# Transparent AI Disclosure Obligations: Who, What, When, Where, Why, How

arXiv: https://arxiv.org/abs/2403.06823 · HTML: https://mlsanity.com/paper/2403.06823/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Mar 2024.

## Built on by (most cited first, 17 of 17)

- ["I Am the One and Only, Your Cyber BFF": Understanding the Impact of GenAI Requires Understanding the Impact of Anthropomorphic AI](https://mlsanity.com/paper/2410.08526/) (2024)
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- [Adoption of Watermarking for Generative AI Systems in Practice and Implications under the new EU AI Act](https://mlsanity.com/paper/2503.18156/) (2025)
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- [More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Production](https://mlsanity.com/paper/2601.11072/) (2026)
- [Label Effects: Shared Heuristic Reliance in Trust Assessment by Humans and LLM-as-a-Judge](https://mlsanity.com/paper/2604.05593/) (2026)
- [The AI Memory Gap: Users Misremember What They Created With AI or Without](https://mlsanity.com/paper/2509.11851/) (2025)
- ["Impressively Scary:" Exploring User Perceptions and Reactions to Unraveling Machine Learning Models in Social Media Applications](https://mlsanity.com/paper/2503.03927/) (2025)
- [Full Disclosure, Less Trust? How the Level of Detail about AI Use in News Writing Affects Readers' Trust](https://mlsanity.com/paper/2601.09620/) (2026)
- [Towards Gaze-Informed AI Disclosure Interfaces: Eye-Tracking Attentional and Cognitive Load While Reading AI-Assisted News](https://mlsanity.com/paper/2605.14999/) (2026)
- [Caring Without Feeling: Affective Dynamics as the Control Layer of Human-AI Agent Collaboration](https://mlsanity.com/paper/2606.18259/) (2026)
- [When Life Gives You AI, Will You Turn It Into A Market for Lemons? Understanding How Information Asymmetries About AI System Capabilities Affect Market Outcomes and Adoption](https://mlsanity.com/paper/2601.21650/) (2026)
- ["I'm happy even though it's not real": GenAI Photo Editing as a Remembering Experience](https://mlsanity.com/paper/2602.03104/) (2026)
- [15 Years of Augmented Human(s) Research: Where Do We Stand?](https://mlsanity.com/paper/2604.03715/) (2026)
- [Voice "Cloning" is Style Transfer](https://mlsanity.com/paper/2605.16578/) (2026)
- [A Regulatory Placebo? The Systemic Failure of Mandatory GenAI Labeling](https://mlsanity.com/paper/2608.16470/) (2026)

## Abstract (arXiv)

Advances in Generative Artificial Intelligence (AI) are resulting in AI-generated media output that is (nearly) indistinguishable from human-created content. This can drastically impact users and the media sector, especially given global risks of misinformation. While the currently discussed European AI Act aims at addressing these risks through Article 52's AI transparency obligations, its interpretation and implications remain unclear. In this early work, we adopt a participatory AI approach to derive key questions based on Article 52's disclosure obligations. We ran two workshops with researchers, designers, and engineers across disciplines (N=16), where participants deconstructed Article 52's relevant clauses using the 5W1H framework. We contribute a set of 149 questions clustered into five themes and 18 sub-themes. We believe these can not only help inform future legal developments and interpretations of Article 52, but also provide a starting point for Human-Computer Interaction research to (re-)examine disclosure transparency from a human-centered AI lens.