Not Everyone’s a Fan of Open Source

Despite the positive aspects of the principles of open source and its widespread use, not everyone is sold on it, with critics pointing to risks in security and sustainability. For example, while the transparency in open-source code may allow anyone to inspect for flaws, it also enables malicious actors to exploit vulnerabilities. In many cases, open-source projects tend to lack dedicated security teams, meaning patches can be slow to release, leaving users exposed. Financial viability is another issue; many open-source projects rely on volunteer developers or donations, making funding unpredictable and threatening long-term support and innovation. Without the financial backing of licensing fees that proprietary software can leverage, sustaining high-quality development and support over time is a challenge. Some critics also argue that while open source enables collaboration, it often lacks the reliability and consistent support associated with proprietary systems, creating potential pitfalls for users and developers alike.

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So, What Is Open Washing?

‘Open washing’ is a term coined by internet policy researcher Michelle Thorne in 2009, referring to where using the word ‘open' as a marketing term allows companies to appear open while maintaining control over their products. The term open washing is, therefore, along the same lines as the term ‘greenwashing,’ where companies claim to be environmentally friendly without substantive action. In open washing, companies appear to use “open” branding to exploit open source’s positive connotations without meeting its core values of transparency and accessibility. This co-opting of the term, therefore, undermines the foundational principles of openness, confusing consumers and diluting the legitimacy of the open-source community (open washing is a negative term).

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Why Has Open Washing Become More Common?

Open source’s transformation from a fringe movement to a widely adopted practice has also made it highly attractive to companies looking to capitalise on its reputation. In the early 2000s, companies were wary of open source. For example, Microsoft’s then-CEO Steve Ballmer even called Linux a “cancer” due to the licence requirements that would obligate them to make their entire codebase open if it incorporated open-source elements. Today, however, open source is seen as innovative, ethical, and collaborative. It is endorsed by tech giants, governments, and educational institutions alike, with open-source projects like Linux, Kubernetes, and TensorFlow at the core of many enterprise systems.

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The Appeal of Open Washing in AI and Big Tech

The stakes are especially high in the field of AI. Many AI models, particularly those from major tech corporations, operate under significant secrecy, which allows them to avoid scrutiny on issues ranging from ethical concerns to regulatory compliance. Open washing appears, therefore, to have become a convenient way for these companies to leverage the credibility of open source without actually relinquishing control or opening their models for true public or scientific examination.

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For example, research by Andreas Liesenfeld and Mark Dingemanse at Radboud University surveyed 45 models marketed as open source and found that few actually meet the standards of true openness. The researchers found that only a handful (e.g. AllenAI’s OLMo or BigScience’s BloomZ) genuinely embody open principles.

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In contrast, models from Google, Meta, and Microsoft often allow limited access to specific aspects, such as the AI model’s weights, but withhold full transparency into the training datasets or the processes behind fine-tuning – factors that are crucial for replicability and accountability.

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Regulatory Incentives for Open Washing

The regulatory environment has also further incentivised open washing, particularly with the introduction of the EU’s AI Act, which came into force on 1 August 2024. This legislation, set to shape the governance of AI in Europe, includes special exemptions for open-source models. These exemptions mean that open-source AI products face fewer compliance requirements, especially regarding dataset transparency and ethical considerations. However, the EU has yet to define “open source” for AI models explicitly, leading to a gap that companies can exploit by labelling restricted models as open.

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This regulatory grey area appears to have encouraged large corporations to stretch the definition of open source. By classifying their models as ‘open,’ they can benefit from reduced regulatory burdens while still keeping proprietary information hidden. This kind of open washing could, therefore, shield companies from scrutiny and enable them to bypass scientific and ethical standards that would otherwise apply.

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Why Open Washing Undermines Openness and Transparency

The widespread practice of open washing could be seen as posing a risk to the integrity of the tech industry. For example, when companies brand restrictive products as open, they dilute the meaning of open source and weaken public trust. This practice could harm consumers and developers who assume these models are accessible for improvement, modification, or auditing. Without full transparency, end-users and even governments can’t fully grasp the capabilities and limitations of these tools, potentially leading to misuse and ethical oversights.

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What Does the Open Source Initiative Say About It?

The Open Source Initiative (OSI) is a global nonprofit organisation that promotes and protects open-source software by maintaining the Open Source Definition, approving compliant licences, and advocating for open-source practices across industries. It is also, therefore, one of the most outspoken critics of open washing. For example, the OSI says that “misuse of ‘open’ erodes the fundamental trust” in open-source communities. According to the OSI, this dilution of open-source principles not only misleads the public but also endangers the health of the open-source ecosystem itself, as genuine open-source projects may struggle to gain traction when overshadowed by well-marketed, quasi-open products.

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Composite Measures of Openness

Recognising that transparency in AI is multi-faceted, researchers have now proposed a composite measure of openness that includes access to datasets, training protocols, licensing clarity, and the model’s documentation. An example of this composite measure is a framework on openness in generative AI, presented at this year’s ACM Conference on Fairness, Accountability, and Transparency (FAccT), by Andreas Liesenfeld and Mark Dingemanse, researchers from Radboud University’s Centre for Language Studies in the Netherlands, specialising in language and AI studies.

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Their framework, with its 14 dimensions of openness, highlights how open-source claims cannot rest on a single factor, such as access to model weights or basic documentation. Instead, the researchers say these claims should involve comprehensive access across multiple domains, offering the public, scientists, and policymakers a way to meaningfully assess openness. The idea is that by developing and implementing composite standards, the tech community could, therefore, discourage open washing and promote genuine transparency.

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Clearer Definitions and Standards for Open Source AI

The current ambiguity around open source, particularly in AI, highlights the need for clearer standards. To tackle open washing, the OSI has recently started working on a formal definition for open-source AI, collaborating with various stakeholders to address unique considerations, like access to training data and replicability. This evolving framework aims to set definitive standards for what constitutes open source in the AI landscape, with the goal of curbing open washing and providing a measure for consumers and regulators to gauge the authenticity of open-source claims.

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The Role of Public Awareness and Advocacy

To counter open washing, it may be important for both consumers and developers to recognise and question the authenticity of open-source claims. Community-driven transparency tools, such as open-source databases and audit platforms, can play a role in empowering users to make informed decisions. As Dingemanse notes, “evidence-based openness assessment is essential for a healthy tech landscape.” Awareness campaigns and advocacy groups can also shed light on open washing practices, pressuring corporations to align with true open-source standards.

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What Does This Mean for Your Business?

As technology continues to evolve and embed itself deeper into everyday life, the importance of distinguishing genuine openness from ‘open washing’ becomes ever more critical. Open-source software’s promise lies in its potential for transparency, innovation, and community-driven growth. However, when companies engage in open washing, they undermine these principles, eroding public trust and complicating the regulatory landscape. This practice not only weakens the authenticity of open-source initiatives but also risks obscuring the boundaries between proprietary and truly open technologies, leading to a diluted understanding of what “open” truly represents.

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The movement to counter open washing is gaining momentum through research, community initiatives, and regulatory efforts, yet it ultimately depends on public awareness and industry accountability. Informed consumers and developers play a vital role in demanding transparency and authenticity from tech giants. With organisations like the Open Source Initiative working to refine definitions and create accountability standards, there is hope for a future where open-source principles are upheld, respected, and protected. Clear standards and genuine openness are essential to sustaining an ecosystem where “open” means more than marketing, symbolising a commitment to collaboration, integrity, and the shared progress of technology.

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With clearer definitions, regulatory oversight, and a strong community voice, it appears possible for the tech industry to preserve the values of openness and transparency while guarding against open washing. By holding companies accountable to genuine open-source principles, users, developers, and policymakers could help ensure that “open” remains a meaningful and respected term in the technology landscape.