Published July 16, 2022 | Version v3
Conference paper Open

Open, multiple, adjunct. Decision support at the time of Relational AI

  • 1. University of Milano-Bicocca, IRCCS Istituto Ortopedico Galeazzi
  • 2. University of Milan, Vita-Salute University San Raffaele


In this paper, we consider some key characteristics that relational AI should exhibit to enable decision hybrid agencies that include subject-matter experts and their AI-enabled decision aids, especially when these latter ones have been developed by following a machine learning approach. We will hint at the design requirements of guaranteeing that AI tools are: open, multiple, continuous, cautious, vague, analogical and, most importantly, adjunct with respect to decision making practices. We will argue that especially adjunction is an important condition to design for. Adjunction entails the design and evaluation of human-AI interaction protocols aimed at improving AI usability, that is decision effectiveness and efficiency, while also guaranteeing user satisfaction and human and social sustainability, as well as mitigating the risk of automation bias, technology over-reliance and user deskilling. These high-level aims are compatible with the tenets of a relational approach to the design of AI tools to support decision making and collaborative practices.

This is the extended version of the article published in the proceedings of the first conference on Hybrid Human Artificial Intelligence (HHAI'22) Amsterdam, the Netherlands, 13-17 June, 2022. To cite this article, please use the following format: Cabitza, F., & Natali, C. (2022). Open, multiple, adjunct. Decision support at the time of relational AI. In HHAI2022: Augmenting Human Intellect (pp. 243-245). IOS Press.



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