Banning Open Source AI Would Be A Mistake

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Banning Open Source AI Would Be A Mistake<br>Nathan Lambert and Kevin Xu<br>Jun 19, 2026

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Audio playback is not supported on your browser. Please upgrade.This post was originally an op-ed co-authored with Kevin Xu of Interconnected for a general, non-technical audience. The gatekeepers — the many media outlets we pitched it to — passed on publishing it. Luckily, we have our own platforms to get the message out. Please help us forward this op-ed to any one you know who is on the fence about open source AI or new to the topic and want to learn more. Thank you.<br>Share

The energy to regulate AI is in the air in Washington. With the recently signed executive order to review AI models, a congressional proposal to legislate AI further, the government possibly taking shares of frontier AI labs, and last Friday’s action prohibiting foreign nationals anywhere from accessing Anthropic’s most advanced models, this may be the opening salvo of more AI regulation to come.<br>We are afraid future actions could inadvertently or intentionally regulate or even ban open source, a much maligned and misunderstood topic in AI. That would be a grave mistake.<br>Open source – simply a process that allows technology to be shared, built, and distributed publicly and transparently – is safe, secure, and drives economic growth. More than 90% of the world’s software was already built on open source and produced more than 8 trillion dollars worth of economic benefits, long before AI entered the picture. Today, open source technology is quietly training, improving, deploying, and securing AI everywhere.<br>For more than three decades, open source has been powering three trends, and upholding three values, which the American society holds dear – education, competition, and innovation.<br>Open source is pro-education because its origin was rooted in academic institutions trying to make technology free and open, not held hostage to the profit-maximizing zeal or the menacing lawyers of large corporations.<br>The precursor of open source is the free software movement, which started in 1983 on the campus of MIT. It was a time when every small act of using software, whether it was teaching students or doing research or improving a printer’s performance, meant paying or dealing with big corporations like AT&T or Xerox. After this struggle gave birth to open source, every student in every university, community college, and coding bootcamp in America now taps into the freedom that open source enables to learn how to program, engineer, and build. Open source is at the heart of technical education everywhere.<br>Open source is pro-innovation because it essentially provides a set of tools plus a community of other users to help anyone turn an idea into reality, for free. Combined with its role in education, it has watered most of the seeds of innovation in recent memory. Some of these seeds stayed as hobbies that brought joy and personal learning to the hobbyists. Others blossomed into huge companies, like Meta, where the initial version of Facebook was built entirely on a stack of open source software.<br>Every day, new ideas or solutions are being coded up in a dorm room, garage, or basement, all because open source lets innovators create without fear of a lawsuit or an expensive bill.

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Open source is pro-competition because it helps the underdogs challenge and compete with the large incumbents, keeping monopolistic threats at bay. Linux, the open source operating system that now runs more than 90% of the world’s cloud computing infrastructure, was the antidote to the Windows monopoly (so much so that former Microsoft CEO, Steve Ballmer, called Linux “cancer”). Android, the open source mobile system, fostered a long string of competitive smartphones before Apple’s iPhone could control the market. Many other examples exist in the more niche, but no less important, segments of self-driving, databases, and semiconductor design.<br>Without the equalizing and democratizing nature of open source, we would all be living with the rent-seeking consequences of more monopolies and less free market competition.<br>Does AI change any of this? No.<br>The duopoly of Anthropic and OpenAI are rapidly concentrating power between them with their closed, proprietary models. Anthropic, in particular, has flexed its monopolistic muscle recently by reducing its most advanced model’s capability when it is being used to improve someone else’s model. While the capabilities of their models are undeniable, so are their price tags and market concentration. Open source AI, mostly in the form of open weight models, has been the only counterweight for startups, educational institutions, and enterprises looking for alternatives.<br>Does open source lead to more safety or security concerns? Not quite.<br>We acknowledge it is worth monitoring the security implications of open source models that may reach...