Project Overview

Like most Copyright laws around the world, the Canadian Copyright Act was designed at a time when big data and large- scale computational processing of data had not become mainstream. However, given that works that are subject to copyright protection are being used as part of data sets for text and data mining activities, including the training of machine learning models, the issue of whether copyright laws need to react to this development has arisen internationally and domestically. In a recent public communication, Innovation, Science and Economic Development Canada (ISED) called for insights into copyright and related issues surrounding TDM, including the use of copyrighted works as training data for machine learning models and the development of AI systems. As Canada and other countries grapple with whether and how to regulate the use of in-copyright works for text and data mining activities and as training data for machine learning models, it is important and timely to examine from an interdisciplinary perspective, the interlinkages between copyright, data mining and artificial intelligence and how to ensure that Canada preserves and promotes the public interest in research and innovation. This project seeks to do that. It seeks to bring together a team of legal and non-legal researchers to consider important practical and technical issues in text and data mining, machine learning and the development of AI systems that implicate copyright rules in Canada. The insights from this interdisciplinary project would then be used to analyse the current state of copyright law in Canada with a view to determining whether the use of copyrighted works for text data mining activities, the training of machine learning models and the development of AI without seeking the permission of the copyright owner is lawful or not. The project would also consider the significance of an ecosystem where text and data mining and the development of AI is not unduly constrained by copyright law for the promotion and democratisation of research and innovation.