The Invisible Networks of Healthcare AI
The Invisible Networks of Healthcare AI
The Invisible Networks of Healthcare AI
Examining the socio-technical & regulatory landscapes of cancer research, this research provides critical insights into how AI emerges as more than a tool—becoming a critical actor in generating, translating, and mediating complex health data and research insights.
Examining the socio-technical & regulatory landscapes of cancer research, this research provides critical insights into how AI emerges as more than a tool—becoming a critical actor in generating, translating, and mediating complex health data and research insights.
Examining the socio-technical & regulatory landscapes of cancer research, this research provides critical insights into how AI emerges as more than a tool—becoming a critical actor in generating, translating, and mediating complex health data and research insights.
Partner
Aalborg University Hospital
Aalborg University Hospital
Aalborg University Hospital
Year
2022-2023
Interdisciplinary Analysis
Interdisciplinary Analysis
Science & Technology Studies (STS)
Science & Technology Studies (STS)
Healthcare AI
Healthcare AI
We developed an innovative Explainable AI (XAI) knowledge base platform that transforms medical research by bridging technological complexity and interdisciplinary understanding. By mapping intricate networks of human and non-human actors, we provide transparent, ethically-informed insights that redefine how AI can be interpreted and utilized in cancer research and personalized medicine.
We employed a unique Science and Technology Studies (STS) perspective that went beyond traditional research methodologies. Through Actor-Network Theory, we traced the complex interactions between human and non-human actors, revealing how technological innovations and scientific knowledge are co-produced. Our approach transformed AI from a mere tool into an active participant, illuminating the intricate networks that generate, translate, and mediate scientific understanding in medical research.
“I guess it's very important for me that I can trust what's coming out of the AI and that it's easy to use” (Molecular Diagnostics Leader)
“I guess it's very important for me that I can trust what's coming out of the AI and that it's easy to use” (Molecular Diagnostics Leader)
“I guess it's very important for me that I can trust what's coming out of the AI and that it's easy to use” (Molecular Diagnostics Leader)
We extend our deepest gratitude to Aalborg University Hospital and the KUBEN Research Group for their invaluable support and collaboration throughout this research project.
— Jorge Luis Braojos Morillas & Rasmus Holst Thomsen
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