Modeling People-AI Interaction: A Case Discussion with Using an Interaction Design Language

  • Juliana Jansen FerreiraEmail author
  • Ana Fucs
  • Vinícius Segura
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11584)


Artificial Intelligent (AI) system development is the current challenge for all areas related to software development practice and research, including Human-Computer Interaction (HCI). Most AI systems’ research has been focused on the performance and accuracy of Machine Learning (ML) algorithms. Recently, new research questions concerning people in the loop of AI systems development and behavior have been emerging such as bias, reasoning, and explainability. In this new people and AI systems scenario, humans and computers collaborate, using their unique and powerful capabilities in a kind of symbiosis. In this new setting, AI systems are now real social actors as they are active players in the interaction with people. Defining and understanding the behavior of an AI system and its motivation for suggestions and reasoning are definitely a complex endeavor. HCI and Software Engineering communities, with their designers and developers, use models to represent, discuss and explore different domain scenarios in different stages of the software development process. In this paper, we present and discuss a scenario represented in an interaction modeling representation and how it can enable the representation and discussion of the people-AI symbiosis.


Artificial Intelligence Interaction model User models Software models 


  1. 1.
  2. 2.
    Barbosa, S.D.J., de Paula, M.G.: Designing and evaluating interaction as conversation: a modeling language based on semiotic engineering. In: Jorge, J.A., Jardim Nunes, N., Falcão e Cunha, J. (eds.) DSV-IS 2003. LNCS, vol. 2844, pp. 16–33. Springer, Heidelberg (2003). Scholar
  3. 3.
    Biran, O., Cotton, C.: Explanation and justification in machine learning: a survey. In: Aha, D.W., et al. (eds.) IJCAI 2017 Workshop on Explainable AI (XAI), Melbourne, Australia, pp. 8–13 (2017)Google Scholar
  4. 4.
    Floridi, L., et al.: AI4People - an ethical framework for a good AI society: opportunities, risks, principles, and recommendations. Minds Mach. 28(4), 689–707 (2018)CrossRefGoogle Scholar
  5. 5.
    Funt, B.V.: Problem-solving with diagrammatic representations. Artif. Intell. 13(3), 201–230 (1980)CrossRefGoogle Scholar
  6. 6.
    Hill, C., et al.: Trials and tribulations of developers of intelligent systems: a field study. In: 2016 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), pp. 162–170. IEEE (2016)Google Scholar
  7. 7.
    Lieberman, B.A.: The Art of Software Modeling. Auerbach Publications, Boca Raton (2006)CrossRefGoogle Scholar
  8. 8.
    Muller, P.-A., et al.: Modeling. Softw. Syst. Model. 11(3), 347–359 (2012)CrossRefGoogle Scholar
  9. 9.
    Nass, C., et al.: Computers are social actors. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems Celebrating Interdependence - CHI 1994, pp. 72–78. ACM Press, Boston (1994)Google Scholar
  10. 10.
    Preece, J., et al.: Interaction Design: Beyond Human-Computer Interaction. Wiley, Chichester (2015)Google Scholar
  11. 11.
    Pressman, R.S.: Software Engineering: A Practitioner’s Approach. Palgrave Macmillan, Basingstoke (2005)zbMATHGoogle Scholar
  12. 12.
    Rossi, F., Mattei, N.: Building Ethically Bounded AI (2018). arXiv preprint: arXiv:1812.03980
  13. 13.
    Samek, W., et al.: Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models (2017). arXiv preprint: arXiv:1708.08296
  14. 14.
    Segura, V., Ferreira, J.J., Fucs, A., Moreno, M.F., de Paula, R., Cerqueira, R.: CoRgI: cognitive reasoning interface. In: Kurosu, M. (ed.) HCI 2018, Part II. LNCS, vol. 10902, pp. 398–409. Springer, Cham (2018). Scholar
  15. 15.
    The Journal of Artificial Intelligence Research (JAIR).
  16. 16.
    Unified Modeling Language (UML).

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Juliana Jansen Ferreira
    • 1
    Email author
  • Ana Fucs
    • 1
  • Vinícius Segura
    • 1
  1. 1.IBM ResearchRio de JaneiroBrazil

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