In this paper, we consider some key characteristics that AI should exhibit to enable hybrid agencies that include subject-matter experts and their AI-enabled decision aids. 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, while also guaranteeing user satisfaction and human and social sustainability. It does so by boosting people's cognitive motivation for interacting analytically with the outputs, reducing overreliance on AI and improving performance.
Cabitza, F., Natali, C. (2022). Open, Multiple, Adjunct. Decision Support at the Time of Relational AI. In Proceedings of the First International Conference on Hybrid Human-Artificial Intelligence (pp.243-245). IOS press [10.3233/FAIA220204].
Open, Multiple, Adjunct. Decision Support at the Time of Relational AI
Cabitza, F;Natali, C
2022
Abstract
In this paper, we consider some key characteristics that AI should exhibit to enable hybrid agencies that include subject-matter experts and their AI-enabled decision aids. 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, while also guaranteeing user satisfaction and human and social sustainability. It does so by boosting people's cognitive motivation for interacting analytically with the outputs, reducing overreliance on AI and improving performance.File | Dimensione | Formato | |
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