Adopt a "No-AI" policy

I earnestly propose we adopt a "no-AI" policy for both technical and ethical reasons.

Readers may better recognize me by my YouTube handle, [Cubician](https://www.youtube.com/@CubicianOfficialMusic). I've been involved with LMMS in some form for over half my lifetime now: first as a pest on the mailing list, then a content creator, and currently, a developer. I don't make this suggestion lightly. LMMS is important to me. I do not think LLMs or other so-called "generative AI" are healthy for LMMS.

# Technical reasons to avoid "AI"

LMMS has not had a stable release in six years at the time of writing. We're finally approaching a release of 1.3-alpha.2, only after a feature freeze full of dedicated bugfix efforts. LMMS has needed and continues to need thoughtful maintenance and refactoring more than anything else. I'm really proud of all the human effort that has gone into making LMMS more stable in the past few months.

Meanwhile, I continue to see people vibe-code features, including but not limited to: VST3 support, user interface overhauls, instrument plugins a human is already working on, and effect plugins we literally already have, the proompters of which then post demo videos, say "it's basically done", but never finish it. The LLM doesn't understand the output because it is incapable of reasoning (and can provide, at best, post-hoc rationale). The prompter doesn't understand the output because they didn't write it. It is the hardest kind of code to maintain: parasitic and verbose code nobody is accountable for, written with no intention whatsoever. This is fundamentally at odds with our needs as a project at this time, and fundamentally at odds with our future efforts at keeping LMMS healthy and maintainable for future developers.

But beyond personal anecdote, there is already real-world negative impact from using LLMs to generate code:

- [How I Dropped Our Production Database and Now Pay 10% More for AWS](http://archive.today/2026.03.06-144058/https://alexeyondata.substack.com/p/how-i-dropped-our-production-database)
- [Claude Tested Everything Except the One Thing That Mattered (AI agent refuses to follow explicit instructions to test `createPost()` in increasingly erratic ways)](http://archive.today/2026.03.09-201135/https://christophermeiklejohn.com/ai/claude/2026/03/08/claude-tested-everything-except-the-one-thing-that-mattered.html)
- [Amazon calls engineers for a “deep dive” internal meeting to discuss “GenAI”-related outages](https://ghostarchive.org/archive/3TfgF)
- GitClear has released reports in [2024](https://www.gitclear.com/coding_on_copilot_data_shows_ais_downward_pressure_on_code_quality) and [2025](https://www.gitclear.com/ai_assistant_code_quality_2025_research) indicating a worsening of key code quality metrics correlating with increased LLM adoption.

And research showing that those who use LLMs to generate code suffer from "deskilling":

- [Brains show less activity when completing tasks with LLMs](https://arxiv.org/abs/2506.08872) compared to completing tasks with search or completing tasks without digital help.
- [Developers who use early-2025 LLMs](https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/) reported higher subjective performance, but were measured to have lower objective performance. This gap between subjective and objective performance was considered notable.
- In an [Anthropic study](https://www.anthropic.com/research/AI-assistance-coding-skills), learners using LLMs demonstrated lower learning rates on average compared to learners not using LLMs.
- [A recent study uses the term "cognitive surrender"](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6097646) to describe the way humans tend to offload key critical thinking skills onto LLMs, even when the output is wrong.
- A paper entitled ["AI Assistance Reduces Persistence and Hurts Independent Performance"](https://arxiv.org/abs/2604.04721) from April 2026 by academics from MIT, Oxford, UCLA, and Carnegie Mellon showed alarming evidence that performing a variety of tasks with the help of AI for only 10 minutes causes "inpaired unassisted performance and reduced persistence". The researchers noted that "although AI assistance improves performance in the short-term, people perform significantly worse without AI and are more likely to give up"; they also pointed out that "these findings are particularly concerning because persistence is foundational to skill acquisition and is one of the strongest predictors of long-term learning".

# Ethical reasons to avoid "AI"

"Generative AI" as it is currently trained and offered is an inherently unethical tool. Stolen training data is fed into noxious datacenters, the construction of which is enabled by political corruption and in spite of civilian protest, driving up electricity, water, and consumer electronics prices for working people already struggling with the cost of living, the final product of which is used to collect data to enable citizen surveillance and war crimes. The math is morally neutral, but the material way it has been employed is morally bankrupt.

## Environmental impact

- [MIT News: Generative AI's environmental impact](https://news.mit.edu/2025/explained-generative-ai-environmental-impact-0117)
- [MIT Technology Review: We did the math on AI's energy footprint. Here's the story you haven't heard.](https://www.technologyreview.com/2025/05/20/1116327/ai-energy-usage-climate-footprint-big-tech/)
- [Benn Jordan — Datacenters Behaving Like Acoustic Weapons](https://youtu.be/_bP80DEAbuo)

## Impact on hardware prices

- [The RAM shortage is coming for everything you care about](https://www.theverge.com/tech/880812/ramageddon-ram-shortage-memory-crisis-price-2026-phones-laptops)
- [Western Digital is already sold out of hard drives for all of 2026 — chief says some long-term agreements for 2027 and 2028 already in place](https://www.tomshardware.com/pc-components/hdds/western-digital-is-already-sold-out-of-hard-drives-for-all-of-2026-chief-says-some-long-term-agreements-for-2027-and-2028-already-in-place)
- [The 2026 storage crisis: Why AI data centers are hoarding every hard drive on the market](https://www.howtogeek.com/dont-count-on-hdds-to-save-you-from-rising-storage-costs/)
- [Gamers Nexus — RAM: WTF?](https://youtu.be/9hLiwNViMak)
- [Gamers Nexus — SSDs: WTF?](https://youtu.be/-O6FQFhNhiw)

## Use in the war industry

- [NYT: Palantir, Anthropic and small start-ups are generating rewards from their investments in defense tech](https://www.nytimes.com/2026/03/18/technology/silicon-valley-war-defense-tech.html)
- [NPR: OpenAI announced Pentagon deal after Trump banned Anthropic](https://www.npr.org/2026/02/27/nx-s1-5729118/trump-anthropic-pentagon-openai-ai-weapons-ban)
- [Gaza: UN experts deplore use of purported AI to commit ‘domicide’ in Gaza, call for reparative approach to rebuilding](https://www.ohchr.org/en/press-releases/2024/04/gaza-un-experts-deplore-use-purported-ai-commit-domicide-gaza-call)
- [Lavender & Where’s Daddy: How Israel Used AI to Form Kill Lists & Bomb Palestinians in Their Homes](https://www.democracynow.org/2024/4/5/israel_ai)
- [Microsoft says it provided AI to Israeli military for war](https://apnews.com/article/microsoft-israel-military-gaza-hamas-artificial-intelligence-20b2adb438b39ee9cb6eb2f52c1ae44a)
- [Google has dropped its promise not to use AI for weapons](https://theconversation.com/google-has-dropped-its-promise-not-to-use-ai-for-weapons-its-part-of-a-troubling-trend-249169)
- ["We want to use it for everything": How Project Maven became central to America’s AI-powered warfare](https://web.archive.org/web/20260312035736/https://www.independent.co.uk/news/world/americas/project-maven-ai-us-airstrike-iraq-anthropic-b2929138.html)

## Stolen training data

- In 2023, [the Washington Post published a list of sources in Google's C4 data set](https://archive.ph/eehKq). A multitude of fediverse instances and personal sites were included. The fediverse is known for its userbase being major proponents of privacy and opt-in consent, making this especially jarring for those who have chosen to use decentralized social media for control over their data.
- In 2025, [a similar leak of Meta's sources was published](https://archive.ph/NZlf3). Meta's list demonstrates how their integration of ActivityPub into their Threads software has enhanced their ability to scrape content without authorization. Threads is widely blocked in some parts of the fediverse, but their scraping of server CDNs has allowed them to get around that. Notably, both the CDN domains of the managed hosting services masto.host and fedi.monster are included in the list; large servers like mastodon.art, which is hosted by the former and has many artists who've left sites like DeviantArt and others due to their AI scraping of user content, had [media unknowingly scraped](https://mastodon.art/@Curator/115022115346692178).
- In March 2026, [a research paper](https://arxiv.org/html/2603.20957v2) showed that simply fine-tuning LLMs resulted in outputs containing up to 90% of entire (copyrighted) books, contradicting LLM companies' previous statements in court that their models do not store copies of training data. After fine-tuning exclusively on a single author, the researchers were able to cause the LLM to output works from over 30 completely unrelated authors across different genres. None of the models were explicitly trained on these books by the researchers, which indicates that LLMs always carry with them a considerable amount of copyrighted materials from training.

And the potential legal ramifications due to said stolen training data:

- [GitHub Copilot litigation](https://githubcopilotlitigation.com/)
- [IEEE article explaining concerns about AI generated code ownership](https://spectrum.ieee.org/ai-code-generation-ownership)
- [Tracker of broader lawsuits against AI companies](https://chatgptiseatingtheworld.com/2025/11/02/tracker-of-tort-lawsuits-v-ai-companies/)

## Miscellany

- Thanks to [ethical-foss/open-slopware](https://codeberg.org/ethical-foss/open-slopware) for compiling many of the sources in this wall-of-text in an accessible way.
- I'm not religious, but even I find [*Magnifica Humanitas*](https://www.vatican.va/content/leo-xiv/en/encyclicals/documents/20260515-magnifica-humanitas.html) compelling.
- I will never forgive LLMs for making my beloved em-dashes and semicolons not cool. `—;—;—;;; —;—;—;—— —;———;;— ——;;;;;;`
- Useless 'bot-skip' issue tag added for aura

# Suggested policy

I would prefer a strict ban, such as that used by the [Zig programming language](https://codeberg.org/ziglang/zig#strict-no-llm-no-ai-policy). The primary developer of Zig is Andrew Kelley, who notably has [contributed to LMMS](https://github.com/LMMS/lmms/commits/master/?author=andrewrk) in the past. Here's an interview where he explains some of his rationale for the strict ban: [JetBrains — Zig 2026: No-AI Policy, $670K Foundation, Left GitHub & Why Zig Isn’t 1.0 - Andrew Kelley Explains](https://youtu.be/iqddnwKF8HQ)

A slightly more lenient policy, such as that used by the [Servo browser](https://book.servo.org/contributing/getting-started.html#ai-contributions) or the [Rust Audio community](https://rust.audio/community/ai/), would also be acceptable to me.

I love LMMS. :green_heart:

Discussion on Discord for additional context

https://discord.com/channels/203559236729438208/784594576223633478/1524114550469824714

Start by reviewing the linked Zig, Servo, and Rust Audio AI-contribution policies, then read the issue's 38-comment discussion and the linked Discord context. Done means reaching a maintainer decision on the policy's scope and documenting the agreed contribution rules; no implementation file or test is identified in the issue.

Written by the indexing model from the issue text.