Apply the rules
Inspect a real distribution using Health AI Developer Foundations terms. Identify its license version, required notices, upstream dependencies and any unresolved permissions.
Licenses / Knowledge library
Health AI Developer Foundations terms
Understand Health AI Developer Foundations terms: permissions, conditions and limitations.
Why learn Health AI Developer Foundations terms?
Make informed reuse and redistribution decisions under Health AI Developer Foundations terms; this lesson is not legal advice.
The problem it solves
Explains the obligations that a license label alone can hide. Verify the exact version and upstream terms.
Where it came from
Do Health AI model terms by themselves establish clinical approval? (Health AI Developer Foundations terms) No. Where should permissions for a MedGemma model be checked? (Health AI Developer Foundations terms) Its linked Health AI terms and model documentation. Does access to a Health AI model replace professional validation? (Health AI Developer Foundations terms) No. Why inspect redistribution obligations for Health AI derivatives? (Health AI Developer Foundations terms) Custom terms can remain applicable downstream. What should a developer distinguish for a Health AI deployment? (Health AI Developer Foundations terms) License permission versus regulatory and clinical suitability.
- Do Health AI model terms by themselves establish clinical approval? (Health AI Developer Foundations terms) No.
- Where should permissions for a MedGemma model be checked? (Health AI Developer Foundations terms) Its linked Health AI terms and model documentation.
- Does access to a Health AI model replace professional validation? (Health AI Developer Foundations terms) No.
- Why inspect redistribution obligations for Health AI derivatives? (Health AI Developer Foundations terms) Custom terms can remain applicable downstream.
- What should a developer distinguish for a Health AI deployment? (Health AI Developer Foundations terms) License permission versus regulatory and clinical suitability.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Do Health AI model terms by themselves establish clinical approval? (Health AI Developer Foundations terms)
- Where should permissions for a MedGemma model be checked? (Health AI Developer Foundations terms)
- Does access to a Health AI model replace professional validation? (Health AI Developer Foundations terms)
- Why inspect redistribution obligations for Health AI derivatives? (Health AI Developer Foundations terms)
- What should a developer distinguish for a Health AI deployment? (Health AI Developer Foundations terms)
More ways to practice
Documentation and sources
- Official specification / license documentation (developers.google.com)
Catalog research notes
- Learning notes checked October 13, 2026. Consult the official source for subsequent changes.
Connect the ideas
Explore next
Real World Example
Clinical Diagnostic Tool Compliance Framework
A health-tech startup developing a diagnostic support application for radiologists.
The business problem
The startup risks legal liability and regulatory non-compliance by failing to enforce usage restrictions and failing to obtain necessary Health Regulatory Authorizations when distributing their AI-enhanced diagnostic model.
How this topic solves it
By adopting the Health AI Developer Foundations (HAI-DEF) terms, the startup establishes a formal compliance pipeline that mandates the inclusion of specific use restrictions in all downstream agreements and ensures that any model derivative undergoes rigorous regulatory review before distribution.
- Integrate the HAI-DEF Terms of Use into the startup's end-user license agreement (EULA) for all downstream clinical partners.
- Implement a mandatory notification system that alerts third-party recipients that the model is subject to HAI-DEF restrictions.
- Conduct a regulatory assessment to determine if the specific diagnostic application requires Health Regulatory Authorization.
- Attach the required Notice text file to all non-hosted distributions of the model derivatives.
- Maintain a clear audit trail of all modifications to the base model to ensure compliance with attribution requirements.
This diagram illustrates the flow of responsibilities when distributing a model derivative.
Entity modifying HAI-DEF
Modified AI model
Overseeing body
Recipient of model
- Developer → creates → Model Derivative
- Model Derivative → seeks authorization → Regulatory Authority
- Developer → distributes with terms → Third-Party User
Expected business outcome
The startup achieves a transparent, legally defensible distribution model that mitigates the risk of being classified as an unauthorized medical device manufacturer.
Limitations and checks
A significant tradeoff is the potential for Google to remotely restrict usage if they reasonably believe the service violates the agreement, which could cause sudden service outages for clinical users. Developers must monitor their usage patterns against the Prohibited Use Policy to prevent such interruptions.