Trademark Search, Artificial Intelligence and the Role of the Private Sector
Sonia Katyal, Aniket Kesari

TL;DR
This paper explores how AI and machine learning are transforming trademark search and selection, impacting legal doctrines, economic considerations, and the roles of consumers and trademark applicants.
Contribution
It introduces a supply-side framework for understanding AI's role in trademark law and empirically evaluates AI-powered trademark search tools.
Findings
AI improves trademark search efficacy
AI tools influence trademark application outcomes
Supply-side considerations are crucial in trademark law
Abstract
Almost every industry today confronts the potential role of artificial intelligence and machine learning in its future. While many studies examine AI in consumer marketing, less attention addresses AI's role in creating and selecting trademarks that are distinctive, recognizable, and meaningful to consumers. Traditional economic approaches to trademarks focus almost exclusively on consumer-based, demand-side considerations regarding search. However, these approaches are incomplete because they fail to account for substantial costs faced not just by consumers, but by trademark applicants as well. Given AI's rapidly increasing role in trademark search and similarity analysis, lawyers and scholars should understand its dramatic implications. This paper proposes that AI should interest anyone studying trademarks and their role in economic decision-making. We examine how machine learning…
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