UGC refers to all publicly available media content that is produced by end-users. UGC can refer to all media technologies, from digital photos and videos to blogs, podcasts and mobile phone content and is published by both traditional media sources (largely broadcasters) and non-traditional media sources (such as eBay, YouTube, and Facebook) (Stribbling and Scott 2008, 6)

UGC is a powerful tool for expression made possible by the digital age. What in the past was a letter to the editor with a restricted audience has been transformed into a supposedly journalistic analysis and critical podcast available to many, for example, the *Presunto Podcast* where a group of independent communicators analyze the work of the media in Colombia. The project is an initiative that began among a group of friends interested in scrutinizing with humor how the national mass media covers the news. Today it is supported by donations, but they have taken advantage of podcast platforms including GooglePodcasts, Apple, and Soundcloud, to create and distribute the content.

Much UGC is not of professional quality and rarely perfect but makes a connection with an audience due to its spontaneity and apparent authenticity. For the creators, the process can be a rewarding experience not only for the pleasure of producing something, but also for the satisfaction of seeing the work recognized by other users, companies and even by the platforms that were used to disseminate it. For consumers, UGC serves as a means of information or entertainment. But UGC can also be created and shared for deliberately harmful, hateful, or misleading purposes. This chapter introduces some salient mechanisms for flagging, moderating, and removing abusive or illegal UGC and identifies the challenges such mechanisms pose for users' freedom of expression.

### **User-Generated Content: Some Salient Features**

While it might be difficult to agree on a single definition of UGC, various descriptions have been presented (Krumm, Davies, and Narayanaswami 2007; Östman 2012; Ruz 2011; Wunsch-Vincent and Vickery 2007) and the following characteristics have been highlighted:

– Creative effort: content creators use their inventiveness to produce an original work or adapt an existing work to craft a new one, for example, when an amateur musician publishes a video performing an original song, or when a user transforms the interview of a politician into a video parody of the politician, for example Donald Trump interviewing himself in confusion (Brown 2020). With transformation, the creator adds a personal creative value to the work. The value might have a collaborative element as in the case of users who collaborate in the creation of entries in Wikipedia or in building another resource such as OpenStreetMap, a map of the world created by users. The pandemic has seen a significant rise in the availability of UGC containing immensely creative and innovative content on topics related to the pandemic and/or generated as distractions from the pandemic.

The features mentioned are useful for establishing the contours of user-generated content, as opposed to professionally created content, from which a certain technical quality of the product is usually expected. User-generated content has become an important marketing tool with users posting recommendations, likes and dislikes for products or services.

### **Typology of User-Generated Content**

UGC can be classified according to the type, format or platform used for distribution (Wunsch-Vincent and Vickery 2007). UGC can take various forms including a poem or opinion piece; audio such as a remake or cover song or a podcast; graphic such as photos or illustrations; video such as a home video or a short film; or a combination of these elements. The platforms used for UGC distribution are varied. There are:

Many of the platforms have a recommendation and rating system that leads to the extent of content consumption and to the popularity, recognition, and notoriety of the creator.

Another approach to the classification of UGC is to examine a person's motivation for content generation. Some creators contribute content as a form of self-expression. Individuals or groups document occurrences in their lives, express opinions, share analysis, comment on other content or report on situations. Some seek social and communicative interaction with like-minded people; others entertain themselves or pass the time; some wish to inform or engage in citizen journalism; others seek to persuade people to certain perspectives; some seek to advertise products or services; some creators engage in activity for the purpose of professional progress; and some seek to educate (George and Scerri 2007).

In examining UGC, original content can be generated by a user independently, for example, creating a blog to document travel. Alternatively, content might be composed in which a user integrates a piece of creative content into an existing work without transforming it, for example, including a copyrighted photo by another author into a travel blog entry. Further transformation can occur with a user changing a pre-existing work, for example, by using a frame from a movie to create a meme that is included in the blog post. UGC can have varying layers of content with different copyright issues associated with each layer (Ruz 2011; Erickson 2014) and with the platform used.

# **The Cultural and Political Relevance of User-Generated Content**

UGC is part of a digital age, where creative activity and cultural production are no longer in the hands of a few, with prescribed methods of production and distribution. For the most part, users who are creators seek to share and not compete for the content they have generated. The experience is "based on expressiveness, performance and collaboration" (Östman 2012, 1005) and involves knowledge, activity, and behaviour with cultural and political relevance.

UGC and users who are creators disrupt traditional media and content suppliers (Senftleben 2008). Yet some of the most significant platforms used for UGC production and distribution are dominant and even monopolistic players in the content-sharing industry, a crucial component of the digital economy. The concentration of power that rests in the hands of a few platform players is a growing concern across multiple fields such as antitrust. For example, the Antitrust Division of the United States Department of Justice filed a lawsuit to prevent Google's anticompetitive and exclusionary behaviour, and to promote the innovative activities of other companies so that they could compete and thrive in the digital market (US Department of Justice 2020). The case, *United States v. Google LLC1* illustrates the struggle amidst the dominant players and between platforms to host UGC.

The dominance of a few platforms also presents concerns about privacy and data collection. The overwhelming dissemination of, and engagement with, UGC on large platforms facilitates these platforms' widespread collection of user data and information. Arguably most importantly, the dominance of a few key platforms such as Google, Facebook, and YouTube, and the concentrated ownership

**1** United States v. Google LLC, No. 1:20-cv-03010 (D.D.C. October 10, 2020).

of such platforms by a small number, Alphabet and Meta, pose substantial issues for the democratization of content-sharing. Significant power over hosting UGC continues to rest in the hands of a few monopoly platforms, thereby undermining the democratization of content-sharing and expansion of user autonomy that UGC so aptly advances by its nature.

### **Cultural Relevance**

The Internet has served as a vehicle for the diffusion of culture. The ease of access to technology to produce and broadcast content has paid off in the generation of creative activity, knowledge, and information. While recognizing the large digital divide between states, societies and individuals, anyone with a smartphone can produce cultural content that reflects personal creative interests or expresses and captures community culture. For example, the science fiction short films produced by a group of eight young Nigerians, The Critics Company, with scarce resources, slow internet, continuous power cuts, everyday objects, and low and mid-range smartphones, have gone viral on social media (Africanews 2019). Without a doubt, the contents are the result of the ingenuity and determination of their producers, who took advantage of technologies and other user content, in this case, tutorials available on YouTube explaining how to produce films with special effects, to find a means of expression and tell their science fiction stories.

The young Nigerian group harnessed the power of UGC, becoming innovators and contributing to the cultural richness of their community. The work of The Critics Company is an example of how UGC is relevant in fostering creation and cultural enrichment. As a result, there is greater autonomy, participation, and diversity. "Technological change empowers individuals to 'tell their stories', to produce cultural goods such as music and to transform the information and media content environment surrounding them… Users may derive a higher value … as the content may be more personalised… users have a greater control" (Wunsch-Vincent and Vickery 2007, 35). Users transform the information and communication ecosystem to make it more relevant to their interests and contexts. UGC is also relevant to creating a sense of identity within a group, community, or society. UGC serves as a mechanism that harnesses collective intelligence to provide information and knowledge, with the potential to improve the quality and scope of access to culture and the right to education.

Cultural relevance is made possible by the proliferation of content in different languages. Although English continues to be the most widely used language on the Internet with 2020 figures at 25.9% followed by Chinese at 19.4% (Johnson 2021), the reality is that UGC is produced in any language, which in turn allows for the enrichment of cultural heritage and the strengthening of different languages. For example, there are many efforts by cultural entities, collectives, and individuals to make visible the Guarani language, the official language in Paraguay spoken by just under 90% of its population (Galeano Olivera 2016, 15). The promotion of UGC in Guarani has used collective collaboration to translate Wikipedia, Firefox, and Facebook, and promoted use of the language, allowing it to progress, be visible and relevant to all the people who speak it. Perhaps UGC in Guarani or any other minority language may not have the same scope as content in English but is important in proclaiming local culture and contributing to keeping languages alive.

Much UGC is derivative in whole or in part, and many creators rely on copyrighted content. The Critics Company may rely on copyright music to create the soundtrack of its film productions, ignoring or disregarding copyright restrictions. Likewise, collective efforts to translate digital content into Guarani are transformative processes that may be infringing copyright. To the extent that creators do not have the authorization of the rightsholders to use content, or are using free licensed content, they are operating under copyright restrictions that can inhibit creative production that contributes to cultural diversity. Some content creators have gone under the radar, perhaps because they do not infringe copyright or perhaps because they have had the good fortune of not running head-on into issues associated with copyright. As copyright regimes become more restrictive, the potential for UGC to promote cultural creation and diversity is at risk.

### **Political Relevance**

UGC plays an equally critical role in democratic participation, activism, and social and political mobilization. Producing and disseminating content in minority languages is both a cultural and political act: it challenges the dominance of hegemonic knowledge production and visibility and fosters and fights to keep alive the world view connected to the society speaking the language. As Östman (2012) argues, UGC is indivisibly involved in political participation and in the acquisition of political attitudes, knowledge, and behaviour.

UGC has been used for critical, political, and social justice purposes. Perhaps the best example of the latter is the role of citizen journalism where individuals take an active role in making and disseminating news content (Bowman and Willis 2003). Citizen journalists often become the only source of information within war zones, as was the case with the war in Syria, where citizens took the risk of documenting the conflict, filling an important void in understanding what had been happening in the country since the 2011 uprising. Many of the UGC products of citizen journalists in Syria today are stored and verified in the Syrian Archive, a digital memory project that preserves UGC and collects human rights violations, so that content can be retained for the future to support accountability and contribute to post-conflict reconstruction and stability (Syrian Archive n.d.).

One of the great appeals of UGC is its honesty, which allows for greater involvement and identification with the message of the content, hence its political relevance. The fact that a group of people can be identified or reflected in the content generated by others can give them enough confidence to express ideas and political views, leading to active civic participation (Östman 2012, 1008). For example, in 2015, the Canadian initiative Project 60 used UGC strategically to encourage First Nation youth to create and share short videos explaining the voting process. The project sought to politically engage a crucial segment of the population, while the content creators educated and empowered their youth peers about the impact and importance of elections for their community (Indigenous Social Media and User-Generated Content n.d.).

Although UGC is a crucial source of cultural and political participation that allows individuals and groups to disseminate knowledge about causes, UGC is, as noted earlier, a tool that has also been used for ill-intentioned and malicious purposes. UGC has been weaponized by people seeking to misinform or influence democratic processes through the creation and dissemination of fake news, abusive content, and deepfakes, a form of synthetic media that uses an image or video to create a fake scenario. One deepfake video created by the Flemish socialist party Vooruit in 2018 which circulated on Twitter and Facebook portrayed Donald Trump teasing and insulting Belgium for remaining in the Paris Agreement. The party's deepfake was intended to raise awareness and generate public discussion about the climate crisis and the video contained several indications that it was fake (Velicer 2021). Yet this instance demonstrates the significant role UGC can play in threatening an informed citizenry and contributing to "epistemological anarchy" (Galston 2020).

UGC, therefore, can be seen as a vehicle in the digital age for freedom of expression. However, as this chapter continues to explore, UGC not only faces issues of user and creator misuse, but also various legal and technological barriers, which are often emanating from the powerful agents of the copyright industry.

# **The Clash between Freedom of Expression and Copyright**

### **Freedom of Expression**

Article 1 of the Universal Declaration of Human Rights states that: "All human beings are born free and equal in dignity and rights".

Human rights are universal and inalienable; indivisible; interdependent and interrelated. They are universal because everyone is born with and possesses the same rights, regardless of where they live, their gender or race, or their religious, cultural or ethnic background. Inalienable because people's rights can never be taken away. Indivisible and interdependent because all rights – political, civil, social, cultural and economic – are equal in importance and none can be fully enjoyed without the others. They apply to all equally, and all have the right to participate in decisions that affect their lives. They are upheld by the rule of law and strengthened through legitimate claims for duty-bearers to be accountable to international standards (UNFPA 2005).

Freedom of expression is a basic human right and constitutes the right of people to express their ideas and opinions, and to issue, access, seek and receive information of all kinds. The right of freedom of expression also protects the ability of individuals to disseminate information and ideas by any means, regardless of borders.

Freedom of expression is recognized as a cornerstone of any free, democratic, and participatory society and is fundamental to the realization of the human being. It protects the most basic of human freedoms, namely the right to think and share opinions with others. It is also fundamental to democracy and the exercise of other rights (UN. Human Rights Committee 2011). For democracy to function, the full and effective participation of citizens is essential, which occurs, in large part, through the realization of freedom of expression. In addition, it also allows for the exercise of other rights such as the right to participate in cultural life, and to enjoy the benefits of scientific progress and its applications. Institutions including libraries often safeguard the right to freedom of expression and participation in cultural and innovative life.

Although, in principle, all expressions are protected by freedom of expression, it is not an absolute right, and it can be limited. For a limitation on freedom of expression to be permissible, according to international human rights standards, the following principles must be met:

– Legality: a law formulated with sufficient precision and accessible to all persons has provided for the limitation

It is worth noting that, according to international human rights standards, any measure restricting freedom of expression on the internet "must be applied by a body which is independent of any political, commercial, or other unwarranted influences in a manner that is neither arbitrary nor discriminatory, and with adequate safeguards against abuse, including the possibility of challenge and remedy against its abusive application" (La Rue 2011, 8). However, regarding the application of copyright on platforms carrying UGC, as will be addressed later in this chapter, the implemented measures tend to use the platforms as a proxy for restricting freedom of expression, in breach of the aforementioned obligation.

The Human Rights Council has stated that human rights offline must be equally protected and guaranteed online. "Freedom of expression applies to the Internet, as it does to all means of communication" (La Rue et al. 2011). At its 20th session the Human Rights Council adopted a resolution that unanimously stated: "the same rights that people have offline must also be protected online, in particular freedom of expression" (UN Human Rights Council 2012, 2). The Internet has undoubtedly provided people with greater access to all kinds of information, but it has also given them unusual opportunities to be active subjects in the creation and dissemination of knowledge and information as seen in relation to UGC. The catalytic power that technology has given people to exercise their rights to freedom of expression has created tension between governments and the powerful, including economic agents of the copyright industry. Technologies that enhance the exercise of freedom of expression confront the legitimate interest of protecting copyright.

# **Copyright**

Intellectual property has two traditional legal domains: copyright and industrial property, that is, patents and trademarks. Copyright deals with the rights of intellectual creators. Its object of protection covers original works in the literary, scientific, and artistic fields, whatever the mode or form of expression. Copyright grants authors the right to authorize or prohibit, for a specific limited time, particular uses of their works. In other words, limited monopolies are granted to creators in relation to their creations. Moreover, copyright regimes protect the activity of expression rather than the ideas, concepts, processes, or procedures themselves. Therefore, copyright protections in themselves do not pose limits on the sharing of ideas. Copyright protection is justified as an important means of encouraging authors and artists to create, thus promoting, enriching, and disseminating a nation's cultural heritage, creative activity, and innovation.

Copyright protects two types of rights: moral and economic. "Economic rights allow right owners to derive financial reward from the use of their works by others. Moral rights allow authors and creators to take certain actions to preserve and protect their link with their work" (WIPO 2016, 9–10). Moral rights allow authors to preserve and protect their connections to their work. Usually, the moral right cannot be transferred to third parties. However, the application of moral rights varies under different national laws. Authors, on the other hand, can grant their economic rights to others known as rightsholders, so they can obtain monetary compensation for certain uses such as reproduction, distribution, public performance, broadcasting or communication, translation, or other adaptations.

Copyright is not an absolute right; it can be limited with the aim of protecting the public interest. Copyright regimes include a list of exceptions and limitations that, according to the Berne Convention, are understood not to conflict with the normal exploitation of the work and not to unreasonably prejudice the legitimate interest of the authors. In general, the list of exceptions and limitations ensures that copyright does not interfere with the exercise of other rights.

Existing copyright regimes can have important implications for the protection and promotion of human rights, particularly freedom of expression. As the increasingly powerful economic agents of the copyright industry are pressing to claim creative works and forms of knowledge, human rights are being infringed (Chapman 2001). Creators are progressively losing control of their works with the result that society faces increasingly insurmountable barriers to the free exchange of information.

Industrialized countries have pushed for increased global copyright protection. The World Intellectual Property Organization (WIPO) reinforces this maximalist copyright view, in which there is little room for discussion, consideration and effective protection of the public interest and human rights. Governments use copyright laws to enhance a country's competitive economic advantage. Policies developed often favour major economic interests, particularly large multinational corporations, to the detriment of protecting access and promoting development in local societies.

The conflict between copyright and human rights has attracted the attention of United Nations (UN) human rights bodies and continues to do so. In 2000, the UN Sub-Commission on the Promotion and Protection of Human Rights, later known as the Advisory Committee of the Human Rights Council, adopted as part of its deliberations a Resolution on Intellectual Property Rights and Human Rights, affirming that the right to the protection of the moral and material interests resulting from one's scientific, literary or artistic productions is a human right, subject to limitations in the public interest with primacy over trade law. The resolution:

Affirms that the right to protection of the moral and material interests resulting from any scientific, literary or artistic production of which one is the author is, in accordance with article 27, paragraph 2, of the Universal Declaration of Human Rights and article 15, paragraph 1 (c), of the International Covenant on Economic, Social and Cultural Rights, a human right, subject to limitations in the public interest.

Declares, however, that since the implementation of the TRIPS Agreement does not adequately reflect the fundamental nature and indivisibility of all human rights…there are apparent conflicts between the intellectual property rights regime embodied in the TRIPS Agreement, on the one hand, and international human rights law, on the other.

Reminds all Governments of the primacy of human rights obligations over economic policies and agreements… (UN Sub-Commission on the Promotion and Protection of Human Rights 2000, 28–9).

Five years later, the UN Committee on Economic, Social and Cultural Rights, in its General Comment No. 17, distinguished between the human rights recognized in Article 15(1)(c) of the International Covenant on Economic, Social and Cultural Rights, and the rights recognized in the intellectual property regimes:

Whereas the human right to benefit from the protection of the moral and material interests resulting from one's scientific, literary and artistic productions safeguards the personal link between authors and their creations and between peoples, communities, or other groups and their collective cultural heritage, as well as their basic material interests which are necessary to enable authors to enjoy an adequate standard of living, intellectual property regimes primarily protect business and corporate interests and investments.

The Committee went on to note that: "The right to benefit from the protection of the moral and material interests resulting from one's scientific, literary and artistic productions seeks to encourage the active contribution of creators to the arts and sciences and to the progress of society as a whole…[and] is intrinsically linked to the other rights recognized in article 15 of the Covenant…" (UN Committee on Economic, Social and Cultural Rights 2006, 2). The other rights, which are mutually reinforced and limitative, are: the right to take part in cultural life, the right to enjoy the benefits of scientific progress and its applications, and the freedom for scientific research and creative activity. Thus, the rights of authors and creators must facilitate, rather than limit, cultural participation and broad access to the benefits of scientific progress.

As for the rights recognized in copyright regimes, the Committee indicated that they should not be equated with human rights. "Human rights are fundamental as they are inherent to the human person as such, whereas intellectual property rights are first and foremost means by which States seek to provide incentives for inventiveness and creativity" (ibid, Para. 2). Nor can the rights associated with copyright be considered human rights as they protect the commercial and business interests and investments of legal entities, whose rights are not protected at the level of human rights. Additionally, copyright, unlike human rights, "are generally of a temporary nature, and can be revoked, licensed or assigned to someone else" (ibid).

To give substance to Article 15(1)(c) of the Covenant and to distinguish its measures from copyright as understood in intellectual property regimes, the Committee outlined further details of the elements and wording contained in Article 15:

To be consistent with all the provisions of Article 15 of the International Covenant on Economic, Social and Cultural Rights, the type and level of protection afforded under any copyright regime must facilitate and promote cultural participation and intellectual progress and do so in a manner that is broadly beneficial to members of society both individually and collectively. These considerations go far beyond the economic calculation that guides copyright. Copyright could be reformed to be more respective to human rights regimes and current tensions with the right to freedom of expression would be reduced.

# **Online Platforms and Copyright Management**

User-generated content would not exist if there were no platforms for publication and broadcast. Types of UGC were presented earlier in the chapter and they can be distinguished by different types of platforms used. The term online platform is used variously to include search engines, social media, creative outlets, communications services, and collaborative services. Some are interactive. Platforms might be non-profit or commercial. The growth of UGC and online platforms has been stimulated by the expanding use of mobile devices along with the increasing sophistication of personal computing capacity.

"An online platform is a digital service that facilitates interactions between two or more distinct but interdependent sets of users (whether firms or individuals) who interact with the service via the internet" (OECD 2019, 20). Platforms or internet intermediaries themselves can be classified in various ways: by types of users, the kinds of data and content mounted, the actions taken in relation to data collected, or sources of revenue. (ibid). Wyrwoll described platforms on which UGC is mounted as blogs, forums, location sharing and annotation platforms, media sharing platforms, microblogs, question and answer platforms, rating and review platforms, and social networks (2014, 20). UGC includes messages, product recommendations, instructions, learning materials, news, comments, advice, articles, blogs, profiles, reviews or creative content ranging from poetry, stories, ideas, to videos posted on forums like Twitter or Reddit; social media like Facebook, TikTok or WeChat; encyclopaedias like Wikipedia; creative outlets like LiveJournal; commercial services like Amazon; shared video sites like YouTube or Vimeo; musical recording sites like Spotify or SoundCloud; and podcasts on Spotify for Podcasters.

The platforms allow people to contribute, evaluate and consume content online. The business models of many platforms are based on third party production of content; the platform providers create the systems to maintain attention and interest, the most common of which is the evaluation and feedback of users and suggestions for similar content.

### **Management of User-Generated Content by Digital Platforms**

Each platform regulates in its terms and conditions the legal aspects related to the dissemination of content by third parties including the intellectual property rights of creators and others that might be affected, rules for behaviour, and any applicable legislation and jurisdiction. Terms and conditions vary across platforms.

The policies are adopted to give users information about the rules that operate in them, but they also translate legal obligations. One legal obligation in the US is the *Digital Millennium Copyright Act* (hereinafter the DMCA), which requires US-based platforms to takedown content that allegedly infringes copyright. The terms and conditions provide certainty and predictability about the digital behaviour that platforms expect from their users and the possible consequences. As a rule, all platforms recognize that the authorship of content remains with the person who creates it. However, for the platforms to function as they have been conceived, the terms and conditions include the transfer of rights to store, copy, share and disseminate the content produced by users. All platforms recognize the importance of copyright. The use of the platforms' services by users is subject to respect for copyright. The terms and conditions of some of the most popular platforms, particularly regarding the transfer of rights, are stated in the following.

#### **Google**

Google creates a licence for the use of UGC that is subject to intellectual property protection while the content remains on any platform owned by the company, including YouTube (Google 2020). Content created by users includes docs, sheets, and slides, blog posts uploaded through Blogger, reviews submitted through Maps, videos stored in Drive, emails sent and received through Gmail, pictures shared through Photos and travel itineraries shared with Google. The licence is global, non-exclusive, and royalty-free. In addition, it allows Google to save and allow public access to the content, as well as to transform it through changing its format or translation. The agreement includes sublicensing to other users so that they can, for example, share the content according to how their platform services work. In relation to the company's video-sharing service, YouTube, users have the option of granting permissions for use through Creative Commons licences.

#### **Facebook**

Facebook's terms and conditions include the creation of a "non-exclusive, transferable, sub-licensable, royalty-free, and worldwide license to host, use, distribute, modify, run, copy, publicly perform or display, translate, and create derivative works of your content", consistent with the user's profile settings, that is, whether the profile is open or closed (Facebook 2020). The licence terminates with the removal of the content, unless third parties who keep their profiles active have shared the content (Facebook 2020).

#### **Twitter**

Terms are similar for Twitter. The company has a global, non-exclusive, royalty-free permission to use, copy, modify, publish, and distribute the content that a user shares on the social media platform. "By submitting, posting or displaying Content on or through the Services, you grant us a worldwide, non-exclusive, royalty-free license (with the right to sublicense) to use, copy, reproduce, process, adapt, modify, publish, transmit, display and distribute such Content in any and all media or distribution methods now known or later developed (for clarity, these rights include, for example, curating, transforming, and translating). (Twitter 2021).

#### **Pinterest, TikTok and Soundcloud**

Pinterest grants a licence with similar characteristics to terms and licences already outlined, stating "You grant Pinterest and our users a non-exclusive, royalty-free, transferable, sublicensable, worldwide licence to use, store, display, reproduce, save, modify, create derivative works, perform and distribute your User Content on Pinterest solely for the purposes of operating, developing, providing and using Pinterest" (Pinterest 2018). There is a separate section on Copyright. TikTok includes in its terms the same transfer of rights, but the license is considered irrevocable and perpetual (TikTok 2019). TikTok has a separate intellectual property policy.

SoundCloud's Terms of Use involve users granting the company a limited, worldwide, non-exclusive, royalty-free and fully paid licence to store, distribute and use the content uploaded to the platform (SoundCloud 2021). The transfer of rights is sub-licensable. However, the termination of the license applies only to the audio, text, and images that users have uploaded to their accounts, but not to the comments or other contributions they have made. The license is perpetual and irrevocable for the latter.

#### **Wikipedia**

Wikipedia, unlike commercial platforms, is committed to supporting access to knowledge, free culture, and the promotion of common goods. To this end, it requires users who contribute to the project to "grant broad permissions to the general public to re-distribute and re-use their contributions freely" (Wikimedia Foundation 2020). Hence, the general rule at Wikipedia is the use of licences such as Creative Commons copyright licences which are free and easy-to-use, and provide a simple, standardized way to give permission to share and use creative work and the GNU General Public License, a series of free software licences that provide users with the freedom to run, study, share, and modify the software.

### **Rules of Behaviour and Copyright Enforcement**

The use of platforms is subject to respect for the copyright of others. By accepting the terms and conditions, users agree not to upload any material that violates the copyrights of third parties. However, many users publish material belonging to other authors, either in its original version or in an adapted form, perhaps in ignorance of requirements to observe copyright, and with or without an intention to infringe on such a right.

Copyright infringement is further complicated when copyright law and policies are misaligned with the practices, cultures, and norms of online platforms. The issue is especially apparent on social media platforms such as Instagram and Twitter that foster redistribution and reposting across other platforms (Meese and Hagedorn 2019, 5). Platform users have a nuanced understanding of copyright. While some users are aware of copyright policies and legislation, copyright law is not always clear about how users can create, share, attribute and manage their content in a practical setting (ibid, 4). For instance, adequate attribution on social media platforms can be difficult for users who are unable to locate the original copy amidst countless other copies (ibid). While some users creating content are aware of copyright law, they may be uncertain how to implement attribution practices; others deliberately infringe copyright in the creation and dissemination of content, once again demonstrating the complexity in users' behaviour.

The platforms have created content moderation mechanisms to enforce copyright and, in the vast majority, respond to the DMCA's legal requirements. In general, content moderation requires rightsholders to request a platform to remove content based on an alleged infraction of rights. The platform must act on any complaint. According to the DMCA, the action to be taken involves removing the content and then notifying users. If the removal of the content is erroneous or represents an abuse by rightsholders, users have the option of contesting the complaint with a counter-notification.

Some contend that the system is designed to encourage complaints from rightsholders and to discourage complaints from users (Cortés Castillo 2013). On the one hand, it is inexpensive for copyright owners to make complaints about alleged violations of their copyright, while on the other hand, the system provides a strong incentive for platforms to "en el puerto seguro de la ley/be in the safe harbour of the law"; that is, to take actions which will ensure legal immunity, and avoid being caught up in legal proceedings against them (Cortés Castillo 2013, 5). Moreover, the platforms have neither the mission nor the incentive to confirm the veracity of allegations or to defend their users against possible excesses by rightsholders. Applying the DMCA's notice, and takedown system guarantees that the platforms are not legally responsible for infringements caused by their users. Therefore, the platforms respond to rightsholders' claims, even when an exception to the copyright or a legitimate use might be involved. The DMCA and platform responses have led to numerous cases of unjustified and abusive content removal, often violating the users' rights to freedom of expression and due process (Cortés Castillo 2013).

Another copyright enforcement mechanism is the European one. Until very recently, Europe mirrored the US notice and takedown system, which recognizes that the platforms are not legally responsible for copyright infringing content but are required to remove it once flagged. With the adoption of the 2019 European Union Directive on Copyright in the Digital Single Market (hereinafter the DSM Directive), the scenario began to change. The controversial Article 17 of the said standard requires platforms to request the rightsholders' authorization, for example, by means of a licence, before copyright-protected works can be uploaded to the website. Without such authorization, the platform would be liable for the copyright infringement of its users. Paragraph 4 states: "If no authorisation is granted, online content-sharing service providers shall be liable for unauthorised acts of communication to the public, including making available to the public, of copyright-protected works and other subject matter, unless the service providers demonstrate that they have: (a) made best efforts to obtain an authorisation …" (Directive (EU) 2019/790 2019). In other words, the European safe harbour for platforms in copyright cases is the implementation of an upload filter, which will screen content before it is published. The system in practice creates a censorship mechanism, in which users will have to obtain the approval of the platform before being able to publish and broadcast content (Heldt 2019).

In international human rights law, there is a strong presumption about the prevention of prior censorship and a focus on the ability to comment on public issues without censorship or restraint to inform public opinion (UN Human Rights Committee 2011; Lanza 2017). Given the importance of the right to freedom of expression for democracy, any sanction for expressions that may infringe on the rights of others should be imposed only subsequently to the publication of content and should never precede it. This ensures, for example, that unpopular ideas or opinions are circulated, and that public debate is not suppressed.

Another approach to dealing with the issue can be found in the Canadian copyright regime with its notice and notice system. Rightsholders who believe that users are violating their copyright must send a notification of possible infringement to the platform. In turn, the platform must forward the notification to the users. The intent of this approach is to discourage online infringements (Stephens 2018). The Canadian system adopted an educational and awareness raising approach, rather than a retaliatory one. Rightsholders do not lose their right to sue, but only a court can determine whether there has been an infringement of copyright and what sanction or remedy might be deemed appropriate.

# **Libraries and User-Generated Content**

There are various ways in which libraries engage with UGC. Library systems may use an information retrieval platform that includes UGC from other knowledgeand content-sharing platforms. Libraries with websites and social media pages will create and share their own UGC. Additionally, libraries' digital information retrieval and discovery systems can enable users to comment, review, and rate content on the library's platform. The latter practice permits users' contribution to the information retrieval process which can critically foster users' expression and knowledge-sharing about the library's materials.

For libraries that use information retrieval or discovery systems incorporating UGC, it is important that the "Libraries … should adopt policies that define the time, place, and way the user contributes the content to the library's discovery system. Additionally, libraries should make it very evident which content is generated by the library and which content is generated by other users (American Library Association 2019). Management mechanisms are important as the way a library system presents and incorporates UGC may influence the way users select books and materials, for instance, based on reviews and ratings other users' postings.

As previously stated, libraries that incorporate UGC in their systems may be supporting users' freedom of expression by providing a public digital space in which users can freely discuss, recommend, or even critically comment on a range of topics. Therefore, libraries should exercise caution when removing UGC, ensuring that it is removed under due process and because of exceptional situations.

# **Copyright Enforcement and Freedom of Expression**

Online platforms have developed reactive content moderation mechanisms including applications of artificial intelligence (AI) to act against potential infringements to their rules and legal obligations (Llansó 2020). The mechanisms rely on another user flagging the content as abusive or illegitimate and potentially a copyright infringement. Pressured by governments, the copyright industry and civil society including non-governmental organizations, non-profit organizations, and users themselves, the platforms have been forced to design proactive mechanisms that allow them to quickly contend with the issues that arise from the dissemination of abusive or illegitimate content (Llansó 2020; Romero Moreno 2020).

Managing UGC on digital platforms also involves the task of addressing false, hateful, or inappropriate UGC with the growing quantities of so-called fake news and deepfakes. Detecting and removing malicious, erroneous abusive content while protecting the right to freedom of expression is a difficult debate in digital environments. Whether platforms should permit the circulation of UGC for leisure, creative innovation, cultural expression, and political causes only, or allow users to be exposed to a full range of UGC regardless of its accuracy, validity or appropriateness presents ongoing conflict and debate between platforms, civil society, and governments. Copyright law can be used to remove certain UGC based on safeguarding an author's copyright-protected work, assuming there is no involvement of fair use or other exceptions to copyright infringement under specific circumstances. Government bodies have increased their attention, taking actions such as the proposal to amend Section 230 of the US Communications Decency Act which protects online intermediaries from laws applied to publishers holding them legally accountable for the speech they host (Electronic Frontier Foundation n.d.). Mechanisms such as fact-checking and labelling concerning UGC as potentially misleading help reduce falsities and offer mechanisms respectful of protecting users' right to freedom of expression (Bazelon 2020).

Proactive systems can use manual or automated techniques. Manual approaches include human review before deciding what action to take, which may be to remove the content, warn the user who uploaded the content or allow the content to be uploaded. Automated techniques use algorithms to flag abusive or illegal content by measuring patterns, matching them to a database of works or any other criteria determined by the platform (Llansó, 2020; Romero Moreno 2020). YouTube, for example, developed a system called Content ID, which makes it easier for rightsholders to identify content uploaded to the platform without authorization (YouTube 2021). The system requires that rightsholders share with YouTube a database with the catalogue of works that belong to them. The automated system then matches the contents found on the platform with those in the database. The Content ID guide states it is available only to rightsholders who hold "exclusive rights to a substantial body of original material that is frequently uploaded by the YouTube creator community." The video-sharing platform has other tools for reporting copyright infringement: an online claim form, a content verification program available to rightsholders to send content removal notifications for several videos at once, and a Copyright Match Tool which is available to any YouTube user who has submitted a valid copyright takedown request and can be used to identify automatically video matches.

Increasingly, platforms rely on AI for content moderation, either proactively to detect content that violates their rules or legal obligations, or to perform automated content evaluation (Llansó 2020). The automated content moderation mechanisms are less dependent on user flagging or enforcing the decision on whether a material violates the platform's content policy, or the law, by automatically removing or degrading the content.

Content moderation is used to identify potential copyright infringement, whether reactive or proactive, and does not examine the veracity of the complaint or whether copyright protections are being abused. In a state of law, it would also not be expected or desirable for a private agent to have the power to determine whether a copyright infringement is occurring. However, content moderation mechanisms are very often used arbitrarily or have the unwanted effect of suppressing freedom of expression (Cortés Castillo 2013, 6). They also ignore the very limitations and exceptions to copyright, thus weakening them.

The DMCA has been used as a tool to takedown and stifle what is considered fair use in some countries. The Ecuadorian government has reportedly invoked the DMCA takedown notice to censor online criticism (Nazer and Stoltz 2017). Content including videos, images, audio clips, text, and memes on Facebook, Twitter, and YouTube criticizing the president and the Ecuadorian government have been taken down from the sites on which they were posted through the DMCA's notice and takedown mechanisms on the grounds of copyright infringement (Vivanco 2014). While using copyright to silence political expression is an extreme step, complainants have exploited copyright to remove opinions, criticisms, poor reviews and to restrict the overall public domain of information resources available to users. Flagging and taking down UGC can serve a legitimate and important purpose especially when protecting democratic processes, the truth, and populations in vulnerable contexts; however, the practice should not jeopardize constitutional rights and freedoms established in specific countries (Heldt 2019).

If content moderation mechanisms are implemented prior to content uploading, as suggested in Article 17 of the DCM Directive, copyright enforcement is likely to become a prior censorship tool. Furthermore, it could be argued that it violates international human rights standards on freedom of expression in relation to the principle of legality; that is, that the limitation on the right is provided by law with sufficient clarity to enable individuals to regulate their conduct.

The usual ways in which content moderation mechanisms are implemented to enforce copyright leave users in the dark, not knowing or understanding why they are being notified or why the content has been removed. Users do not receive enough information to understand that their content has been flagged as copyright infringement because the uploaded material matched with a copyrighted work in a database. The lack of transparency about how content moderation mechanisms are implemented to enforce copyright and the high incentives that platforms have to respond to the powerful copyright industry leaves users defenceless, affecting their fundamental rights to express and inform themselves, to share their opinions and ideas, and even to engage in democratic life.

# **Conclusion**

UGC is a creative form of digital expression that has exploded thanks to technological developments and the expansion of the Internet. The reasons for creating and sharing UGC are endless. It is undeniable that UGC plays an important role in the cultural and political participation of societies. UGC contributes to the generation of knowledge and information, offers an opportunity to tell stories from a non-hegemonic point of view, and connects people with common interests. UGC is a powerful communication tool.

Never before have there been so many possibilities for exercising freedom of expression. Advances in digital technologies, telecommunication, and the growth of the use of mobile devices have led to diverse and creative ways of expressing oneself and sharing ideas and opinions with others. Unhappily, there are negative aspects arising from the capacity for users to generate misinformation and disinformation. Copyright regimes have become barriers, sometimes significant ones, to the dissemination of a cultural, informational, and even political asset of contemporary history.

While the flagging or removal of content because of copyright infringement is a valid mechanism, this chapter has evidenced ways in which rightsholders can appeal to copyright enforcement mechanisms to serve ill-intended purposes and to stifle public expression. Some valid mechanisms for addressing copyright infringement today may have the potential to inform future policies for dealing with unlawful behaviour and content online. However, policies and practices in relation to online content creation must be developed holistically to carefully address the needs of all stakeholders including civil society, governments, Internet intermediaries, copyright regimes, users, creators, and original authors.

Copyright and its enforcement through various content moderation mechanisms on online platforms represent a threat to the exercise of freedom of expression. "Since 1999, the UN Special Rapporteur, together with [others] …, has issued annually a Joint Declaration on Freedom of Expression, reaffirming its central role for human rights and fundamental freedoms" (UN Human Rights n.d.). The Joint Declarations by the Special Rapporteurs for Freedom of Expression of the international and regional human rights systems have since 2011 consistently expressed the view that content moderation mechanisms applied to online platforms represent a significant threat to the enjoyment of freedom of expression on the Internet.

To meet the challenges posed by technological developments to copyright protection, it is essential to balance the legitimate interests of authors and rightsholders with the general interests of individuals and the community in enjoying their rights to freedom of expression. Governments must not forget their obligations under international human rights law and should refrain from promoting disproportionate measures that are responsive to the lobbying of powerful economic forces in the copyright industry. The socio-economic development of a country, often the argument for creating more protectionist copyright regimes, depends on many factors external to the creative industry, including the existence of conditions for the enjoyment of freedom of expression, for collective intelligence and collaboration to find space to flourish.

Online platform owners must also recognise the threat to freedom of expression inherent in content moderation mechanisms and mitigate it. Certainly, the platforms must be more transparent and accountable about the technical mechanisms they develop to meet their legal obligations, how they implement them, and the impact they have on users' rights to freedom of expression. It is increasingly critical that future copyright regimes be developed which respect human

rights. Authors and rightsholders have legitimate interests in protecting their works and investment, but these interests should never outweigh societal significance in protecting human rights.

# **References**

"Syrian Archive." n.d. https://syrianarchive.org/.

# H. Andrés Izquierdo **20 Artificial Intelligence and Text and Data Mining: Future Rules for Libraries?**

**Abstract**: Artificial Intelligence (AI) is not a general method but an umbrella that includes many digital tools that are changing the library environment. Chatbots, document classification, personalized services, text and data mining (TDM), intelligent education, and user discovery are some of the AI tools that offer new and broad possibilities for research, access, and use of vast amounts of data. But there is growing attention and discussion on how global and domestic copyright law should allow or impede access to the use of data. This chapter examines current AI trends for libraries, focuses on TDM, and presents relevant regional and domestic copyright legislative developments on the subject. The analysis indicates that norms passed to regulate TDM vary in content and objectives from country to country, yielding an ill-suited environment for libraries to work as a channel for international research based on AI tools. It concludes with a dialog centered on the evolving relationship between knowledge, AI, TDM, and the creation of new limitations and exceptions (L&Es) for copyright law. This chapter informs the reader of impacts of recent AI, TDM, and copyright developments on libraries and highlights policy developments that could bring a more uniform international legislative body of law in which libraries could operate and support researchers.

**Keywords:** Artificial intelligence; Text data mining; Copyright and electronic data processing; Fair use (Copyright); Electronic information resources – Fair use

# **Introduction**

Artificial intelligence (AI) and machine learning (ML) have shown significant practical progress in recent years. AI and ML algorithms are creating a much-automated society, modifying many aspects of life. A recent survey of more than 2,200 leaders, managers, and contributors across a wide range of industries and geographies reveals how the drive to implement AI is reshaping organizational culture and processes and creating new mandates for Chief Information Officers and other technology leaders. Most organizations are still in the early stages of the process to implement AI or to experience benefits at scale. Just 5% are implementing AI widely across the organization; 18% have implemented it in a few processes; 19% are running pilot projects; 13% are planning AI adoption, while

27% are still investigating it. But even if changes are not being currently implemented, the same survey showed that more than 63% of respondents expect AI to drive dramatic or significant organizational change (MIT SMR Connections 2020).

Some of the leading examples of private-sector growth today, like Amazon or Facebook, depend on the use of ML to optimize production methods, supply chains, marketing, and pricing. AI applications are growing across various sectors: transportation, health care, agriculture, finance, law, cybersecurity with autonomous detection and decision making to enhance reaction times to threats, and defense with autonomous and semi-autonomous weapons systems (Harris 2017; Metz 2015).

Libraries are not foreign to technological changes, as there are many tools to be implemented in the service of patrons, research, and education. An ExLibris Whitepaper reported that some critical transformational forces in libraries, such as AI, TDM, and ML, are not widely understood (ExLibris n.d.). Chatbots, document classification, personalized services, TDM, intelligent education, and user discovery are just some of the AI developments in libraries (Wheatley and Hervieux 2019; Cervone 2011; Pinfield, Cox and Rutter 2017).

TDM serves as a useful tool to navigate the insurmountable amount of data and information currently available while bringing new insights and understanding in many fields of knowledge. For example, TDM can be used in linguistics to analyze large bodies of text to extract syntactic or grammatical patterns; in medicine, TDM can find associations between a gene and a disease, or between a drug and an adverse event; in general, TDM is turning into the standard practice in pharmaceutical research, journalism, information retrieval, and consumer information.

Libraries often play a role in supporting TDM research because they:

But there is an interesting problem as current regulations, or the lack thereof, affect how libraries can support TDM research through these three mechanisms. More often than not, there is no specific answer on how to address issues arising under contract law, laws prohibiting the circumvention of technological protection measures (TPMs), or cross-border copyright issues. What happens when a TDM research project is developed with catalogs of libraries in different countries? Can researchers develop TDM projects lacking legal access to the data or the information? Is it possible to engage in international projects and share the results? Can librarians negotiate to eliminate or reduce contractual restrictions on researchers' rights to engage in TDM? As technology advances, more questions continue to grow on how to balance copyright laws with user access and innovation.

As a partial response to these questions, some developed nations have passed laws to regulate TDM practice. Still, the results show laws that are not compatible between those same countries. The TDM articles recently passed within the Directive (EU) 2019/790 of the European Parliament and of the Council of 17 April 2019 on Copyright and Related Rights in the Digital Single Market and Amending Directives 96/9/EC and 2001/29/EC (Text with EEA Relevance) [hereinafter DSM Directive] (IFLA 2021; Directive (EU) 2019/790 2019) will be incompatible in many parts with the 2018 Japanese TDM copyright reform (Japan 2020) or the recent *Google*1 or *HathiTrust*2 rulings of the United States Court of Appeals for the Second Circuit which are discussed later in this chapter. The diverse regulatory practices create an unstable, fragmented, and complex international environment for libraries and users of information protected by copyright laws. Most developing countries that have not initiated updates to their copyright laws provide librarians with limited chances to make available copyrighted works for TDM projects.

A recent study by the Program on Information Justice and Intellectual Property at the College of Law at the American University Washington explains that there is relatively widespread authorization in research, private reproduction, and in general exceptions for making reproductions of whole works needed to build non-public TDM research databases (Flynn et al 2020). If librarians or researchers decide on using flexible and open interpretations of the existing limitations and exceptions (L&Es) such as the right to research, digital reprography, or private or personal use, not having explicit rules on the matter could bring high levels of uncertainty given the rapidity of AI technological developments to explore and exploit information. Moreover, countries with a restrictive interpretation of L&Es, for example Argentina (Argentina 2011) will undoubtedly forbid librarians to allow any TDM on their printed or digital copies of the available works, except with an appropriate license. AI and TDM discussions are intensifying worldwide in diverse forums, including the Organization for Economic Co-operation and Development (OECD) and World Intellectual Property Organization (WIPO), but no consensus model has emerged (WIPO n.d.).

The existing literature is incomplete on how libraries will be affected by the current TDM legislative changes. There have been studies on how the TDM laws are being framed in the United Kingdom (UK), European Union (EU), and

**1** Authors Guild, Inc. v. Google, Inc., 804 F.3d 202 (2d Cir. 2015.

**2** Authors Guild, Inc. v. HathiTrust, 755 F.3d 87 (2d Cir. 2014).

Japan, as well as studies on the previously mentioned TDM *Google* and *Hathi-Trust* cases in the US. Google was allowed to undertake unauthorized digitizing of copyright-protected works, create search functionality, and display snippets from works. The HathiTrust case allowed libraries in the HathiTrust projectto digitize copyrighted works for the purpose of permitting full-text searches, allowing member libraries to provide patrons with certified print disabilities access to the full text works, and for the libraries to preserve the copyrighted books in digital form.

TDM studies in Europe include Geiger, Forsio and Bulayenko (2018) and Hugenholtz (2019), explaining how the new TDM articles of the DSM Directive put AI developers, journalists, commercial research labs, and other innovators at a competitive disadvantage in comparison with the United States, and other studies highlight concerns (Quintais 2020; Stephenson 2020; Hilty, Harhoff and Drexl 2016; Margoni and Dore 2016; and Caspers and Guibault 2016). Analysis of developments in the US can be found, for example, in Sag (2009), arguing that acts of copying that do not communicate the author's original expression to the public do not generally constitute copyright infringement; Carroll (2019), asserting that text and data mining is legal in the United States because fair use permits copying and archiving data to enable and validate TDM research; and Sag (2019) explaining why applying copyright's fundamental principles in the context of new technologies implies that copying expressive works for non-expressive purposes should not be counted as infringement. Worldwide research is available at, for example, Flynn et al (2020), stressing the need for international leadership on the diverse mechanisms that countries may use to authorize TDM research and the adoption of rules permitting cross-border TDM projects. Okediji (2019) and Litman (1994) provide general information on L&Es. Flynn and Palmedo provide a description of "openness" of copyright exceptions (2017).

But not much has been developed reviewing the current impact of AI changes on libraries compared to the current copyright legislative modifications. This chapter reviews how TDM practices and legislation, or the lack thereof, affect access to information by patrons at libraries.

This chapter adopts an interdisciplinary perspective. The first part addresses the concepts of AI, ML, and TDM based on the most recent government, scientific and technological research, while considering the social impacts of the technologies for libraries. The second part of the chapter reviews and analyzes the legal aspects by reference to regional and national contexts. Questions are raised on the capacity of the current L&Es in regional or domestic laws to advance access to data from the various perspectives of librarians, researchers, and users. The third part provides recommendations to facilitate dialog between copyright, AI and TDM, and suggests possible solutions for future policy changes in law, research, and technology.

# **Artificial Intelligence and Text and Data Mining**

In examining how libraries are involved in AI, AI must be explained, along with TDM, and the changes to access in the knowledge environment. This section anchors key concepts to build towards how libraries are involved in the technological changes by exploring the nature of AI and TDM, its history, and various international perspectives on its growth and development.

Nobody would have imagined that the 1950s question posed by Alan Turing, "Can machines think?"would be the current trend in technological development today (Turing 1950). This British mathematician is known to be one of the many who opened the way to decades of work on a machine's ability to show intelligent behavior. Following slow early development, more recently, AI and ML have shown significant practical progress. The unique confluence of vast amounts of data, including the internet, algorithms, and modern computing, is opening a new chapter for AI and ML development. There is an increased ability to train existing algorithms with vast quantities of data samples and with the use of modern computing, particularly Graphics Processing Units (GPUs) and storage capacity. AI has emerged in the past decade faster than in the first 70 years of artificial intelligence development (Shi 2011; Martinez et al 2019).

### **Brief History of Artificial Intelligence**

Artificial intelligence (AI) is not a recent technology; the algorithms used today have been in existence for several decades (Stone et al 2016). Emerging from Turing's work (Turing 1950) came the Turing test where a machine and a human are compared to determine if a machine is indistinguishable from a human. Late in 1956, the field of AI was born with a workshop organized at the Dartmouth Summer Research Project on Artificial Intelligence (McCarthy et al 1955). John McCarthy, jointly with Nathaniel Rochester, Marvin Minsky, and Claude Shannon, organized a two-month ten-man study of AI. The objective was to proceed on the basis that every aspect of learning or any other feature of intelligence could in principle be so precisely described that a machine could be created to simulate it; the workshop also intended to find how to make machines use language, form abstractions and concepts, and "solve kinds of problems now reserved for humans, and

improve themselves" (McCarthy et al 1955, 2). The researchers defined AI as the problem of making a machine behave in ways that would be called intelligent if a human were so acting.

The two-month Dartmouth project fell short, but history shows a continued advancement in AI decade after decade. In the 1950s, AI research focused on game playing; in the 1960s on search algorithms and general problem solving (Minsky 1961; Shi 2011); and in the 1970s AI explored natural language understanding and knowledge representation (Feigenbaum 1984; Shi 2011, 4). The 1980s came with a slowdown in AI development called the "AI Winters" and a slowing down of research funding (Martinez et al 2019, 15–16). But in the 1990s and early 2000s, AI resurged with some successes.

To name a few, in 1997 there was a fundamental shift in AI capabilities when IBM's chess-playing expert system Deep Blue defeated reigning chess champion Gary Kasparov (Kasparov 2017); in 2005 Google's English translation tool for Chinese and Arabic texts topped an international exercise to find the best Chinese and Arabic translation technology (Kanellos 2005); in 2011 IBM Watson defeated Jeopardy former champions Brad Rutter and Ken Jennings (Markoff 2011); and in 2016 Google's DeepMind made an AI system to defeat Lee Sedol at the ancient board game Go (Cao 2019).

The AI accomplishments were made possible by a mix of integrated advances in AI algorithms, the availability of vast amounts of data samples, and high-performance computers. Estimates indicate that 90% of all data have been created in the past two years (Statspotting 2012). The increased ability to train existing algorithms using the data available combined with greater processing capacity and improved storage capacity has allowed AI in the past decade to achieve more than was possible during the first 50 years of development.

The mix of elements has brought dramatic AI advances in neural network or deep learning methods:

In describing the course of AI development, the Defense Advanced Research Projects Agency (DARPA) has identified three "waves." The first wave focused on handcrafted knowledge that allowed for system-enabled reasoning in limited situations, though lacking the ability to learn or address uncertainty, as with many rule-based systems from the 1980s. The second wave, from approximately the 2000s to the present, has focused on advances in neural networks and machine learning (e.g., image recognition, language translation) using statistical models and big data sets. The third wave will focus on contextual adaptation—learning and reasoning as the system encounters new tasks—moving towards general AI (Harris 2017).

As a response to the advances in AI, several countries and regions around the world have already released reports on how to prepare for the upcoming challenges. On this race for being first in the technology, governments have released their forthcoming strategies; the White House Office of Science and Technology Policy (OSTP) with its National Artificial Intelligence Research Resource Task Force is preparing a response; the European Parliament's Committee on Legal Affairs has adopted three reports on artificial intelligence (Geneva Internet Platform 2020); the House of Commons' Science and Technology Committee in the UK commissioned a report on artificial intelligence (UK Parliament 2016); the Chinese State Council has produced a plan (China. State Council 2017; Webster et al 2017), and the Center for Security and Emerging Technology of the Russian Federation has developed a strategy (Konaev 2019). Expert committees have also produced reports and policy documents with the High-Level Expert Group on AI appointed by the European Commission, the expert group on AI (AIGO) of the Organization for Economic Co-operation and Development (OECD), and the Select Committee on AI of the UK House of Lords (UK. Parliament. House of Lords 2017). The private sector and the universities are also doing their share of research and development, with numerous studies and research documents published on the subject.

### **What is Artificial Intelligence?**

A definition of AI is of utmost importance, especially when the subject is pending for legislation around the world. Ultimately a definition matters from a copyright perspective to provide the scope of the law. But this task poses a challenge as the technology is always in flux. Governments have given diverse definitions but overall, there is no commonly accepted definition of AI, in part because of the many diverse approaches to research in the field. This lack of agreement on a single definition will possibly bring issues in future legislative processes at the international, regional, and domestic level, but the lack of a precise, universally accepted definition of AI has also helped the field to grow and advance at an ever-accelerating pace.

For the US government there is no commonly accepted definition of AI although Section 238 (3) (f) and (g) of the FY2019 *National Defense Authorization Act* (NDAA) directs the Secretary of Defense to produce a definition of artificial intelligence and includes the following:

The closest approach to a definition is found in the White House 2019 National AI R&D Strategic Plan report by which AI "enables computers and other automated systems to perform tasks that have historically required human cognition and what we typically consider human decision-making abilities" (US National Science and Technology Council 2019, 1). The US strictly relates the future development of AI to the increase of computing power, the availability of large datasets and streaming data, and algorithmic advances in machine learning. In a recent presentation, an official of the Department of Defense called AI "the new oil, and the governments or the countries that get the best datasets will unquestionably develop the best AI" (Cronk 2020).

The UK agrees there is no single definition of AI but notes in a Select Committee report, citing others, that there is a tendency to describe "AI by contrasting it with human intelligence and stressing that AI does not appear 'in nature.' At present, the capacity of 'AI machines' is narrow and specific; they can complete what Margaret Boden, Professor of Cognitive Science at the University of Sussex, has described as 'specialised tricks'". The report concludes AI is "a set of statistical tools and algorithms that combine to form, in part, intelligent software that specializes in a single area or task. This type of software is an evolving assemblage of technologies that enable computers to simulate elements of human behavior such as learning, reasoning and classification" (UK Parliament. House of Commons. Select Committee on Artificial Intelligence 2019, Paragraph 4).

But a European report goes further, citing others as stating "The broadest definition of artificial intelligence (AI) characterises it as the attempt to build machines that 'perform functions that require intelligence when performed by people'" (Sartor and Lagioia 2020, 2). The High-Level Expert Group on AI (AI HLEG) of the European Union provides a definition:

Artificial intelligence (AI) systems are software (and possibly also hardware) systems designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data, reasoning on the knowledge, or processing the information, derived from this data and deciding the best action(s) to take to achieve the given goal. AI systems can either use symbolic rules or learn a numeric model, and they can also adapt their behaviour by analysing how the environment is affected by their previous actions. As a scientific discipline, AI includes several approaches and techniques, such as machine learning (of which deep learning and reinforcement learning are specific examples), machine reasoning (which includes planning, scheduling, knowledge representation and reasoning, search, and optimization), and robotics (which includes control, perception, sensors, and actuators, as well as the integration of all other techniques into cyber-physical systems. (European Commission. Independent High-Level Expert Group on Artificial Intelligence 2019, 6)

China gives the broadest definition of all countries:

The development of AI has entered a new stage. After sixty years of evolution, especially in mobile Internet, big data, supercomputing, sensor networks, brain science, and other new theories and new technologies, under the joint impetus of powerful demands of economic and social development, AI's development has accelerated, displaying deep learning, cross-domain integration, man-machine collaboration, the opening of swarm intelligence, autonomous control, and other new characteristics (China State Council 2017; Webster et al 2017, 2).

Some of the definitions are linked to a military approach with significant implications for national security. The US Department of Defense (DOD) and other nations are developing AI applications for a range of military functions. So far, applications of AI are found "in the fields of intelligence collection and analysis, logistics, cyber operations, information operations, command and control, and in a variety of semiautonomous and autonomous vehicles" (US Congressional Research Service 2020).

Yet many AI systems perform only a fraction of the activities listed in any definition. Activities such as pattern recognition, language processing and practical suggestions, are activities done independently by every system. But there are other more sophisticated systems that may combine diverse capacities, as in the example of self-driving vehicles.

### **Machine Learning and Artificial Intelligence**

Machine Learning (ML) is the name for a comprehensive family of techniques used for new forms of AI data analysis becoming essential tools for prediction and decision-making (Lehr and Ohm 2017). There is an increased ability to train existing algorithms with vast quantities of data samples.

As already noted, AI has applications across many sectors ranging from agriculture and cybersecurity, through defense and health care to transportation. Many commodities and services, including email spam filters, medical diagnoses, product marketing, and self-driving cars, are now dependent on ML algorithms (Coglianese and Lehr 2017). ML has entered the realm of national security and defense and is one of the main reasons governments are looking for advancement on AI. The latest cyber operations use ML to enhance mission-critical tools and capabilities, with the newest learning models detecting distributional traffic shifts, anomalous network behavior patterns, and creative attacks as they originate (Guerra and Tamburello 2018). More precisely, ML can help identify malware, network anomalies, intrusion detection, rank aggregation of information, deep packet inspection, and detect cyber threats ranging from hacking into government or military networks to cyber-attacks on corporations and personal accounts. Most notable examples include: the Titan Rain incident in 2003, when US Department of Defense facilities, NASA laboratories, Lockheed Martin and other systems were hacked into and lost many terabytes of information; the cyber incidents directed against Estonia and Georgia, leading to severe disruption of media, government and banking systems; the US fight against the Islamic State of Iraq and Syria (ISIS); or the 2014 cyber-attack on Sony Pictures Entertainment by the group Guardians of Peace who stole data and disabled computer systems.

Three main approaches to ML are commonly found: supervised learning, reinforcement learning and unsupervised learning. In supervised learning the machine learns through supervision or teaching. More precisely the machine is given a training set that will allow it to find the correct answer. Under this system, the data scientist acts as a guide to teach the algorithm the right responses (Mokhtarian 2018). "Supervised learning requires that the algorithm's possible outputs are already known and that the data used to train the algorithm is already labeled with correct answers" (Castle 2017). This type of learning is found in systems designed to recognize objects, for example, face recognition, systems for automated translation, clinical decision support systems based on symptoms and diagnoses, systems for assessing loan applications, insurance and customer recommendation systems, and online purchases.

By way of an example, a binary algorithm was able to classify 1600 US judicial opinions on successor liability (Fagan 2015). Binary classification algorithms can learn to identify between two choices after being trained on a dataset of images or words that are properly labeled with the options and some identifying characteristics. In this case, the algorithm was able to examine the words of each opinion and determine the probability of it belonging to the relevant class with relevant meaning that the court applied any type of successor liability legal standard to the facts. Another example can be seen with the algorithm Correctional Offender Management Profiling for Alternative Sanctions (COMPAS), a risk assessment software used to forecast which criminals are most likely to reoffend. The Department of Corrections of Wisconsin State

uses the Correctional Offender Management Profiling for Alternative Sanctions tool, commonly known as COMPAS, for criminogenic risk and needs assessments and unified case planning. This actuarial risk assessment contains offender information specifically designed to determine their risk and needs and inform dynamic case plans that will guide the offender throughout his or her lifecycle in the criminal justice system (Wisconsin. Department of Corrections n.d.).

Fairness in algorithms has been questioned with abundant literature questioning possible bias emanating from the use of automated decision-making systems (for example, Spielkamp 2017).

Reinforcement learning is close to supervised learning, as both systems require training through examples. But "reinforcement learning is a framework that shifts the focus of ML from pattern recognition to experience-driven sequential decision-making" (Stone et al 2016, 9). The ML approach typically involves creating training methodologies that enable a system to explore independently, perform multiple trials at tasks, and learn from the experiences. As explained in a 2016 US Senate hearing on the dawn of artificial intelligence in relation to "Learning physical actions in the open world: Research efforts have been underway on the challenges of enabling systems to do active exploration in simulated and real worlds that are aimed at endowing the systems with the ability to make predictions and to perform physical actions successfully" (US Congress. Senate. Committee on Commerce, Science and Transportation. Subcommittee on Space, Science, and Competitiveness 2016, 13). The machine learns through rewards or penalties that are linked to the outcomes of such actions. Examples include systems that learn to play games by rewards linked to victories and penalties to defeats; or investment systems where rewards are linked to financial gains and penalties to losses. When the system is working at its full potential, AI applications can take independent actions in the real world.

A third relevant ML system is unsupervised learning. Contrary to supervised or reinforcement learning, unsupervised learning works without receiving external instructions, learning without human-authored labels. Under this system, the machine works through clustering and dimensionality reduction while seeking to identify structure among unlabeled data (Hinton and Sejnowski 1999; Le 2012). Common examples of unsupervised learning algorithms are found in research of audience segmentation, customer investigation, pattern recognition, and anomaly detection or cyber-operations. Unsupervised learning is often characterized as supervised learning with an unknown output, as it is difficult in many circumstances to generate objective criteria to classify the results as either failed or successful (Hinton and Sejnowski 1999). The fact that a machine can independently identify and resolve processing problems makes this learning method closest to answering Turing's original question "Can machines think?" (1950) posed earlier in this chapter, although it has not yet arrived.

# **Library Applications of Artificial Intelligence**

There are many ways in which libraries are getting involved with AI tools. TDM, document classification, chatbots, and user discovery, are some of the current AI tools being implemented (Asemi, Ko, and Nowkarizi 2021). Furthermore, some AI tools are becoming essential tools. This section examines the role of libraries in relation to aspects of AI. There has been some hesitancy in adopting the technology on an everyday basis (Wheatley and Hervieux 2019; Cervone 2011). Concerns raised about AI in libraries in the previously mentioned ExLibris whitepaper on AI included: "... human creativity and empathy would no longer be necessary due to the efficiency of AI …and valuable human characteristics are devalued and rare … AI would magnify injustices such as inequality, bias, and discrimination, and help propagate misinformation ...AI might jeopardize data privacy" (ExLibris n.d., 13).

A 2017 report by the UK's Society of College, National and University Libraries (SCONUL) found that some key transformational forces, such as AI, TDM, and ML, were not widely understood: from the survey only 4% considered AI skills for libraries were critically important; 28% deemed them important; 32% not important and 35% did not know, yet intellectual property skills were viewed as critically important by 25% and important by 60% (Pinfield, Cox, and Rutter 2017, 43 Figure 7). The same survey found in terms of key trends and their impact in the future that 10% of libraries thought AI and ML would have a transformational impact, 21% significant, 32% small, 5% none, and 32% did not know (Pinfield, Cox, and Rutter 2017, 15).

# **Chatbots**

Chatbots, also known as digital assistants or intelligent agents, are computer programs that can simulate an intelligent conversation through text or speech, and use speech or character recognition tools to provide information to users with examples such as Siri or Google Assistant. Chatbots with embodied representation are being used by libraries (Talley 2016). The University of Oklahoma incorporated a chatbot Bizzy to answer frequent questions from students, such as library schedules, or places to print (University of Oklahoma. University Libraries 2019). The chatbot also helps students with basic research, but more complex questions are addressed directly by the library staff. The Helsinki Central Library Oodi uses an app from the Finland-based technology company Headai, to create Obotti to help discover new books either by voice search, proximity and location of the books, or popular uses (Pun 2019).

Georgia Tech's Jill Watson, University of Murcia's Lola and Staffordshire University's Beacon are chatbots to answers students' most frequently asked questions (Young 2019; Staffordshire University 2019). Studies support the creation and use of chatbots as a big percentage of the questions asked face-to-face to librarians do not require librarian expertise (Talley 2016). In one study, two-thirds of the total questions asked of librarians by students related to library locations and their attributes, all of which staff with minimal training might easily answer; only 16% of transactions concerning subject-based questions required professional help (Bishop and Bartlett 2013).

### **Classification of Library Documents**

Classification of library documents comes as another significant challenge. The increasing amounts of information produced each year require new methods to facilitate effective searching, retrieval, and organization. Although many current approaches to classification can rapidly identify the overall topic of a document, there is a need for systems that can efficiently organize documents into the correct subfields or areas of specialization (Kowsari et al 2017). Among diverse classification proposals, some research has examined techniques based on semantic document classification, contrary to the traditional keyword classification approach. For example, a recent research paper proposed that by using the "Wikipedia knowledge to analyze the semantic information behind document keywords, Wikipedia matching can overcome the semantic mismatch problem encountered in keyword matching" and improve the accuracy of document similarity computation and in turn the accuracy of document classification (Wu et al 2017).

New approaches have examined new ML and deep learning techniques for document classification as part of a subset of ML tools that deploy multilayered processes, account for billions of data points, and continuously adjust their classification rules. Some propose a mix of diverse approaches for document classification (Zenun, Imran, and Yayilgan 2019). Flannery from the University of Notre Dame was able to automatically generate summaries for a special library collection of more "than five thousand Catholic Pamphlets by implementing summarization techniques through Natural Language Processing (NLP)" (Wang 2020, 2).

### **Intelligent Education**

Another potential AI development for libraries is intelligent education which offers AI personalized learning, automated counseling, assessment, platforms for game-based teaching, and even education decision making. The American Federation of Teachers and the IBM Foundation have collaborated to build Teacher Advisor with Watson. The program uses artificial intelligence technology to answer inquiries from educators and help them develop personalized lesson plans (Harris 2016). "IBM and MIT have signed a 10-year, \$240 million partnership agreement that establishes the MIT-IBM Watson AI Lab where IBM researchers and MIT students and faculty will work side by side to conduct advanced AI research" (MIT News Office 2017) to transform higher education and research centers. The American Library Association (ALA) has highlighted the importance of AI for libraries in the future (ALA 2019). Personalized learning promises that every student will experience an educational approach that is tailored to his or her individual abilities and needs, increasing students' motivation and reducing their likelihood of dropping out. But for AI-based learning systems to work correctly, big data on every student would be needed to train the system, and this could bring ethical issues; students might disagree on how their data might be shared and used by AI algorithms (Wachter and Mittelstadt 2019).

# **Information Discovery by Users**

Another AI application in libraries that will grow exponentially is user discovery with its potential to help patrons with more accurate search results (Li, et al 2019). Traditionally, research and discovery methods use MARC formats as standards for representing and communicating bibliographic and related information in machine-readable form. But new methods are being developed by which "AI-based discovery services such as Yewno reach into the digital text to promote discovery via concepts generated from the full texts themselves" (Pun 2019). SCONUL also believes AI and ML are likely to be at the heart of "'datafied' scholarship – research increasingly underpinned by large datasets and digital artefacts, involving open, networked, algorithmically-driven systems" operating in a networked research environment with the potential to replace traditional methods of dissemination and discovery (Pinfield, Cox, and Rutter 2017, 4).

# **Text and Data Mining**

In addition to the impact on search and discovery, TDM is becoming a growing practice and has already been outlined with its capacity for interpretation of large bodies of raw and processed data through the identification of patterns. Article 2 (2) of the DSM Directive defines TDM as "any automated analytical technique aimed at analysing text and data in digital form in order to generate information which includes but is not limited to patterns, trends and correlations" (Directive 2019/790 2019). As the scale of published information increases, TDM uses algorithms to analyze large bodies of content in search of patterns and information in much reduced periods of time compared to a human reader, while bringing new insights and understanding in many fields of knowledge (Sag 2019). Without connections being explicitly identified or mentioned in papers, for example, TDM can be used in linguistics to analyze large bodies of text to extract syntactic or grammatical patterns (Hugenholtz 2019); in medicine, TDM could find associations between a gene and a disease, or between a drug and an adverse event (Borghi n.d.); and in general, TDM is nowadays standard practice in pharmaceutical research, journalism, information retrieval, and consumer information (Eskevich and Van den Bosch 2016). In the next section, the legal approach taken by different countries is examined as TDM norms are becoming uneven, fragmented, and complex for libraries, researchers, and users of information (Caspers et al 2017).

# **The Copyright Landscape Affecting TDM Research**

TDM can unlock new research capabilities in scientific and scholarly literature but to perform effectively, TDM needs full access to data from text materials and databases. There are currently two primary possibilities for lawful data access: one option is to obtain open access materials that are freely available for download and reuse; a second option is to use materials limited by copyright restrictions and typically subject to specific permission rules for access and manipulation. A third possibility is to use public domain texts in which copyright has expired or was never attached. Under the first option, contents are commonly made available for download under a Creative Commons or similar license that allows a more open redistribution and reuse than a traditional copyrighted work. Open access publications are on the rise with databases such as PubMed Central containing more than seven million full-text articles for text mining and other types of reuse. The second option is to access content from publishers' subscription-based journals, which restricts access to their publications under the applicable copyright legislation or negotiated purchasing contracts. Some cross-publisher collaborations provide access to subscription-based content but do not seem to provide researchers with comprehensive access to the published literature to conduct TDM research (Carroll 2019).

When copyright is the limitation for access to content, every country has a distinct set of rules to allow, limit, or possibly forbid TDM activities. Some countries have developed specific rules for TDM use such as Japan with Article 47 (Japan 2020), United Kingdom (UK Copyright Act 2020) with Section 29A, and Germany with § 60d on TDM (Germany. Urheberrechtsgesetz, UrhG/Act on Copyright and Related Rights 2017). The EU DSM Directive explicitly includes an exception for TDM research activities (Directive (EU) 2019/790 2019) whereas other countries like the US have allowed TDM specific activities through the existing fair use doctrine. Countries that have not addressed TDM through legislation or court rulings, may allow TDM research through copyright exceptions and limitations such as the right to research, reprography, private or personal use, digital storage, or low TPMs. There are other examples of countries where domestic copyright legislation has a restrictive interpretation blocking any possibility for TDM research (Flynn et al 2020).

Comprehensive legislation on TDM is an essential tool for libraries so they can assist their patrons and users to legally access materials and databases within their collections, make reproductions, store the information, and share the results without any copyright violations (IFLA 2020). Countries have diverse regulations on how TDM is allowed to be performed.

# **TDM Legislation**

Regulations on TDM usually come as an exception within the current copyright regime, allowing users to mine copyright works to which they have lawful access. Such an exception enables researchers and other legitimate users to undertake data mining on substantial amounts of data, as TDM is a new vital tool for research and academic libraries. Support for TDM commonly includes access to legally accessed materials, not only on-site but remotely, and with the right to retain copies for storage and further study (IFLA 2020). Few countries have passed legislation to allow TDM activities, as many others are still updating their laws. In the following sections, the recently passed copyright exception and limitation provisions from the European Union (EU), United Kingdom (UK), Germany, and Japan are discussed.

### **European Union**

The EU is modernizing its copyright rules in response to new consumer behaviors with the adoption of various directives regarding the new digital environment (European Commission 2021). In 2017, for example, a regulation was passed on cross-border portability of online content services to allow consumers who buy or subscribe to films, sports broadcasts, music, ebooks, and games, to access the content as they travel within EU countries (European Commission 2018). Likewise, in 2017 a Directive and a Regulation implemented the Marrakesh Treaty in the EU to allow content access for the blind, visually impaired, or otherwise print disabled people [hereinafter the Marrakesh Directive] (Directive (EU) 2017/1564 2017; Regulation 2017/1563) and in 2019, the DSM Directive adopted new copyright L&Es focusing on the online availability of content across the EU, including exceptions in Articles 3 and 4 on TDM (Directive (EU) 2019/790; Geiger, Frosio and Bulalyenko 2018).

Articles 3 and 4 of the DSM Directive aim to provide a harmonized environment for researchers across Europe. First, the Directive creates mandatory L&Es for researchers carrying out TDM projects, which guarantees a more uniform implementation across Europe. Second, the L&Es cover both commercial and non-commercial uses making research available for legally accessed materials. And third, contractual provisions created by rightsholders cannot override the non-commercial usages while protecting TDM research from the contractual enclosure (Geiger, Frosio and Bulayenko 2018); but the two exceptions are not equally robust as the commercial use of Article 4 can be restricted by private agreements (Eskevich and Van den Bosch 2016), as outlined below.

#### **DSM Directive Article 3**

Article 3 creates a mandatory copyright exception for non-commercial scientific research performed with TDM. Any contractual provisions contrary to the TDM exception shall be unenforceable, and the TDM project can only be advanced by research organizations or cultural heritage institutions. The exception includes reproductions, extractions, and storage of works; but the user requires lawful access. To fully comprehend the scope of Article 3, it is necessary to review the beneficiaries of the exception, research organizations, and cultural heritage institutions; the conditions of use such as lawful access and TPMs; as well as the limitations that the DSM Directive TDM provision will encounter compared to other domestic legislation.

#### **Beneficiaries of the Exception**

Under the DSM Directive, the first group of beneficiaries of the exception, research organizations, is outlined in Recital 12 and includes a wide variety of entities whose primary goal is to conduct scientific research and/or educational services. It encompasses universities and their libraries, research institutes, or any other entity, such as hospitals, that carry out research. The Directive limits the research organization by requiring it to operate under a not-for-profit basis, reinvest all profits into its scientific research, or work under a public interest mission recognized by a European Member State. Recital 11 allows research organizations to benefit from the exception when their research activities are carried out in the framework of public-private partnerships, but organizations for which commercial enterprises have a decisive influence on the research project, such as shareholders or members that could obtain preferential access to the research results, are not considered research organizations for the DSM Directive. "Public broadcasting organizations and commercial research institutes, for example, are therefore excluded from the scope of Art. 3, but might still find solace in Art. 4" (Hugenholtz 2019).

The second group of beneficiaries of the TDM exceptions in Recital 13 and Article 2(3) is cultural heritage institutions. The DSM Directive defines them as any "publicly accessible library or museum, an archive or a film or audio heritage institution." The definition includes libraries and museums, notwithstanding the type of works they hold in their permanent collections and archives. It includes national libraries and archives, as well as any in educational establishments, research organizations, or public sector broadcasting organizations. Since the definition is so ample, some cultural heritage institutions could be included as research organizations. However, the exception does not apply to the general public and there is no overarching right to TDM for members of the public to engage in non-commercial research purposes. Unaffiliated individuals or researchers are clearly excluded from the DSM Directive, as contrasted with the UK situation which includes unaffiliated researchers within its TDM exception in § 29A (UK Copyright, Designs and Patents Act 1988 2020).

#### **Lawful Access**

Regarding the usage conditions, lawful access is a big player in the TDM process. Lawful access in Recital 14 of the DSM Directive covers content available under an open access policy, or through contractual arrangements between rightsholders and the beneficiaries of the exception, research organizations or cultural heritage institutions.

Open access content refers "to scientific information that is free of charge to the user and that is reusable" (European Commission 2020). Programs and expert groups on open data include OpenAIRE and the European Open Science Cloud (EOSC). An example of institutional policies for open access in the US is provided by the University of California: "Each Faculty member grants to the University of California a nonexclusive, irrevocable, worldwide license to exercise any and all rights under copyright relating to each of his or her scholarly articles, in any medium, and to authorize others to do the same, for the purpose of making their articles widely and freely available in an open access repository" (University of California Academic Senate 2020).

Contractual arrangements for content cover subscriptions and content that is freely available online. Recital 14 states: "[I]n the case of subscriptions taken by research organisations or cultural heritage institutions, the persons attached thereto and covered by those subscriptions should be deemed to have lawful access". Thus, the lawful access condition is divided between free and paid services. When lawful access for users is linked to institutional subscription services payments, the organization's budget capacity comes to play an essential role. "Only a few research organisations will be able to acquire licenses for all databases that are relevant for a TDM research project" (Geiger, Frosio, and Bulayenko 2020, 29) which in turn will limit the development of TDM for a relevant number of research organizations. If each institution's funding capacity determines the research results in TDM, lawful access conditions will grow the differences between institutions and might increase the scientific and innovation gap between developed and less developed European nations.

The limitations to lawful access for content attached to a paid subscription have been highlighted by examples of restrictions imposed on copyrighted content during the COVID 19 pandemic. Craig and Tarantino noted:

Unfortunately, however, at the institutional level, there typically remains a great deal of uncertainty around what constitutes lawful fair dealing practices, and a reluctance to rely on the user rights of students and educators in the face of threats of litigation and liability. With increasing uncertainty around this question in Canada, we can expect to see educational institutions continue their cautious approach to educational copying, entering costly and restrictive commercial licenses, purchasing expensive paper and digital copies, and imposing onerous limits and responsibilities on instructors tasked with continuing to satisfy learning objectives under ongoing quarantine conditions. Here, as elsewhere, the COVID-19 crisis has only revealed and exacerbated long-standing problems in our copyright system and its operationalization (Craig and Tarantino 2020, 26).

Lawful access also presents an additional layer of control. Article 3 (3) of the DSM Directive allows rightsholders to apply TPMs "to ensure the security and integrity of the networks and databases where the works or other subject matter are hosted. Such measures shall not go beyond what is necessary to achieve that objective". Dusollier notes:

Despite the expressed intention of the European lawmaker to safeguard a balance between the rights of the copyright holders and the interests of the users and society at large, the anti–circumvention provisions give the rights owners preference: the protection is broad and surely extends beyond the boundaries of copyright; the exceptions are overridden, albeit the empty promise of the article 6(4) (2003, 462).

Recital 16 of the DSM Directive goes further to explain the reasoning behind the provision and frames the application of a potentially high number of access requests and downloads of works. Hence, rightsholders can use TPMs for cases where their systems or database security and integrity could be jeopardized. But the Directive also sets a recommended balance between TPMs and security risks, as they both should "not exceed what is necessary to pursue the objective of ensuring the security and integrity of the system and should not undermine the effective application of the exception".

Questions have been raised regarding the reach of the Article 3 exception, as it puts the EU in a disadvantageous AI research position (Samuelson 2018; Drexl et al 2019). While the EU divides the TDM regime between non-commercial and commercial use, other countries such as the US and Japan have avoided that approach, allowing TDM without regard for the commercial purpose or the type of user. As already noted, the US court rulings of *Google* and *HathiTrust* have allowed commercial use of TDM research under fair use exceptions. And Japan, the first country to pass a TDM copyright provision, does not distinguish between commercial and non-commercial use, the information analysis does not necessarily have to be conducted for scientific research purposes, and TDM is open to all users. This approach follows Japan's objective to promote the development of AI and big data industries (European Alliance for Research Excellence 2018). Consequently, EU firms might ship offshore their TDM research to places with less restrictive TDM legislation, or non-EU firms may avoid investing in TDM research in the EU because of the DSM Directive restrictions (Samuelson 2018).

#### **DSM Directive Article 4**

Contrary to Article 3, Article 4 creates an exception that has no restriction on the type of user or the commercial purpose; however, the exception can be overridden by contractual agreements or a unilateral declaration (Quintais 2020). It includes all kinds of users without regard to any affiliation: any organization, corporation, or individual researcher can make use of the TDM exception. In addition, Article 4 allows any reproduction and extraction of lawfully accessible works whether for commercial or non-commercial use. But the exception does give rightsholders an opt out option: it is applicable only on condition that the rightsholders have not expressly reserved the use of works.

This Article brings a separate legal regime for TDM practice, as the marked differences with Article 3 make it more of a business transaction. Article 4 is a provision that allows any person or organization to engage in TDM projects for any purpose, as long the rightsholder consents to the use. Article 4(3) and Recital 18 give the rightsholders the option to reserve their rights by "the use of machine-readable means, including metadata and terms and conditions of a website or a service". But they can also reserve their rights by other means, "such as contractual agreements or a unilateral declaration". In practice, a publisher is free to control access for commercial use, to license by contractual agreements, or to unilaterally block or prohibit any use of its works. The risk comes, as stated by Hugenholtz, if publishers "offer paid-for text and data mining as value-added services and will be reluctant to grant TDM licenses to third parties" (Hugenholtz 2019). As a result, Article 4 could effectively create and legitimize a derivative market for TDM activities through contracts, licenses, and even exclusivity over works and content.

Article 4 could also put the EU in a disadvantageous research position, as the opt out option in the DSM Directive does not match other jurisdictions' least restrictive TDM provisions. At the forefront of TDM open regulations, Japan allows any TDM use, including commercial research, without any rightsholder compensation. Japan's legislation also allows a TDM user to be free of a rightsholder's economic retribution when accessing data or information, making incidental electronic copies of the works, or during database research. Similarly, since the *Google* case in the US, corporations may engage in TDM projects without any rightsholder compensation if they meet the required fair use conditions Some countries that lack specific provisions to limit the use of TDM, like Belize (Belize 2000), Barbados (Barbados 1998), or Panamá (Panama 2012), may allow free exploitation under fair dealing or Article 9(2) of the Berne Convention. These alternative markets might encourage researchers, organizations, and corporations to explore nations with fewer limitations on TDM projects.

### **United Kingdom**

After several studies assessing costs and benefits of a copyright reform, the UK was the first Member State to adopt a TDM exception on 19 May 2014. The UK Copyright, Designs and Patents Act 1988 has provided for a text and data analysis exception for non-commercial research. According to UK law, the making of a copy of a work by a person who has lawful access to that work does not infringe copyright if it is made so that that person can carry out a computational analysis of anything included in that work for non-commercial research purposes. The exception does not cover reproduction of databases (Geiger, Frosio and Bulayenko 2020, 22).

The text of Article 29A of the UK's *Copyrights, Designs, and Patents Act* reads: "a person who has lawful access to the work may carry out a computational analysis of anything recorded in the work for the sole purpose of research for a non-commercial purpose". The scope of the exception was framed after Article 5.3(a) of the Directive 2001/29/EC of the European Parliament and of the Council of 22 May 2001 on the Harmonisation of Certain Aspects of Copyright and Related Rights in the Information Society [hereinafter InfoSoc Directive], a norm that requires a scientific research purpose with a non-commercial character (Directive 2001/29/ EC 2001).

Article 5(3) is not a mandatory exception for EU members.

With the exclusion of temporary copies (Article 5(1)), exceptions and limitations are *optional* for EU Member States to implement. All L&Es are subject to the three-step test contained in Article 5(5): they shall only be applied in certain exceptional cases, which do not conflict with a normal exploitation of the work or other subject matter, and do not unreasonably prejudice the legitimate interests of the rightholder (Rosati 2019, 128).

The UK government therefore made an active choice to introduce a TDM exception to UK law, stating: "This will enable key research without undermining publishers' control over IT systems or commercial exploitation" ("Modernising Copyright" 2012, 37). As stated by the UK Intellectual Property Office, the creation of the exception does not mean that "researchers or companies can now access material for free, as researchers or their institutions still have to buy access to content if that is the business model of the publisher" (UK Intellectual Property Office 2014, 5).

But non-commercial use is not the only relevant restriction to the UK exception. A second meaningful restriction requires the person undertaking the research to already have lawful access to the works to be used (Article 29A (1)). The UK Intellectual Property Office defines lawful access as being where "researchers have the legal right to access a copyright work to read it" (UK Intellectual Property Office 2014, 7). Very similar to the limits of the DSM Directive, content that may be lawfully accessed includes journals and database subscriptions, and works published under open licenses including Creative Commons and Open Government licenses. But as seen above with the DSM Directive, the link to subscription services payments means the researcher's budget capacity comes to play an essential role and risks increasing the scientific and innovation gap for UK researchers.

The third significant limitation comes from Article 29A (2), as the exception applies only to reproduction but not communication of the work. Contrary to other TDM exceptions that allow reproduction and sharing of the work, Article 29A (2) does not allow the researcher "to share the TDM research information to any other person" except where the transfer is authorized by the copyright owner. The UK Intellectual Property Office is clear on this restriction, stating works "can't be shared, sold, or made publicly available in any way and anyone doing so could be sued for copyright infringement" (UK Intellectual Property Office 2014, 7). And even though article 5(3) of the InfoSoc Directive that inspired Article 29A, allows both reproduction and communication, the UK decided to preclude the communication option in its own law. In TDM research, sharing the results is an essential second part of the process. Sharing helps develop knowledge as it allows other researchers to collaborate, or even develop new research projects from the same information. Sharing data performs the same function as a book does when it is published, printed, distributed and makes the information contained available for discovery and use. Other countries' legislation allows sharing of TDM: Germany allows sharing within a close research circle, even for third parties to review results; Japan allows sharing without restrictions.

As a result, the UK TDM copyright exception might be ripe for review. Since the exception was framed before Brexit and partially inspired by Article 5(3) of the InfoSoc Directive, the UK may consider new rules for engaging TDM research that would align with the current international approaches, or even, with the DSM Directive. But even though the DSM Directive might be a starting point for reform, including a mandatory commercial use as in Japan or the US, it might also bring better competitive results for UK researchers. Framing exceptions on par with the most forward-looking countries could also bring international projects to the UK.

#### **Germany**

Germany and other European countries, for example, France, that had passed copyright exceptions on TDM before the DSM Directive will need to adjust their norms to reflect the new EU TDM exceptions. Contrary to some parts of Articles 3 and 4 of the DSM Directive, section 60d of the German Copyright and Related Rights Law (Germany. Urheberrechtsgesetz, UrhG/Act on Copyright and Related Rights 2017) creates an exception for TDM limited to non-commercial purposes. The German exception allows researchers to reproduce the copyrighted material to create a corpus of data, but only allows the work to be available to a specifically limited circle or to third parties to monitor the quality of scientific research (Geiger, Frosio and Bulayenko 2020, 23). This restriction is not included in the DSM Directive. Furthermore, section 60d requires that, once the research work is finalized, the corpus and the source material's reproductions need to be deleted unless sent to libraries, archives, museums, or educational establishments for long-term storage (Articles 60e and 60f). Again, this disposition would be contrary to the DSM Directive.

### **Japan**

Japan was the first country to amend its copyright law in 2009 to include a TDM exception (Japan. Copyright Act 1970), which was later modified by a 2018 amendment that broadened the exception scope (Japan. Copyright Act 2020). The 2009 TDM provision was introduced to allow computer information analysis, authorizing reproduction and adaptation of works used for TDM projects. The exception included a broad definition of informational analysis, had no commercial use restrictions, and the TDM projects did not need to be carried out exclusively for scientific research purposes (Caspers and Guibault 2016). But the exception also had some relevant limitations: all the TDM tasks were required to be performed exclusively using a computer, which brought questions regarding future applicability if new technologies came into play. Some commentators noted that while "The Japanese list of detailed exceptions has the merit of clarifying a number of potential legal uncertainties in the online environment, it has the disadvantage of being bound by state-of-the-art technologies. As soon as technology changes, the list might need to be updated" (Borghi and Karapapa 2013, 62).

The exception also suffered from a lack of clarity, and seemed to exclude raw data, as well as databases (Triaille, De Meeûs d'Argenteuil, and De Francquen 2014). Issues of uncertainty were raised by others.

Hence, the Japanese TDM exception appears to cover a broad range of TDM exceptions, both commercial and non-commercial, and both for research and other purposes. However, there are some concepts in the exception that are not entirely clear and may cause uncertainty, especially the last phrase of the provision (Caspers and Guibault 2016, 69).

The limitations and uncertainties in the law created the need for an amendment to the 2009 TDM copyright exception and the 2018 Amendment introduced additional TDM provisions, while offering a broader scope for TDM and the technologies involved (Ueno 2021). Article 30–4 expanded the scope of works for TDM use, while introducing the types of exploitation that can be performed. The article allows the exploitation of any copyrighted work that is not intended for enjoying or causing another person to enjoy the ideas or emotions expressed in such work (Ueno 2019).

The definition of enjoying becomes a key element to set the reach of the limitation. Ueno notes that in Japan "copyright is a right protecting only an interest in the inherent exploitations aimed at 'enjoying' or causing another person to 'enjoy' a work". He refers to the Japanese Copyright Office (JCO) perspective:

that the economic value of a work is normally realized when a person who views or listens to the work pays compensation for such work in order to enjoy the ideas or emotions expressed in a work and satisfies the person's intellectual or emotional desires (Ueno 2019, Slides 10–12).

Acts performed not for the purpose of enjoying the ideas or emotions expressed in a work would not prejudice the interests of the copyright holder. Examples of non-enjoyable uses are given in article 30–4(iii) with works used during computer data processing that do not involve perceiving the "expressions through the human sense".

Article 30–4(ii) gives an even broader reach to the TDM exception as it offers a comprehensive inclusive list of foreseeable steps in a TDM project. For the Japanese copyright law, it is permissible to exploit work, "in any way and to the extent considered necessary". This includes actions such as the "extraction, comparison, classification, or other statistical analysis of language, sound, or image data, or other elements of which a large number of works or a large volume of data is composed". The Article gives the right to extract all the required works, classify and compare them, run any TDM process, as well for processing statistical analysis of all types and sizes of works, thus eliminating any possibility of restricting AI data processing.

Japan copyright TDM exceptions show the most open legislation for TDM use. Contrary to the exceptions of the European DSM Directive, the UK, or Germany, Japan offers an exception flexible enough to offer an open environment for research and exploration of a broad spectrum of TDM projects, limited only if there is an enjoyment of the work that is being used.

# **Court-based TDM**

### **United States**

There are diverse cases that need to be considered to determine the legality of TDM in the United States, as the law is not specifically covered by statute. Cases such as *Williams & Wilkins Co. v. United States*3, *Authors Guild, Inc. v. Google, Inc.*4*,* and *Authors Guild, Inc. v. HathiTrust*5, already mentioned, have built a solid legal precedent to allow TDM in the United States (Sag 2019). This section concentrates on explaining the fair use statute and naming the key cases for TDM in the United States.

#### **The Law of Fair Use and TDM**

Copyright fair use doctrine was initially developed by the Courts in the US to allow unauthorized copying of copyrighted works where it was beneficial to society. *Folsom v. March*6 is regarded as the first case. Courts developed fair use to further the United States Constitution Art. I, § 8, cl. 8 purpose of promoting the "progress of science and useful arts". Latman (1958) outlines the history of fair use before codification. Samuelson (2017) discusses ten types of justifications for L&Es and considers the relative utilities of specific and open-ended L&Es. While authors are one of the intended beneficiaries of copyright "the ultimate, primary intended beneficiary is the public, whose access to knowledge copyright seeks to advance by providing rewards for authorship" (*Authors Guild, Inc. v. Google, Inc* 2015, 13).

Courts have recognized that the ultimate goal of copyright is to "expand public knowledge and understanding" (*Authors Guild, Inc. v. Google, Inc* 2015, 12) while giving creators limited temporary monopoly over their works. Fair use also provided a First Amendment safety valve (Cunard, Keller, and Potenza 2021). Related case law includes *Eldred v. Ashcroft*7, *Harper & Row Publishers*, *Inc. v.*

**3** Williams & Wilkins Co. v. United States, 487 F.2d 1345 (Ct. Cl. 1973), aff'd by an equally divided Court, 420 U.S. 376 (1975).

**4** Authors Guild, Inc. v. Google, Inc., 804 F.3d 202 (2d Cir. 2015).

**5** Authors Guild, Inc. v. HathiTrust, 755 F.3d 87 (2d Cir. 2014).

**6** Folsom v. Marsh, 9. F.Cas. 342 (C.C.D. Mass. 1841).

**7** Eldred v. Ashcroft, 537 U.S. 186, 219-20 (2003).

*Nation Enterprises*,8 and *National Rifle Association of America v. Handgun Control Federation of Ohio*9 and so,

as the 20th century wore on, the uncodified fair use doctrine became the main common law limit on copyright's exclusive rights. Cases typically involved parodies and burlesques, scholarly, quotations, critical commentary, and news reporting, although not all of the defenses prevailed (Stephenson 2017, 19).

Fair use was codified with Section 107 of the 1976 Copyright Act (US Copyright Act 2021) which formalized fair use into a four-factor statute. The four factors used to determine if the use made of a work in any particular case is fair are*:*

The US Copyright Office (2021) provides guidelines to the four factors. Under the first factor, the Court considers the extent to which the new work is "transformative". As *Mattel, Inc. v. Walking Mountain Productions*10 states, the work must add "something new, with a further purpose or different character, altering the first with new expression, meaning, or message". Under the second factor, the Court considers whether the copyrighted work is "of the creative or instructive type that the copyright laws value and seek to foster'' (Leval 1990, 1117; Patry 2021, § 4.1). This factor rarely plays a significant role in the determination of a fair use dispute. The third factor "asks whether the amount and substantiality of the portion used in relation to the copyrighted work as a whole, are reasonable in relation to the purpose of copying" as in *Dr. Seuss Enters, L.P. v. Penguin Books*.11 Under the fourth factor, Courts must question "whether actual market harm resulted from the defendant's use... and whether 'unrestricted and widespread conduct of the sort engaged by the defendant ... would result in a substantially adverse impact on the potential market' for the original or its derivatives" as noted in *Campbell v. Acuff–Rose Music, Inc.*12

**8** Harper & Row Publishers, Inc. v. Nation Enterprises 471 U.S. 539, 560 (1985).

**9** Nat'l Rifle Ass'n of Am. v. Handgun Control Fed'n of Ohio, 15 F.3d 559, 562 (6th Cir. 1994).

**10** Mattel, Inc. v. Walking Mountain Prods., 353 F.3d 792, 800 (9th Cir.2003).

**11** Dr. Seuss Enters., L.P. v. Penguin Books, 109 F.3d 1394, 1399 (9th Cir.1997).

**12** Campbell v. Acuff–Rose Music, Inc., 510 U.S. 569 (1994).

Each of the four factors is to be examined independently and then weighed against each other. In *Campbell* the court found that Section 107's four factors are not to ''be treated in isolation… all are to be explored, and the results weighed together, in light of the purposes of copyright''*. Authors Guild, Inc. v. Google, Inc.*13 noted that each factor is part of the question of "how to define the boundary limit of the original author's exclusive rights in order to best serve the overall objectives of the copyright law to expand public learning while protecting the incentives of authors to create for the public good". The court noted: