AI and Copyright – Hugh Stephens Blog

No Surprise: Ontario Court Asserts Jurisdiction in Canadian Media Lawsuit Against OpenAI

A judge sitting at a bench in a courtroom, wearing a black robe with a red collar, Canadian flags in the background.

Image: Shutterstock

The Ontario Superior Court has ruled it has jurisdiction to hear the case against ChatGPT owner OpenAI brought by a consortium of Canadian media companies led by the Toronto Star. The media enterprises, who include the Globe and Mail, PostMedia, CBC/Radio Canada, Canadian Press and Metroland Media Group, are suing the US company for copyright infringement, circumvention of technological protection measures (TPMs), breach of contract, and unjust enrichment as a result of OpenAI’s scraping of their websites to obtain content to train its AI algorithm. The allegations also cover OpenAI’s use of Retrieval Augmented Generation (RAG) to produce contemporary search results from paywall-protected content that augment ChatGPT’s AI-generated responses. When the suit was brought in November 2024, OpenAI had challenged the Ontario court’s jurisdiction on the basis, among others, that it had no physical presence in Canada. As pointed out by this legal blog, a court may presumptively assume jurisdiction over a dispute where one of five factors is present:

The defendant is domiciled or resident in the province.
The defendant carries on business in the province.
The tort was committed in the province.
A contract connected with the dispute was made in the province.
Property related to the asserted claims is located in the province.

The court found that OpenAI carries on business in Ontario notwithstanding its lack of a physical presence and was a party to contracts in Ontario as a result of tacitly accepting the terms of service regarding access to the media companies websites when it scraped them.

OpenAI wanted the venue of the litigation changed to the United States to take advantage of developments in US law regarding unauthorized reproduction of copyright protected content for use as AI training inputs. To date, while many cases are still ongoing, US courts have tended to support a fair use argument by AI developers allowing them to access copyrighted content without permission on the basis that the end use is “transformational”, resulting in a new product that does not compete with the original work. In Canada, the fair use doctrine does not apply and exceptions to copyright protection are either explicitly laid out in the law (e.g. for law enforcement or archival preservation purposes) or are governed by the fair dealing provisions of the Copyright Act. These require that an unauthorized use fall into one of eight categories (research, private study, education, parody, satire, criticism, review and news reporting) that is in turn subject to various court-interpreted criteria such as amount of the work copied, the purpose of the copying, market impact etc. AI developers have been lobbying for the introduction of a text and data mining (TDM) exception into Canadian copyright law, but so far this has been successfully resisted by Canada’s creative community. All this to say that it is more difficult for AI companies to avoid liability for unauthorized use of copyright protected material in Canada than in the US, thus the importance of whether the Ontario court has jurisdiction.

Back in September, on the basis of previous Canadian court rulings where courts ranging from provincial courts to the Supreme Court of Canada asserted jurisdiction over large digital US companies operating virtually in Canada, such as Google (who challenged Canadian legal authority over them on the basis of lack of a physical presence), I predicted (guessed would be a more accurate term) that the Ontario court would be loath to surrender jurisdiction simply because the company was headquartered in the US. The earlier cases were for defamation rather than copyright infringement, and my “prediction” was based more on a hunch than legal analysis, but I am satisfied that I called it right. OpenAI has no compunction about selling services and collecting revenues in Canada and presumably (I hope) pays taxes here, although it is not subject to the Digital Services Tax (DST) that the Carney government threw overboard in a vain attempt to placate Donald Trump. Recall that Trump had threatened to terminate trade talks if Canada proceeded to implement the long-planned DST, so Canada blinked. Trade talks resumed until Trump found another excuse to end the talks, in this case the anti-tariff ads on US television placed and paid for by the Ontario government to which he took offence. But there is no doubt that OpenAI does business here; it just doesn’t want to be subject to Canadian law and Canadian courts. It can’t have it both ways.

While this is a victory for Canadian sovereignty, just because the Ontario Superior Court has confirmed its jurisdiction, this doesn’t mean that once the substantive proceedings begin copyright infringement will be found. Lawyer Barry Sookman, in an analytical blog post on this topic, has noted that in determining whether the alleged copyright infringements occurred in Canada, “the court relied heavily on the Supreme Court decision in SOCAN for the proposition that the territorial jurisdiction of the CCA (Canadian Copyright Act) extended to where Canada is the country of transmission or reception.” However, “SOCAN applied the real and substantial connection test to the communication to the public right” whereas the alleged copying involved the right of reproduction.

Sookman continues;

“…that test does not apply to the reproduction right. (The Federal Court has) held that the only relevant factor is the location in which copies of a work are fixed into some material form. The locations where source copies reside or acts of copying onto servers located outside of Canada, are not infringements” (according to the cases cited).

Inside baseball information but important when it comes to determining copyright infringement. On the other hand, it seems to me that the infringement involved not just, potentially, the reproduction right (the copying) but also the communication right, because OpenAI, through Microsoft, provided RAG content to users in Canada and elsewhere purloined from behind the paywalls of the media companies. So, we will have to see. Lots of fodder for IP lawyers.

In the meantime, deep-pocketed OpenAI will appeal the jurisdictional ruling—and will likely lose again. The appeal will buy time for it to negotiate licensing deals with the complainants. This is increasingly the model in the US as AI developers, including OpenAI, are reaching licensing agreements with content owners, particularly media organizations. To date, OpenAI has signed licensing deals with the Associated Press, the Atlantic, Financial Times, News Corp, Vox Media, Business Insider, People, and Better Homes & Gardens, among others, while being sued (in addition to Toronto Star et al), by the New York Times and a collection of daily newspapers consisting of the New York Daily News, the Chicago Tribune, the Orlando Sentinel, the Sun Sentinel of Florida, San Jose Mercury News, The Denver Post, the Orange County Register and the St. Paul Pioneer Press. Even META, that arch-opponent of paying for media content–which it claims adds no value to its users– has struck a media deal with news publishers, including USA Today, People, CNN, Fox News, The Daily Caller, Washington Examiner and Le Monde. (One wonders if this will cause it to rethink its position of thumbing its nose at Canada’s Online News Act, where it “complied” with the legislation by blocking all Canadian news links).

In another content area, OpenAI and Disney have just agreed on a three-year output deal, allowing it to use Disney characters (subject to certain limitations) in its AI creations. (Meanwhile Disney is suing Google for using its characters in Google’s AI offering). Open AI is currently facing 20 lawsuits, including the Toronto Star case, and needs to resolve these legal challenges before its expected public offering next year or 2027. The spectre of impending lawsuits will inevitably lower the IPO price.

Most if not all of these lawsuits are going to end in settlements via voluntary licensing agreements, but that will only happen if OpenAI thinks the alternative (losing a major lawsuit) is a worse outcome. If it can wriggle out from the Toronto Star case by invoking some specious argument related to jurisdiction, it will. If it can’t it, will eventually open its chequebook and provide the Canadian media outlets some compensation for the valuable curated content it has hijacked. Canadian courts need to stay the course to help ensure that this happens.

AI Training and Nurturing Cultural Industries in Asia: Finding the Right Balance

Text and Data Mining (TDM) Exceptions and Compulsory Licensing Solutions Carry Heavy Risks

A scale balancing two labeled blocks, one marked 'TDM' and the other marked '©', representing the debate between Text and Data Mining and copyright.

Text and data mining (TDM) is a hot topic in many countries. In jurisdictions where exceptions to copyright protection are embedded in legislation rather than determined by the courts on a case-by-case basis (as in the US), TDM has become a favoured vehicle of AI developers, although compulsory licensing has also been floated by some as a potential solution. AI developers see TDM as a loophole allowing access to copyright protected works for algorithm training without payment or permission. Compulsory licencing would establish a statutory regime requiring rights-holders to provide access to their content upon payment by users. While seemingly offering a middle ground, it is fraught with problems. Meanwhile, content industry stakeholders have been vocal on the need to protect their intellectual property, while in some cases resorting to legal action.

TDM has been on the front burner in the UK, Australia and Canada, and Asia is facing many of the same issues. From India to Malaysia to Japan, and from Korea to Hong Kong to Singapore, access to copyrighted content for AI training is front and centre although being played out in different ways. Some countries already have instituted limited TDM exceptions while others are reviewing options. In India, which has long used compulsory licences in the patent field, and which has provision for compulsory licences under certain narrowly specified circumstances in its Copyright Act, both TDM and wider compulsory licensing are being pushed by the AI industry. A common thread in all countries is the concern by rightsholders that their valuable proprietorial content is being or may be taken and reproduced to provide training inputs to a commercial process without authorization or compensation. These concerns are not misplaced.

Compulsory licensing is a “solution” (actually opposed by many in the AI industry who believe that all content should be “free”) that strips away the rights of content owners to determine how their valuable intellectual property will be used. In effect, it is a form of expropriation. While compulsory licences may set a price for use (which may or may not be seen as fair), they don’t address other issues that are normally included in licensing deals such as how the work is to be used, or any specific limitations related to the content. There is also the difficult issue of equitably distributing collected funds.

Voluntary licensing where rights-holders can opt-in is a fairer and more feasible solution, offering mutual benefit to both the content and AI industries. A growing voluntary licensing market exists for print, AV and music content—but AI developers have been slow to respond, a key reason being the mixed signals they are receiving from various governments. Rather than negotiate, the AI industry would rather push for a broad exemption legalizing the practice of helping themselves to protected content owned by others. The pretexts advanced are either a) they are not really copying (just turning content into data tokens is the argument) or, b) if they are, they should be allowed to continue doing so in the name of “innovation”. There is also the implicit threat that if laws and regulations are too protective of the creative sector, AI development funds will go elsewhere, to more compliant jurisdictions.

This argument does not hold water as many factors go into making investment decisions regarding facilities such as data centres, notably the availability and cost of talent, land, power, etc. It is worth noting that while Malaysia does not have a TDM exception in its copyright law (whereas Singapore does), investment is pouring into Johore Bahru–just across the causeway from Singapore–because of Malaysia’s relative competitive advantage in input costs. The AI industry’s “fear factor” threatens to start a race to the bottom as governments around the world don’t want to be left behind as the AI race heats up. While it is clear that AI will transform some industries and has the potential to increase productivity in many areas, it may lead to more job losses than gains whereas the cultural sector is both a key economic driver in all the Asian economies in question and an important pillar of national identity.

India

India is a good case in point. It is a well known cultural and technological powerhouse with a creative economy that was estimated by WIPO to be valued at over $30 billion (USD) in 2023, with 20% growth in creative exports generating over $11 billion. Prime Minister Modi has called on the creative sector to further increase its share of GDP. Yet the TDM issue has raised its head in India, especially after OpenAI was sued by several Indian media entities for copyright infringement. In May Reuters reported that the Ministry of Commerce had set up an expert panel to examine the AI training issue. Both domestic and international content industries in India are concerned that creation of a TDM copyright exception or widening of compulsory licensing in India’s copyright law will undermine the incentive to create new content, and stall the development of a voluntary licensing market for AI training. Careless implementation of TDM or bringing in a misplaced compulsory licensing regime risks throwing out the baby with the bathwater.

Malaysia

As in India, AI industry lobbyists in Malaysia have called for implementation of a TDM exception. The case of neighbouring Singapore is often cited, but Singapore is a particularly poor example to follow. Singapore’s overly-broad TDM exceptions, referred to locally as exceptions to facilitate “computational data analysis”, combined with severe limitations on use of contract law to control access to copyright protected works, have weakened Singapore’s creative sector and held back the development of licensing options. There is no need for introduction of a TDM exception in Malaysia. Kuala Lumpur can distinguish itself by offering an appropriate balance between AI development and fostering important cultural industries, encouraging the development of a mutually beneficial licensing market. Its other attributes have helped it to successfully attract significant high-tech investment without undermining its investment in content creation.

Japan

Japan, which has a TDM exception in its copyright law, is often held out by AI developers as a model for the kind of copyright law they would like to see replicated elsewhere, but the impression that anything goes in Japan with respect to use of copyrighted content is mistaken and based on misunderstandings. As I outlined in a blog post last year (Japan’s Text and Data Mining (TDM) Copyright Exception for AI Training: A Needed and Welcome Clarification from the Responsible Agency), Japan’s TDM exception does not apply if the user of the copyrighted data “enjoys” the content. As an example, this means that if a user derives benefit through using the copied material to create outputs based on the reproduced content, the TDM exception does not apply. As this website succinctly puts it, “Expressive intent invalidates the safe harbour.” As is the case elsewhere, the limits of the law are being tested in court. Yomiuri Shinbun, Japan’s largest paper, as well as Nikkei and Asahi Shinbun, are suing Perplexity AI for copyright infringement in Tokyo District Court. Meanwhile a market for licensing content is beginning to develop.

Korea

Korean content companies are also turning to the courts for redress against unrestricted copying by digital platforms. Korea’s three terrestrial broadcasters, KBS, MBC, and SBS filed suit in January against Korean tech giant Naver claiming the platform used their news content to train its AI application. The broadcasters had earlier put Naver on notice not to use their content without permission. Naver is, broadly speaking, the Korean version of Google. It has recently been reported that more lawsuits are pending against Naver, this time from the Korean Newspaper Association.

Korea does not have a TDM exception in its copyright law, but it has (at least in theory), adopted the US fair use doctrine as a result of the US-Korea Free Trade Agreement. However, although fair use was incorporated into Korean law in 2011, its has seldom been used and the Korean courts have been very reluctant to apply it, and where they have, the application has been very narrow, essentially limited to non-commercial use. To date there have been no fair use cases brought to the Supreme Court, and lower courts tend to rely on the specified exceptions that apply in Korean law. Because of this there have been attempts to introduce a TDM exception, and more are expected in the current National Assembly. Various versions have been proposed that are of concern to rightsholders, including broad interpretations that would not distinguish between commercial and non-commercial use. Korea, one of the cultural giants in Asia, needs to tread carefully if it wants to maintain this leading cultural export, while encouraging development of content licensing.

Hong Kong

Hong Kong does not have a TDM exception in its current copyright law but under pressure from the AI sector is considering the idea. The Intellectual Property Department launched a public consultation late last year, receiving input from stakeholders representing both sides of the argument and has come forth with recommendations to the legislature (Legco). It has proposed a TDM exception for both commercial and non-commercial use but with a number of limitations; 1) access to content must be lawful (i.e. no use of pirated content); 2) a public record must be kept of copyrighted works used in AI training (transparency requirement); 3) the TDM exception will not apply where licensing schemes (i.e. licences that have been issued by the Copyright Tribunal) exist; and 4) rightsholders can reserve their rights by opting out.

There are problems with this proposal, despite the limitations. Requiring rightsholders to opt-out stands the existing basis of copyright on its head, as it has in the EU (i.e. users normally need to obtain permission from rightsholders in advance) while the licensing provision provides limited relief. While not as potentially destructive as some proposed TDM exceptions elsewhere, it is questionable if Hong Kong needs a TDM exception given that voluntary licensing alternatives are increasingly available. At present, the recommendations are with the Legco; given public skepticism about the proposal, legislation is not expected until 2026 at the earliest.

Conclusion

Lawmakers and regulators in Asia are grappling with a common problem; how to incentivize the development of responsible AI while continuing to encourage and promote all-important content industries. Cultural expression is particularly important in Asia as an expression of values, and throwing the cultural sector under the bus in the hopes of attracting some ephemeral hi-tech AI jobs is a false bargain. It’s like eating the seed grain from which the bounty of cultural creativity springs. Undermining the nurturing environment provided by sound copyright protection, whether through compulsory licensing or creation of TDM exceptions, is bad public policy.

Strong cultural industries enable the development of strong content licensing markets for AI development, enabling a virtuous circle of further creativity. A strong cultural sector and strong, sustainable digital industries, especially those powered by AI, go hand-in-hand. Asian regulators need to exercise prudence and weigh the consequences of rash action. The winners will be those that find the right balance between encouraging innovation and fostering creativity.

Australia Stands Up for its Creative Sector: A Useful Lesson for Canada and Others

Two coffee mugs side by side, one featuring the Australian flag and the other featuring the Canadian flag.

Image: Shutterstock

Australia just took an important stand in the tug-of-war being waged in many countries over whether, how and to what extent tech companies can use copyrighted content (text, music, images and so on) to train AI platforms by reproducing the content and extracting its essence without permission or compensation to rightsholders. Attorney-General Michelle Rowland has announced that while Australia will be undertaking consultations on revisions to its copyright laws to help address the needs of the AI industry, a Text and Data Mining (TDM) exception has been ruled out. Some countries, like the UK, have TDM exceptions for limited purposes (such as research and non-commercial use) in their laws while several other countries have TDM under review. Existing TDM exceptions allow reproduction of copyrighted content without the authorization of the rightsholder for research, data analysis, and in some cases for AI training purposes.

There is currently no TDM exception in Canadian law but as I noted in a recent blog post (“Canada’s Creative Sector Uneasily Awaits the Carney Government’s Next Steps on AI Training”), pressure is building from the AI sector to incorporate TDM into Canada’s Copyright Act. The government currently has yet another consultation paper on AI out for public comment and the Canadian cultural sector is organizing to protect creator’s rights, specifically calling on the Canadian government to “ensure that the Copyright Act is not modified through an exception permitting Text and Data Mining (TDM) or any other exception allowing technology developers or users to use protected works…to train generative AI systems without authorization or compensation…”. In doing so, it is taking a leaf from the book of Australian creators who mounted strong opposition to a proposal from the Productivity Commission, (PC) an independent research and advisory body created by an Act of Parliament some 25 years ago, that proposed in a report in August that Australia adopt a TDM exception. To say that this proposal put the cat amongst the pigeons would be an understatement.

The Commission has a reputation for denigrating the value of intellectual property and seeing it as an obstacle to industrial development rather than as an essential partner. In 2015 it proposed shortening the term of copyright protection from the current life of the author plus seventy years (“life plus 70”), a generally accepted international standard, to just “life plus 15”, (far lower than the Berne Convention minimum and a standard not adopted anywhere) while introducing a US-style fair use regime into Australia. There was strong pushback then, (it didn’t happen) and there was strong pushback this year (see here and here, for example) when the PC proposed introducing a TDM exception. It was particularly criticized for its lack of consultation with the creative industries in developing this proposal.

Now the Australian government has put its foot down, ruling out TDM but indicating that it will look at alternative solutions. These include examining whether to establish a new “paid collective licensing framework” under the Copyright Act for AI, or whether to maintain the status quo through voluntary licensing, clarifying how copyright law applies to material generated through the use of AI (i.e. whether there should be copyright protection for outputs produced by or with AI) and looking at the establishment of a new small claims forum to address lower-value copyright infringement matters.

It is generally accepted that AI is here to stay and will continue to need vast amounts of content for training. In most cases, copyrighted content is the kind of curated, high value work that AI developers need but until now, have preferred to appropriate without permission rather than pay for through licensing. In effect they have decided to ask for forgiveness after rather than permission beforehand. This has led to a plethora of lawsuits globally, including the recent $1.5 billion settlement that Anthropic has agreed to pay out to settle a class action suit brought by authors in the US. “Forgiveness” can be expensive. Inside the US, AI developers are arguing their copying is fair use, although at the same time they are beginning to hedge their bets by licensing content from a number of sources, ranging from media to music to image companies. Outside the US, AI companies have been beating the TDM drum, hoping that creation of wide TDM exceptions will obviate the need to negotiate with content owners. Nonetheless, voluntary licensing is growing globally. However, the surest way to kill a nascent licensing market is to give the tech industry a “get out of jail free” card by introducing a broad TDM exception. Australia has just rejected that option. Canada and others considering introducing new, or broadening existing, TDM loopholes should do the same.

It is not clear where Australia’s AI and Copyright review will end up, other than to note that it will not include TDM. As I have noted above, among other things it will be considering “collective licensing”. Collective licensing could help address the problem of remunerating individual rightsholders, in contrast to licence agreements signed between AI developers and corporate entities like media companies. However, Australia needs to steer clear of compulsory licensing which strips away the rights of copyright owners. Compulsory licences authorize use upon payment of a statutory or negotiated fee but remove the right of a copyright holder to withhold consent for use, or to impose specific limitations. A voluntary licence framework is fair to everyone. Compulsory licensing is not.

Canada and Australia have many things in common, (as well as a number of differences of course, beyond poutine vs vegemite). Among their commonalities is the desire to protect and foster a unique cultural identity in the face of global cultural homogenization. This is even more important in Canada given the realities of the struggle faced by 6 or 7 million Francophones to preserve their culture in a sea of 375 million Anglophones. Canada followed Australia’s lead (although less successfully) in requiring major online platforms to contribute financially to (i.e. pay for the use of) news media content. It should do the same by putting the idea of a TDM exception firmly to one side and instead focus on encouraging the development of voluntary licensing market for copyrighted content when used in AI training.

Canada’s Creative Sector Uneasily Awaits the Carney Government’s Next Steps on AI Training

Blasting a Wide TDM Hole in the Structure of Copyright is Not the Answer

A cartoon-style illustration showing a fist breaking through a brick wall labeled 'COPYRIGHT', with the fist wearing a band labeled 'TDM', surrounded by explosive graphical effects. — Image: Author (via DALLE-E)

The ongoing wrestling match-cum-dance between the creative sector and AI developers over the uncompensated and unauthorized use of copyrighted content for AI training is being played out in different ways in different countries. In the US it is largely a legal play in the courts at the moment, with mixed results for both sides. However, President Trump has made concerning public comments siding with the AI industry, saying it is impractical for AI developers to pay copyright holders for AI training (and besides, China doesn’t do it). Congress is still considering its options. In Australia, the Productivity Commission, never a friend of intellectual property, has just issued an interim report recommending the adoption of a Text and Data Mining (TDM) exception in Australia to boost development of the AI industry locally. The Australian creative sector mobilized quickly and has pushed back hard against this proposal, with the government now saying that it has no plans to amend the Copyright Act. In the UK, where there is a TDM exception but only for non-commercial purposes, the Starmer government quickly adopted a pro-AI strategy, part of which was to propose an expansion of TDM to include commercial purposes, although subject to an opt-out for rights-holders. That ignited a major storm among leading British creatives from Paul McCartney and Elton John on down. Through a unified campaign, British creators were able to gain support in the Upper Chamber (House of Lords) to slow down the legislation. As a result, the TDM issue has now been earmarked for further consultation and study. One thing is certain, the creation of a wide TDM exception is a sure way to stifle a nascent but rapidly developing licensing market for copyrighted content used for AI training.

It seems as if TDM, or more permissive TDM, is testing the boundaries of copyright just about everywhere. So, what about Canada? Canada has no TDM exception in its copyright law and, unlike the US, has clearly defined fair dealing exceptions that do not lend themselves to expansive court interpretation. Like other countries, it is trying to figure out how to not get left behind as the AI race accelerates. Canada initially had a first mover advantage in terms of AI research, given the work of Geoffrey Hinton, Yoshua Bengio and others, but recently it has been falling behind, notably lacking native startups. The cluster effect is not happening, with Canadian innovation going elsewhere for commercialization. To address these challenges, the new Carney government has appointed a dedicated Minister of Artificial Intelligence and Digital Innovation, former journalist Evan Solomon. This is the first time such a position has existed. One of Solomon’s first acts was to accelerate launch of an AI strategy beginning with a new consultation released on October 1 (closing at the end of this month), in the form of a survey to “help define the next chapter of Canada’s AI leadership”. This survey asks many relevant questions regarding AI and how it could be best developed in Canada but manages to mostly steer clear of the thorny question of AI training and copyright. The only question tangentially related to this issue is the following;

“Which infrastructure gaps (compute, data, connectivity) are holding back AI innovation in Canada, and what is stopping Canadian firms from building sovereign infrastructure to address them?”

Clearly this consultation is not going to turn over the TDM rock, at least not directly.

In the past couple of years, the government has issued two consultation papers on AI, one in 2021 and another last year as well as a “What We Heard” report. This report, issued earlier this year, summarizes the “great divide” between AI developers and the content industry. It’s first observation was that “Creators oppose the use of their content in AI without consent and compensation” but then goes on to say that “User groups support clarifications that TDM does not infringe copyright”.

After a couple of other observations about the centrality of human authorship and the need for transparency surrounding the use of copyright-protected works in the training of AI, the paper observed that there is “no consensus about whether existing legal tests and remedies are adequate”. That is the nub of the issue. There is no consensus, and while the courts are struggling with this issue (including in Canada, as I wrote about here and here), what Canadian creators fear is the introduction of a wide TDM exception in the name of maintaining “Canadian competitiveness”.

The launch of the new AI strategy and the evolution of the way in which copyrighted content is described in government consultation documents is indicative of the pressures on the government to shore up Canada’s AI strategy. It is interesting to note the shift in the definition of TDM from 2021 to today.

The definition provided in the 2021 consultation document described TDM as follows;

“The process of conducting TDM may require the making of reproductions of large quantities of works or other copyright subject matter to extract particular data and information from them. This process may be carried out using scientific or text-based data, as well as images, sounds, or other creative works.”

In the most recent consultative document, that definition has evolved;

“Text and data mining (TDM) consists of the reproduction and analysis of large quantities of data and information, including those extracted from copyright-protected content, to identify patterns and make predictions.”

Note the shift from “works” to “data”.[i] It’s a subtle difference but is hugely significant because data and facts are not protectable under copyright whereas the creative elements of original works are. The cultural sector is rightly concerned.

The Coalition for the Diversity of Cultural Expressions (CDCE), a major arts and creatives lobby group, is currently pressing Ottawa on a number of cultural issues, including AI. Among its AI asks are to;

Ensure that the Copyright Act is not modified through an exception permitting Text and Data Mining (TDM) or any other exception allowing technology developers or users to use protected works…to train generative AI systems without authorization or compensation;
Adopt national legislation on generative AI that requires developers of generative AI systems to disclose the training data they use; and
Adopt legislative provisions requiring public identification of content that is purely AI-generated.

Against these demands is the pressure coming from AI advocates who will argue that if the US loosens restrictions on use of copyrighted content for AI training, Canada will have no recourse but to follow. In other words, as goes the US, so goes Canada (or for that matter, the UK, Australia and others). Thus, what is happening in the US courts, and perhaps in Congress, is of critical importance for the creative sector everywhere including, in particular, Canada.

The issue of AI training on copyrighted content will need to be resolved sooner or later. Licensing solutions are developing quickly and if Canada can wait a bit longer it may be able to adopt licensing as the preferred solution (although the “What We Heard” report noted that “Some (intervenors) argued that licensing is an unnecessary burden because it may not be clear that copyright is engaged or that works used in TDM are being reproduced in the first place.”). There is pressure on the Carney government to take early action since AI industry developments are moving at lightning speed. With the TDM train gaining momentum in Canada and elsewhere, Canadian creators are understandably uneasy about what is likely to happen next.

As the CDCE notes, culture is a major economic and social pillar in Canada. In 2023, it generated $63.2 billion in value added and employed 669,600 people. Throwing all that under the bus in the name of remaining competitive on AI is a flawed choice, a point also made by the creative sectors in the UK, Australia and elsewhere. However, with the AI horse well out of the barn, copyright cannot be seen as an obstacle to innovation, an accusation freely levelled at it by some in the AI industry. Rather, it must be seen as a partner in innovation, which is where licensing comes in.

Blasting a wide TDM hole in the protection and incentive structure that copyright provides the creative sector is not the answer. The creative sector is watching and waiting anxiously.

[i] I am indebted to Erin Finlay, partner at Stohn Hay Cafazzo Heim Finlay LLP for drawing these changing definitions to my attention

When Will AI Developers Take Responsibility for the Products They Provide Their Subscribers?

What They are Doing Really Bugs Me

Illustration comparing a Midjourney-generated image of Bugs Bunny on the left with Warner Bros. copyrighted images of Bugs Bunny on the right, featuring different styles and settings.

Image: US District Court Filing

I confess to having been a lifetime fan of Bugs Bunny, that “Wascally Wabbit”, and not just because I worked for Time Warner at one point in my career. His insouciance, his ingenuity and his cultural achievements (have you seen Bugs perform opera or conduct a symphony orchestra?) are legend. Thus it was with some interest that I read the headline in my morning newspaper “Warner Bros. sues AI Company over Images of Bugs Bunny and other characters”. It was based on a generic AP report that appeared in many journals across North America. The AI company in question is Midjourney. Hollywood Reporter has done a deeper dive comparing images produced with Midjourney’s AI program to copyrighted Warner Bros. (WB) images, drawn from the lawsuit submission. This is not the first confrontation between Hollywood and Midjourney. In June Disney and Universal brought a similar suit alleging that the AI company’s image generator produces near replicas of its copyrighted characters.

Just in case you forget what Bugs looks like, Warner Bros. (technically now known as Warner Bros. Discover) has a complete description in its lawsuit;

Many of the Looney Tunes characters are ubiquitous household names, and these characters have expressive conceptual and physical qualities that make them distinctive and immediately recognizable. Bugs Bunny, for example, is a playfully irreverent anthropomorphic gray and white rabbit, who has a star on the Hollywood Walk of Fame. Bugs Bunny has an overbite that showcases his two long front teeth, oversized feet with white fur, and is often depicted eating a carrot.

Does this description look anything like the image produced by Midjourney, as reproduced in the filing (see paragraphs 85 and 86), which I have pinched as the image for this blogpost. Scroll up or down to see the full range of characters at issue, ranging from Tweetie to Batman.

Midjourney’s response to the earlier lawsuit, and now to Warner Bros. is that they are not responsible for any copyright infringement that may occur. You see, it is the users of their service who are to blame. Not them. According to their court filing:

“The Midjourney platform is an instrument for user expression. It assists with the creation of images only at the direction of its users, guided by their instructions, in what is often an elaborate and time-consuming process of experimentation, iteration, and discovery.

Midjourney users are required by Midjourney’s Terms of Service to refrain from infringing the intellectual property rights of others, including Plaintiffs’ rights, Midjourney does not presuppose and cannot know whether any particular image is infringing absent notice from a copyright owner and information regarding how the image is used.”

Warner Bros. points out that Midjourney could easily control infringing outputs by (1) excluding WB content from training its AI system (2) rejecting prompts from users requesting WB characters and (3) using technical means to screen images. But instead, Midjourney has become a vending machine for WB content, selling a commercial service powered by AI that was developed using infringing copies of WB works and then allows users to reproduce or download infringing images or videos. These outputs directly compete with WB copyrighted content.

Midjourney’s defence strikes me as similar to arguments used by the manufacturers of guns. “Guns don’t kill people. People kill people.” Except that there are a number of limitations on the kind of gun you can sell, and its capabilities. While the law varies from jurisdiction to jurisdiction, what is common are restrictions on selling automatic and semi-automatic weapons. The reasons are obvious. While there is a use for some kinds of guns (gun clubs, hunting etc.) there is no legitimate need for unlimited lethality. Not all gun purchasers (like AI software users) can be trusted so limitations are placed on what gun manufacturers are allowed to make available to the public. Similarly, while there are many uses for image-generating AI platforms, there are also legal limits to what is acceptable, such as when AI is used to create child porn. AI companies have agreed to set and enforce guardrails against this, and are clearly capable of doing so. Since, regrettably, not all users can be trusted, to simply to ask them to acknowledge and abide by Terms of Service is inadequate. So, if AI companies can stop some categories of use, they are equally capable of marketing a service that avoids copyright infringement. Enough of the “blame the user” nonsense. Design and market a service that conforms to the law.

Another good example of the “blame the user” excuse is META’s creation of “flirty chatbots” using virtual images of celebrities such as Taylor Swift, Scarlett Johanson, etc. According to Variety, quoting a report from Reuters who researched the issue, the celebrity AI chatbots “routinely made sexual advances, often inviting a test user for meet-ups.” In some cases, when they were asked for “intimate pictures,” the chatbots “produced photorealstic images of their namesakes posing in bathtubs or dressed in lingerie with their legs spread.” Many of these chatbots, which clearly violate the right of publicity of the subjects, were user produced. But users could not produce these images, and cross the line into illegality, unless they were enabled to do so by the program produced by META. META claims that the production of such images violates its rules, which prohibit the direct impersonation of public figures. But of what use is a rule if it is not enforced?

If AI developers design products that are easily misused and then enable (even encourage) their users to do so, it is high time for them to accept responsibility. They are able to establish guardrails; they just don’t want to as it is easier to free ride, while attracting as many users as possible. Midjourney is a good case in point, but Warner Bros has just fired a shot across their bow. Just as Bugs did in Captain Hareblower.

Does OpenAI (ChatGPT) Have a Presence in Canada? Should it be Subject to Canadian Law?

Based on Common Sense, the Answer Should be “Yes”

Image: Shutterstock

Late last year a consortium of major Canadian media companies (including the Toronto Star, Globe and Mail, CBC-Radio Canada, Canadian Press, Metroland and PostMedia) sued OpenAI, founders and operators of ChatGPT (and Dalle E), for copyright infringement, seeking injunctive relief and damages. OpenAI moved to dismiss the case on jurisdictional grounds. The Ontario Superior Court is now reviewing that question. As the Globe and Mail reports, OpenAI is trying to argue that the Ontario court has no jurisdiction because the company has no physical presence in Canada. It is headquartered in San Francisco and registered in Delaware.

As I commented in an earlier blog posting on this issue, the fact that the US fair use doctrine does not apply in Canada, combined with the closed nature of fair dealing exceptions and the lack of a Text and Data Mining exception in Canadian law, could prove troublesome for OpenAI. However, OpenAI would rather defend its case in California where it can resort to US “fair use” arguments, as it is doing in its defence against the copyright infringement and trademark dilution lawsuit brought against it by the New York Times. (The NYT case is being heard in the Southern District of New York). While the interpretation of whether fair use applies to unauthorized use of copyrighted materials for AI training is evolving in the US, and the outcome is far from certain, fair use and so-called “transformative use” have no applicability in Canada.

OpenAI claims that none of its corporate entities named in the suit conducts business in Ontario nor has a physical presence there. It also claims that the alleged conduct (web-crawling and copying) overwhelmingly takes place outside Canada. The lawyers for the plaintiffs concede that OpenAI’s servers are outside Canada but instead focus on other aspects of OpenAI’s conduct and presence. They note the websites of the media companies that were (and are) being crawled by OpenAI are hosted in Canada (which is one reason why the NYT suit is being heard in New York, because the content that OpenAI copied is located in New York City). Microsoft, which is a 49% owner of OpenAI, sells OpenAI’s products and services in Canada and its models are “reproduced and hosted” in a Microsoft data centre in Toronto. The suit alleges that the copyrighted content was copied not just once for AI training but is continuously accessed and reproduced through what is known as “Retrieval Augmented Generation” (RAG) whereby (according to the complaint) OpenAI’s models are “provided continuous access to an additional data set (the “RAG Data”), which is continually updated in response to user prompts.”

There is no doubt that OpenAI operates in Canada, offering products to Canadian residents such as ChatGPT subscriptions and accepting payment in Canadian dollars, although it may not be incorporated or have a bricks-and-mortar office. In fact, its student discount offers are pitched specifically as being only for students in the US and Canada. If physical presence in a country is a requirement for the exercise of judicial jurisdiction, it makes me wonder how Elsevier and the American Chemical Society were able to sue Sci-Hub in the US and win substantial damages (which were never paid) given that Sci-Hub had and has no presence in the US. Would Russia or Kazakhstan, which is where its servers are believed to be located, have been the appropriate jurisdictions?

This is no doubt a complex legal question, and we will have to wait to see how the Court rules. In addition to noting the various forms in which OpenAI operates in Canada, the plaintiffs have pointed out that were the Court to surrender jurisdiction, this would amount to giving up the ability to regulate a large part of the digital economy and constitute an affront to Canadian sovereignty, an argument dismissed by OpenAI’s legal team as hyperbolic and sentimental. However—and although this is not based on any legal analysis, which I am not capable of providing– I have a hunch that the sovereignty argument will carry some weight.

In the past, Canadian courts have not shied away from asserting jurisdiction over cases involving Silicon Valley giants, which have been quick to seek transfer of court proceedings to California. I can think of several cases that fit into this category, notably the Equustek case in which the Supreme Court of British Columbia’s decision requiring Google to de-index certain information from its global search results was upheld by the Supreme Court of Canada after Google had appealed the BC court’s ruling claiming Canada was applying its law extraterritorially. Another was a defamation case in BC where the plaintiff, a resident of both California and British Columbia, sued Twitter in BC for defamation for repeatedly allowing defamatory tweets despite being requested to remove them. Twitter wanted the case moved to California where it could hide behind the notorious Section 230 of the 1996 Communications Decency Act. This legislation has been interpreted by US courts to absolve digital platforms of responsibility for user content they host and disseminate. The BC court refused precisely because under US law the plaintiff would have had no cause of action because of the existence of Section 230. In another case Google tried to invoke the jurisdictional argument, as well as Section 230, in a Quebec defamation case. Google argued the Quebec court had no jurisdiction because its server was located in the US. That argument didn’t fly, nor did Google’s argument that it was protected by Section 230 because of the CUSMA/USMCA trade agreement.

None of these cases is an exact match for the OpenAI case, of course, but I somehow doubt if the Ontario Superior Court is going to let this one go. There have only been a couple of other AI/Copyright cases in Canada along similar lines, CANLII v Caseway AI, where both parties were Canadian entities, and several class action suits brought by authors in British Columbia including a suit against Nvidia by local author J.B. MacKinnon. As far as I am aware, no decision has been reached in any of these suits. New legislation to address unauthorized use of copyrighted content for AI training does not seem to be on the immediate horizon in Parliament so it is left to Canadian courts to establish some guidelines regarding Canadian law in this area. The Toronto Star et al. v OpenAI case would fit this bill perfectly.

Hold the Champagne: The Two AI Training/Copyright Decisions Released in the US Last Week Were a Mixed Bag for AI Developers

Illustration of a champagne bottle being popped, enclosed in a red circle with a slash indicating 'no champagne'.

Image: Shutterstock.com

Last week I wrote about the questionable ethics of META’s use of pirated content to train its AI model, Llama, pointing out the ethical issues involved with META’s admitted use of pirated online libraries, such as LibGen (Library Genesis), to feed content to Llama for training purposes. This is quite apart from whatever legal issues that may arise from the widespread practice of ingesting copyrighted content for AI training by making an unauthorized copy from any source (such as a legitimate library, through purchase of a single copy of a work, or from publicly available internet sources, for example) not to mention the additional element of taking that content from pirate sources. The day after that blog was posted the first of what will be a series of legal decisions in the US regarding cases brought by authors and copyright holders against AI companies was issued, followed by another a day later. Both cases were heard in the Northern District of California, in the same San Franciso court house, but handled by different judges.

I updated last week’s blog to make reference to the Bartz v Anthropic case (hereafter “Anthropic”), but given the importance of that decision, combined with a decision released in another California court room a day later (Kadrey et al v META), these cases merit further exploration–especially since they were widely trumpeted by AI advocates as opening the door to unauthorized use of copyrighted content for AI training on the basis of “fair use”.

Fair use is the complex legal doctrine used in the US to determine exceptions to copyright protection. US readers are well aware of the intricacies and idiosyncrasies of fair use but for those not overly familiar with how it works, here is a short summation I drew from a blog post on fair use vs fair dealing that I wrote a few years ago.

In the US context, fair use is an affirmative defence against copyright infringement and is determined by the courts on a case by case basis, judged against several fairness factors (purpose and character of the use, the nature of the work copied, the amount and substantiality of the amount of the work used, and the effect of the use on the value of the original work)… Fair use is not defined by law. Some examples are given in US law of areas where the use is likely to be fair (criticism, comment, news reporting, teaching, scholarship, research) but these are illustrative and not exhaustive. In short, it is the courts that decide. This in turn can lead to extensive litigation as to what is and is not fair use, and it is worth noting that different judicial circuits in the US have at times come up with conflicting interpretations.

Or, for that matter, two different judges in the same circuit delivering decisions just days apart on similar issues but with some significantly different outcomes, as we saw last week (although in these cases both found fair use by AI developers with regard to the copyrighted works at issue).

On the Anthropic case, US District Judge William Alsup ruled, on summary judgement, that the use of copyrighted works for AI training, even though done without authorization, is highly transformative and does not substitute for the original work (“The technology at issue was among the most transformative many of us will see in our lifetimes”). It thus qualifies, according to Alsup, as fair use because the transformative nature of the use overrides or swallows the three other fair use factors, including the important fourth factor (effect of the use on the value of the work). He notes there was no allegation that the output of Anthropic’s model, known as “Claude”, produced content infringing the works of the plaintiffs. However, Judge Alsup then went on to consider the legality of Anthropic’s actions to download more than 7 million works from pirate libraries (such as Books3, Library Genesis and the Pirate Library Mirror) to constitute its reference library, which it initially planned to use for AI training. He concluded this was a prima facie case of copyright infringement, whether Anthropic intended to use some or all of the pirated works to train Claude or not. (“Anthropic seems to believe that because some of the works it copied were sometimes used in training LLMs (Large Language Models), Anthropic was entitled to take for free all the works in the world and keep them forever with no further accounting “.) Damages, to be decided at trial, could be substantial. Alsop did not, however, rule explicitly on whether or not the use of pirated works for AI training purposes could be a fair use.

Because of the controversial nature of Alsup’s findings on transformation and fair use, there is no question that this case will be appealed. While there have been many criticisms of the fair use elements of Alsup’s ruling, a particularly clear and trenchant analysis was put forth by Kevin Madigan of the Copyright Alliance (Fair Use Decision Fumbles Training Analysis but Sends Clear Piracy Message).

The second case last week to reach the decision stage was Kadrey et al v META. In this case District Judge Vince Chhabria found that META’s use of the works of the plaintiffs, thirteen noted fiction writers, to train its AI model (“Llama”) was also fair use. Chhabria, like Alsup, found that META’s use was transformative on the first fairness factor dealing with the purpose and character of the use (“There is no serious question that Meta’s use of the plaintiffs’ books had a “further purpose” and “different character” than the books—that it was highly transformative.”) but unlike Alsup, Chhabria put much greater emphasis on market harm, (the fourth fairness factor dealing with the effect of use on the value of the work) suggesting that it could be determinative. Unfortunately for the plaintiffs, however, Chhabria considered their arguments with respect to market harm to be unconvincing. There was no evidence that Llama’s output reproduced their works in any substantial way or substituted for the specific works at play nor was there evidence, according to the judge, that the unauthorized copying deprived the authors of licensing opportunities.

Chhabria suggested that a far more cogent argument would have been that use (unauthorized reproduction) of copyrighted books to train a Large Language Model might harm the market for those works by enabling the rapid generation of countless similar works that compete with the originals, even if the works themselves are not infringing. In other words, causing indirect substitution for the works rather than direct substitution. This is the theory of “market dilution”, which was also put forward speculatively by the US Copyright Office in its recent Pre-Publication Report on AI and copyright. Since this wasn’t presented as an argument, Chhabria could not rule on it but in effect he is inviting future litigants to pursue this line of argument, noting that his decision on fair use relates only to the works of the thirteen authors who brought the case.

The clearest way to illustrate his line of reasoning is to quote directly,

“In cases involving uses like Meta’s, it seems like the plaintiffs will often win, at least where those cases have better-developed records on the market effects of the defendant’s use. No matter how transformative LLM training may be, it’s hard to imagine that it can be fair use to use copyrighted books to develop a tool to make billions or trillions of dollars while enabling the creation of a potentially endless stream of competing works that could significantly harm the market for those books”.

This editorializing, known in legal circles as obiter dicta, is not binding nor precedential, yet will undoubtedly have some influence given Chhabria’s stature. It is likely that one of these days Judge Chhabria will have the opportunity to put these theories into practice when ruling on a similar case, but one where the plaintiffs have made a better case for market harm. He has provided them a roadmap.

While these two cases have fired the first shots in what is going to be a lengthy war, they do not seem to be dispositive. There are enough caveats and nuances to be able to conclude that the AI developers are far from being out of the woods. Both “victories” have a sting in their tail, especially Judge Alsup’s finding on piracy. Neither copyright advocates nor AI developers should be breaking out the champagne just yet. But whichever way it turns out, there will be some sure winners; the lawyers for each side.

Copyright Litigation in China: Some Interesting AI-Related Decisions from Chinese Courts

A wooden gavel resting on a circular base in front of a red backdrop featuring the flag of China.

Image: Shutterstock

These days just about any information in North America related to China, especially regarding intellectual property (IP), is highly negative. The narrative is along the lines of “China is an adversary with deliberately lax IP laws who has stolen and continues to steal our IP, etc.”. This characterization of China is reinforced by our political leaders (When asked during the Leaders’ debate what was the greatest security threat to Canada, Prime Minister Carney replied with one word. “China”). Donald Trump continues to have an obsession with China, the latest manifestation of which is the recent announcement that the US will revoke the visa status of an undetermined number of Chinese students currently studying in the US. (Over a quarter of a million students from China are currently studying at American colleges and universities, many simply seeking an alternative to studying in the hyper-competitive environment at home). The “China as IP thief” narrative is supported by government publications such as the annual Special 301 Report produced by the Office of the US Trade Representative (USTR) which this year had ten full pages on China. One excerpt will suffice to give you the flavour of the report. “In 2024, the pace of reforms in China aimed at addressing intellectual property (IP) protection and enforcement remained slow…Concerns remain about longstanding issues, including technology transfer, trade secrets, counterfeiting, online piracy, copyright law, patent and related policies, bad faith trademarks, and geographical indications.” Well, that covers the waterfront. One wonders how Chinese brands, innovators and creators manage to survive in such an environment.

This is not to dismiss the darker side of China’s long IP history. Have there been cases of industrial espionage involving China? Yes, certainly. There have also reportedly been more than 1200 intellectual property theft lawsuits brought by US companies against Chinese entities in either the US or China over the past 25 years. There is no question that IP protection in China is not all it could and should be, or that some Chinese companies and other entities have been aggressive in seeking to acquire IP by less than transparent means. But that is not the whole story. While the number of IP infringement lawsuits against Chinese entities over the years sounds like a lot, this business website estimates that the number of IP litigation cases globally totals around 12,000 annually. There are several thousand patent litigation cases alone in the US each year. A lot of US companies sue other US companies in the patent, trademark and copyright field. And Chinese companies sue Chinese companies.

In the past, Chinese IP laws had loopholes, were often weakly enforced and were dealt with by courts that had scant knowledge and training in IP matters. That is rapidly changing as China not only climbs the innovation ladder, but has come to dominate it in some areas, such as EV’s and EV batteries, cashless payment systems, renewable energy and others. It is rapidly catching up in generative AI. While this has been happening, Chinese courts have been producing some interesting and increasingly sophisticated decisions when it comes to AI and copyright. China–like other countries–is grappling with several aspects of this issue. There is the question of finding the right balance between protecting creators and innovators while using domestic creative works to spur AI training, development and research. Another element is the extent to which AI assisted or created works qualify for copyright protection. There is currently no Text and Data Mining (TDM) exception in Chinese law to allow AI training on copyrighted content nor is there a definitive interpretation as to whether content produced by AI can be protected by copyright. However, several court decisions, which we examine below, have shed some light on this complex question.

Dreamwriter Case

In one of the earlier cases, which I wrote about back in 2020, (the Dreamwriter case), a Chinese court (in Shenzhen) ruled that an automated article written by an AI program (Dreamwriter), created by Tencent, which had been copied and published without permission by another Chinese company, Yinxun, was nevertheless subject to copyright protection because it met the originality test through the involvement of a creative group of editors. These people had performed a number of functions to direct the program, such as arranging the data input and format, selecting templates for the structure of the article, and training the algorithm model. The article was ruled to be a protectable work, and Yinxun was found to have infringed.

Li v Liu Case

The relatively loose interpretation regarding the degree of human engagement required to protect the output of an AI program in the Dreamwriter case has been supported by other Chinese courts. In the prominent Li v Liu case, the Beijing Internet Court ruled that Mr. Li, who had created the image of a young woman using the AI program Stable Diffusion, had provided “significant intellectual input and personalized expression” in creating the image through a series of prompts. As explained in detail by this article from Technollama, the prompts (along with a number of negative prompts) were sufficient for the court to decide that Li had met the standard of creative expression.

These were Li’s prompts;

“ultra-photorealistic: 1.3), extremely high quality highdetail RAW color photo, in locations, Japan idol, highly detailed symmetrical attractive face, angular symmetrical face, perfect skin, skin pores, dreamy black eyes, reddish-brown plaits hairs, uniform, long legs, thighhighs, soft focus, (film grain, vivid colors, Film emulation, kodak gold portra 100, 35mm, canon50 f1,2), Lens Flare, Golden Hour, HD, Cinematic, Beautiful Dynamic Lighting”

Liu, who had been sued by Li for using the AI generated image without authorization, was found liable for infringement and fined 500 CNY (about USD75).

At that time (late 2023), this decision was considered ground-breaking for image-based works given the position of the US Copyright Office (USCO). USCO had denied copyright registration to several generative-AI created image works owing to insufficient human creativity. (see If AI Tramples Copyright During its Training and Development, Should AI’s Output Benefit from Copyright Protection? Part One: Stephen Thaler and Part Two: Jason Allen). Since then (in January of this year) the USCO has taken a more nuanced position, permitting registration of an AI assisted work (an image called A Single Piece of American Cheese, created by graphic artist Kent Kiersey). Although Kiersey used InvokeAI to create the work, in the view of the US Copyright Office, sufficient human creativity was involved through the “selection, coordination, and arrangement of material generated by artificial intelligence”.

Plastic Chair Case

If China has been in the forefront of acknowledging that human control over AI tools used to generate content qualifies the works for copyright protection, a more recent case has reset the pendulum somewhat. As recounted in this blog by UK-based market research firm IAM, very recently a court in Jiangsu Province dismissed a copyright infringement claim brought by a designer against a company that manufactured, without a licence, children’s plastic chairs based on her AI-based designs. The designer, Feng Runjuan, had created three designs using the AI program Midjourney and posted them to social media, including the prompt she had used. Her prompt was “Children’s chair with jelly texture, shape of cute pink butterfly, glass texture, light background“. The company manufacturing the chairs approached Feng to license the designs but was unable to reach an agreement with her. They then went ahead anyway (without a licence) to produce chairs that bore some similarity to the original designs, using Feng’s original prompt with some tweaks. Feng sued. There was little doubt that the chair manufacturing company had used her prompts to produce the chair design, but the key question was whether the AI generated designs qualified as original works meriting copyright protection.

Feng was unable to reproduce the original images using her prompts owing to the randomness of the AI program. This suggested to the court that it was the AI program making the design decisions, not the person providing the prompts. As outlined in the IAM article referenced above, the court held that a user must provide a verifiable creative process that shows the:

adjustment, selection and embellishment of the original images by adding prompts and changing parameters; and
deliberate, individualised choices and substantial intellectual input over the visual expression elements, such as layout, proportion, perspective, arrangement, colour and lines.

It concluded that the original images did not qualify as original works and thus they could not be protected. Feng’s lawsuit failed.

So now we have a situation where one Chinese court has ruled that the prompts generated by Li in what I will call the “young girl image” case constituted sufficient intellectual input and personalized expression to qualify for copyright protection, even though the actual image was generated by an AI program, whereas another court has denied copyright protection for a work also produced with prompts, albeit simpler and far fewer. The difference seems to be the degree of human involvement in creating the prompts, although the fact that Ms. Feng in the plastic chair case was unable to reproduce the original images seems to have also weighed against her. As anyone who has ever used an AI program will know, identical prompts will produce different images owing to the way the program works. Does that disqualify the artist? I would hope not, but the degree of control is clearly a key factor, as both the rulings of Chinese courts and the recent USCO decision to register the work A Single Piece of American Cheese would seem to show. Both Chinese court decisions are defensible, demonstrating careful and reasoned consideration, and are helpful in establishing parameters for use in determining whether works are AI assisted or AI created.

Ultraman Case

Another area where Chinese courts have left their mark is on the topic of AI liability for copyright infringement. In what is known as the “Ultraman” case, a Chinese court (the Guangzhou Internet Court, upheld on appeal by the Intermediate Peoples’ Court in Hangzhou) delivered a ruling of contributory infringement against a company that provided AI generated text-picture services through its website. The complainant was the Chinese licensee of the Japanese company that owns the rights to the cartoon character Ultraman. When the defendant’s website (effectively a chat-bot capable of generating AI images at its users’ request) was asked to generate an Ultraman-related image, it generated a character that appeared to be substantially similar to the claimant’s licensed Ultraman. The court had to decide whether the defendant had infringed the plaintiff’s reproduction and derivative production rights and if so, what remedies were applicable.

In its ruling the court decided that even though the defendant did not directly infringe the licensee’s rights, its failure to exercise a reasonable duty of care to prevent infringements (for example, by cautioning users or providing adequate filtering or blocking mechanisms), rendered it liable for contributory infringement. It was ordered to compensate the claimant the amount of CNY 10,000, about USD1500 (considerably less than the damages sought of CNY300,000). Here we have another sophisticated and well reasoned decision, which appears to have been the first instance globally of recognizing the liability of an AI platform for contributory copyright infringement. It does not create any legal precedents but is a useful contribution to the emerging debate.

These cases well illustrate the growing sophistication and complexity of IP rulings in China and are reflective, in my view, of an economy that is rapidly moving up the innovation and creativity ladder. When it comes to IP protection in China, is the glass half empty or half full? I would argue the latter, even though this may not be the most popular interpretation these days. One thing that I am willing to predict with certainty is that we can expect more interesting and thoughtful IP legal decisions from the Chinese legal system in the months and years ahead.

How will Mark Carney’s Cabinet Appointments Impact Canada’s Cultural and Copyright Industries?

Group photo of Prime Minister Mark Carney's new Cabinet, featuring members seated and standing in a formal setting with a colorful mural in the background.

Image credit: Reuters

As Canada’s cultural community assesses the make-up of Prime Minister Mark Carney’s new Cabinet, two common phrases come to mind, “Hope Springs Eternel” and “Grasping at Straws”. The cultural and copyright industries have a number of legitimate concerns, which were well articulated in a pre-election brief published by the Coalition for the Diversity of Cultural Expressions (CDCE), as I outlined in an earlier blog post. Among the CDCE’s requests in the area of copyright was a plea for fair remuneration for writers and publishers for the use of their works in the education sector. There was yet another reminder of the need for the long-promised establishment of an Artists Resale Right in Canada, along with a reiteration of the request to extend the private copying regime to electronic devices (as is done in Europe), a measure that would help in restoring royalties in the music sector. The final copyright ask was to amend the definition of a sound recording to ensure that performers and record labels receive compensation for the audiovisual use of their works. CDCE’s brief also argued for “proper implementation” of the Online Streaming Act so that streaming services and social media platforms contribute financially to the production of Canadian content as well as support for retention of–and increased funding to–the CBC. There were also policy positions regarding the use of copyrighted content for AI training purposes.

What are the chances that all or any of these requests will be addressed by the new Carney government? One might think that with all the hoopla during the election about Canadian identity in the face of repeated attacks on Canada’s integrity by Donald Trump, there will likely be some significant measures taken to strengthen Canadian culture, although the Liberal election platform does not have much to say on Canadian cultural enterprises–other than the CBC. The CBC gets some love as a “cornerstone of our national identity” and will not only not be defunded, as threatened by the opposition Conservatives, but will get an additional $150 million cash infusion as well as having its funding put on a statutory basis. As a quid pro quo the national broadcaster will have to strengthen accountability and its commitment to local news, promote Canadian culture and combat disinformation. Increased funding (we don’t know how much) will be provided to the Canada Council for the Arts, Telefilm Canada, the Canadian Media Fund and the National Film Board. That is all good stuff, but there is not a whisper of copyright reform or of changes to copyright legislation in the platform.

The lack of any overt reference to copyright issues is probably understandable given the focus of the election, which was on standing up to Donald Trump and building the Canadian economy. It is not a bread-and-butter issue for most voters, important as it is to the cultural community. Therefore, we have to look beyond the Party Platform to the roster of appointed ministers and examine their backgrounds to see if there is any prospect of progress. On this score, the story is a bit more positive.

The two key ministers, the Minister of Industry, Science and Economic Development (which holds the statutory mandate for administering the Copyright Act), Mélanie Joly, and the new Minister of Canadian Identity and Culture, formerly labelled Canadian Heritage, (a ministry that has an important though subsidiary role to play on copyright), Steven Guilbeault, both represent Quebec ridings. This is significant given the importance of support for culture and cultural enterprises in the province and the influence of the creative community there. Guilbeault is also Carney’s “Quebec lieutenant”, which gives him extra influence. Joly, most recently Foreign Minister, is a former Minister of Canadian Heritage herself, as was Guilbeault in a previous incarnation. Thus, they know the cultural files. The CDCE was quick to congratulate both on their election, noting Joly’s appointment was a “promising signal” with respect to copyright.

Maybe. But it is unlikely that either Joly or Guilbeault will pick up the copyright ball unless they are pushed to do it. If they do, given the minority government status of the Liberals, they will need the support of another party. The Bloc Quebecois, with 22 seats(or 23, depending on what happens in the riding of Terrebonne where the Liberals won by exactly one vote out of almost 50,000 votes cast), would be logical supporters for the kind of changes to the Copyright Act sought by Canadian creators represented by the CDCE.

While having familiarity with cultural industry issues from having spent time in the past as Canadian Heritage minister is a plus, the reality is that while both Joly and Guilbeault are strong ministers, both struggled during their previous tenures at Heritage. Guilbeault’s first love is the environment, a role he held for 4 years under Justin Trudeau as Minister of Environment and Climate Change, making him Public Enemy No. 1 for Alberta Premier Danielle Smith. Her new public enemy is the current Environment Minister, Julie Dabrusin, who served briefly as Guilbeault’s Parliamentary Secretary at Environment. Dabrusin would have been an inspired choice for Minister of Canadian Identity and Culture given the role she played as Chair of the Standing Committee on Canadian Heritage that produced the report “Shifting Paradigms”. Among other things, her Committee recommended changes to the Copyright Act to narrow the problematic education fair dealing exemption that has done so much damage to writers and publishers in Canada. But it was not to be. However, she will do just fine as Minister of the Environment. As for being attacked by Danielle Smith, that is probably a badge of honour for any environment minister. The only scenario under which Smith would not attack a federal environment minister is if Carney pulled a page from Donald Trump’s playbook and appointed someone with such an anti-environment track record (like current EPA Administrator Lee Zeldin) as to effectively disqualify them from the job. But I digress.

Joly and Guilbeault are not the only ministers who will play on copyright issues. Among the new ministers announced on May 13 was Evan Solomon, the Minister for Artificial Intelligence and Digital Innovation. This is a new Ministry (having an Minister for AI may be a world first) and it is not altogether clear what Solomon’s mandate will be, as pointed out by Michael Geist. This is especially true as he does not have a functioning department to inherit. There are lots of issues for him to resolve, including the salient one of how and on what conditions AI developers will have access to copyrighted content for training AI algorithms. Canada has no text and data mining exception in its copyright law, let alone a broad exemption for AI training such as AI developers are seeking in the US and elsewhere. Some Canadian AI developers have been quick to use the pretext that AI development will flee Canada if they are not given free and unfettered access to creative content of others, a self-serving scare tactic if there ever was one, as I wrote about here. The fact is all countries are wrestling with the issue of how to protect valuable cultural industries while enabling responsible AI to develop. Licensing is the most obvious solution.

The CDCE had three requests with respect to AI training.

no Copyright Act amendment to allow technology development companies to continue using protected works, productions, and performances to train generative AI systems without authorization or compensation
implementation of legally binding measures requiring the disclosure of training data used in AI systems, and
ensuring that all AI-generated content is clearly identified, so that the public is fully informed about the nature of the content it consumes

Solomon no doubt will become involved in these questions. His background is as a journalist, a prominent one at that. As such, one might surmise that he has some understanding of the role of content creators and the need to foster and protect creative expression. But he will be subjected to lots of attention from the tech community, so we will just have to see how it plays out.

When I read all these tea leaves, I have the uneasy feeling that the times are not particularly propitious for the kind of political leadership sought by the cultural industries in Canada, particularly those sectors needing some attention to the copyright file. However, as I noted at the outset, “hope springs eternal”. And if hope fades, one can always “grasp at straws”. There are quite a few of them lying around. But are there enough to build any kind of useful structure? That is the question.

Should We Throw Copyright Under the Bus to Compete with China on AI?

An illustration depicting a stick figure running away from a bus labeled 'AI,' while another figure labeled 'C' appears to have been hit or is lying on the ground.

Image: Shutterstock (author modified)

If this sounds about as responsible as “we should legalize theft of patents at home because patent infringement is rife in China”, then you may well ask where such a nonsensical and counterproductive idea came from. From OpenAI, the company behind ChatGPT, for one, the same company being sued by the New York Times for copyright infringement for copying and using NYT content without permission to train its AI algorithms.

Sam Altman, CEO of OpenAI, is one of the “tech bro’s” now cozying up to Donald Trump. He is a vocal advocate of allowing the AI industry unfettered access to copyrighted content as part of the AI training process. Last year, in a submission to the UK Parliament OpenAI claimed that it would be “impossible” to train AI without resort to content protected by copyright. Now, it maintains that allowing AI companies to scoop up copyrighted content without authorization or payment is not only “fair use”, a legally unproven proposition that is currently very much a live issue before the courts in the US and elsewhere, but is essential for “national security”. To cite a few choice tidbits from OpenAI’s submission to the Office of Science and Technology Policy (OSTP) filed in response to the Office’s request for submissions on the Trump Administration’s AI Action Plan;

“Applying the fair use doctrine to AI is not only a matter of American competitiveness—it’s a matter of national security… If the PRC’s developers have unfettered access to data and American companies are left without fair use access, the race for AI is effectively over… access to more data from the widest possible range of sources will ensure more access to more powerful innovations that deliver even more knowledge.”

And, one could add, more profit for AI companies.

In other words, if the US government doesn’t give AI companies free and unfettered access to whatever content it desires, regardless of whether it is protected by copyright (think curated news content, musical compositions and artistic works, not to mention the published works of countless authors), then China will win the AI race, threatening the national security of the US. Or so Altman’s argument goes.

The AI industry is already a practitioner of the art of helping themselves to OPC (other peoples’ content) without permission, then claiming fair use when they are caught doing it. That is what has led to the multiplicity of lawsuits now before the courts, brought by various authors and content owners. Raising the bogeyman of China and wrapping themselves in the flag by invoking “national security”, is a new wrinkle in the attempts by the tech industry to undermine established copyright law and to wriggle out from under their legal obligations.

“National security” is a convenient catchphrase and pretext in common use today to try to justify and legalize the unjustifiable and the illegal. Donald Trump invoked national security when he used the International Economic Emergency Powers Act (IEEPA) to override USMCA/CUSMA obligations made to Canada and Mexico, treaty obligations that he himself signed in his first term in office. The immediate excuse was the flow of fentanyl across the northern and southern borders of the US. Never mind that the amount of fentanyl seized by US border agents at the Canadian border came to a grand total of less than 43 lbs. for all of 2024, or just 0.2% of the total. (The equivalent for Mexico was 21,148 lbs). National security, and in particular playing the China card, is a political winner these days in Washington.

OpenAI’s position is all the more outrageous because it went into fits when the Chinese startup, DeepSeek, launched its new and much cheaper product, allegedly having used OpenAI’s capabilities to improve its own model. OpenAI cried foul and IP infringement, a case of blatant hypocrisy if there ever was one.

OpenAI and other generative AI companies that have built their training model on permissionless copying are clearly nervous about the possible outcomes of the numerous court challenges to its practices currently underway. Most of these cases are in the US although similar lawsuits have been launched in the UK, Canada, India and Germany. While it is impossible to predict the outcome of specific cases, in a recent decision (Westlaw v Ross), a US court rejected fair use as a defence in the context of AI training data. It did not accept that copying the content was a transformative use, but rather one that created a product that competed in the market with the original source material. Given the legal uncertainties, it looks like the tech industry is trying to hedge its bets by lobbying to have all AI training uses declared to be “fair use” based on national security considerations.

It gets worse than that. Another of the tech bro’s, Mark Zuckerberg, gave the green light to training of META’s AI model on pirated material. This was not accidental. Employees reported removing © marks from books downloaded as training materials.

In Canada, in a similar search for a rationale to explain away copyright infringement, a company that was helping itself to copyright-protected curated legal case data to build an AI based legal reference service, claimed that forcing it to license the content would stifle innovation and drive AI businesses out of the country. See CanLII v CasewayAI: Defendant Trots Out AI Industry’s Misinformation and Scare Tactics (But Don’t Panic, Canada). The AI developers’ strategy seems to be that if you don’t want to license and pay for IP protected content, (or perhaps the owner of the content prefers not to license it, as is their right) just take it and claim some overriding purpose, like protecting domestic innovation or national security.

But what about the argument that if China doesn’t respect intellectual property (IP), we need to adopt the same approach in order to compete? While Chinese courts in recent years have taken a much more robust position with respect to protecting the rights of IP owners, including patents, trademark and copyright, I am not going to argue that suddenly China has become a “rule of law” country. Rather, it is a “rule by law” state, the law being whatever the leadership of the Chinese Communist Party (CCP) decides it will be at any given moment. This is a fact. However, to suggest that the West, in particular the US, should adopt China’s legal modus operandi so as not to lose the so-called “AI race” not only undermines all the values and principles on which our society is based, including the principles of private property, fairness and transparency, but also dismisses three centuries of legal developments in the protection of IP, especially copyright. The evolution of copyright law has resulted in the creation of industries that contribute far more to the economic and cultural wellbeing of our society than any of the questionable outputs of the AI industry.

Yes, AI is here to stay. It can be put to beneficial or nefarious uses and has an undoubted strategic component. It can also be used to undermine and weaken human creativity. Is that the goal we are seeking?

It is worth noting that the tech bro’s have an easy and legal way out. In most instances, they can acquire access to the content they need legitimately. A market for licensing training data for AI development already exists and is further developing rapidly, as I wrote about earlier. Using Copyrighted Content to Train AI: Can Licensing Bridge the Gap? But just taking it and claiming “fair use” is easier and cheaper. And morally and probably legally wrong.

We have seen a lot of rogue policy making in Washington of late, from the illegal deportation of US residents, to the gutting of US government agencies, to the declaration of a tariff war against the world. It is time to take a more considered approach. Rash decisions in response to tech lobbying could lead to untold consequences and collateral damage to content industries that would be impossible to roll back and remedy. Thus, I was relieved to note that Michael Kratsios, Director of the US Office of Science and Technology Policy, the same OSTP to which OpenAI submitted its comments regarding AI training and national security, stated in a recent speech on American innovation that;

“…promoting America’s technological leadership goes hand in hand with a threefold strategy for protecting that position from foreign rivals. First, we must safeguard U.S. intellectual property and take seriously American research security…”

That is a welcome recognition of the importance of IP as part of the process of innovation.

In this respect, the existing framework of copyright law has survived and adapted for over 300 hundred years. It has evolved with each new technological development, but the fundamental principle of giving an “author” of an original work the right to control how that work is used as well as the ability to earn a return from its use for a statutory period, with only limited exceptions, has remained unchanged. To undermine this principle in a flawed attempt to grasp the Holy Grail of AI leadership is self-defeating. Instead of sipping from AI’s Holy Grail we will be drinking from the poisoned chalice of IP theft.

Throwing copyright and the rule of law under the bus on the pretext that this is what’s needed to compete with China is not only self-serving, it is a sure path to ultimately losing the secret sauce of creativity and innovation. A country that steals IP rather than creating and respecting it will always lose the race.

Tag: AI and Copyright

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