GPAI Intellectual Property (IP) Primer

This is a simple and practical guide to intellectual property (IP) for AI practitioners. The targeted audience is small and medium-sized enterprises (SMEs) who plan to develop or employ AI technologies, but it is also useful for anyone who is interested in AI. In this document, “AI” is synonymous to an information system that uses machine learning (ML) technologies in some part of the system. An AI system is a machine-based system that is capable of influencing the environment by producing an output (detections, predictions, recommendations, or decisions) for a given set of objectives. It uses machine and/or human-based data and inputs to: (i) perceive real and/or virtual environments; (ii) abstract these perceptions into models through analysis in an automated manner (e.g., with machine learning), or manually, and (iii) use model inference to formulate options for outcomes. AI systems are designed to operate with varying levels of autonomy. This document consists of five sections. Chapter 1 (What is Intellectual Property (IP)?) provides an overview of the concepts of intellectual property. Chapter 2 (IP Issues in AI) describes IP issues specific to AI. Chapter 3 (Difference Between Jurisdictions) is on legal rules, with a special focus on differences between different jurisdictions. Chapter 4 (IP Management for SMEs) has tips for SMEs on how to manage IP. Each section is concluded with a list of useful resources. The readers are encouraged to follow these links to further understand the topics. Finally, the last chapter, Chapter 5, is dedicated to FAQs.