Made by Human, not by Gen-AI
Website | Github | CC0 Licensed
This is a repository that aims to provide a collection of badges to symbolize that you didn’t use generative AI (notably LLMs) for the creation of your project. By using this, you are expected to ensure that AI-generated code makes up less than 1% of the total written lines of code in your project. You can use the badge only if you ask for assistance like a smart grepper.
Note that nobody will check your code , and if you are against AI use in your codebase but are unsure about the number of lines of code written by AI, you can still use the badge. The goal is to be transparent and to try to reduce the abusive use of AI in codebases.
This repository is accompanied by an explanation that tries to be backed by scientific research to support every claim. But this part is still a work in progress .
What is the ‘by-human’ expected use of AI ?
AI should not be used in the project to generate code. It can instead be used as:
A smart grep or a smart google . For example, fetching in a new codebase where something is implemented or maintained.
Reviewer helper . When having a lot of PRs having an AI to catch bug.
Learn a codebase (example: how do you do X ?) to learn by example or to explain something if there is no documentation. You should write the documentation after if you are maintaining the project.
Using AI to ask for help with a bug , but not to write the fix for yourself.
Asking how a feature could be implemented , but not to write the final implementation for yourself.
Every time you use an AI to help you think, it must be reviewed by a Human. You must also take responsibility of the elements the AI generated or told you.
Note that AI should be used sparingly and only after a Human was unable to provide a quick solution/alternative . You should always take into consideration the output of the AI and the consumption of energy & ecological footprint before using it.
Badge usage
You can copy paste code to your repository or directly use the logos in your project.
## Made by human
a href="https://github.com/Supercip971/by-human"><br>picture><br>source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/Supercip971/by-human/main/transparent-light.svg"><br>source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/Supercip971/by-human/main/transparent-dark.svg"><br>img height="96" align="right" alt="Made by humand, not by gen AI badge" src="https://raw.githubusercontent.com/Supercip971/by-human/main/transparent-light.svg"><br>picture><br>a>
[Project name] is made by **Humans**, and not by a generative AI.
More information can be linked to the [by-human](https://github.com/Supercip971/by-human) repository.
Made by human
[Project name] is made by Humans , and not by a generative AI.
More information can be linked to the by-human repository.
Raw badges
Name
Picture (Dark)
Picture (Light)
transparent-dark.svg +<br>transparent-light.svg
transparent-slim-dark.svg +<br>transparent-slim-light.svg
filled-dark.svg + filled-light.svg
filled-slim-dark.svg + filled-slim-light.svg
Why do we think writing using generative AI is problematic?
Writing using generative AI is inferior in multiple ways. It may appear better and more efficient, but comes with important drawbacks that we enumerate here.
1. Copyright, plagiarism and license-washing
1.1 Plain and obvious license-washing
AI can license-wash unknowingly, and it has already been shown that it can be used to do it on purpose [1].
TL;DR: Claude Code was used to ‘rewrite’ an entire project, which was then relicensed under the MIT instead of the LGPL.
This is a clear license violation.
If one were to claim that it was not, then would tanslating a book remove its copyright?<br>Accepting such a claim would effectively mark the end of copyleft and copyright protections.
1.2 Plagiarism, and not obvious license-washing
When making an LLM learn, it is unable to grasp the license of the code.<br>As shown in two research papers, [2] [3] Large Language Models are generating 3.35% of strong copyleft licensed code and are:
not aware of reusing copyleft code and cannot be asked, through the prompt, to avoid reusing existing code in the responses.
This paper [2] also states that<br>accepting a copyleft request may lead to an increase in copyleft stolen code. (By a factor of 2 to 5).
Ultimately, LLMs are blatantly plagiarizing code. It is a far cry from a human learning about a chunk of code and then creating something based on obtained knowledge;<br>a human fundamentally understands the whole picture and the idea behind the code, and does not rely on rote memorization.
But when an LLM learns, it takes in a large quantity of code from a variety of sources and may spit it back out verbatim to oblivious users. Meaning that the strongly licensed part of the code is in its database, raising concerns about the respect of license.
This is different from a human importing...