Certificate course
Digital Media, AI and Information Integrity
Creating, verifying and distributing information in an automated environment: information integrity, manipulated media, generative AI, verification, provenance, disclosure and human oversight.
This certificate is one of six that support Media Card applications. The Media Card is administered by EurAV European Audio Visual CLG, not by EANE.
See all six courses in this collection ≈ 77 minutes total11 credits to earn the certificate
Learning outcomes
Upon successful completion, learners will be able to:
- ▸Explain how information spreads and fails online
- ▸Verify images, video and AI-generated claims using practical methods
- ▸Use generative AI in media work with appropriate checking and disclosure
- ▸Keep meaningful human oversight over automated publishing
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Compulsory modules · all 11 required
How information travels now: platforms, feeds and incentives
How claims actually move online: ranked feeds, sharing loops, platform incentives, lost context, closed groups, and why corrections rarely catch up.
Information integrity: what it means and how it fails
What information integrity means across content, process and source, how it degrades by accident or design, and what a community loses when trust collapses.
Misinformation, disinformation and coordinated manipulation
How to tell organised manipulation from ordinary error, and how to report a suspicious trend without presenting it as public opinion or giving it free reach.
Generative AI in media production
What generative AI can and cannot reliably do in a newsroom or content team, and how to keep editorial judgement with a named person.
Hallucination: why AI invents facts and how to catch it
Why AI systems state invented facts, quotes and citations with confidence, and the practical checks that catch fabricated detail before publication.
Verifying images and video
A practical sequence for checking photos and video before you publish: earliest version, frame-by-frame inspection, location and weather, metadata, and the filmer.
Deepfakes, voice cloning and synthetic people
How synthetic audio and video are made, why detection is unreliable, and how to assess and report a suspected deepfake without amplifying it.
Provenance, watermarking and authenticity signals
How content credentials, watermarks and archived originals help you establish where media came from, and why a missing signal proves far less than people assume.
Disclosing AI use to your audience
How to decide which AI use your audience needs to know about, and how to word, place and standardise disclosure so it informs readers without becoming noise.
Automation with a human in the loop
How to build automated feeds, alerts and summaries that keep a named, empowered human answerable, with review tiers, logging, monitoring and a working stop switch.
Data protection, digital security and the wider costs of AI
How to protect audience data, sources and confidential material when using AI tools, and how to weigh the copyright, energy and labour costs behind the models.