How to do things with style: A pragmatic history of style as a site for debates about authorship, commodification and technological reproducibility

Assessing perspectives on artificial intelligence applications to gastroenterology

In 2023 the scholarly communities are witnessing a spring of Artificial Intelligence (AI) powered tools for scientific work. Scholars are tempted to integrate various time-saving AI applications in their workflow, from data analysis to disseminating research results. Among these novel “research assistants”, several enhanced discovery services apply machine learning to identify the most relevant results for the information seeker and visualize them to the user in innovative ways. The rapid emergence of these tools has raised concerns about the impact of AI technology on scientific research and led to requirements of transparency, accountability, and explainability of the new AI tools. From the systems viewpoint, responsibility for the impact of technology extends beyond developers to the broader society. The user communities, including librarians providing services for academia, are considered counterparts in the effects of AI technology systems. Individuals decide how they behave with the new information technology, for example, whether they trust the system and its outcome. Thus, an individual user is also part of the socio-technical evolution of building transparent, accountable, and explainable AI. In this study, we explore the challenges of adopting AI tools in scientific research on the level of an individual librarian working for academia. We aim to detect poorly addressed mindsets around explainability, fairness, and privacy, named “blind spots” in AI ethics (Hagendorff, 2022). The goal is to understand the “determinants” of librarians’ information behavior with novel AI tools. We focus on two AI-powered visual discovery services: openknowledgemaps.org and www.litmaps.com. These tools help users to navigate and analyze research articles as concept graphs. In this poster, our primary research question is: What are the determinants of librarians’ intentions when they adopt/use new AI-powered tools? We conducted an expert evaluation (Tessmer, 1993) on these two discovery services using the Theory of Planned Behavior (TPB) as a theoretical framework that explains human behavior through three individual beliefs: attitudes, norms, and control. This framework helped us detect new “blind spots” in the behavioral determinants that have remained unnoticed in the recent discourses about AI ethics in libraries. Our study indicated a lack in the area of normative beliefs, a “blind spot”: The social pressure to quickly adopt the newest technology and the lack of library-specific norms for using AI in academia may become a handicap for an individual librarian who contemplates whether or not to use an AI tool.

Topicality. Digitalization of society is accompanied by deep changes in social, economic and political relations, generating uncertainties and risks. The growth of technology, particularly artificial intelligence, is transforming the nature of information, communication and management, creating "blind spots" that require insight and systemic analysis. The purpose of the article. To identify and investigate the mechanisms of the formation of "blind spots" as a phenomenon that characterizes the self-organization of uncertainties and risks in a digitalized society. Special attention is paid to illusions of cognitive perception and their impact on social interactions. Research methodology. The methodological basis includes the concept of singularity, the ideas of scenario planning by Pierre Wack, of the singularity by Ray Kurzweil and the theory of self-organization of social systems. Metaphors of "black swan", "gray rhinoceros" and other images are used to structure risks and uncertainties. The main conclusions of the discussion. The article emphasizes the importance of critical thinking, a universal approach to education and the introduction of ethical norms for the use of artificial intelligence as key aspects in countering the formation of "blind spots" and overcoming risks in the modern digital environment.

The 'theoretical turn' within the arts and humanities in the 1970s and 1980s has, for many, had its day, with work produced under its rubric all too often feeling tired or even downright lazy. In its place - whilst hazarding against an outright rejection of theory - this book, introduced by Mieke Bal, presents work by a new generation of scholars responding directly to Bal's idea of the 'travelling concept'. By taking a concept from one discipline and, with a genuine understanding of its origin, thoughtfully applying this in a new context, exciting new possibilities are opened up for analysis of artworks and other cultural objects. Here, we find these 'travelling concepts' employed in fresh explorations of subjects as diverse as the paintings of Poussin and of Adam Elsheimer; Chantal Akerman's film; the Museum of the French Revolution and the work of German Jewish painter Charlotte Salomon. This is a uniquely illuminating contribution to the edgy territorial conflicts between visual culture, art history and cultural studies.

Human versus machine in medicine: can scientific literature answer the question?

In this chapter, I will treat postmodernism in the United States and in Canada predominantly as a historical phenomenon, which peaked in cultural production and scholarly discussion from the 1960s through the 1980s. Exploring the field of literature, my survey of post-modernism in both countries will chart what I deem the heyday of the critical reception and promotion of post-modernism in the respective national literatures, while also pointing out the blind spots and fault lines that come with this perspective. More precisely, I will examine, for the United States, the literary production and critical debate of the 1960s and 1970s—notably the “theoretical turn” of writers and critics toward experiment and “surfiction” (Raymond Federman). For Canada, the 1970s and 1980s will be of major relevance, with literary texts and scholarship concentrating on a postcolonial revaluation of marginality, “ex-centricity,” and the rewriting of history. The focus will be on Anglophone Canadian literature, while neglecting the literary production of Quebec and other French-speaking literatures in Canada (see chs. 7 and 8 for approaches across linguistic and intranational borders). Likewise, for reasons primarily of practicability, I will narrow down my exploration of postmodernism to the genre of fiction writ-ing, thus eclipsing poetry and drama.1

The rapid advancement of Artificial Intelligence (AI) technologies has precipitated a paradigm shift in various sectors, including the creative industries, thereby posing intricate challenges and opportunities for copyright law. This article aims to comprehensively analyze the influence of AI on copyright law, delineating the multifaceted implications of AI-generated content on traditional legal frameworks. Employing a systematic review methodology, the article examines scholarly research, legal frameworks, case studies, and policy proposals to unravel the complexities at the intersection of AI and copyright law. The key findings reveal conceptual challenges related to authorship, originality, and the application of moral rights to AI-generated works, alongside legal ambiguities stemming from the international variance in copyright law adjustments. The analysis also highlights significant legal cases and policy initiatives, particularly within the European Union and the World Intellectual Property Organization (WIPO), which are pivotal in shaping the evolving discourse on copyright law in the digital and AI age. The article underscores the pressing need for legal adaptation and international collaboration to accommodate the novel realities introduced by AI, advocating for a balanced approach that fosters innovation while protecting intellectual property rights. The implications of this study are far-reaching, suggesting that the future of copyright law lies in its ability to evolve in response to technological advancements, thereby ensuring that it continues to fulfill its role in promoting creativity and cultural enrichment in a rapidly changing digital landscape. Through this exploration, the article contributes to the ongoing dialogue among legal scholars, policymakers, and stakeholders, calling for further research and legislative action to address the challenges and opportunities presented by AI in the copyright domain.

In the new paradigm in which artificial intelligence plays a critical role in operating a social and technological system, copyright laws have a lot of legal issues. In this paper, the copyright laws of two countries (the UK and Korea) are compared to distinguish the characteristics of major developed and emerging countries. In general, whereas major developed countries such as the US and the UK are favourable to the protection of new technology, emerging and developing countries have tried to lower the level of regulation of new technology in order to promote the business related to the new paradigm. In the case of artificial intelligence, the UK has a legal system that can cover work created by means of artificial intelligence, in contrast, Korea has no copyright law on artificial intelligence, including computer-generated work. Thus, the emerging countries have mitigated the regulations on copyright in order to support the catch-up strategies of their companies. The copyright law on artificial intelligence in emerging and developing countries needs to be designed for fair competition and fair trade. In addition, the duration of protecting work created by means of artificial intelligence should be shortened, because artificial intelligence can produce a lot of work in a very short time. This paper compared several case laws to compare the cases of copyrights related to artificial intelligence or computer-generated works.

Penelitian ini bertujuan untuk mengetahui serta memahami urgensi pengaturan AI dalam UU Hak Cipta di Indonesia serta potensi AI sebagai subjek hukum dalam sistem hukum di Indonesia, Penelitian ini menggunakan metode penelitian normative serta menggunakan pendekatan perundang-undangan atau statue approach serta pendekatan perbandingan atau comparative approach. Adapun rumusan masalah dalam penelitian ini adalah Apa urgensi pengaturan artificial intelligence dalam rezim hukum hak cipta di Indonesia? Dan Bagaimanakah potensi artificial intelligence sebagai subjek hukum dalam sistem hukum di Indonesia ? Dalam penelitian ini menemukan bahwa dalam UUHC Indonesia tidak mengenal AI sebagai subjek hukum, sehingga AI berdasarkan pada UUHC Indonesia tidak dapat digolongkan sebagai pencipta serta potensi AI untuk diakui sebagai entitas baru berkaitan dengan subjek hukum selain manusia dan badan hukum yang sebelumnya telah diakui sebagai subjek hukum di Indonesia sangat terbuka, mengingat AI dapat dipersamakan dengan badan hukum sesuai dengan teori-teori badan hukum serta adanya konsep Work Made For Hire yang terdapat dalam UUHC Amerika Serikat yang dapat diadopsi oleh Indonesia untuk mengakomodir AI sebagai suatu entitas baru berkaitan dengan subjek hukum yang diakui di Indonesia. Kata Kunci: Kecerdasan Buatan, Hak Cipta, Subjek Hukum This study aims to determine and understand the urgency of AI regulation in the Copyright Law in Indonesia as well as the potential of AI as a legal subject in the legal system in Indonesia, This study uses normative research methods and uses a statutory approach or statue approach and a comparative approach. This study found that the Indonesian Copyrights Law does not recognize AI as a legal subject, so AI based on the Indonesian Copyrights Law cannot be classified as a creator and the potential for AI to be recognized as a new entity related to legal subjects other than humans and legal entities that have previously been recognized as legal subjects in Indonesia is so open, considering that AI can be equated with legal entities in accordance with theories of legal entities and the concept of Work Made For Hire contained in the United States Copyrights Law which can be adopted by Indonesia to accommodate AI as a new entity related to legal subjects recognized in Indonesia. Keywords: Artificial Intelligence, Copyright, Legal Subject REFERENCES ABC. “Ada Sejumlah Kekhawatiran di Balik Tren Avatar Buatan Lensa.” TEMPO.CO. Last modified December 13, 2022. Accessed November 6, 2023. https://www.tempo.co/abc/8118/ada-sejumlah-kekhawatiran-di-balik-tren-avatar-buatan-lensa. Amboro, F. L. 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Chest computed tomography (CT) is the most frequently performed imaging examination worldwide. Compared with chest radiography, chest CT greatly improves the detection rate and diagnostic accuracy of chest lesions because of the absence of overlapping structures and is the best imaging technique for the observation of chest lesions. However, there are still frequently missed diagnoses during the interpretation process, especially in certain areas or "blind spots", which may possibly be overlooked by radiologists. Awareness of these blind spots is of great significance to avoid false negative results and potential adverse consequences for patients. In this review, we summarize the common blind spots identified in actual clinical practice, encompassing the central areas within the pulmonary parenchyma (including the perihilar regions, paramediastinal regions, and operative area after surgery), trachea and bronchus, pleura, heart, vascular structure, external mediastinal lymph nodes, thyroid, osseous structures, breast, and upper abdomen. In addition to careful review, clinicians can employ several techniques to mitigate or minimize errors arising from these blind spots in film interpretation and reporting. In this review, we also propose technical methods to reduce missed diagnoses, including advanced imaging post-processing techniques such as multiplanar reconstruction (MPR), maximum intensity projection (MIP), artificial intelligence (AI) and structured reporting which can significantly enhance the detection of lesions and improve diagnostic accuracy.

The emergence of artificial intelligence (AI) technology has brought about significant changes in various facets of our existence, altering not only how content is generated but also how it is consumed. AI-generated content, such as music, art, and literature, has become increasingly prevalent, raising a range of legal and ethical challenges regarding copyright ownership, infringement, and ethics. This paper explores the interaction between AI and copyright law, examining the legal implications of AI-generated content and its impact on copyright ownership along with the ethical considerations of using AI to create content, and its implications on the copyright law. Additionally, the paper shall also examine role of AI in detecting and enforcing copyright infringement. The paper shall provide recommendations for adapting copyright laws to accommodate the challenges posed by AI generated content. The discuss on the potential for new legal frameworks that could better accommodate AI-generated content, including the possibility of recognizing AI as a legal author is also made while considering the potential for alternative licensing arrangements that could better balance the interests of creators, users, and the public. Overall, this paper aims to provide insights into the legal and ethical complexities arising from the interaction between AI and copyright law, and to encourage further discussion and research in this important area while discussing relevant case studies like Raghav, where a work by an AI system was first given the copyright and then revoked. The challenges posed by AI-generated content are significant, but with careful consideration and collaboration, a legal and ethical framework can be developed that enable us to harness the potential of AI while protecting the interests of creators, users, and the public

Artificial intelligence (AI) technology is becoming more advanced and capable by the day. In recent years, there has been discourse across industries and disciplines about AI and the role it is and will increasingly play in innovation in the arts and sciences. AI is already being used to create original artwork, play games, and drive cars, among many other things. Given the continuous advancements in AI, it is important that a decision is made regarding the treatment of AI-driven creation under the United States intellectual property (IP) regimes, most notably under copyright law. A major argument among legal scholars and technologists is that not granting copyright for these AI-driven works will disincentive innovation and investment in the AI space and is therefore not in our country’s best interest. Others argue that AI-driven creation is incompatible with the economic and policy considerations behind copyright law and that including AI-driven creations would, at best, require a fundamental redefinition of copyright and, at worst, destroy the incentives for human-driven creation that spurred the creation of copyright law in the first place. This paper explores the legal standards and practicality of protecting AI-created works under copyright law. Copyright law seeks to promote innovation in art and culture by granting limited monopoly protections for “original works of authorship.” This paper explores the values, intentions, legal standards, and practical application of copyright law and examines the tensions that exist when applying them to AI-created works. I conclude that the public domain is the most appropriate place for AI-created works to be in the copyright regime.

Objective: The objective of this study is to investigate the impact of AI breakthroughs on copyright and challenges faced by intellectual property legal protection systems. Specifically, the study aims to analyze the implications of AI-generated works in the context of copyright law in Indonesia. Method: The research employs a normative legal approach, utilizing secondary data sources including books, legal journals, research findings, and statutory regulatory documents. The study focuses on relevant legal frameworks, such as Law No. 28 of 2014 governing copyright in Indonesia. The analysis is based on existing literature and legal documents to understand the current state of AI-generated works and their eligibility for copyright protection. Result: The research findings reveal that according to Law Number 28 of 2014 in Indonesia, AI-generated works do not meet the originality standards required for copyright protection. However, users of AI-generated works are still bound by the terms and conditions set by the AI platform, which can limit their rights to the work. The impact of AI developments on copyright law includes challenges related to determining creators and copyright holders, redefining the concept of originality, increased instances of copyright infringement, issues concerning moral and personality rights, and collaborations involving both humans and AI. Additionally, challenges related to database protection and patent protection in the context of AI are also highlighted. Conclusion: In conclusion, the advancement of AI technology introduces complexities in intellectual property law. The existing legal frameworks, such as copyright laws, need further adaptation and clarification to effectively regulate AI-generated works in the digital era. Addressing issues related to originality, creatorship, and collaborative works involving AI requires careful consideration and legal adjustments. Additionally, challenges related to database and patent protection in the realm of AI need to be addressed to ensure comprehensive intellectual property protection in the face of evolving technologies. Legal adaptation and clarification are crucial to navigating the intricate intersection of AI and intellectual property law.

Currently, radiologists must interpret large quantities of images and identify diseases on a daily basis. The minimization of errors is crucial for high-quality diagnostic imaging and optimal patient care. Brain imaging is frequently used in clinical practice; however, radiologists are prone to overlook some regions in brain imaging and make perceptual errors, thus leading to missed diagnoses. These regions, also known as "blind spots", comprise a number of intricate areas, including the posterior fossa, cerebral sulci and pia mater, cranial nerves (CNs), intracranial arteries, dural sinuses, sella and parasellar region, Meckel's cave, skull base, scalp, orbit, and pterygopalatine fossa (PPF). Therefore, the knowledge of normal computed tomography (CT) and magnetic resonance imaging (MRI) manifestations and common lesions in these blind spots is imperative to avoid false-negative results. This article graphically discusses and analyzes these common blind spots of brain imaging using real representative cases. It also provides comprehensive strategies to address missed diagnostic errors in radiology, including enhancing the selection of imaging protocols, implementing a multi-reviewer reporting system, adopting structured reporting templates, employing error measurement or detection strategies, and promoting the use, development, and refinement of artificial intelligence (AI) to improve diagnostic accuracy and efficiency. This article may also increase junior doctors' awareness of these blind spots and assist them in their daily work, and thus has continuing education implications.

This article contributes to the dynamic debate surrounding the intersection of artificial intelligence (AI) and copyright law, offering a fresh perspective that builds upon interdisciplinary analyses. Focusing on the cognitive processes underpinning creativity in both human and AI contexts, the study draws a detailed parallel between Vincent Van Gogh's iconic “Starry Night” and its AI‐generated counterpart generated through DeepDream technology. Central to the investigation is the application of psychological and neuroscientific theories to understand and compare the creative processes in humans and AI. Based on such exercise, the article first examines whether art generated with AI, devoid of human emotions and motivations yet capable of mimicking human creative cognitive processes, qualifies for copyright protection. The analysis suggests that the similarities between human and AI creativity, particularly in their cognitive structuring, could render the work “original” according to different jurisdictional standards and interpretation of copyright law. Second, the article investigates whether AI infringes copyright if protected material is used for its training and processing. This question becomes particularly relevant in light of recent legal actions against AI‐artwork generators in California, which raise issues of potential infringement by AI using latent diffusion techniques on existing artworks. The discussion provides an original perspective that can advance the ongoing debate on the use of copyrighted material for AI training. The paper aims to contribute to the ongoing debate about AI and copyright by challenging the traditional human‐centric view of authorship in copyright law. The article argues for a nuanced understanding that acknowledges the complex nature of creativity, transcending the binary division between human and artificial sources. This approach is critical in redefining legal frameworks, ensuring they are adaptive to the evolving landscape of AI capabilities. At the same time, the article addresses the implications of AI drawing inspiration from existing art, recognizing the need to balance different stakeholders' interests when drawing policy considerations. Ultimately, the goal is to provide a layered perspective that not only deepens the legal discourse but also respects and fosters the coexistence and mutual advancement of both human and artificial creativity in the digital age, in line with the purpose of copyright.