This workshop critically examined the trend toward rapid and seamless human—AI interactions and considered alternative forms of prosocial engagement. We focused on the role of designers and developers in fostering user empowerment, skill development, and appropriate reliance on AI for responsible decision-making. Our discussions centered on friction-in-design and the core concepts of’programmed inefficiencies’ and’frictional protocols’ that involve design elements intentionally included to promote cognitive engagement and thoughtful interaction with AI, even if they might be slower. The workshop featured contributions on design principles that balance efficiency with engagement, methods for revealing and reducing biases in explainable AI systems, and considerations for a meaningful future with AI. In this first edition, this workshop set the stage for future research and community-building efforts around’Frictional AI’ to encourage more informed and reflective human-AI interactions.
Natali, C., Frischmann, B., Cabitza, F. (2024). Stimulating Cognitive Engagement in Hybrid Decision-Making: Friction, Reliance and Biases (preface). In Proceedings of the Workshops at the Third International Conference on Hybrid Human-Artificial Intelligence co-located with (HHAI 2024) (pp.9-15). CEUR-WS.
Stimulating Cognitive Engagement in Hybrid Decision-Making: Friction, Reliance and Biases (preface)
Natali C.;Cabitza F.
2024
Abstract
This workshop critically examined the trend toward rapid and seamless human—AI interactions and considered alternative forms of prosocial engagement. We focused on the role of designers and developers in fostering user empowerment, skill development, and appropriate reliance on AI for responsible decision-making. Our discussions centered on friction-in-design and the core concepts of’programmed inefficiencies’ and’frictional protocols’ that involve design elements intentionally included to promote cognitive engagement and thoughtful interaction with AI, even if they might be slower. The workshop featured contributions on design principles that balance efficiency with engagement, methods for revealing and reducing biases in explainable AI systems, and considerations for a meaningful future with AI. In this first edition, this workshop set the stage for future research and community-building efforts around’Frictional AI’ to encourage more informed and reflective human-AI interactions.| File | Dimensione | Formato | |
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