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AI Act transparency: audit chatbots and synthetic content

Transparency is not about adding a generic label to everything: first identify whether your company is a provider or a deployer and which specific obligation is triggered.

What you will achieve now

A decision or proof applied to “AI Act transparency: audit chatbots and synthetic content”.

  • 1 Understand the criterion
  • 2 Do a small practice exercise
  • 3 Save evidence

A brief note covering what you did, what went well, what failed, and what you would review next.

  • Locate chatbots and content generated or manipulated with AI.
  • Distinguish information when interacting with an AI, machine-readable marking, and notice to people who are exposed.
  • Save a dated audit without presenting the exercise as legal advice.

What the official guidance says

The European Commission’s guidelines on Article 50 explain transparency obligations for certain systems. They apply from 2 August 2026. Among the cases described are informing anyone who interacts directly with an AI, marking generated or manipulated content in a detectable way, and notifying people exposed to deepfakes, emotion recognition systems, or texts on matters of public interest without human review or editorial control.

There is an important nuance: the Commission also describes a transitional period for certain generative systems placed on the market before 2 August 2026, until 2 December 2026. Do not turn a start date into a one-size-fits-all answer: check the system, your company’s role, and the current guidance.

Five-step audit

  • List every chatbot, assistant, and public channel.
  • Indicate whether your company provides it, deploys it, or only uses it internally.
  • Review what content is generated or modified and whether there is editorial review.
  • Check the visible notice and technical marking when applicable.
  • Save a screenshot, URL, owner, date, and corrective action.

Primary sources

  • Commission guidelines on transparency obligations .
  • Guidance on transparency of AI-generated content .
  • Official summary of transparency rules .

If you have saved the evidence from this lesson, continue with “Diagnosis and first AI pilot for an SME”. If not, repeat the check before moving on.

Learn with a verifiable reference

Aulafy distinguishes stable concepts from data that changes—versions, prices, models, and commands. Check the course card for the review date, verified scope, and primary sources.

“Editorial review” means structure, claims, and sources have been reviewed. It does not mean every command has been executed: when a technical test exists, it will be labelled as such.

Complete Aulafy mapSee how this lesson fits without leaving your path.

Complete Aulafy map

How all courses connect

This is not a checklist. Start with the foundation, choose an outcome, and go deeper only when your project needs more control.

  1. 1Understand
  2. 2Apply or build
  3. 3Operate with confidence
01

Choose an application

Turn the foundation into a visible outcome: a website, a business improvement, media, or an interactive experience.

Continue into the technical branch when you need to maintain code, data, or infrastructure.

02

Build with code

Prepare your environment, work with coding agents, and run models while keeping control of your projects.

This branch prepares you to design and operate reliable AI systems.

03

Take systems to production

Combine retrieval, agents, evaluation, security, deployment, and model adaptation when the problem requires it.

You do not need every course: choose the component your system needs and return as it grows.

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