Organizations in pharmaceutical, financial, and other regulated sectors face rising pressure to
review large volumes of complex documents against strict and frequently evolving standards, while
preserving the traceability needed to defend decisions to auditors and regulators. Large language
model (LLM) based automation offers clear efficiency gains, but single-agent deployments raise
well-documented concerns about hallucination, opacity, and insufficient auditability, particularly
as regulatory regimes such as the European Union Artificial Intelligence Act begin to impose
explicit human oversight and logging obligations on high-risk systems. This paper proposes a
conceptual framework for multi-agent AI quality control in the review of regulated documents.
The framework decomposes the review task across specialized agents, including extraction,
domain compliance checking, adversarial cross-validation, audit and traceability, and human
interface functions, coordinated by an orchestrator and grounded in a governed regulatory
knowledge base. We describe design principles, architecture, a step-by-step workflow, quality
control mechanisms such as confidence scoring and entailment-based cross-checking, and
evaluation metrics suited to regulated settings. An illustrative scenario drawn from
pharmaceutical Good Practice (GxP) document review demonstrates the framework in use, and a
secondary example from financial disclosure review indicates its generality. We close with a
discussion of open challenges, including correlated error propagation across agents built on
shared foundation models, computational overhead, regulatory acceptance, and security risks
such as prompt injection, and we outline directions for empirical validation.
Michael Ominyi· INTERNATIONAL JOURNAL OF SOC...· 0 citations
This paper examines the three principal legal frameworks governing platform liability for thirdparty content in the transatlantic digital economy: the European Union's Digital Services Act
(DSA), the notice-and-takedown regime of the U.S. Digital Millennium Copyright Act (DMCA)
Section 512, and the broad immunity conferred by Section 230 of the U.S. Communications
Decency Act (CDA), and extends the comparison to the United Kingdom's Online Safety Act,
India's intermediary guidelines, and Australia's social media minimum age regime. Drawing on
enforcement developments through December 2025, including the European Commission's first
DSA fine against X, preliminary findings against Meta and TikTok, the bipartisan Sunset Section
230 Act, the TAKE IT DOWN Act's notice-and-removal mandate, and the Third Circuit's
algorithm-focused ruling in Anderson v. TikTok, the paper argues that these regimes rest on
incompatible theories of platform responsibility. The DSA imposes affirmative, tiered due
diligence duties structured around systemic risk; the DMCA conditions a copyright-specific safe
harbor on procedural compliance with notice-and-takedown; and Section 230 provides close to
unconditional immunity for most other content-related claims, an immunity now under sustained
doctrinal and legislative pressure. The paper traces the doctrinal history of each regime, situates
the analysis within the academic literature on collateral censorship and risk-based governance,
surveys recent case law and enforcement actions across six jurisdictions, and considers the
pressures, legislative, judicial, and market-driven, that may push these regimes toward
convergence or deepen their divergence, concluding with practical implications for platforms
operating across jurisdictions.
Michael Ominyi· INTERNATIONAL JOURNAL OF SOC...· 0 citations
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