Gulyamov Said Saidakhrarovich (Tashkent State University of Law; Academy of Science of the Republic of Uzbekistan), Thomas Hoeren (ITM Münster (FRG)), Saidakhror Gulyamov, Islambek Rustambekov (Tashkent State University of Law), Sirio Zolea (Roma Tre University), Edward Juchniewicz (University of Gdansk), Purvi Pokhariyal (National Forensic Sciences University), & Andrey Rodionov (Tashkent State University of Law) have posted Democratizing Innovations: A New Perspective on Intellectual Property to Advance Social Justice in the Age of Ai on SSRN. Here is the abstract:
The rapid advancements in artificial intelligence (AI) capabilities have catalyzed intense debates surrounding the attribution of authorship and ownership of intellectual property (IP) generated through the use of AI systems. As AI becomes increasingly adept at autonomously producing creative outputs such as art, literature, and music, fundamental questions arise regarding the proper allocation of rights and profits from these novel artefacts. The existing legal frameworks, grounded in traditional notions of individual human authorship, struggle to account for the intricate dynamics of collaboration involved in AI-driven creative processes. This destabilizing effect of AI also extends beyond authorship attribution to encompass the distribution of commercial gains accrued from the exploitation of IP assets.This study presents a comprehensive, interdisciplinary analysis aimed at developing a paradigm shift in how society conceptualizes authorship, allocates creative credits, and distributes profits in the emerging era of AI-generated intellectual property. Drawing on a multilayered methodology combining quantitative and qualitative approaches, the research puts forth a central hypothesis that traditional notions of authorship, focused solely on individual human creators, are inadequate in the context of AI-assisted intellectual works. Instead, authorship should be reimagined as a distributed construct, encompassing both the AI systems and the multitudes of data contributors whose collective inputs enable and refine the capabilities of these autonomous creative agents.Grounded in theories of distributive justice, the study further proposes that the commercial profits derived from IP created by AI systems should not accrue solely to the corporations deploying these technologies. Rather, corporate governance structures should be reformed to facilitate an expanded profit distribution model that recognizes and rewards those who provide the data and social knowledge underpinning the development of AI systems. The research offers innovative conceptual frameworks, including the notion of "derivative data rights" and collective licensing regimes, as pathways to actualize more equitable benefit-sharing.Through the integration of legal, ethical, and technological perspectives, this work aims to catalyze a fundamental rethinking of intellectual property rights, corporate social responsibility, and the relationship between artificial intelligence and human creativity. By aligning AI innovation with principles of social justice, transparency, and collective welfare, the proposed solutions hold the potential to democratize prosperity and empower diverse stakeholders to co-shape our algorithmic future.
