[$] MOT: a tool to fight openwashing in AI
The Model Openness Tool (MOT) aims to clarify the openness of large language models (LLMs) amidst concerns of openwashing. Arnaud Le Hors discussed the challenges of assessing model openness at the Open Source Summit North America 2026. The tool is part of a broader effort to establish clearer definitions and frameworks for evaluating the openness of AI models.
- ▪Many LLMs are labeled as open source, but often do not meet the Open Source Initiative's criteria.
- ▪The Model Openness Framework (MOF) categorizes models into three classes based on their openness and completeness.
- ▪Restrictions in model licenses can lead to legal risks for users who assume they can freely use and modify downloaded models.
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| Original publisher | LWN.net (Linux Weekly News) |
| Canonical URL | https://lwn.net/Articles/1073420/ |
| Publication time | Wed, 27 May 2026 15:52:01 +0000 |
| Retrieval time | 2026-05-27T15:58:01.753Z |
| Last seen | 2026-05-27T15:58:04.586Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | sSF4ofGZcQQm |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Did you know...? LWN.net is a subscriber-supported publication; we rely on subscribers to keep the entire operation going. Please help out by buying a subscription and keeping LWN on the net. By Joe BrockmeierMay 27, 2026 OSSNA Many large language models (LLMs) are described as open source, but if one looks a bit deeper it turns out that is not actually so; the model may be free to download, it may be "open weight", but it does not fit the Open Source Initiative (OSI) Open Source Definition (OSD). Assessing the actual openness of models is not easy, as Arnaud Le Hors explained in his talk about the Model Openness Tool (MOT) at Open Source Summit North America 2026.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at LWN.net (Linux Weekly News).