Artificial intelligence is becoming the third party in the delivery of these four streams of healthcare and Peng Liu, Jiaxin Zhang, Shuaiqi Chen, and Shanguang Chen’s paper describes this emerging complementation in their paper “Human-AI teaming in healthcare: 1+1>2?” I have inserted abstracts from the paper below.
Human-AI teaming in healthcare: 1 + 1 > 2? | npj Artificial Intelligence
https://www.nature.com/articles/s44387-025-00052-4
PengLiu1 , Jiaxin Zhang1,2,ShuaiqiChen1,2 & Shanguang Chen3 1234567890():,; 1234567890():,;
"While humans and AI-powered machines are expected to complement each other—for example, leveraging human creativity alongside AI’s computational power to achieve synergy (“1+1>2”) — the extent to which human–machine teaming (HMT) realizes this potential remains uncertain. We investigated this issue through reliability analysis of data from 52 empirical studies in clinical settings. Results show that medical AI can augment clinician performance, yet HMT rarely achieves full complementarity."
"Two factors matter: (1) teaming mode, with the simultaneous mode (clinicians review diagnostic cases and AI outputs concurrently) yielding greater benefits than the sequential mode (clinicians make initial judgments before reviewing AI outputs); and (2) clinician expertise, with juniors benefiting more than seniors. We also addressed two practical questions for medical AI deployment: how to predict or explain HMT reliability, and how to achieve clinically significant improvements. These findings advance understanding of human–AI collaboration in safety-critical domains"
"Artificial intelligence (AI) systems are transforming professional domains, ranging from medical diagnosis and surgery to driving and piloting. These AI-powered machines sometimes surpass human capabilities in computational and analytical efficiency, accuracy, consistency, and scalability. We focus on their role in healthcare, where AI is poised to address critical challenges, such as clinician errors—a major contributor to medical accidents and patient harm. Powerful AI machines like predictive analytics and surgical robots are expected to reduce clinician errors and enhance patient safety, thereby revolutionizing healthcare delivery worldwide4,5. In fact, clinicians have utilized computer-based clinical decision support systems (CDSS) since the 1970s.
Recent technological breakthroughs in machine learning, deep learning, and multimodal large language models6–8 have expanded these machines’ capacity to process diverse medical data, including images, text, and phenotypic information. Despite these promising developments, significant debate surrounds the integration of AI into clinical practice. One pathway involves using AIto “automate” certain human tasks and substitute human professionals in these tasks. Proponents, including researchers and AI companies, argue that AI outperforms human doctors in specific areas such as image-based diagnostics9,10, suggesting that automating these tasks could reduce patient harm from a utilitarian perspective11. However, this radical pathway faces economic, regulatory, ethical, and legal hurdles12,13. For instance, removing humansfromthedecision-makingloopcomplicatesliabilityissueswhenAI systems err. Clinicians may resist such changes due to concerns about job displacement, while healthcare organizations might hesitate to fully trust AI-driven clinical practice14. Another pathway is to “augment” human professionals by keeping them in the loop. This mode, usually referred to as “human-machine augmentation”, “human-machine collaboration”, “human-machine partnership”, “human-in-the-loop”, “human-machine hybrid”, “human-machine symbiosis”, or “human-machine teaming” (HMT),involves clinicians using machines to support decision-making and other tasks. Clinicians emphasize that machines should act as partners and that the joint human-machine system must remain fundamentally clinician-directed or human-centered"
HIFA profile: Richard Fitton is a retired family doctor - GP. Professional interests: Health literacy, patient partnership of trust and implementation of healthcare with professionals, family and public involvement in the prevention of modern lifestyle diseases, patients using access to professional records to overcome confidentiality barriers to care, patients as part of the policing of the use of their patient data Email address: richardpeterfitton7 AT gmail.com