Lumotia/docs/hardware/nlnet-genai-policy.md

name, description, type, tags, captured_at, status, related, source_url, policy_in_force, policy_version

name	description	type	tags	captured_at	status	related	source_url	policy_in_force	policy_version
NLnet GenAI policy (v1.1, 2026-01-26)	Verbatim NLnet GenAI policy filed alongside the pendant research because NLnet NGI Zero Commons Fund is the recommended primary funding pathway. Read before drafting any NLnet application or doing GenAI-assisted work on a funded project.	reference	funding nlnet genai-policy compliance open-source foss hardware pendant	2026/04/27	active	docs/hardware/pendant-research-2026-04-27.md	https://nlnet.nl/foundation/policies/generativeAI/	2025/12/08	1.1 (2026/01/26)

NLnet GenAI policy

Filed in this folder because the pendant research recommends NLnet NGI Zero Commons Fund as the primary funding pathway. Any application we submit, and any GenAI-assisted work on a funded project, must comply with this policy.

TL;DR

If we apply to NLnet and use GenAI in the application:

1. Disclose the use. Drafting, translation, summarisation. All count.
2. Maintain a prompt provenance log: model used, dates and times of prompts, the prompts themselves, the unedited output. Submit with the application.
3. Trust your own skills first. NLnet explicitly encourage applicants to write their own proposals.

If we receive a grant and use GenAI during project development:

1. All outputs must be legally publishable under a FLOS licence. Verify GenAI-assisted code does not reproduce copyrighted material.
2. Purely AI-generated outputs are not eligible for payment. Under EU law they fall into the public domain (no copyright protection).
3. Don't pass AI work off as your own. Human contributors remain accountable for accuracy, originality, integration.
4. Disclose substantive use publicly. README declaration of how GenAI is used (logic, tests, docs, etc.).
5. Mark generated content per commit. Specify model and version, include prompts and outputs (or summary), in commit messages or equivalent. Don't host the log on a third-party platform that could disappear.

Failure to comply may result in rejection of the proposal or termination of a running grant.

Funding pathway hooks

• Next deadline: apply before 1 June 2026.
• Office hour (live Q&A): 2026/04/29, "Ask us Anything" https://nlnet.nl/events/20260429/office-hour/index.html (worth attending given the deadline proximity).
• Recent precedent: 57 projects received NGI Zero grants in the 2026-04-09 announcement. Pendant research notes audio-hardware precedents (Tiliqua, MILAN) that are directly relevant.
• Application format: short web form. The compass research estimates 4 to 8 hours of focused effort. Two-month decision after submission.

Pendant project compliance plan

If we apply for the Corbie Pendant track:

• Licences: CERN-OHL-S-2.0 for hardware, GPL-3.0-or-later for firmware, CC BY-SA 4.0 for documentation. (Picked in the compass research.)
• Prompt provenance log: start one before drafting. Capture every Wren/Claude prompt that contributes to the application text, in a structured log alongside the proposal draft.
• README declaration: Corbie's existing "Pre-alpha; contribution process TBD" line stays, plus a new GenAI-disclosure section before any NLnet milestone work begins.
• Commit hygiene: for any pendant-project commit that uses GenAI-generated content, the commit message follows NLnet's example format (Author: Harry Hacker with CodeLLM-3.4, prompt cited, output attached).

Verbatim policy text

Below is the full policy as captured 2026/04/27 from the email forward. Reformatted from the email body for readability; semantic content unchanged.

Foundation of the policy

This policy is grounded in longstanding principles that apply to all NLnet-funded work. From these fundamental principles we have deduced what we consider common sense consequences with regards to the use of GenAI.

Fundamental principles:

1. FLOS licence. All projects must be free/libre/open source: all scientific outcomes must be published as open access, and any software and hardware developed must be published under a recognised free and open source licence in its entirety.
2. No misrepresentation. Grantees and applicants should not claim work as their own, if it is not. This has always been true and GenAI doesn't change that.
3. Project quality. Grantees are expected to deliver project outcomes to the best of their ability. Tools may assist but do not replace human responsibility for correctness, clarity, and reproducibility.

Use of GenAI in the application process

We encourage applicants to trust their own skills and write their own proposals. That being said, applicants may use GenAI tools in preparing applications, but any such use must be disclosed. This includes drafting, translation, or summarisation. It applies both to written proposals and to materials provided during interactive evaluation. Disclosure allows evaluators to understand how the proposal was produced and ensures fairness.

How to disclose. If GenAI is used in the application process a prompt provenance log must be maintained. This log should list:

• the model used,
• dates and times of prompts,
• the prompts themselves,
• the unedited output.

Instructions about how to submit the prompt log for applications are provided on the proposal form: https://nlnet.nl/propose/

Use of GenAI in project development

• Grantees must ensure that all submitted work can be legally published under a FLOS licence. This includes verifying that GenAI-assisted outputs do not reproduce copyrighted or incompatible material.

  • Example: when using a code assistant, check the assistant's terms of use, and ensure that outputs are not reconstructed from copyrighted sources.
  • Example: Under EU law, purely AI-generated outputs without substantial human intellectual contribution are not eligible for copyright protection. In any case, outcomes purely generated by AI are not allowed to be submitted as work eligible for payment (as part) of the grant.

• Grantees must not present AI-generated content as if it were their own human-authored work.

  • Explanation: When we provide a grant to a person to develop a project, we expect that person to do the work. They should not outsource the work to another person while pretending they did it themselves. Similarly, grantees should not deliver GenAI outcomes and pretend it was their own human effort. Human contributors remain accountable for accuracy, originality, and integration of GenAI-supported work.

• Use of GenAI must not reduce the quality, clarity, reliability, or reproducibility of the work.

  • Explanation: Tools may assist, but human responsibility for quality remains. Human contributors are expected to understand and be able to explain design and code decisions.

• It is allowed to work on the topic of GenAI itself within the scope of a grant, but only if this is explicitly part of approved work.

Transparency and logging for project development

Use of GenAI should be disclosed and transparent. For any substantive use of GenAI that materially affects outputs, public disclosure is required, making it available to both users and contributors.

• The general stance toward the use of GenAI within a project should be disclosed and transparent for the public by providing a broad description.

  • Example: A codebase declares, typically in its README, broadly how GenAI is used (logic, boilerplate, tests, documentation, etc.).
  • Example: A project publishes its own policy for contributors, outlining its dos and don'ts with regards to the use of GenAI.

• Generated content should be marked as such. When adding (partially) generated code, make sure the provenance is clear for each such contribution. Specify which model was used (including version), and how it was used. Provide the used prompts/interactions and resulting output, or a summary thereof.

  • Example: When using git, distinguish commits that add generated code and include the used model and prompts in the commit message.
  • Make sure to provide the information in a logical place where it can easily be found. Avoid hosting it on third-party platforms that require a log-in or may disappear over time.

• If GenAI is not used for generating code but only for tasks like testing or creating documentation, it suffices to provide a general description of the use in the README. More detailed logging on a per-commit basis is preferred but not required.

Alternative methods for logging

The goal of disclosure is to inform NLnet, users and contributors about the extent to which GenAI was used to generate project results. If you prefer to use different methods for logging with equivalent results, this can be acceptable too. Use common sense to determine such equivalence and make sure you are able to answer questions about the use of GenAI from the NLnet team.

Exceptions for grantees with active projects

For grantees with ongoing projects (Memorandum of Understanding signed before 8 December 2025), logging is not required retroactively. It applies to milestones started after the policy came into force.

Grantees of ongoing projects who feel that none of the disclosure options offered above will work for them can propose a personalised plan for transparency to their contact person at NLnet.

Non-compliance

Failure to comply with the above policy may result in rejection of the proposal or ultimately in the termination of the running grant.

Scope

This policy explicitly deals with GenAI only (such as Large Language Models). NLnet is a strong proponent of automation and of deterministic and reproducible generation of source code, formal and symbolic proofs, etc. based on specifications and scientific and engineering rigour. Similarly, it does not in any way seek to prevent the use of other forms of machine learning, fuzz testing or other beneficial use cases. When in doubt, contact NLnet.

Note 1: AI copyright in the EU

See: Generative AI and Copyright, page 93, a report requested by the European Parliament's Committee on Legal Affairs.

Given this framework, it follows that purely AI-generated outputs, those created automatically by an AI system without substantial human intervention, are not eligible for copyright protection in the EU. Such outputs are considered to fall into the public domain, making them freely available for anyone to use, reproduce, or adapt without seeking permission or providing attribution. The legal and commercial implications of this are significant. For creators and companies investing in AI systems that generate music, art, or text, there is no proprietary right over the final output unless a human has contributed in a way that meets the "intellectual creation" standard.

https://www.europarl.europa.eu/RegData/etudes/STUD/2025/774095/IUST_STU(2025)774095_EN.pdf#page=95

Note 2: Example commit messages

Author: Harry Hacker <hh@example.org>
Date: Sun Jan 18 10:32:15 2026

    Fix compliance tests

    Fix several mistakes in generated code, make it compile; manually
    verify each test with RFC123 specification.

Author: Harry Hacker with CodeLLM-3.4 <hh@example.org>
Date: Sun Jan 18 10:52:08 2026

    Generate compliance tests

    Prompt: Generate tests for compliance with RFC123 messages.
    Output: (this commit)

Source

Captured from email forward 2026/04/27 10:42 BST. Authoritative source: https://nlnet.nl/foundation/policies/generativeAI/