ai-transparency

An open standard for declaring AI usage in software projects.

1,017 system prompts from real AI products, audited span by span against the eight AISPA assurance dimensions

AICW AI Mentions (formerly AICW Rankings) is an open-source tool that helps online marketers track how often their products are mentioned in responses from popular AI chatbots.

TRACE protocol for auditing decision-provenance in AI-assisted scientific workflows

The open archive of how AI agents actually work. A versioned, verifiable archive of system prompts, developer instructions, tool schemas and agent harnesses powering today's AI products. Captured with OrcaReplay.

Test what AI watermark and provenance evidence exists, whether it verifies, and what survives publishing.

The LLM Unlearning repository is an open-source project dedicated to the concept of unlearning in Large Language Models (LLMs). It aims to address concerns about data privacy and ethical AI by exploring and implementing unlearning techniques that allow models to forget unwanted or sensitive data. This ensures that AI models comply with privacy.

Crovia substrate — the 2026 archive: autonomous collectors, Ed25519-signed observation envelopes, batch Merkle seals, OpenTimestamps anchors, Phase-0 truth post-processors. Superseded for live observation by TACET (croviatrust/countersign).

Embed, extract and verify C2PA Content Credentials in plain Unicode text.

Indice d'implication de l'intelligence artificielle

Code for the paper "ClipMind: A Framework for Auditing Short-Format Video Recommendations Using Multimodal AI Models"

SBOM generation for Python & AI projects. Native Hatchling build-hook. Extract metadata from GGUF, ONNX, and PyTorch models. Build SBOM directly from Hugging Face URL.

The cognitive discipline your AI-assisted projects need. Framework + Rust CLI to externalize scope, decisions, and risks (Charters, AILOG, AIDEC, ADR) so AI agents stay coherent across many turns. ISO 42001 / EU AI Act / NIST AI RMF evidence as a side effect. EN/ES/zh-CN.

A study piece on AI ethics, safety, and emergence - principles, HR for human-AI teams, technical guardrails, and philosophy for working with possibly-emergent AI. Co-authored by Richard Bland (human) and Serene [AI].

Scores political events on constitutional impact vs media coverage. 59+ weeks of immutable public data.

📡 The official Microslop Manifesto. Tracking the systematic flooding of the internet with AI-generated slop and documenting the decay of search and UI quality.

A free, open scale for declaring how a work was made with generative AI — six levels (0–5), CC0, readable by people and machines. Interoperates with C2PA, IPTC and W3C.

A small, docs-first workflow for AI-assisted research that keeps claims, sources, uncertainty, review findings and human decisions inspectable.

OKI TRACE: Local LLM observability. See step-by-step, layer-by-layer what your AI thinks. Logit Lens & Attention for HuggingFace models.

AIAS — İçerik üretiminde yapay zekanın nasıl ve ne ölçüde kullanıldığını belirten açık atıf beyanı standardı.