From Reports to Reality: Testing Consistency in Instagram's Digital Services Act Compliance Data
- URL: http://arxiv.org/abs/2507.01787v1
- Date: Wed, 02 Jul 2025 15:13:25 GMT
- Title: From Reports to Reality: Testing Consistency in Instagram's Digital Services Act Compliance Data
- Authors: Marie-Therese Sekwenz, Ben Wagner, Hans De Bruijn,
- Abstract summary: The Digital Services Act (DSA) introduces rules for content moderation and platform governance in the European Union.<n>This study examined compliance with DSA requirements, focusing on Instagram.<n>We develop and apply a multi-level consistency framework to evaluate DSA compliance.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: The Digital Services Act (DSA) introduces harmonized rules for content moderation and platform governance in the European Union, mandating robust compliance mechanisms, particularly for very large online platforms and search engines. This study examined compliance with DSA requirements, focusing on Instagram as a case study. We develop and apply a multi-level consistency framework to evaluate DSA compliance. Our findings contribute to the broader discussion on empirically-based regulation, providing insight into how researchers, regulators, auditors and platforms can better utilize DSA mechanisms to improve reporting and enforcement quality and accountability. This work underscores that consistency can help detect potential compliance failures. It also demonstrates that platforms should be evaluated as part of an interconnected ecosystem rather than through isolated processes, which is crucial for effective compliance evaluation under the DSA.
Related papers
- The AI Imperative: Scaling High-Quality Peer Review in Machine Learning [49.87236114682497]
We argue that AI-assisted peer review must become an urgent research and infrastructure priority.<n>We propose specific roles for AI in enhancing factual verification, guiding reviewer performance, assisting authors in quality improvement, and supporting ACs in decision-making.
arXiv Detail & Related papers (2025-06-09T18:37:14Z) - Improving Regulatory Oversight in Online Content Moderation [2.1082552608122542]
The European Union introduced the Digital Services Act (DSA) to address the risks associated with digital platforms and promote a safer online environment.<n>Despite the potential of components such as the Transparency Database, Transparency Reports, and Article 40 of the DSA to improve platform transparency, significant challenges remain.<n>These include data inconsistencies and a lack of detailed information, which hinder transparency in content moderation practices.
arXiv Detail & Related papers (2025-06-04T16:38:25Z) - MSDA: Combining Pseudo-labeling and Self-Supervision for Unsupervised Domain Adaptation in ASR [59.83547898874152]
We introduce a sample-efficient, two-stage adaptation approach that integrates self-supervised learning with semi-supervised techniques.<n>MSDA is designed to enhance the robustness and generalization of ASR models.<n>We demonstrate that Meta PL can be applied effectively to ASR tasks, achieving state-of-the-art results.
arXiv Detail & Related papers (2025-05-30T14:46:05Z) - AI-Supported Platform for System Monitoring and Decision-Making in Nuclear Waste Management with Large Language Models [1.6795461001108096]
This paper presents a multi-agent Retrieval-Augmented Generation (RAG) system that integrates large language models (LLMs) with document retrieval mechanisms.<n>The system ensures regulatory decisions remain factually grounded, dynamically adapting to evolving regulatory frameworks.
arXiv Detail & Related papers (2025-05-27T20:29:53Z) - Doing Audits Right? The Role of Sampling and Legal Content Analysis in Systemic Risk Assessments and Independent Audits in the Digital Services Act [0.0]
The European Union's Digital Services Act (DSA) requires online platforms to undergo internal and external audits.<n>This article evaluates the strengths and limitations of different qualitative and quantitative methods for auditing systemic risks.<n>We argue that content sampling, combined with legal and empirical analysis, offers a viable method for risk-specific audits.
arXiv Detail & Related papers (2025-05-06T15:02:54Z) - AlignRAG: Leveraging Critique Learning for Evidence-Sensitive Retrieval-Augmented Reasoning [61.28113271728859]
RAG has become a widely adopted paradigm for enabling knowledge-grounded large language models (LLMs)<n>Standard RAG pipelines often fail to ensure that model reasoning remains consistent with the evidence retrieved, leading to factual inconsistencies or unsupported conclusions.<n>In this work, we reinterpret RAG as Retrieval-Augmented Reasoning and identify a central but underexplored problem: textitReasoning Misalignment.
arXiv Detail & Related papers (2025-04-21T04:56:47Z) - Do as We Do, Not as You Think: the Conformity of Large Language Models [46.23852835759767]
This paper presents a study on conformity in large language models (LLMs) driven collaborative AI systems.<n>We focus on three aspects: the existence of conformity, the factors influencing conformity, and potential mitigation strategies.<n>Our analysis delves into factors influencing conformity, including interaction time and majority size, and examines how the subject agent rationalizes its conforming behavior.
arXiv Detail & Related papers (2025-01-23T04:50:03Z) - Service Level Agreements and Security SLA: A Comprehensive Survey [51.000851088730684]
This survey paper identifies state of the art covering concepts, approaches, and open problems of SLA management.
It contributes by carrying out a comprehensive review and covering the gap between the analyses proposed in existing surveys and the most recent literature on this topic.
It proposes a novel classification criterium to organize the analysis based on SLA life cycle phases.
arXiv Detail & Related papers (2024-01-31T12:33:41Z) - An Empirical Study on Compliance with Ranking Transparency in the
Software Documentation of EU Online Platforms [7.461555266672227]
This study empirically evaluate the compliance of six major platforms (Amazon, Bing, Booking, Google, Tripadvisor, and Yahoo)
We introduce and test automated compliance assessment tools based on ChatGPT and information retrieval technology.
Our findings could help enhance regulatory compliance and align with the United Nations Sustainable Development Goal 10.3.
arXiv Detail & Related papers (2023-12-22T16:08:32Z) - Accountability in Offline Reinforcement Learning: Explaining Decisions
with a Corpus of Examples [70.84093873437425]
This paper introduces the Accountable Offline Controller (AOC) that employs the offline dataset as the Decision Corpus.
AOC operates effectively in low-data scenarios, can be extended to the strictly offline imitation setting, and displays qualities of both conservation and adaptability.
We assess AOC's performance in both simulated and real-world healthcare scenarios, emphasizing its capability to manage offline control tasks with high levels of performance while maintaining accountability.
arXiv Detail & Related papers (2023-10-11T17:20:32Z) - Auditing Recommender Systems -- Putting the DSA into practice with a
risk-scenario-based approach [5.875955066693127]
European Union's Digital Services Act requires platforms to make algorithmic systems more transparent and follow due diligence obligations.
These requirements constitute an important legislative step towards mitigating the systemic risks posed by online platforms.
But the DSA lacks concrete guidelines to operationalise a viable audit process.
This void could foster the spread of 'audit-washing', that is, platforms exploiting audits to legitimise their practices and neglect responsibility.
arXiv Detail & Related papers (2023-02-09T10:48:37Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.