The FDA’s 26 GenAI questions.What the public is saying.
Public feedback on the regulation of generative AI-enabled medical devices.
95 responses so far to the FDA’s GenAI questions.
Over the first 31 days, industry contributed 57 of 95 submissions (60%), more than all other groups combined. Academia / other contributed the fewest, with 6. There are 31 days remaining before comments close on October 19.
FDA GenAI feedback over time.
The largest daily total was 14 submissions on August 18, the opening day. The next busiest days were September 4 and September 8, with 9 and 8 submissions respectively. With 31 days remaining, the total stands at 95.
The FDA GenAI questions getting the most attention.
Of the FDA’s 26 questions, these three appear most often across 95 public submissions so far. Counts show references, not agreement; each card also highlights leading recommendations or positions in the coded filings.
Does a two-axis framework, AI device activity and the consequence of relying on an incorrect output, capture the dimensions of risk?
34 of 95 filings name itWhat extra oversight does an AI that plans and acts in multiple steps need?
32 of 95 filings name itTop themes shaping the FDA GenAI discussion.
A synthesis of the top emerging themes across public submissions. These themes connect several FDA questions and will evolve as new submissions are reviewed. Counts show submissions raising each theme, not agreement.
Public feedback on all 26 FDA GenAI questions.
Explore each question and the submissions that discuss it.
Does a two-axis framework, AI device activity and the consequence of relying on an incorrect output, capture the dimensions of risk?
34 of 95 filings name itHow should the continuum from non-directive to action-directing outputs, and the risk that changes along it, be accounted for?
23 of 95 filings name itWhen clinical information goes straight to the patient, does the risk change, and what safeguards help without underestimating patients?
25 of 95 filings name itShould it matter whether the clinician using the AI is a generalist or a specialist?
19 of 95 filings name itHow is risk assessed when a conversation starts with non-directive information and drifts into action-directing?
22 of 95 filings name itHow should under-escalation be weighed against over-escalation?
27 of 95 filings name itIs the two-step approach, benchmark the AI, then confirm it in clinical use, the right way to evaluate these devices?
23 of 95 filings name itShould an AI device’s position on the risk map help decide how much evidence it must bring before market?
15 of 95 filings name itDo the ten benchmark competencies, from clinical knowledge to generalizability, add up to enough evidence of safety and effectiveness?
31 of 95 filings name itHow can a benchmark score be shown to predict real-world behavior?
26 of 95 filings name itWhen can a device be confirmed without a prospective clinical study, and what earns that lighter path?
26 of 95 filings name itHow do you get statistically meaningful performance numbers when synthetic inputs are mixed with real ones?
21 of 95 filings name itWhere is synthetic data good enough, and where is it not?
22 of 95 filings name itFor open-ended AI outputs, who is the performance comparator: a clinician panel, generalists, specialists, or the human-AI team?
25 of 95 filings name itCould the AI be measured against what would have happened without it: unaided judgment, a delayed specialist, or no intervention?
23 of 95 filings name itWhat role should independent third parties play?
26 of 95 filings name itDoes the approach still work for devices built on other model architectures, such as multimodal vision-language models and world models?
12 of 95 filings name itCan greater premarket uncertainty about a GenAI device’s benefit-risk profile be accepted through greater reliance on postmarket monitoring?
29 of 95 filings name itHow should an AI device be monitored after launch, and what sets the cadence?
41 of 95 filings name itCould AI supervisory agents help carry out postmarket monitoring?
27 of 95 filings name itWhat roles should clinicians and institutions play in monitoring, without diluting manufacturer accountability?
27 of 95 filings name itWith the premarket competency assessment as the baseline, which post-deployment changes need re-evaluation, and how much?
29 of 95 filings name itHow can a change-control plan cover changes that cannot be fully specified in advance?
21 of 95 filings name itWhen the foundation model’s developer changes the model, how does the device maker detect it and respond, so safety and effectiveness are not compromised?
30 of 95 filings name itWho’s saying what?
All audiences shown for comparison.Provisional mapping: industry includes startups, large companies and consultants; practitioners includes clinicians and health systems. Academia is shown separately. Filings are not a representative population survey.
The conditions matter.
How much autonomy is accepted?
Highest accepted autonomy, compared across two consequence levels.
Two debates worth watching.
Two themes drawn from the FDA’s questions.The public submissions behind the FDA GenAI discussion.
Browse the filings, contributors and original source documents.
Explore the 26 FDA questions
Counts show coverage among the selected audience, not agreement.