ARTIFICIAL INTELLIGENCE AND INTELLECTUAL PROPERTY: CHALLENGES AND OPPORTUNITIES

Abstract

This article examines the complex relationship between artificial intelligence (AI) and intellectual property (IP) law, focusing on the legal, ethical, and practical implications of AI-generated content and inventions. It identifies four core challenges: (1) determining ownership and authorship of AI-generated works, (2) addressing patentability and inventorship for AI systems, (3) resolving copyright disputes over AI training data, and (4) reconciling international legal disparities in IP frameworks. The analysis draws on landmark cases such as Thaler v. Comptroller-General of Patents (2021) and ongoing litigation involving GitHub Copilot, alongside scholarly debates from Abbott (2020), Sag (2019), and Yanisky-Ravid and Liu (2018). The article highlights the tension between existing human-centric IP laws and the autonomous capabilities of AI, arguing that rigid adherence to traditional frameworks risks stifling innovation. Conversely, it explores opportunities for AI to enhance IP systems, including streamlining patent examinations, democratizing access to innovation, and improving infringement detection. Ethical considerations, such as accountability for AI outputs and transparency in training data, are emphasized as critical to balancing innovation with fairness. By synthesizing case law, academic literature, and real-world examples, the article advocates for adaptive legal reforms, such as creating new IP categories for AI-generated works and fostering international cooperation. It concludes that collaboration among policymakers, technologists, and legal experts is essential to modernize IP frameworks for the AI era. This work serves as a foundational resource for understanding the evolving interplay between AI and IP, offering actionable insights for stakeholders navigating this transformative landscape.