The supportive AI framework: from recommending to supporting
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Author (Corporation)
Publication date
25.06.2025
Typ of student thesis
Course of study
Collections
Type
04B - Conference paper
Editor (Corporation)
Supervisor
Parent work
Augmented cognition
Special issue
DOI of the original publication
Link
Series
Series number
Volume
1
Issue / Number
Pages / Duration
303–317
Patent number
Publisher / Publishing institution
Springer
Place of publication / Event location
Cham
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
This paper presents the Supportive AI Framework, a conceptual framework for the design of human-AI collaboration to augment human cognition. AI-based decision support systems that are recommendation-driven (i.e. the AI makes a recommendation, and the human must decide whether to accept or reject it) often overstrain humans. The reason for this is the problem known as the ‘ironies of automation’, which occurs when humans are expected to supervise a technology that exceeds human capabilities. In terms of recommendation-driven AI, this is an impossible task for humans, as they must decide on AI-generated recommendations that take into account far more data and factors than humans are able to consider. Against this background, the Supportive AI Framework aims to go beyond recommendation-driven AI towards AI that explicitly supports cognitive processes of human decision-making, human learning, human trusting, and human motivation. This as a complement to providing comprehensibility through explainable AI and interpretable models. The Supportive AI Framework is theory-based and includes theories from the areas of natural decision making, experiential learning, intrinsic motivation, socio-technical system design and complementary function allocation.
Keywords
Human-AI collaboration, Augmented cognition, Decision-making, Critical infrastructure, Complementary function allocation
Event
19th International Conference, AC 2025 and 27th HCI International Conference, HCII 2025
Exhibition start date
Exhibition end date
Conference start date
22.06.2025
Conference end date
27.06.2025
Date of the last check
27.11.2025
ISBN
978-3-031-93723-1
978-3-031-93724-8
978-3-031-93724-8
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Closed
License
Citation
Wäfler, T., Hamouche, S., & Eisenegger, A. (2025). The supportive AI framework: from recommending to supporting. In D. D. Schmorrow & C. M. Fidopiastis (Eds.), Augmented cognition (Vol. 1, pp. 303–317). Springer. https://doi.org/10.1007/978-3-031-93724-8_22