Call for Papers
Special Issue on Human-centred AI in healthcare: Challenges appearing in the wild
To appear on ACM Transactions on Computer-Human Interaction
http://bit.ly/HCIAIHealth
Deadline [extended]: November 12th, 2021
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: November 12th, 2021
- First-round reviews to authors: December 14th, 2021
- 2nd round submission deadline: February 11th, 2022
- 2nd-round reviews to authors: April 8th, 2022
- Camera ready version: May 13th, 2022
- Publication: August, 2022
Authors are encouraged to send an abstract (e.g., 500 words) to HCIAIHealth@acm.org 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