1,720,968 research outputs found
Behind the Steele Curtain: An Empirical Study of Trademark Conflicts Law, 1952-2016
Full text linkThe law on international trademark disputes is founded on precedent from 1952. Steele v. Bulova Watch Co. is the first and only Supreme Court decision addressing the question of how far the Lanham Act should be extended beyond the United States\u27 national borders when international infringement is at issue. The decision laid the foundation for a three-pronged test that focuses on the factors of defendant nationality, effects on US commerce, and conflicts with foreign law. Although international trademark conflicts have multiplied dramatically--particularly throughout the last decade--there has been no systematic and comprehensive account of the actual state of the law. Courts and commentators continue to rely only on a small set of leading cases--Steele and a handful of appellate court opinions--when testing the territorial scope of the Lanham Act, thus ignoring the landscape of lower courts\u27 decision-making. To address this blind spot, an empirical study of the field\u27s case law from its inception in 1952 until 2016 was undertaken. The results, presented in this Article, reveal that much of the conventional wisdom regarding the state of judge-made law in trademark conflicts cases is questionable, if not incorrect. This Article not only provides new and unexpected insights into the actual extension of US trademark law beyond national territory but also explains which factors drive the outcome of extraterritoriality testing in practice, how these factors interact with one another, and how each factor has been shaped overtime. Based on these findings, this Article suggests several corrections to existing doctrine. More succinctly put, in the interest of aligning judicial practice with the realities of socioeconomic globalization, the current overextension of the Lanham Act must be curbed. The doctrine of trademark extraterritoriality that has evolved in the wake of Steele is an anticompetitive detriment rather than a rights holder panacea
Generative AI, Reproductions Inside the Model, and the Making Available to the Public
No full textThe training of generative artificial intelligence (AI) models requires the collection and analysis of a staggering amount of data, most of which consist of copyright-protected works. To date, the question whether reproductions of these works are created inside the models during their training has seldom been discussed. This is a serious blind spot in the debate given that such reproductions – e.g., inside ChatGPT’s or Stable Diffusion’s models – could be made available to end users and, therefore, to the public when AI services are offered online. Under the InfoSoc Directive, this might be copyright infringement. EU Member States’ national copyright laws would then apply and their national courts would have international jurisdiction. Seen in this light, the widely propagated narrative that non-EU AI developers are not subject to EU copyright law is an illusion
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Trademark and unfair competition conflicts ::historical-comparative, doctrinal, and economic perspectives /
No full text"Both in Europe and the United States, a socioeconomic cataclysm of industrialization and market liberalization-including the invention of branding, mass advertising, and marketing psychology-was the driving force behind the construction of modern trademark and unfair competition laws. During the last two centuries, legal doctrine accordingly underwent partly groundbreaking transformations. Many of these account for today's transatlantic dichotomy, particularly in the field of trademark and unfair competition choice of law, or conflicts law. My analysis will focus on the most relevant characteristics of legal doctrine between the eighteenth and twenty-first centuries. I argue that a closer look at conceptual and structural differences, as well as commonalities between European and US law, provides the basis for a reconceptualization of the field"-
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Generative AI and the Scope of EU Copyright Law: A Doctrinal Analysis in Light of the Referral in Like Company v. Google
No full textAbstract
This article offers a doctrinal analysis of the copyright implications raised by Like Company v. Google Ireland (C-250/25), the first case to bring generative AI before the Court of Justice of the European Union. It examines whether the training and output of systems like Gemini infringe exclusive rights under EU copyright law. We argue that AI model training may involve acts of reproduction under Art. 2 of the InfoSoc Directive, while the dissemination of AI-generated outputs, especially through public interfaces, may trigger the right of communication to the public under Art. 3. Particular concerns arise when protected content is recognisably reproduced or when AI outputs serve as functional substitutes for original works, thereby affecting the normal exploitation of those works. While not a formal infringement criterion, such functional substitution is relevant in assessing the application of exceptions and compliance with the three-step test. The paper also challenges the applicability of the text and data mining exception to generative uses, highlighting its incompatibility with the limitations imposed by the three-step test. Ultimately, the analysis supports a technologically neutral, rights-based interpretation that safeguards the economic viability of creative production in the algorithmic age
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Urheberrecht und Training generativer KI-Modelle
No full textGenerative AI (e.g., ChatGPT) generates texts, images, music, and videos. The technology is based on extensive training with copyrighted data. In the USA, AI developers rely on "fair use"; in Europe, the prevailing view is that the exception for "Text and Data Mining" (TDM) applies. The interdisciplinary study refutes this approach, as generative AI training fundamentally differs from TDM. It also explains why AI developers outside Europe are immediately subject to EU copyright law if their AI systems are accessible in the EU. Overall, it becomes clear that a more thorough, technology-oriented consideration and an adaptation of the law to reality are required.PublishedGenerative KI (z.B. ChatGPT) erzeugt Texte, Bilder, Musik und Videos. Die Technologie basiert auf dem umfangreichen Training mit urheberrechtlich geschützten Daten. In den USA berufen sich KI-Entwickler auf „fair use“; in Europa gilt nach verbreiteter Ansicht die Schranke für „Text und Data Mining“ (TDM). Die interdisziplinäre Untersuchung widerlegt diesen Ansatz, weil sich generatives KI-Training fundamental von TDM unterscheidet. Überdies wird u.a. auch erklärt, warum KI-Entwickler außerhalb Europas dem EU-Urheberrecht unmittelbar unterliegen, wenn ihre KI-Systeme in der EU zugänglich sind. Insgesamt wird deutlich: Eine gründlichere technologisch orientierte Betrachtung und eine Anpassung des Rechts an die Realität sind erforderlich
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