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In Helprin's Jeffersonian defense of private property, the author explains why the popular campaign for an open source approach to intellectual property undermines not just the possibility of an independent literary culture but threatens the future of civilization itself.

What can and can’t be copied is a matter of law, but also of aesthetics, culture, and economics. The act of copying, and the creation and transaction of rights relating to it, evokes fundamental notions of communication and censorship, of authorship and ownership—of privilege and property. This volume conceives a new history of copyright law that has its roots in a wide range of norms and practices. The essays reach back to the very material world of craftsmanship and mechanical inventions of Renaissance Italy where, in 1469, the German master printer Johannes of Speyer obtained a five-year exclusive privilege to print in Venice and its dominions. Along the intellectual journey that follows, we encounter John Milton who, in 1644 accused the English parliament of having been deceived by the ‘fraud of some old patentees and monopolizers in the trade of bookselling’ (i.e. the London Stationers’ Company). Later revisionary essays investigate the regulation of the printing press in the North American colonies as a provincial and somewhat crude version of European precedents, and how, in the revolutionary France of 1789, the subtle balance that the royal decrees had established between the interests of the author, the bookseller, and the public, was shattered by the abolition of the privilege system. Some of the essays also address the specific evolution of rights associated with the visual and performing arts. The volume is a companion to the digital archive Primary Sources on Copyright (1450-1900), funded by the UK Arts and Humanities Research Council (AHRC). Privilege and Property is recommended in the Times Higher Education Textbook Guide (November, 2010).

In response to the failure of U.S. copyright law to protect foreign authors, nineteenth-century American publishers evolved an informal practice called the \"courtesy of the trade\" as a way to mitigate the public goods problem posed by a large and evergrowing commons of foreign works. Trade courtesy was a shared strategy for regulating potentially destructive competition for these free resources, an informal arrangement among publishers to recognize each other's wholly synthetic exclusive rights in otherwise unprotected writings and to pay foreign authors legally uncompelled remuneration for the resulting American editions. Courtesy was, in effect, a makeshift copyright regime grounded on unashamed trade collusion and community-based norms. This Article examines a particular feature of this informal system: the courtesy paratext. Typically appearing in the form of letters or statements by foreign authors, courtesy paratexts prefaced numerous American editions of foreign works published from the 1850s to the 1890s. These paratexts—supplements to the text proper—played a prohibitory role (not unlike the standard copyright notice) and also extolled the regulating and remunerating virtues of the courtesy system. Authorial paratexts continued to accompany texts well into the twentieth century—including, notably, American editions of James Joyce's and J.R.R. Tolkien's works—and enable us to observe the principles of courtesy as they operated less overtly to govern American publishers' treatment of unprotected foreign works. A little-examined source for understanding the history of copyright law and informal publishing norms, courtesy paratexts offer insight into a form of private ordering that rendered the American public domain a paying commons.

The use of Artificial Intelligence (\"AI\") machines using deep learning neural networks to create material that facially looks like it should be protected by copyright is growing exponentially. From articles in national news media to music, film, poetry and painting AI machines create material that has economic value and that competes with productions of human authors. The Article reviews both normative and doctrinal arguments for and against the protection by copyright of literary and artistic productions made by AI machines. The Article finds that the arguments in favor of protection are flawed and unconvincing and that a proper analysis of the history, purpose, and major doctrines of copyright law all lead to the conclusion that productions that do not result from human creative choices belong to the public domain. The Article proposes a test to determine which productions should be protected, including in case of collaboration between human and machine. Finally, the Article applies the proposed test to three specific fact patterns to illustrate its application.

\"4 The law is codified in Title 17 of the United States Code, as amended (the \"Copyright Act\").5 A. Basic Concepts Copyrights protect original, minimally creative authored works, such as writings, music, images, audio or audiovisual recordings, and architectural works6 that are fixed in a tangible medium of expression.7 Only the copyrighted expression is protected, not the underlying ideas, procedures, methods, discoveries, concepts, or \"useful articles. [...]copyright registration is required to bring suit for copyright infringement in the United States.'s Moreover, prompt registration enables the would-be infringement plaintiff to avoid the additional cost associated with expediting registration applications and can entitle the owner to statutory damages of up to of $150,000 per infringement and reasonable attorney's fees.19 In certain cases, attorney fees in copyright infringement cases can far outweigh actual damages.20 The prospect of potential statutory damages can be a powerful deterrent to potential willful infringers. The Copyright Act does not include a definition of \"photograph\" but the term includes photographs that are created with a camera and captured in a digital file or other visual medium such as film.33 (6) Computer Software and Apps. Copyright in software extends to source code, which is copyrightable expression, but does not protect anything functional, such as the program's logic or system design or algorithms.34 HTML (hypertext markup language) is not considered to

How to protect the creations of artificial intelligence (\"AI\") systems through copyright law is one of the most significant and complex legal issues of our time. Debated by stakeholders around the world, the issue has so far evaded consensus. However, a series of administrative and judicial rulings has altered the landscape. In 2019, a Chinese district court affirmed the copyrightability ofa news article written by an AI-powered robot, clarifying that it was the AI developer that should be deemed copyright owner ofthe news article. In 2020, the United States Patent and Trademark Office, the European Patent Office, and the United Kingdom High Court prominently denied patent applications designating an AI system as an inventor. This Article reveals the profound implications of these recent AI rulings for copyright protection of AI-generated works. It examines how these rulings shed new light on the nature and scope of authorship and ownership, two legal issues that are central to deciding whether and how AI-generated works merit copyright protection. Drawing on its in-depth study ofthe recent AI rulings, the Article proposes a broad-based, forward-looking approach to protecting AI-generated works through a two-tiered legal mechanism. It suggests that legislators may consider awarding sui generis rights to AI works generated with human contributions, while those generated autonomously by AI systems without such contributions should be placed in the public domain without copyright protection.

With rapid technological advancement, artificial intelligence (AI) undeniably aids humans in various ways, particularly in new creations and innovations. This study focuses on the present obstacles and ramifications pertaining to the legal governance of AI-generated works in the context of Malaysian copyright law, Copyright Act 1987. It first identifies the problems related to Al such as authorship and ownership rights of AI, whether AI can infringe a copyrighted works and highlights the implications of recognising AI-created works. This study also makes comparisons and discusses several legislations, regulations and judicial decisions from other jurisdictions such as the European Union, United States and United Kingdom. It also proposes several strategies on future domestic copyright laws in Al that address the problems identified in the study by maintaining with the current standing of the domestic copyright law. The study recommends not to recognise AI as author nor owner, but encourage Al-created works into public domain, enact a prospective Al regulatory guidelines and code of ethics, and foster collaboration from diversity of members from various sectors by establishing a nationwide commission to evaluate the impact of AI and advice on necessary measures.

Scientific publications provide a wealth of peer-reviewed, high-quality data that have been maintained over time, resulting in data persistence. As data repositories with rich provenance information, publications are indispensable sources for the integration and extension of networks of interlinked Findable, Accessible, Interoperable and Reusable (FAIR*1) bio/geodiversity data. In this way, they form pivotal fact- and knowledge-based contributions to applications that address the biodiversity crisis. The mobilization of data preserved in scientific publications is hindered, however, by distinct copyright legislation contexts for publications versus the data that they contain. Moreover, legislations concerning copyright continue to lack harmonization across jurisdictions, their interpretation is difficult, and the applicable legal national scope can be uncertain. We clarify and highlight that data within scientific publications are not copyrightable and thus can be openly and freely reused once legal access has been gained to their enclosing publication*2. To ensure that publications are as accessible as possible, a joint statement supported by the Biodiversity Heritage Library (BHL), the Consortium of European Taxonomic Facilities (CETAF) and the Society for the Preservation of Natural History Collections (SPNHC) (Benichou et al. 2023) recommends that authors and publishers make their works as accessible as possible by using a CC-BY license or preferably waive copyright (CC0) to their publications. Explicitly associating a public domain mark (PDM, e.g., the PDM from Creative Commons) to their published data, provides users with certainty about reusability. Yet, by setting works and bio/geodiversity data into the public domain, they do not become a free-for-all. We stress that data need to be associated with clear provenance information in alignment with scientific best practices and the scientific community's social norms. This includes providing detailed attribution to authors of cited works and reused data. Proposed data governance labels, for example, modeled after the Local Contexts labels developed by the international Indigenous Peoples and Local Communities (IPLC) community, would enable authors to communicate social and ethical contexts and applicable rules to data users for ensuring the sustainability of a shared environmental and data commons. Categories of Local Contexts labels that are of interest and applicable in the sciences are, for example, those that communicate (1) correct citation information and ask for attribution when knowledge and/or data are reused (Traditional Knowledge label (TK) Attribution), (2) an interest in being recognized and acknowledged due to a significant relationship with and responsibility for samples and data (Biocultural label (BC) Provenance), (3) the verification of the data and their context following a community protocol (TK Verified), (4) that non-commercial use (TK Non-Commercial/BC Non-Commercial) or (5) outreach activities (TK Outreach/BC Outreach) are generally permitted, while for other uses direct contact and engagement is required, or (6) an openness to collaboration and partnerships (TK Collaboration/BC Collaboration). There are concerns about the tension between the goal of achieving open data (e.g., Anonymous 2014) to enable and promote open science (e.g., UNESCO 2021) and, at the same time, imposing restrictions on these data in the form of governance labels. Furthermore, while the reference of the publication through which data are published, as well as more specifically bibliographic references cited for specific data within the publication, provide sufficient information for attribution and provenance, much more fine-grained and nuanced contextual information (e.g., in the form of metadata) is needed for assuring responsible reuse. Such context-providing metadata unlock the full potential of the data and enable their reusability. This can be done using machine-actionable markup tags in combination with human-readable labels that inform machines and human users about the semantics of the data as well as their ethical and social dimensions that govern responsible and sustainable reuse. Future work is needed to discover, differentiate and define the quality and scope of the appropriate contexts that are necessary and sufficient for being able to fully and responsibly reuse the data in different situations.

Is there one public domain, or are there many? The scholarly literature predominantly assumes there is only one, for references abound to \"the public domain\" in the singular. Yet, even a cursory review of this literature reveals that scholars sometimes define this term differently. So if there is only one public domain, but many definitions, perhaps one objective of scholarly discourse about the public domain should be to seek consensus on the one \"true\" definition.