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UID:pretalx-citizen-science-communication-trust-2026-XG9SRA@ifkw.rz.tu-bs.d
 e
DTSTART;TZID=CET:20261005T134500
DTEND;TZID=CET:20261005T140000
DESCRIPTION:1. Context: AI in critical care research\n\nArtificial intellig
 ence (AI) is being increasingly integrated into clinical research and care
 \, including in resource-limited settings. I explore how these development
 s challenge existing models of participation\, communication and trust\, d
 rawing on practice-based work at OUCRU Vietnam. I argue that AI-enabled cl
 inical research in critical care creates a form of constrained participati
 on\, in which patients contribute to knowledge production but cannot meani
 ngfully engage with or understand it.\n\nOUCRU is based at the Hospital fo
 r Tropical Diseases (HTD)\, a tertiary hospital for infectious diseases in
  southern Vietnam. Its intensive care unit (ICU) operates under significan
 t constraints\, including high patient loads and limited monitoring equipm
 ent. Tetanus\, for instance\, has a mortality rate of 30 to 40 per cent gl
 obally and requires continuous monitoring and rapid intervention\, placing
  substantial pressure on clinical staff. In response\, OUCRU has developed
  an affordable\, wearable monitoring device that continuously captures pat
 ients' vital data\, and uses an algorithm to detect early signs of deterio
 ration and alert clinicians.\n\n2. Constrained participation and trust\n\n
 Patients enrolled in this research contribute continuous streams of vital 
 data that inform both clinical decisions and knowledge production. Their c
 ontribution constitutes a form of participation in scientific research\, a
 lbeit one that is passive and mediated by clinical care. This raises impor
 tant questions about what counts as participation in such data-intensive r
 esearch.\n\nIn this setting\, participation is true but highly constrained
 : patients are severely ill\, often unconscious\, and consent is typically
  provided by family members. Clinicians and researchers\, who are responsi
 ble for communicating with patients and families\, are not always equipped
  to explain the "black box"\, how algorithmic systems function or what the
 ir limitations are. This challenge is intensified by Vietnamese culture wh
 ere patients and families defer strongly to medical authority and have lim
 ited reference points for understanding AI. Trust\, in this case\, is shap
 ed by necessity and structural dependence rather than informed engagement.
   \n\n3. AI disclosure \n\nUnlike auxiliary diagnostic tools\, AI technolo
 gies in ICUs do not simply generate data but actively shape clinical decis
 ions. This has direct implications for patients' autonomy and dignity (Mon
 tanari Vergallo et al.\, 2025). Thus\, the use of AI must be adequately co
 mmunicated\, even when full understanding is proven challenging.\n\nThe qu
 estion is how much information to communicate\, and how. One approach is t
 o match the obligation to inform to the level of risk on patient safety\, 
 where higher risk systems require more extensive explanation. However\, si
 mply providing more information is not sufficient. Transparency alone does
  not build trust\; information must be intelligible and accessible to thos
 e who need to act on it (O’Neill\, 2018). In this setting\, the gap betw
 een what the technology does and what patients and families can meaningful
 ly understand remains significant.\n\n4. The role of science communication
 \n\nI would argue that science communication has a critical role in addres
 sing this gap. At OUCRU\, communication has traditionally focused on trans
 lating complex research findings to make them accessible and support publi
 c trust in science. However\, in the context of AI in clinical research\, 
 communication becomes a condition for ethical practice rather than a final
  step. \n\nThe challenge is to develop forms of explanation that are accur
 ate\, accessible\, and usable within the realities of critical practices. 
 This requires moving upstream\, from disseminating results to shaping how 
 research is explained and understood at the point of participation.\n\n5. 
 Practice contribution\n\nI propose a practice-based inquiry into how AI is
  currently communicated to patients and families across several OUCRU clin
 ical studies\, with the aim to develop practical guidance for clearer and 
 more responsible communication during consent and care discussions.\n\nThi
 s includes identifying what information is necessary\, how it can be expla
 ined in plain language\, and developing practical tools such as communicat
 ion scripts\, checklists\, and training for healthcare workers that can be
  integrated into clinical practice.\n\nBy examining a setting where partic
 ipation is constrained but stakes are high\, this work contributes to a br
 oader discussion on citizen science\, communication\, and trust. It argues
  that as AI becomes more prominent in research and care\, new communicatio
 n practices are needed to support understanding and maintain trust through
 out the research process and beyond.
DTSTAMP:20260721T203735Z
LOCATION:Room 1
SUMMARY:Communicating AI in critical care: Trust and participation under co
 nstraint - Trang Nguyen
URL:https://ifkw.rz.tu-bs.de/citizen-science-communication-trust-2026/talk/
 XG9SRA/
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