Problem Statement: The exponential proliferation of Large Language Models (LLMs) has precipitated profound challenges to entrenched copyright regimes and economic equilibria in creative sectors. This manuscript rigorously dissects the intertwined crises of intellectual property infringement and market disequilibrium induced by AI-generated content, proposing an innovative Integrated Socio-Technical-Economic-Ethical (ISTEE) Framework for governance.Methodology: This study adopts a conceptual theoretical framework augmented by novel modeling, characterized as an Interdisciplinary Synthesis that innovatively combines doctrinal legal analysis, quantitative economic modeling (including econometric and game-theoretic approaches), normative ethical inquiry, and quantitative simulations. This synthesis represents methodological originality by bridging disparate disciplines to provide a holistic evaluation, addressing the lack of primary empirical data through rigorous theoretical integration and secondary data synthesis. It scrutinizes copyright doctrines (e.g., Fair Use under 17 U.S.C. § 107), contemporaneous litigation, and economic impacts via labor displacement metrics and market saturation models. Frameworks of Algorithmic Accountability (Diakopoulos, 2016) and Creative Disintermediation underpin the systemic risk evaluation, augmented by sensitivity, uncertainty analyses, and civil rights perspectives (Civil Rights, 2025).Key Findings: Doctrinal inadequacies permit unchecked ingestion of copyrighted corpora, fostering infringement at scale, with 59 active U.S. lawsuits as of November 11, 2025 (CDSS Berkeley, 2025), including recent settlements like Universal Music Group's (UMG) with Udio on October 29, 2025 (Reuters, 2025). Econometric projections indicate 6-7% U.S. workforce displacement under baseline AI adoption (Goldman Sachs, 2025), with global estimates of 92 million jobs displaced by 2030 offset by 170 million new roles (World Economic Forum, 2025), though recent data show no immediate apocalypse (Brookings, 2025). Generative AI could automate up to 26% of tasks in arts, design, entertainment, media, and sports (UOC, 2025), with creative industries facing polarization and revenue risks (HEC Paris, 2025; CISAC, 2024). Ethical analyses reveal entrenched biases amplifying representational harms, compounded by attribution ambiguities, privacy violations, and societal risks, including cultural homogenization, as assessed by the LLM Ethics Benchmark (Nature, 2025).Conclusion/Implication: Imperative policy reforms encompass mandatory watermarking (Kirchenbauer et al., 2023), reciprocity-based licensing inspired by Creative Commons (World Economic Forum, 2025), and adaptive legislation harmonizing innovation with equity via the proposed ISTEE Framework. Absent intervention, creative ecosystems risk significant destabilization, cultural homogenization, and diminished human capital investment, potentially exacerbating civil rights disparities.