How Do We Explain Open-Source AI?

Open-source AI has long been a nebulous concept, lacking a clear and universally accepted definition. This ambiguity has led to confusion and inconsistency in how the term is applied across the technology landscape. For years, the criteria for what constitutes open-source AI were unclear, leaving room for varying interpretations and marketing ambiguities. As a result, its promise—characterized by transparency, accessibility, and collaborative innovation—was often compromised by incomplete or misleading representations. Recently, a breakthrough emerged, establishing a formal definition through the Open Source Initiative (OSI). This new definition aims to provide clarity and set standards for what qualifies open-access AI, ensuring that systems are truly open for use, modification, and sharing, while also mandating transparency regarding training data and model components. Hence, this MIT Technology Review article clarifies the definition of open-source AI, bringing an end to researchers’ long search for a precise explanation. 

According to the article, the Open Source Initiative (OSI) has established a new definition for open-source AI, aiming to standardize what qualifies as open-source in the field. The article suggests that this definition, developed by a diverse group including researchers and tech company representatives, mandates that an open-source AI system must be usable, modifiable, and shareable without requiring permission. Additionally, the system’s components, training data, and source code should be inspectable. The article notes that the lack of a clear standard previously caused confusion and misuse of the term “open source” by companies. While the new definition requires transparency about model weights and allows some discretion regarding training data, it seeks to address issues like the opaque practices of major AI firms. The article concludes that OSI plans to enforce this standard and publish a list of compliant models, which is expected to include names like Pythia and OLMo.

Researchers have long disagreed over what precisely explains open-source AI. We finally have an answer. Read through the preceding text to find out.