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cloud.google.com·7h ago
AI Research
arXiv CS.AI·Jul 29·5 min read
"We'll have to see how it works": An interview study to understand collaborative practices in interdisciplinary artificial intelligence and healthcare research
TL;DR
An interview study reveals that developing AI for healthcare requires effective collaboration among diverse stakeholders, highlighting the need for tailored communication and tools. Key findings emphasize the challenges of integrating clinician and patient perspectives in AI research.
✦ Why It Matters
Tailor your communication strategies to effectively engage diverse stakeholders in AI healthcare projects.
Key Takeaways
- Adapt communication tools for different stakeholder audiences.
- Incorporate clinician and patient perspectives in AI development.
- Recognize the unique challenges of interdisciplinary AI research.
- Engage in knowledge sharing practices to enhance collaboration.
Full Summary
Interdisciplinary collaboration is essential for developing artificial intelligence (AI) in healthcare, involving data scientists, clinicians, and patients. This study employs inductive thematic analysis of 13 semi-structured interviews with participants from early-stage AI-in-healthcare research consortia in the UK.
Findings indicate that stakeholders must modify both the tools they use and the information they share based on their audience, particularly when engaging with clinicians and patients. Key areas of focus include the novelty of AI research participation, methods of knowledge sharing, and the integration of clinician and patient perspectives.
The study underscores that while AI can enhance healthcare, it also introduces new challenges to interdisciplinary collaboration.