Articles · Diagnostics & imaging
The Responsibility for AI Medical Devices Lies with Developers, Not Doctors
Generative AI medical devices raise questions of accountability. Provider groups are calling for developers to be held responsible for their safety.
30 October 2026 · 3 min
Key points
- Generative AI medical devices are monitored by developers, not by doctors.
- These devices are intended for hospitals, clinics, and small practices.
- Check the developer's accountability and associated risks before use.
What are generative AI medical devices and what do they do?
Generative AI medical devices are tools that use artificial intelligence to generate information or recommendations in the health sector. These can include chatbots that answer medical questions or applications that synthesize medical data to assist in diagnosis.
These devices have the ability to accept various inputs and produce different outcomes based on the same inputs. They are designed to assist doctors and patients in decision-making, but do not completely replace human expertise.
It is important to note that these devices may have associated risks, and the responsibility for their safety and performance is a subject of debate among developers and providers.
Who benefits from these devices and who does not?
Generative AI medical devices are useful for healthcare professionals, such as doctors, hospitals, and clinics. They can assist in diagnosis by providing information and recommendations based on medical data. They can also be used in telemedicine to facilitate remote consultations.
In contrast, these devices are not intended for patients who lack medical knowledge or who cannot correctly interpret the information generated. Their use without the supervision of a professional may lead to errors or misinterpretations of the recommendations.
- Healthcare professionals
- Hospitals and clinics
- Telemedicine
- Patients with limited medical knowledge (not recommended)
- Individuals who cannot interpret medical information
- Small and rural practices that may have difficulties integrating these technologies.
How are AI medical devices used in practice?
Generative AI-based medical devices are used in various ways in medical practice. These can include chatbots that provide medical information or tools that synthesize clinical data. Their use depends on the type of device and its purpose.
To use these devices, it is important to follow these steps:
- Check if the device is approved by the relevant authorities, such as the FDA.
- Ensure that you have access to the user instructions and operating guidelines.
- Use the device as directed, following all recommendations.
- Monitor the results and reactions to the use of the device.
- Report any issues or adverse effects to the developer or authority.
- Consult a doctor if you have any concerns or questions regarding the use of the device.
Where can you find information about costs and approvals for these devices?
Information about the costs and approvals of generative AI-based medical devices is not always publicly available. It is important to check official sources for the most accurate data.
- Visit the manufacturer's official website for details on pricing and availability.
- Check the associated mobile applications for cost information.
- Talk to your family doctor for recommendations and information about device approvals.
- Ask at the pharmacy about the availability and prices of AI devices.
- Check the websites of regulatory agencies, such as the FDA, for the approval status of devices.
What to watch out for: risks and responsibilities in the use of medical AI.
The use of medical devices based on generative AI comes with certain risks. It is important to be aware of the responsibilities that fall on developers and healthcare providers. The latter do not wish to be held accountable for the errors of the devices, arguing that developers should monitor their performance.
Check the following aspects: - Who is responsible for the safety of the device? - Is there a system for reporting encountered issues? - Does the device have an assessment of associated risks? - Is responsibility clarified in the event of errors? - What safety measures are implemented for human use?
Transparency in the functioning of AI models is essential for identifying potential errors.