Identifying Challenges and Opportunities in Human-AI Collaboration in Healthcare

By S. Park, Pei-Yi Kuo, A. Barbarin, Elizabeth Kaziunas, Astrid Chow, Karandeep Singh, Lauren Wilcox, Walter S. Lasecki. 2019

86 citations recorded by the source corpus.

The proposed workshop will identify research questions that will enable the field to uncover the types of work, labor relations, and social impacts that should be considered when designing AI-based healthcare technology. The workshop aims to outline key challenges, guidelines, and future agendas for the field, and provide collaboration opportunities for CSCW researchers, social scientists, AI researchers, clinicians, and relevant stakeholders in healthcare, to share their perspectives and co-create sociotechnical approaches to tackle timely issues related to AI and automation in healthcare work.

Subfields: Applied Psychology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Emma Beede
2. E. Baylor
3. Fred Hersch
4. A. Iurchenko
5. Paisan Ruamviboonsuk
6. Laura M. Vardoulakis
7. Lauren Wilcox
8. Pranav Rajpurkar

Citations in the corpus

• A Human-Centered Evaluation of a Deep Learning System Deployed in Clinics for the Detection of Diabetic Retinopathy (2020, background): “Human-centered evaluation of interactive, deep learning systems—within clinical environments—is an open area of research [30].”