The Illusion of Open-Source: a Closer Look at Licensing and Accessibility

In the current era of artificial intelligence development, access to open-source large language models has become a point of interest for both developers and enthusiasts. However, as some have observed, not all open-source models are created equally. Some projects carry the label of open source while simultaneously requiring end users to submit personal information or register for accounts in order to gain access to the model or its associated files. This practice not only contradicts the ethics of true open-source distribution, but also raises concerns about privacy, spam, and data misuse.

The Problem With Conditional Access

One notable issue arises from the requirement to download and apply something called a data protection deletion request filter. This is a file sent to users, which they are advised to install in order to update and limit access to certain data within the large language model. The website that provides this model recommends applying this output filter every six months, and it is implied that they will email it to the user.

Herein lies a serious problem. Why must users provide their contact details just to access a supposedly open-source tool? Why not simply post this filter file publicly on the website? The insistence on collecting personal contact information raises questions about user tracking, marketing intentions, and data control. This is the first major strike against what is claimed to become an open-source model. Open-source projects should not impose such barriers in order to access them.

Mandatory Accounts: Another Red Flag

The second strike relates to the distribution platform itself. In many cases, users are directed to third-party platforms like Hugging Face to download the model. While Hugging Face is a well-known platform in the field of machine learning, it frequently requires users to register and create an account before they can access certain models or data repositories. Even if the model is technically open-source, putting it behind an account wall defeats the purpose of open access.

Upon reviewing several listings on Hugging Face, it became evident that nearly all of them require account creation before access is granted. The bottom of each page typically displays a message stating: Sign up to review the conditions and access this model. This is not in alignment with the ideals of openness. Not all users want to enlarge their digital footprint. Many are actively trying to reduce it. Requiring an account introduces additional risk, such as exposure to spam or vulnerability in the event of data breaches.

What Does Open Source Really Mean?

When discussing the concept of open-source, it is essential to go beyond the technical definition. Open-source does not only mean that the source code is visible and modifiable. It also means that the software or model is truly accessible — without restrictive licensing, without paywalls, and without account creation requirements. The current state of many so-called open-source artificial intelligence models does not reflect this standard.

There is a difference between legally permissible open-source and philosophically open-source. The latter promotes freedom of use, ease of access, and privacy for the user. If one must surrender personal information or agree to intrusive terms of service before accessing a model, then that model is not genuinely open-source by ethical standards.

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Refusal to Participate

For these reasons, some users have taken a principled stance by refusing to install or use models that are not truly open-source in nature. They decline to provide contact information. They refuse to create accounts on platforms like Hugging Face. They reject systems that compromise their privacy or force them to agree to legal terms that indemnify the creators against any use of the model.

This decision is not one of technical capability, but of ethical alignment. There is no justification for requiring a user to disclose their identity or contact details in order to download a piece of software that claims to become open to the public. A true open-source community thrives on trust, transparency, and minimal barriers to entry.

There Are Better Alternatives

Fortunately, there are alternatives available. Although not as numerous as proprietary models, there are still five to ten large language models that are genuinely open-source and publicly available. Many of these can be found on platforms like GitHub, without the need to register or sign in.

Even Meta, the parent company of Facebook — a company that has been widely criticized for its handling of data — offers a large language model that is publicly downloadable on GitHub. Access to these models typically does not require any account creation or agreement to restrictive legal terms. Users can simply download the files, inspect the code, and begin working with the model as they see fit.

What Is the Motivation Behind These Restrictions?

One must ask why platforms and developers impose these restrictions under the guise of open source. The answer is likely rooted in marketing, monetization, and data collection. By requiring users to sign up, companies can build databases of contact information. This enables them to send promotional material, track user behavior, or potentially upsell additional services or tools.

This is not inherently malicious, but it is inconsistent with the spirit of open-source. True open-source initiatives should not rely on user data collection as a prerequisite for access. They should not use legal disclaimers to shift all liability onto the end user while presenting the software as a free and open tool.

Final Thoughts

The idea of open-source software and models is deeply embedded in principles of freedom, transparency, and community. Artificial intelligence, as a transformative technology, deserves an open ecosystem where developers, researchers, and hobbyists can participate without having to sacrifice privacy or autonomy.

Although some companies and institutions continue to dilute the meaning of open-source, it is important for the community to stand firm in its expectations. Users must question any requirement that asks for contact information, forces account creation, or hides critical resources behind login walls. These practices erode the foundation upon which open-source has been built.

Until developers and hosting platforms remove these restrictions, some will continue to reject the label open source as it is currently applied. They will choose instead to support the models and communities that uphold both the legal and ethical principles of true openness.

In conclusion, not everything that claims to become open-source lives up to that name. It is up to the community to demand better, protect privacy, and hold platforms accountable. Open-source must remain open — in both code and access.