- Linux positions AI as an assistance tool, not as a developer replacement
- Human contributors are still fully responsible for their submissions
- Transparency tagging will reveal where AI is used
Linux has confirmed the use of generative AI to support coding is acceptable, but has established several requirements to ensure high-quality output.
For example, code must be compatible with GPL-2.0-only and it must include proper SPDX identifiers.
More importantly, though, while AI assistants like Microsoft Copilot may be accepted in the development process, human developers ultimately remain responsible for the output, reviewing code, ensuring licence compliance and taking full accountability (as before).
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Linux says AI is fine, but humans are still accountable
The move positions AI tools as an assistant rather than a human replacement, with AI agents condemned from signing off code and only humans permitted to certify the Developer Certificate of Origin.
A new ‘Assisted-by’ tag will be added for transparency, used to disclose AI involvement, detailing the model and tools used.
“When AI tools contribute to kernel development, proper attribution helps track the evolving role of AI in the development process,” the Github page reads.
Confirmation from the project behind one of the biggest open-source projects on the planet comes after months of internal debate. Finally, a sensible middle ground seems to have been reached, whereby AI assistance is broadly accepted, but ‘AI slop’ is not.
The decision to implement transparency tagging is also noteworthy, with Linux founder Linus Torvalds previously dismissing total AI bans as unrealistic. Instead, liability for security flaws, copyright issues and so on all sits with the contributors personally.
As for the move’s impacts on the industry, Linux has become one of the first and most influential projects to establish boundaries for AI in such a way.
Looking ahead, we could see more companies and projects adopt similar rules, while others may forge their own way, but Linux has certainly kickstarted a broader discussion about where AI fits in the development lifecycle.
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