Social Consensus: Contribution to Design Methods for AI Agents That Employ Personal Data

  • Milica PavlovicEmail author
  • Francesco Botto
  • Margherita Pillan
  • Carmen Criminisi
  • Massimo Valla
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 903)


The emerging complex IoT ecosystems, embodied through Artificially Intelligent (AI) Agents on the front-end interaction with the user, rise many new considerations to be taken into account during the design process, among which the use of sensitive personal data. This paper introduces a case study, a concluded project of a system supported by AI algorithms for delivering tailored services to the drivers, including insurance offerings and supporting drivers in practicing safer driving style. We report on a segment of user studies done within this project that relates to the use of personal data, and we discuss the notion of emerged user values within. Accordingly, we observe and propose inclusion of social consensus considerations within the design process and evaluation of the same.


Design methods Human-systems integration AI agents Personal data Social consensus 



This work has been partially funded by TIM S.p.A., Services Innovation Department, Joint Open Lab Digital Life, Milan, Italy.


  1. 1.
    Arslan, P., Casalegno, F., Giusti, L., Ileri, O., Kurt, O.F., Ergüt, S.: Big Data as a Source for Designing Services. Web (2017)Google Scholar
  2. 2.
    Colombo, S.: Morals, ethics, and the new design conscience. In: Rampino, L. (eds.) Evolving Perspectives in Product Design: From Mass Production to Social Awareness. Franco-Angeli (2018)Google Scholar
  3. 3.
    Friedman, B., Kahn, P.H., Borning, A., Huldtgren, A.: Value sensitive design and information systems. In: Early Engagement and New Technologies: Opening Up the Laboratory, pp. 55–95. Springer, Dordrecht (2013)CrossRefGoogle Scholar
  4. 4.
    Kalbach, J.: Mapping Experiences: A Complete Guide to Creating Value Through Journeys, Blueprints, and Diagrams. O’Reilly Media, Inc. (2016)Google Scholar
  5. 5.
    Kankainen, A., Vaajakallio, K., Kantola, V., Mattelmäki, T.: Storytelling group—a co-design method for service design. Behav. Inf. Technol. 31(3), 221–230 (2012)CrossRefGoogle Scholar
  6. 6.
    Krueger, R.A.: Focus Groups: A Practical Guide for Applied Research. Sage Publications (2014)Google Scholar
  7. 7.
    Mitchell, W.J.: Me++: The Cyborg Self and The Networked City. MIT Press (2004)Google Scholar
  8. 8.
    Pillan, M., Varisco, L., Bertolo, M.: Facing digital dystopias: a discussion about responsibility in the design of smart products. In: Proceedings of the Conference on Design and Semantics of Form and Movement—Sense and Sensitivity, DeSForM 2017. InTech (2017)Google Scholar
  9. 9.
    Taebi, B.: Bridging the gap between social acceptance and ethical acceptability. Risk Anal. 37(10), 1817–1827 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Milica Pavlovic
    • 1
    • 3
  • Francesco Botto
    • 2
  • Margherita Pillan
    • 1
  • Carmen Criminisi
    • 3
  • Massimo Valla
    • 3
  1. 1.Interaction & Experience Design Research LabPolytechnic University of MilanMilanItaly
  2. 2.Fondazione Bruno KesslerTrentoItaly
  3. 3.Joint Open Lab Digital Life, Services Innovation DepartmentMilanItaly

Personalised recommendations