Hybrid intelligence: understanding how AI reframes risk and uncertainty in dementia care

This article investigates how Artificial Intelligence (AI) systems reshape risk and uncertainty in dementia care by proposing a conceptual shift from technological efficacy to hybrid intelligence. Drawing on empirical research conducted in both residential and home-based care settings in Italy, and based on interviews with professional and informal caregivers, the study explores how AI technologies such as telemonitoring systems and GPS trackers not only assist but co-construct care practices. Rather than functioning as neutral tools, AI systems emerge as epistemic and moral agents that actively participate in framing vulnerability, distributing responsibility, and redefining what counts as actionable risk. The analysis reveals that far from eliminating uncertainty, AI redistributes it, often intensifying the interpretive and affective labour of caregivers. Through the lens of hybrid intelligence, the article foregrounds the relational and situated nature of human-AI collaboration and argues for a critical reconceptualisation of risk in algorithmic health environments. This reframing emphasises the socio-technical entanglements, epistemic asymmetries, and moral decisions embedded in contemporary care infrastructures.

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Publication Details

Journal
Health Risk & Society
Published
2026-04-12
DOI
https://doi.org/10.1080/13698575.2026.2659025
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Hybrid intelligence: understanding how AI reframes risk and uncertainty in dementia care

Francesco Miele, Veronica Moretti, Ludovica Rubini, Martina Consoloni
Health Risk & Society
Artificial Intelligence in Healthcare and Education
article

Hybrid intelligence: understanding how AI reframes risk and uncertainty in dementia care

Francesco Miele, Veronica Moretti, Ludovica Rubini, Martina Consoloni
article en

Abstract

This article investigates how Artificial Intelligence (AI) systems reshape risk and uncertainty in dementia care by proposing a conceptual shift from technological efficacy to hybrid intelligence. Drawing on empirical research conducted in both residential and home-based care settings in Italy, and based on interviews with professional and informal caregivers, the study explores how AI technologies such as telemonitoring systems and GPS trackers not only assist but co-construct care practices. Rather than functioning as neutral tools, AI systems emerge as epistemic and moral agents that actively participate in framing vulnerability, distributing responsibility, and redefining what counts as actionable risk. The analysis reveals that far from eliminating uncertainty, AI redistributes it, often intensifying the interpretive and affective labour of caregivers. Through the lens of hybrid intelligence, the article foregrounds the relational and situated nature of human-AI collaboration and argues for a critical reconceptualisation of risk in algorithmic health environments. This reframing emphasises the socio-technical entanglements, epistemic asymmetries, and moral decisions embedded in contemporary care infrastructures.

Health Risk & Society
University of Trieste (IT), University of Bologna (IT)
Reduced inequalities
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
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