Corporate Governance-Based Liability for Artificial Intelligence-Driven Intellectual Property Violations: Reconstructing Business Law Accountability in the Era of Generative Artificial Intelligence
DOI:
https://doi.org/10.56861/nalarnagara.v1i3.124Keywords:
Artificial Intelligence Governance; Corporate Liability; Intellectual Property Law; Business Law; Algorithmic Accountability; Generative Artificial Intelligence; Corporate Governance, Tata Kelola Kecerdasan Buatan; Tanggung Jawab Korporasi; Hukum Kekayaan Intelektual; Hukum Bisnis; Akuntabilitas Algoritmik; buatan generatif Intelijen; Tata Kelola PerusahaanAbstract
The rapid development of generative artificial intelligence has significantly transformed contemporary business models, enabling corporations to automate creative processes, produce digital content at scale, and develop data-driven innovation strategies. While these technological advancements offer substantial economic benefits, they simultaneously raise complex legal challenges, particularly regarding the protection of intellectual property rights. Generative artificial intelligence systems are often trained on large-scale datasets that may contain copyrighted materials, patented technologies, or proprietary databases, thereby increasing the potential risk of intellectual property infringement. In many cases, the output produced by artificial intelligence systems may replicate or imitate protected works without the authorization of the original rights holders. This situation raises fundamental questions concerning legal responsibility, especially when artificial intelligence systems operate autonomously within corporate infrastructures.
This article examines the problem of corporate accountability when artificial intelligence systems deployed in business operations lead to intellectual property violations. Using a normative legal research method combined with a comparative legal approach, this study analyzes how existing legal frameworks address corporate liability in relation to artificial intelligence-driven intellectual property infringement. The analysis focuses on regulatory developments in the European Union, the United States, and Indonesia.
The findings indicate that traditional fault-based liability doctrines are insufficient to address the complex accountability challenges posed by artificial intelligence technologies. Therefore, this article proposes a governance-based liability model that integrates corporate governance principles, technological risk management, and compliance mechanisms. By emphasizing preventive accountability through algorithmic transparency, dataset auditing, and corporate oversight, this framework aims to reconstruct business law accountability in the era of generative artificial intelligence.
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