As companies rapidly integrate artificial intelligence into their workflows and user-facing platforms, it is more important than ever for creators—and those who may not identify as creators but are—to understand their fundamental copyright rights within their respective countries. Yet the responsibility for developing copyright education often falls to intellectual property professionals who, despite deep subject expertise, may have limited training in designing accessible, engaging instruction for non-specialists. The result is a familiar divide: educational resources tend to be either overly simplified or prohibitively complex.
As a copyright specialist working within libraries, I advocate for and actively build a middle ground between these extremes. Through library workshops, classroom visits, and the creation of research guides, I focus on translating complex copyright concepts into practical, usable knowledge that empowers creators to make informed decisions about their work—particularly in AI-mediated environments.
This session is a call to action for copyright and IP professionals to make a concentrated, collective effort to rethink how we approach copyright education in the age of AI. By prioritizing pedagogical skill-building alongside legal expertise, we can create more effective learning experiences that center creators’ needs. Strengthening copyright education is not simply about awareness—it is about ensuring creators are not left behind as technologies evolve and that they are equipped with the knowledge necessary to protect, license, and advocate for their work.

Generative Artificial Intelligence (GenAI) is rapidly reshaping academic practice, simultaneously amplifying human capabilities and challenging foundational scholarly norms. This paper offers a comprehensive examination of GenAI’s role in open education, including research, scholarly writing, teaching, and publishing. It first surveys evolving copyright and intellectual property frameworks, highlighting the openness of AI-generated works that are born in the public domain. The uncertain “grey zone” of human–AI collaboration, and emerging fair use/dealing jurisprudence around training data and text and data mining exceptions are also addressed The analysis then turns to authorship, plagiarism, and academic integrity, noting that plagiarism of AI is not possible, whereas fraud can be committed when AI use is not disclosed. AI can constitute deceptive practice even when no human is directly plagiarized.
Benefits and challenges for authors, editors, reviewers, and publishers are explored, including productivity gains, enhanced accessibility for non-anglophone scholars, scalable feedback in education, and workflow efficiencies in editorial and production processes. These advantages are weighed against risks such as the erosion of human judgment and creativity, amplification of bias and inequity, environmental costs, the proliferation of hallucinations, misinformation, and automated scholarly fraud.as well as the malevolent oligarchic concentration of AI platform ownership. Openness must be supported with concrete institutional, publishing, and governmental policy actions. GenAI can be directed toward a symbiotic, human-centered future in education, but this will require sustained ethical oversight, adaptive regulation, and a commitment to true openness.

Independent musicians, like many others, face numerous challenges when it comes to getting remuneration for their work. Most streaming music services pay smaller musicians/ bands very little to not at all, and with the disruptions of COVID and increasing geopolitical tensions with the US, touring is an increasingly fraught endeavour. The music industry and their lobbying have captured much of the policy process, so despite new calls from creators for stronger copyright protection, copyright reform is a limited avenue for solutions without stronger antitrust and anti-monopoly actions. However, projects like EPL\ts Capital City Records provide alternative models for public streaming infrastructure that prioritize care and community. To this end, our panel will explore how public infrastructure (public streaming platforms, community/public radio, non-profit venues) might help remedy issues facing musicians in Canada that result from the corporatization and concentration across record and tech companies in the digital age. We will discuss our ongoing research on this topic and other possible models for public infrastructure and governance, and share insights from our interviews with independent musicians on what contributes to a sustainable independent music creator community in Canada. A particular focus of this presentation will be to consider ways that public institutions, like universities, can play a much larger role in advocating for, and serving as a model of, public infrastructure for music communities.

Canada, like most countries globally, is reexamining its copyright laws and policies in response to the widespread adoption of generative AI tools. The emergence of these tools has raised key copyright issues, such as the copyrightability of AI-generated works, the legality of using copyrighted material for AI training, and liability for infringing AI-produced works. In 2023, Canada conducted a public consultation on these issues, inviting Canadians to review existing copyright policy considerations in light of their experiences with generative AI. The government received 103 submissions from a variety of stakeholders. Our project aims to understand public opinion on whether and how copyright laws and policies should be reshaped in response to generative AI. To achieve this, we have extracted the opinions expressed in all submissions, categorized the contributors to this consultation, and examined patterns in their views. We seek to identify whether there are correlations in the opinions of individuals and groups within the same stakeholder category regarding the three main issues of AI training, AI ownership, and AI infringement, and to understand what these correlations might be (if any). We will also review the Government’s “What We Heard” document to determine if any stakeholder category had a disproportionate impact on the Government’s observed outcomes of the consultation. Lastly, the project will explore the extent to which public opinion on copyright policy considerations remains consistent or is evolving, and the potential direction of copyright amendments related to generative AI in Canada.

I am proposing a lightning talk that brings awareness to how publishing companies are covertly adding clauses to contracts that give them the right to sell an author’s work in order to train AI models without the authors knowledge or consent. It is more widely known that generative AI is a large language model that uses a mathematical algorithm to predict the likelihood of which word should complete the next sentence. However, the lack of accuracy is allowing false information entering academic spaces that are supposed to be build integrity. Additionally, people are becoming increasingly aware the information used to train generative AI is data scraped from all across the internet regardless of author’s knowledge and consent. Previously, AI only had access to information that was published. My growing concern is about the books that are not written. Traditionally, in a publishing contract, publishing and reproduction right remain with the author and the editor. However, large publishing houses are adding stipulations into the fine print to reserve the right to sell the publishing rights to any third party that they see fit without the consent or knowledge by the author. In other words, publishers are reserving the right to sell authors data to train AI models without the author’s informed consent. I would like to use this lightening talk to bring awareness to anyone who is publishing work to methodically read the contract and check the fine print before they sign away the rights to their work.

This lightning talk introduces audience members to section 3 of the Terms & Conditions for OCLC’s WorldCat Entities, “Use of WorldCat Entities Services.” The first two of this section’s five clauses licence the WorldCat Entities data under a CC BY-NC 4.0 license, and permit attribution through the inclusion of an entity’s URI. The remaining three, however, restrict certain forms of use and access and permits OCLC to revoke use or access at their discretion. We will turn to the CC BY-NC 4.0 legal code and other Creative Commons documentation to get a sense of whether OCLC have violated the license terms or have found the exact loopholes they needed. No matter the answer, why OCLC chose to apply this license only to then add what appear to be additional restrictions remains a lingering question.

Like many of us in academia, I regularly speak with our campus community about copyright, licensed materials, and academic integrity. Like many of us who work with copyright even beyond academia, I occasionally find myself down an interesting (at least, interesting-to-me) rabbit hole. And like a certain bear of very little brain, I occasionally find myself stuck in that rabbit hole and need a little help getting out.
This workshop begins with a short talk about Winnie-the-Pooh to illustrate examples of some common and complicated copyright questions. From there we move into an open discussion where participants are invited to share their favourite exemplars of copyright issues. Finally, I’ll describe a thematic conference for which my colleague and I worked backwards, hunting for intellectual property quandaries to slip copyright literacy into events where audiences are already engaged.

Details forthcoming.

Indigenous cultural heritage was codified by UNESCO’s 2003 Convention for the Safeguarding of the Intangible Cultural Heritage, Canada is one of only a few countries that have not ratified this Convention. As such, there is limited formal protection of Indigenous Canadians’ intangible cultural heritage, and few avenues to seek redress when intellectual property is stolen.
While Canadian copyright law does introduce challenges for Indigenous peoples, particularly in terms of collective ownership, commodification of sacred knowledge, and international application, it also offers unique legal opportunities. This presentation will therefore provide an overview of some of the challenges of applying Canadian copyright law to Indigenous materials, and in particular intangible cultural heritage, as well as the potential opportunities it can afford.

This presentation by CARL and ARL highlights a crisis invisible to most researchers: major academic publishers are using license agreements to restrict the use of AI and computational research methods that are legal under copyright law. These restrictions exist in contracts that only libraries see, negotiate, and sign—while researchers and students remain completely unaware that their rights as scholars are being curtailed by these contracts.
Drawing on licensing agreements from major publishers and interviews with North American librarians, this session reveals how contract clauses prohibit training AI tools or sharing research software; how publishers demand premium fees for “”AI rights”” to already-licensed research; and how libraries face impossible liability terms for policing all user activities. Attendees will understand how a hidden system of research restrictions—imposed not by law, but by private contracts agreed to behind closed doors—is reshaping what kinds of research are institutionally permitted in the age of AI.

Our research team ran a survey and hosted focus groups in Fall 2025 to find out what the copyright specialist position looks like today at Canadian colleges, institutes, and universities. Our study updates and expands the “”cross-Canada selfie”” shared by Erin Patterson at the 2016 ABC Copyright Conference.
In this research project, we invited employees responsible for managing or delivering copyright services across all levels of post-secondary schools in Canada tell us what their everyday work looks like. We also wanted to understand how the copyright specialist position has stayed the same or has changed over the past 10 years.
Our research team will share some preliminary findings that have arisen from our study thus far.

As AI systems rely on large-scale ingestion of online content, creators, educators, and cultural heritage institutions need better ways to communicate how they want their work to be used. Even though copyright law provides important protections, it was not designed to govern machine-driven reuse at scale. This tension has caused confusion, frustration, and a growing sense that the norms of the digital commons are eroding. Creative Commons Signals offers a new way to express creator expectations in the age of AI where works may be used in AI training or other automated processes. These new expressions can indicate a creator’s desire for credit, financial support, or other forms of acknowledgement, without attempting to expand copyright beyond its intended scope. This presentation introduces the foundational concepts behind Creative Commons Signals and considers fundamental questions: Can a voluntary, non-binding system meaningfully influence AI developers or AI systems? What might impede platforms from adopting CC Signals consistently enough to matter? What options do creators have whose expectations conflict with the various incentives driving AI development? How might CC Signals interact with existing CC licenses when expectations and copyright permissions diverge? This presentation provides an opportunity to think about how CC Signals might work and what it would take for this new framework to succeed in a rapidly evolving AI ecosystem.

In English speaking Canada, 2012 became an important pivot point in the collective licensing of copyright. Post-secondaries in every province except Quebec needed to decide whether or not to continue collective licensing with Access Copyright. The 29 university library members of CARL (the Canadian Association of Research Libraries) became an important microcosm in looking at how decisions were made. 12 CARL members opted out of a relationship with Access Copyright; 11 CARL members signed the new Access Copyright license; and the six Quebec university library members continued their licensing with Copibec. The author interviewed 13 copyright officers and seven university librarians at CARL institutions to learn about how the decision to opt-in or opt-out of licensing was made. Differences in university administration; institutional perception of risk; and the ability of individual institutions to build their own compliance regimes seem to have been the deciding factors in deciding whether or not sign the new Access Copyright license.

Courts around the world are seeing a growing wave of litigation over the use of copyright protected works to train large scale Generative AI models. Although early public attention has centred on U.S. cases, the underlying analytical frameworks don’t always translate neatly into Canadian law. This presentation looks at how several of the issues emerging in the U.S. might be approached in Canada, focusing in particular on the key differences between the U.S. doctrine of “fair use” and Canada’s fair dealing framework.
Canadian courts rely on a two step, enumerated purpose analysis grounded in CCH and later Supreme Court jurisprudence, as distinct from the more open-ended inquiry, largely focused on transformational use, that now frames American fair use decisions. This raises several questions: for instance, will Canadian courts treat AI training as a form of “research”? To what extent do the circumstances of acquisition matter, or the circumstances under which the underlying data was assembled? The discussion also considers whether the market impact factor—which can be nearly determinative in U.S. fair use cases—may hold comparatively less weight in Canada’s holistic, user-rights oriented framework.
Finally, the talk explores whether the absence of a central inquiry on transformation in Canada risks pushing the law toward a more rigid, categorical approach, and in doing so, losing sight of copyright’s basic aim of fostering new creative expression, or whether we will see a further shift in Canada towards transformative use.
These considerations suggest that Canada’s path through emerging AI related copyright questions may leave our law itself transformed as Generative AI collides with the Copyright Act.

Copyright collective societies like Access Copyright are entrusted with the administration of rights for works in their repertoires. But what constitutes those repertoires, and how accurately are those rights represented?
Building on the observation explored on Howard Knopf’s blog that Access Copyright lists public domain works in its “pre-cleared” Repertoire, this study identifies other categories of titles represented as being licensed under a “Comprehensive Licence” or available under a “Pay Per Use” licence. We focus on works that raise questions about the legitimacy of Access Copyright’s claimed scope of rights, including works from publishers who do not appear to be affiliated with Access Copyright and works that are self-published and/or openly licensed, including the titles published through the University of Toronto Libraries Open Monographs partnership with the University of Toronto Press.
Our presentation outlines our methodology, our findings, and considers the practical consequences of Access Copyright’s practices for copyright holders, institutions relying on comprehensive licences, and policymakers.

In 2024 Ontario Tech University hired a copyright librarian for the first time. Many student questions received in the first months centred on intellectual property protection, as graduate students in particular created and invented over the course of their thesis research. In response, in collaboration with the university’s IP Officer, we developed a workshop for graduate students to address this newfound status as creators. It built on existing knowledge of copyright for users and expanded it to include other forms of IP rights and questions such as understanding the balance of seeking multiple forms of IP protection, commercializing work, and how the home academic institution and its policies fit into IP.

The Canada Copyright Act states that ownership of a work and its authorized use belongs solely with the author/creator of the work, however, it fails to explicitly define who or what the term “author” can apply to. In this lightning talk, I want to explore the implications of allowing works created by generative AI to be copyright protected–and what that could mean for authorship in Canada. Changes to current legislation in favour of this have the potential to create an imbalance between copyright holders and public users, redefine “originality” in authored materials, and devalue human creativity by allowing the use of copyrighted materials to teach AI programs through text and data mining (TDM).
Generally, authorship is “attributed to a natural person who exercises skill and judgment in creating the work…” Legal personhood is not a monolith; historically, marginalized groups were denied the right to be recognized as legal persons and were therefore excluded from civil procedures, which extends to the right to own property, including intellectual property. Within this social and historical context, what rights can or should be granted to generative AI systems that allow them to be trained using TDM to generate works–and own the intellectual property rights to that output? Can legal personhood be granted to AI programs?
Between economic considerations of the AI industry and previous legal precedence of non-human entities being granted personhood, this may very well be a real possibility, and it may affect the moral rights of authors under the Copyright Act, which allows creators to defend against infringement and liability against unauthorized use of their works.

Licensing rules for creative work often remain abstract until you attempt to build something. This session moves copyright law out of the lecture hall and into a live generative art demonstration where licensing choices have immediate, visual consequences. Using TouchDesigner, I will build a reactive visual system in real time, pausing at each step to display and explain the implications of different licensing options. Whether selecting public domain audio, Creative Commons samples, commercial asset packs, or AI-generated content, we will examine how each choice fundamentally alters what the finished work can legally achieve, including its eligibility for live performance, online sharing, or redistribution to other artists. The demonstration will unfold across three distinct frameworks, starting with fully open-source materials (CC0 and CC-BY) that offer freedom from restrictions, moving to restricted materials (CC-BY-NC audio and EULA-gated models) where commercial use is blocked, and concluding with a mix of commercial and AI-generated sources where ownership rights are ambiguous. This progression will illustrate just how complex the decision-making process becomes for creatives once legal considerations are fully factored in.

A researcher who writes with liberal quotation, but is upset at anyone copying from her own work. An instructor who requires students to post to public websites, but rails against students posting syllabi externally. A publisher whose publication agreement bars the author from sharing more than 25% of their own book to prevent “”AI misuse””, but commercially licenses the full text of their published books to AI companies…
Copyright law reflects complex social ideas about who is a “valid” creator – certain types of works are recognized as protectable, while others are not. Statute and caselaw also reflect ideas about who is a “valid” -user- of existing works – for example, the kinds of uses that fit within fair use and fair dealing, or the fact that, very broadly speaking, courts tend to be more tolerant of artistic uses from genres of art familiar to the presiding authority.
But many types of copyright “uses” occur without direct interaction with courts or statutes, and our interpersonal and small-scale business interactions also illustrate our complex and sometimes internally contradictory thinking about who is a valid “user” and who gets to make decisions about what is a valid “use”.
Presenter Nancy Sim of the University of Minnesota s has been struggling with these ideas for years, and invites you to join together for an interactive session exploring contradictory or contestable ideas of “valid uses/users”. Bring examples from terms of use, contracts, syllabi, court cases, and your own knowledge and experience.

As academic institutions recognize the value of games as text and collections grow, many practices for preservation come from the user community. Users have been finding ways to back up video games for the majority of their commercial history. Devices used to create preservation copies go back as far as the 1980s, with hobbyists continuing to derive new ways of backing up save files and bit for bit copies of games. At the same time, the games industry has been an active participant in lobbying for restrictive copyright legislation and pursuing litigation that hampers the preservation of games. The application of technical protection measures and end user license agreements as a means of evading fair dealing has impacted end users and libraries alike, regardless of medium.
How can impediments to game preservation impact the preservation of other types of materials? How can libraries use available exceptions to support end users in accessing TPM-protected materials long-term? What needs to change in Canadian copyright law in order to allow institutions to do preservation work? And how has interference from the games industry provided roadblocks that impact users of all kinds? We want to hear from a room full of copyright experts!