Canadian Federation of Library Associations Position on Copyright in the Age of Generative Artificial Intelligence

The Canadian Federation of Library Associations (CFLA) recently published a position paper on the Canadian government's consultation on Copyright in the Age of Generative Artificial Intelligence.

The CFLA document looks at technical issues, text and data mining, authorship and ownership of works generated via artificial intelligence, and liability for copyright violations regarding AI.

In its summary, the CFLA concludes:

"Copyright law should not be utilized as a tool to tackle the broader societal challenges that may result from the effects of generative AI on society. Nor should AI innovation be constrained in Canada by laws that are inflexible and have fewer exceptions than other competing jurisdictions, such as the US, which has an expansive fair use doctrine for AI developers and researchers to rely on."

"AI possesses the capacity to revolutionize numerous occupations beyond individual creators, and such disruptive innovations have been seen throughout human history such as the printing press, automation in industry, and the digital disruption of the internet, to name a few examples. Addressing the resultant innovative disruption by supporting training for new opportunities in jobs related to AI development or by supporting worker retraining through organizations like community colleges, universities and public libraries, should be approached at an economic and society wide level ... As well, the Canadian government should invest in more grants and support for Canadian creative industries and for creators in the long term."

"As it currently stands there is a huge swath of information that is unavailable to Canadian higher education researchers and smaller independent AI researchers because of technological protection measures and prohibitive licensing fees to access some data sets. This includes licensed library resources that in many cases require additional text and data mining agreements to be able to be used by institutional researchers for TDM [text and data mining] purposes. Researchers may need access to many sets of data in order to complete a project, and there is a real risk that these research projects might not be realized. There is a societal risk of a regime of monopolistic access to data, where large AI or data companies are the only ones that can afford to gather, purchase or assume the risk of accessing data sets ... Democratic access is reduced under licensing regimes. It is in the public interest for Canadian AI researchers to have robust exceptions when it comes to TDM."