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Stimulating Cognitive Engagement in Hybrid Decision-Making: Friction, Reliance and Biases (preface)

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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.
Original languageEnglish
Title of host publicationHHAI-WS 2024 Proceedings of HHAI 2024 Workshops
Subtitle of host publicationProceedings of the Workshops at the Third International Conference on Hybrid Human-Artificial Intelligence co-located with (HHAI 2024)
EditorsP. Ericson, N. Khairova, M. De Vos
PublisherCEUR-WS
Pages9-15
Number of pages7
Publication statusPublished - 2024
Externally publishedYes
Event3rd International Conference on Hybrid Human-Artificial Intelligence, HHAI-WS 2024 - Malmo, Sweden
Duration: 10 Jun 202411 Jun 2024

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR Workshop Proceedings
Volume3825
ISSN (Print)1613-0073

Conference

Conference3rd International Conference on Hybrid Human-Artificial Intelligence, HHAI-WS 2024
Country/TerritorySweden
CityMalmo
Period10/06/2411/06/24

Funding

We extend our sincere gratitude to all the participants, speakers, and the HHAI conference organizers who contributed to the success of this workshop. Special thanks go to the members of the Programme Committee for their expertise and commitment. C. Natali gratefully acknowledges the PhD grant awarded by the Fondazione Fratelli Confalonieri, which has been instrumental in facilitating her research pursuits. F. Cabitza acknowledges funding support provided by the Italian project PRIN PNRR 2022 InXAID - Interaction with eXplainable Artificial Intelligence in (medical) Decision making. CUP: H53D23008090001 funded by the European Union - Next Generation EU.

FundersFunder number
European Commission
Fondazione Fratelli ConfalonieriH53D23008090001

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