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Verified 2026-08-14

OSI Open Source AI Definition

The **Open Source Initiative’s Open Source AI Definition (OSAID) 1.0** states when an AI system qualifies as **Open Source AI**—not merely when weights are downloadable. Core freedoms: use for any purpose; study/inspect components; modif...

What it is

The Open Source Initiative’s Open Source AI Definition (OSAID) 1.0 states when an AI system qualifies as Open Source AI—not merely when weights are downloadable. Core freedoms: use for any purpose; study/inspect components; modify (including to change output); share with or without modifications.

<!-- IMAGE: four freedoms + three preferred-form pillars: data info, code, parameters -->

MEDIUM PRIORITYDIAGRAM
◷ IN PRODUCTION

Visual Spec & Architecture Diagram

OSI Open Source AI Definition pillars as pillars/blocks (data openness expectations, code, weights—as summarized in chapter). Footer 'read live OSI text'.

Educational Focus: Anchors the definition chapter visually.

Why it matters

Marketing says “open.” OSAID gives an independent yardstick. Open weights ≠ OSI Open Source AI. Many popular models are valuable and redistributable under community licenses yet do not claim OSAID compliance.

How it works (plain)

OSAID says the preferred form for making modifications to ML systems must include:

  1. Data Information — enough detail for a skilled person to build a substantially equivalent system (provenance, scope, selection, labeling, processing; listings of public and third-party data sources)—under OSI-approved terms.
  2. Code — complete source to train and run (processing, training, validation, tokenizers, inference, architecture, etc.) under OSI-approved licenses.
  3. Parameters — weights/configs under OSI-approved terms (may include intermediate checkpoints / optimizer state examples).

“Open Source models” / “Open Source weights” under OSAID still require the data information and code used to derive those parameters.

Everyday example

Getting a baked cake vs getting the recipe, ingredient list with sources, and kitchen settings. A cake alone is not the preferred form to modify the recipe.

Try it

Pick one “open” model you like. Check OSAID’s three pillars: data information, training/inference code, parameters. Mark each yes/partial/no—without shaming; just classify.

Myths

⚠️ Myth: If I can git clone weights, it’s open source.
✓ Reality: OSAID needs freedoms + preferred form elements.
⚠️ Myth: OSAID bans commercial use.
✓ Reality: The freedoms include use for any purpose without asking permission (see definition text).

Sources