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# Pratiques responsables de PAI en matière de médias synthétiques: Un cadre pour l’action collective
- URL: https://www.aigl.blog/pratiques-responsables-de-pai-en-matiere-de-medias-synthetiques-un-cadre-pour-laction-collective/
- Published: 2026-09-18T18:58:12.000Z
- Updated: 2026-09-18T18:58:12.000Z
- Description: A French-language framework setting out recommended practices for the responsible development, creation, sharing and publication of synthetic media. It gives 20 practices on transparency, disclosure, provenance, consent, detection and platform responses.
- Author: Jakub Szarmach
- Tags: Framework, AI Governance, Risk Management, Technical Controls, Responsible AI, Disinformation, #aigl-library

## ⚡ Quick Summary

Published by Partnership on AI, this framework sets out responsible practices for developing, creating, sharing and publishing synthetic media. It defines synthetic, or generative, media as visual, audio or multimodal content generated or modified—usually using AI—that can realistically simulate objects, people or events. The framework is aimed at technology and infrastructure developers, media creators, and those who share or publish this content; these categories can overlap, including for social-media platforms.

Its stated purpose is to manage risks from synthetic media while enabling responsible and beneficial uses. Built from feedback from more than one hundred global partners and PAI’s work with industry, civil society, media, journalism and academia, it proposes 20 practices across four sections. Central mechanisms are transparency about tools and their limits, direct and indirect disclosure of synthetic content, consent, provenance and detection measures, published policies, reporting channels, and corrective action for harmful content. It distinguishes direct disclosure—such as labels, contextual notes, watermarks and warnings—from indirect disclosure, including cryptographic provenance, traceable elements in training data and outputs, metadata, pixel composition, and on-image statements. PAI says it will not audit or certify organisations; the practices are suggested guidance and the document is intended to evolve through annual and ad hoc review.

## 🧩 What’s Covered

The framework proceeds from a definition and purpose statement to role-specific recommendations and two scoped annexes.

- **Purpose, participation and governance:** The opening explains that the recommendations seek to align norms and practices, support both newer and larger actors, and complement other synthetic-media standards and policies internationally. Participating organisations may join a PAI community of practice and contribute to an annual analysis or case study, but PAI does not provide audit or certification.
- **Ethical and responsible use:** Section 1 calls for collaboration on research, technical solutions, media-literacy initiatives and policy proposals. It identifies entertainment, arts, satire, education and research as possible responsible uses, while recognising contextual grey areas. It lists techniques that can be either responsible or harmful, including impersonation, fabricated realistic characters or events, alterations to authentic media, and wholly synthetic soundscapes.
- **Technology and infrastructure designers:** Section 2 asks tool and infrastructure providers to explain capabilities, limits and risks; provide creator and distributor disclosure mechanisms; and apply indirect disclosure elements across code, datasets, training models and software where possible. It also covers privacy-respecting data-sharing research, manipulation detection, durable and accessible disclosure methods, open-source approaches, and published ethical-use policies with restrictions.
- **Creators:** Section 3 covers large-scale producers as well as amateurs, artists, influencers, activists and satirists. It recommends transparency about informed consent where contextually appropriate, ethical-use restrictions and the capabilities, limitations and risks of synthetic content. Creators should disclose synthetic elements where their absence would alter how content is perceived and use available disclosure tools.
- **Distributors and publishers:** Section 4 distinguishes active editorial channels from passive, third-party-content platforms. Both should disclose synthetic content when its presence is established and publish their approach. Active channels should correct harmful content, provide source and context, pursue privacy-reserving provenance, and ensure transparent informed consent; passive channels should implement reporting measures, label, demote or remove known harmful content, and educate users.
- **Scope and risks:** Annex A focuses primarily on realistic audiovisual synthetic media rather than synthetic text or generative AI generally, while noting that some guidance can help with synthetic text. Annex B lists risks including impersonation, fraud, harassment, disinformation, child exploitation, political manipulation, market manipulation, non-consensual intimate content, extortion and fabricated public opinion.

## 💡 Why it matters?

The framework provides an operational division of responsibility across the synthetic-media lifecycle rather than treating disclosure as a task for creators alone. Tool providers are asked to build disclosure and detection capabilities; creators to use them and communicate relevant consent and context; and distributors to disclose, respond and inform users. This is directly relevant to teams establishing controls for realistic generated or manipulated audio-visual content.

Its distinction between direct labels and indirect provenance mechanisms helps organisations consider both audience-facing information and content-level signals. The document also links disclosure design to resistance to manipulation, privacy, accessibility and communication of uncertainty, while identifying harms ranging from fraud and harassment to election manipulation.

## ❓ What’s Missing

The framework is deliberately high level and presents suggested practices rather than auditable requirements. PAI explicitly says it will not audit or certify organisations. It does not prescribe performance thresholds, testing procedures, implementation timelines, enforcement processes, or a method for resolving the contextual grey areas between responsible and harmful uses. Although it names mechanisms such as watermarks, cryptographic provenance and C2PA, it does not provide technical specifications for deploying them. Its primary scope is realistic audiovisual synthetic media, not synthetic text or generative AI as a whole; it says guidance on text may still be useful. The document also recognises that realism thresholds vary with audiences’ media literacy and global context, without setting a common threshold.

## 👥 Best For

Technology and infrastructure providers designing disclosure, provenance, detection and acceptable-use controls; creators working with realistic generated or manipulated media; and media organisations or platforms setting publication, reporting and response practices. It is particularly useful for cross-functional teams that need to map responsibilities among tool providers, creators and distribution channels.

## 📄 Source Details

*Pratiques responsables de PAI en matière de médias synthétiques: Un cadre pour l’action collective* is a 10-page French-language publication by Partnership on AI, dated February 2023\. No individual authors are named. The cover states that this French translation includes technical terms that may lack equivalents and directs readers to the original English framework in cases of ambiguity.