AI is rewriting code and the rules: where does that leave open source values?
Open source software thrives on transparency and collaboration, while today’s most advanced AI coding assistants are often built as closed, proprietary systems.
As generative AI becomes more widespread, developers and organizations are asking whether these two worlds can truly co-exist.Opposing philosophies: Open vs. closed development
On the surface, the philosophies of open source development and current AI development appear completely opposed. Open source projects are transparent – anyone can inspect the code, reuse it under defined licenses, and contribute improvements.
In open source, attribution and licensing are core; developers choose licenses that specify how their code can be used and that often require preserving credits.
AI coding assistants, however, operate as opaque learned models. They ingest vast amounts of code (much of it open source) and produce suggestions without revealing the original sources.
The AI’s knowledge is a statistical amalgamation, often lacking clear provenance for the code it generates. Snyk’s researchers warn that black-box AI tools may blend code from multiple sources, risking inadvertent violations.
While open source is built on shared ownership, most AI tools are driven by corporate interests and remain closed. Once AI-generated code is written, there is generally no clear mechanism in place to track, update, or secure code if it turns out to be flawed.
In contrast, open source projects typically release regular updates and security patches, helping to safeguard code where projects remain actively maintained.Opening up models and data
Companies are often reluctant to open up their models or training data, citing competitive advantage and security. This lack of transparency can clash with open source values. In fact, parts of the free/open-source (FOSS) community have reacted strongly against the incursion of black-box AI code into their domain.
There’s a very real fear that AI tools could siphon off open source code without proper credit or compliance, undermining the very premise of open collaboration.
Yet, despite these differences, AI and open source are deeply interconnected.
