Approaches for controlling how data is used in AI pipelines.

Live controls for classifying and blocking Search, Agent, and Training bots, alongside managed preference signals and monetization tools.

A machine-readable licensing schema for clearly signaling reuse permissions and conditions (including payment or use restriction).

Creative Commons framework for communicating expectations and building governance infrastructure around AI use of shared knowledge.

Internet Engineering Task Force is working on a standardized preference signal for AI agents and crawlers ("building blocks that allow for the expression of preferences about how content is collected and processed for Artificial Intelligence (AI) model development, deployment, and use.")

Add subdomains to make content accessible to AI with blocking and monetization.

Rights-cleared book licensing platform for AI training, reference, and transformative use.

Community-centered dataset platform for sharing AI-relevant data under contributor-controlled licenses, access rules, and governance terms.

Registry of signed, attributable rights declarations for public-domain and openly licensed works, linked through content-derived identifiers.

Certification program for AI models and companies that meet stated consent and licensing criteria for training data.

Open-source protocol for privacy-preserving AI and analytics across distributed datasets without centralizing the underlying data.

Content Credentials-based preference system for asking supported generative AI models not to train on or use a creator's files.

Research-backed proposal for modular standard data licenses tailored to AI data sharing.

Enterprise anti-scraping product that detects and blocks persistent content scrapers, now positioned as part of broader AI and LLM bot management.

AI content registry that links content-derived identifiers and timestamps to declarer identity, TDM permissions, and licensing preferences.

OpenMined architecture for permissioned data contribution and attribution-based access in AI systems.

Contributor compensation and licensed visual training-data program tied to Bria's commercially safe generative AI stack.

Live collective licenses for internal AI reuse and external AI training, alongside announced transactional AI rights for copyrighted works.

UK collective licensing offer for AI model training, fine-tuning, and RAG over published text content.

Machine-readable licensing layer that lets websites declare AI usage terms and pricing.

Independent creative registry for recording AI opt-out requests, offering content licensing, and certifying human-created work.

Rights-cleared content marketplace and monetization layer for RAG, assistants, and other AI applications.

Multimodal dataset supplier offering off-the-shelf and custom image, video, and audio training data through Zedge and GuruShots creator networks.

Trade alliance of dataset licensors pushing for legal clarity, ethical sourcing, and scalable licensing markets for AI training data.

Marketplace for ethically sourced, annotated datasets used to train and fine-tune AI systems.

Platform NoAI label that emits HTML and HTTP signals stating artwork is not authorized for third-party AI-training datasets.

robots.txt and HTTP crawler directives can express AI crawler preferences, including disallow rules, per-response X-Robots-Tag headers, and newer Content Signals for search, AI input, and AI training, plus an experimental content-use extension.

Licensed Factiva news and business-information sources made available for enterprise GenAI products, APIs, and research workflows.

A simple anti-scraping tool intended to protect datasets from basic crawlers/scrapers.

Proposal for a commons-based infrastructure for large-scale access to digitized European books with conditional commercial access.

Edge bot-management layer for detecting and blocking AI crawlers and fetchers that scrape website content.

Distributed language-model training approach that lets data owners contribute experts without sharing raw data or giving up opt-out control.

Music licensing platform for rights-cleared AI training data and audio assets.

Licensed-content marketplace for the faith ecosystem, seeded with a pooled guarantee for AI assistants and search experiences.

Hugging Face Hub access-control feature requiring authenticated users to submit an access request before downloading; approval can be automatic or manual.

Finalized v1 API and content-packaging framework through which already-licensed AI systems can request content; separate licensing and bot blocking are required.

Working group standardizing cryptographic authentication for bots and AI agents on the web.

Embedded image and video metadata fields for expressing data-mining preferences, including prohibitions on generative-AI training.

Pilot marketplace for licensing premium publisher content to AI products, initially tested in enterprise and consumer Microsoft Copilot.

Opt-in program that gives NMA publishers access to AI content licensing opportunities with Bria and ProRata.

A 50/50 revenue-share platform connecting publishers with AI companies, with 1,000+ publications and content creators listed as partners.

AI training data platform for compliant exchange of proprietary, real-world datasets across sectors.

Coalition pursuing licensing, compensation, and enforcement for publisher content used by AI systems.

Rights-cleared multimodal data licensing and model-support services for generative AI developers and enterprise partners.

Participatory governance framework for communities to define conditions for data reuse, including AI training.

Opt-in music dataset licensing program that pays rights holders for AI training use of tracks and catalogs.

A proposed machine-readable opt-out convention for commercial AI training via an `ai.txt` file.

Python package and API helpers for checking whether works are opted out before model training.

Registry and opt-out workflow for marking works that should not be used in future AI training datasets.

Publisher coalition building shared standards and licensing frameworks for responsible AI use of journalism.

Licensed access to Stack Overflow's developer knowledge corpus for AI training, fine-tuning, RAG, and agentic use cases.

Asset-level protocol for binding machine-readable TDM and AI-training preferences to digital works.

W3C Community Group report for expressing text and data mining rights reservations and policy links, designed to support the EU DSM Directive's Article 4 mechanism.

Local Contexts labels that let Indigenous communities express culturally specific conditions for access and reuse of knowledge and data.

Marketplace and sourcing network for licensed, non-public real-world datasets for AI model training.

Publisher-oriented trust file that can also declare whether AI training is allowed through a machine-readable `datatrainingallowed=` field.

Proposed AT Protocol mechanism for users to declare data-reuse preferences such as generative-AI training.

Marketplace for rights-managed visual and biometric datasets tailored to AI training and evaluation.

Marketplace connecting rightsholders and accredited AI developers for governed, rights-cleared multimodal datasets.

Platform for structuring, licensing, delivering, and tracking professional video datasets for AI model training.

Enterprise-grade APIs and structured dumps for Wikipedia and sister projects, designed for large-scale reuse in AI, search, and knowledge graphs.