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Francisco Nunes <[log in to unmask]>
Wed, 26 May 2021 19:39:29 +0100
text/plain (97 lines)
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CFP for the Special Issue on Human-centred AI in healthcare:
Challenges appearing in the wild

To appear on ACM Transactions on Computer-Human Interaction
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Deadline: October 29th, 2021
More information: http://bit.ly/HCIAIHealth

DESCRIPTION:
Artificial intelligence (AI) holds great promise to improve our healthcare
systems. Current AI-based systems already support drug development, triage,
screening, diagnosis, and patient follow-up; and the potential is to
completely reconfigure the way our healthcare systems work. In the face of
such strong potential, many scientists have devoted their research to the
development of AI-based systems, and PubMed has seen a tenfold increase in
the number of publications mentioning AI, in the past two years alone.
Nevertheless, and despite the strong optimism, few AI-based systems have
been integrated in everyday care.

Going the “last mile” with AI-based systems will require not only robust
algorithms, but also dealing with implementation challenges and
guaranteeing that AI-based system fit the needs and practices of patients,
carers, clinicians, and clinical researchers. In other words, we need
Human-Computer Interaction and a Human-Centred perspective to help unleash
the AI potential in healthcare.

The HCI community has often been seen as contributing at the margins of the
creation of AI-based systems for healthcare. As the majority of research
studies focused on demonstrating technical feasibility and performance of
algorithms, they could draw on retrospective datasets and refrain from
involving users. However, as AI-based systems start to integrate healthcare
systems, there is a pressing need for exploring questions related to: i)
What constitutes Human-Centred AI in healthcare? ii) How to design AI-based
interactive systems for healthcare? and iii) How to deploy and evaluate
AI-based systems in practice and what are the sociotechnical and ethical
implications for the human end-users?

Guiding the next generation of HCI work on AI for healthcare are the
contributions of the community to Explainable AI, as well as the studies on
accountability, transparency, fairness, and ethics. The few ethnographic
studies describing AI-based systems use in practice will also be useful in
illuminating the assessment of these type of solutions in context. Still,
important work is yet to come as designing Human-AI interactions is
extremely complex due to the variety of workflows triggered by different
datasets, the current lack of iterative prototyping tools, and the
difficulties of communicating AI capabilities to the design team.


TOPICS OF INTEREST:
* Ethnographies that unpack the use, appropriation, and other
sociotechnical aspects of AI-based systems in healthcare, in self-care,
clinical care, or clinical research;
* Expectations, perspectives, and misalignments between users and
developers;
* Theoretical discussions of key concepts appearing in the Human-Centred AI
literature for healthcare, including explainable AI, accountable AI, as
well as fairness or ethics in AI;
* Theoretical discussions (re-)visiting key HCI concepts in the space,
including patient-clinician interaction, shared decision-making, or
self-care;
* Applications and designs that explore and advance Human-Centred AI in
healthcare;
* Methodologies, methods, approaches, or adaptations needed for creating
appropriate human-AI interactive systems;
* Reviews of existing research on the design, integration, and/or
evaluation of ML and AI technology in healthcare.


IMPORTANT DATES:
* Full paper submission deadline: October 29th, 2021
* First-round reviews to authors: November 30th, 2021
* 2nd round submission deadline: January 28th, 2022
* 2nd-round reviews to authors: March 11th, 2022
* Camera-ready version: April 29th, 2022
* Publication: May-June, 2022
> Authors are encouraged to send an abstract (e.g., 500 words) to
[log in to unmask] for feedback on the relevance and fit to the special
issue.


SPECIAL ISSUE EDITORS:
Tariq Osman Andersen, University of Copenhagen and Vital Beats ApS
Francisco Nunes, Fraunhofer Portugal AICOS
Lauren Wilcox, Google and Georgia Tech
Enrico Coiera, Macquarie University
Yvonne Rogers, University College London

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