024-32nd European Conference on Information Systems. , Paphos, Cyprus (2024)

    Google Scholar 

  33. Zheng, Q., Gou, J., Camarinha-Matos, L.M., Zhang, J.Z., Zhang, X.: Digital capability requirements and improvement strategies: Organizational socialization of AI teammates. Inf. Process. Manag. 60, 103504 (2023). https://doi.org/10.1016/j.ipm.2023.103504

    Article  Google Scholar 

  34. Deloitte Insights: The social enterprise in a world disrupted: Leading the shift from survive to thrive, https://www2.deloitte.com/content/dam/insights/us/articles/6935_2021-HC-Trends/di_human-capital-trends.pdf, (2021)

  35. European Commission: AI Act, https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai, last accessed 2024/05/10

  36. Pereira, L.M., Lopes, A.B.: Machine Ethics: From Machine Morals to the Machinery of Morality. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-39630-5

    Book  Google Scholar 

  37. Pereira, L.M., Saptawijaya, A.: Programming Machine Ethics. Springer International Publishing, Cham (2016). https://doi.org/10.1007/978-3-319-29354-7

    Book  Google Scholar 

  38. Sharma, A., Lin, I.W., Miner, A.S., Atkins, D.C., Althoff, T.: Human–AI collaboration enables more empathic conversations in text-based peer-to-peer mental health support. Nat Mach Intell. 5, 46–57 (2023). https://doi.org/10.1038/s42256-022-00593-2

    Article  Google Scholar 

  39. Mallick, R., Flathmann, C., Lancaster, C., Hauptman, A., McNeese, N., Freeman, G.: The pursuit of happiness: the power and influence of AI teammate emotion in human-AI teamwork. Behav. Inf. Technol. (2023). https://doi.org/10.1080/0144929X.2023.2277909

    Article  Google Scholar 

  40. McDuff, D., Czerwinski, M.: Designing emotionally sentient agents. Commun. ACM 61, 74–83 (2018). https://doi.org/10.1145/3186591

    Article  Google Scholar 

  41. Camarinha-Matos, L.M., Afsarmanesh, H.: Towards a Reference Model for Collaborative Networked Organizations. In: Information Technology for Balanced Manufacturing Systems. BASYS 2006. Springer: Boston, MA, pp. 193–202 (2006). https://doi.org/10.1007/978-0-387-36594-7_21

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Acknowledgements

This work was supported in part by the Portuguese FCT program UIDB/00066/2020 (Center of Technology and Systems – CTS).

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Authors and Affiliations

  1. NOVA School of Science and Technology, UNINOVA-CTS and LASI, Universidade Nova de Lisboa-DEEC, 2829-516, Caparica, Portugal

    Filipa Ferrada & Luis M. Camarinha-Matos

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  1. Filipa Ferrada
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  2. Luis M. Camarinha-Matos
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Correspondence to Filipa Ferrada .

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Editors and Affiliations

  1. NOVA University Lisbon, Monte Caparica, Portugal

    Luis M. Camarinha-Matos

  2. Polytechnic University of Valencia, Valencia, Spain

    Angel Ortiz

  3. Mines Saint-Etienne Univ Clermont, Saint-Etienne, France

    Xavier Boucher

  4. IMT Mines Albi, Albi, France

    Anne-Marie Barthe-Delanoë

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Ferrada, F., Camarinha-Matos, L.M. (2024). Emotions in Human-AI Collaboration. In: Camarinha-Matos, L.M., Ortiz, A., Boucher, X., Barthe-Delanoë, AM. (eds) Navigating Unpredictability: Collaborative Networks in Non-linear Worlds. PRO-VE 2024. IFIP Advances in Information and Communication Technology, vol 726. Springer, Cham. https://doi.org/10.1007/978-3-031-71739-0_7

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  • DOI: https://doi.org/10.1007/978-3-031-71739-0_7

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