Evaluating the Negative Impacts of New Technologies on Intellectual Property Law Using Neutrosophic Z Numbers

Abstract

Emerging technologies like generative AI and blockchain present significant challenges to intellectual property (IP) law, creating ambiguity in assigning ownership and protection. This study addresses the need for robust methods to assess these negative impacts from a legal practitioner's perspective, where uncertainty is prevalent. We introduce and empirically test an assessment methodology using newly formulated Neutrosophic Z-numbers, which explicitly incorporate truth, indeterminacy, and falsity, along with their respective reliabilities. A quasi-experimental design was employed with 30 INDECOPI IP law practitioners, divided into control and experimental groups (the latter receiving specialized training). Participants assessed case studies involving new technologies. Results showed the experimental group demonstrated a statistically significant (p < 0.001) greater ability to identify and analyze the negative IP implications, particularly for AI and blockchain. This research offers a novel tool for IP impact assessment, with practical implications for professional training and regulatory development, contributing to more effective IP rights protection in the digital age.