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AI is used in some healthcare settings, but the evidence reviewed does not show that doctors generally hide its use. The important question is what a particular tool does, how it affects your care, and whether its purpose, performance and limits are explained clearly.
Are doctors using AI without telling patients?
There is no single answer for every clinic or appointment. AI can refer to an authorized medical device, a generative chatbot, a research model or software used for administrative work. Those uses are not interchangeable, and an AI system’s presence somewhere in healthcare does not mean it is making a decision about every patient.
The U.S. Food and Drug Administration (FDA) maintains a list of AI-enabled medical devices authorized for marketing in the United States. That list describes a specific, U.S.-regulated device landscape; it does not establish how often doctors use AI or whether a particular clinician disclosed a tool’s role. See the FDA’s AI-enabled medical device list.
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The available official guidance treats transparency as an important safety and trust issue, not as proof of widespread concealment. FDA, Health Canada and the U.K.’s Medicines and Healthcare products Regulatory Agency (MHRA) say that relevant information should be communicated to the people who need it, including patients and health professionals. The guidance states: “Transparency is essential to patient-centered care and for the safety and effectiveness of a device.” Read the joint transparency principles.
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What kind of AI is involved?
Before judging an AI use, identify what category it belongs to. A tool that helps analyze medical images, a chatbot that generates text, and software that assists with scheduling raise different questions about purpose, risk and oversight.
- AI-enabled medical device: A tool intended for a medical purpose, such as supporting a defined clinical task. Its authorization or evidence applies to a specified use, not automatically to other tasks or patient groups.
- Generative AI or a large language model: A system that generates text or other content. It should not be assumed to have the testing, intended use or regulatory status of a medical device.
- Administrative software: AI may support non-clinical work. Its use does not by itself mean that an algorithm made a diagnosis or treatment decision.
- Research model: AI used in research raises questions about research oversight and participant protections. WHO’s July 21, 2026 report addresses ethics review and oversight of AI-related health research; it is not evidence about routine clinician disclosure.
WHO’s 2023 statement on large language models called for clear evidence of benefit before widespread routine use in health. That is a caution about evaluating these systems, not evidence that every use is unsafe or hidden. Read WHO’s statement on large language models in health.
What should transparency tell you?
For a medical device, FDA, Health Canada and MHRA organize transparency around practical questions: who the tool is for, why it is being used, what it does, where and when it is used, and how its output fits into care. The useful details depend on the tool’s intended purpose and context.
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- Inputs and outputs: What information does it use, and what does it produce—a score, alert, recommendation, prioritization or something else?
- Role in the workflow: Does the output inform a clinician’s judgment, or does it automate an action? How does the clinician review it and retain responsibility for the care decision?
- Evidence and limitations: What performance evidence applies to this specific use? What risks, known biases, data gaps or limits should be considered?
- Monitoring: How is safety and performance monitored over time, including for errors or declining performance?
- Patient information: What relevant details are provided to patients, and when?
Transparency and explainability are related but distinct. Transparency is about communicating relevant information about the system and its use. Explainability concerns how understandable the basis for an output is. Not every AI system can provide a simple account of its internal logic, so a clear explanation of purpose, evidence, limits and human oversight still matters. The FDA says transparency can help people weigh risks and benefits, detect errors or declining performance, and identify possible bias.
What can you ask your doctor?
If you want to understand a tool’s role in a specific part of your care, ask direct questions. These are practical questions based on regulator transparency principles; they are not a statement that the law guarantees a particular disclosure in every place or circumstance.
- “Is an AI tool involved in this part of my care?”
- “What does it do, and what information does it use?”
- “Does it make a recommendation or a decision?”
- “How do you check its output?”
- “What are its limits for someone like me?”
A useful answer should clarify the tool’s task and how its output is used, rather than treating “AI” as a complete explanation. If the tool is a medical device, you can also ask what evidence applies to its intended use and what role your clinician plays in reviewing the result.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Does AI use mean the doctor is hiding something?
No such conclusion follows from the existence of AI in healthcare or from the fact that regulators emphasize transparency. The official sources summarized here establish principles and concerns; they do not establish that physicians as a group intentionally conceal AI use, nor do they provide a reliable rate of disclosure or non-disclosure.
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How to judge a specific AI tool
If you are evaluating a named tool, compare it only with alternatives intended for the same task and audience. A device authorized for a defined medical use should not be treated as interchangeable with a general-purpose chatbot.
- Intended use and patient population
- Quality and relevance of evidence for that use
- Regulatory status in the relevant country
- Place in the workflow and degree of clinician oversight
- Known risks, limitations, bias and data needs
- Information provided to patients, including relevant privacy details
- How updates and ongoing performance are monitored
Authorization for one use does not establish that a tool is suitable for another patient, condition or task. The FDA’s list is specific to devices authorized for marketing in the United States; check the regulator and labeling relevant to your location and the use in question.
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