Publishing Services
Publishing Services supports our affiliates' creation of scholarly publications. We provide consultations about general publishing questions, and publish journals, books, dynamic scholarly serials, and textbooks through our University of Minnesota Libraries Publishing imprint.
AI Training and Copyright: Should Intellectual Property Law Allow Machines to Learn?
This article examines the intricate legal landscape surrounding the use of copyrighted materials in the development of artificial intelligence (AI). It explores the rise of AI and its reliance on data, emphasizing the importance of data availability for machine learning...
The copyright protection of AI-generated content in video games
Abstract The increasing use of artificial intelligence in video game development, particularly through advanced procedural content generation, challenges traditional copyright frameworks. While AI-generated content is now integral to enhancing efficiency and player experience, its copyright status remains disputed, especially regarding...
Do not go gentle into that good night: The European Union's and China's different approaches to the extraterritorial application of artificial intelligence laws and regulations
Putting AI Ethics into Practice: The Hourglass Model of Organizational AI Governance
The organizational use of artificial intelligence (AI) has rapidly spread across various sectors. Alongside the awareness of the benefits brought by AI, there is a growing consensus on the necessity of tackling the risks and potential harms, such as bias...
Shaping the future of AI in healthcare through ethics and governance
Abstract The purpose of this research is to identify and evaluate the technical, ethical and regulatory challenges related to the use of Artificial Intelligence (AI) in healthcare. The potential applications of AI in healthcare seem limitless and vary in their...
Pocket Constitutions: America’s Founding Document in Small Print
For a document that is usually found behind glass casing in museums and galleries, many have taken advantage of the ability to carry it in their purse, wallet—or better yet—their pocket. The US Constitution is one of the oldest and...
Letting sleeping wasps lie: general-purpose AI models and copyright protection under the European Union AI Act
Abstract This article addresses two principal research objectives: first, to examine how and to what extent the provisions of the EU AI Act (EUAIA) dedicated to general-purpose artificial intelligence (AI) models (GPAIm) govern the intersection of copyright and AI, through...
TDM copyright for AI in Europe: a view from Portugal
Abstract The development of artificial intelligence (AI) justified the introduction at the level of the European Union (EU) of a new copyright exception regarding text and data mining (TDM) for purposes of scientific research conducted by research organizations and entities...
Bias Preservation in Machine Learning: The Legality of Fairness Metrics Under EU Non-Discrimination Law
AI copyright policy considerations for Botswana and South Africa – Compensation for starving artists feeding generative AI
The balancing act which domestic intellectual property policy is now challenged to strike is between fostering growth in technological innovation and incentivising creative labour. Ordinarily, these two considerations should not be mutually exclusive, but generative artificial intelligence (Gen AI) has...
Why fairness cannot be automated: Bridging the gap between EU non-discrimination law and AI
Civil law regulation of artificial Intelligence in the Russian Federation
The purpose of this article is to identify the normative gaps in the legal regulation of the use of artificial intelligence technology and related systems, as well as to identify the degree of need for a more comprehensive legal regulation....
Teaching fairness to artificial intelligence: Existing and novel strategies against algorithmic discrimination under EU law
Empirical evidence is mounting that artificial intelligence applications threaten to discriminate against legally protected groups. This raises intricate questions for EU law. The existing categories of EU anti-discrimination law do not provide an easy fit for algorithmic decision making. Furthermore,...
Auditing of AI in Railway Technology – a European Legal Approach
Abstract Artificial intelligence (AI) promises major gains in productivity, safety and convenience through automation. Despite the associated euphoria, care needs to be taken to ensure that no immature, unsafe products enter the market, especially in high-risk areas. Artificial intelligence systems...
Natural Language, Legal Hurdles: Navigating the Complexities in Natural Language Processing Development and Application
This article delves into the legal challenges faced in developing and deploying Natural Language Processing (NLP) technologies, focusing particularly on the European Union’s legal framework, especially the DSM Directive, the InfoSoc Directive, and the Artificial Intelligence Act. It addresses the...
Online Courts and the Future of Justice
In Online Courts and the Future of Justice, Richard Susskind, the world’s most cited author on the future of legal services, shows how litigation will be transformed by technology and proposes a solution to the global access-to-justice problem. In most...
AI and Bias in Recruitment: Ensuring Fairness in Algorithmic Hiring.
The integration of Artificial Intelligence (AI) in recruitment processes has revolutionized hiring by increasing efficiency, reducing time-to-hire, and enabling data-driven decision-making. However, despite these advancements, concerns about algorithmic bias and fairness remain central to ethical AI deployment. This paper explores...
NeurIPS Creative AI Track 2025: Humanity
NeurIPS 2025 Mexico City –Call for Socials
CacheMind: From Miss Rates to Why -- Natural-Language, Trace-Grounded Reasoning for Cache Replacement
arXiv:2602.12422v1 Announce Type: cross Abstract: Cache replacement remains a challenging problem in CPU microarchitecture, often addressed using hand-crafted heuristics, limiting cache performance. Cache data analysis requires parsing millions of trace entries with manual filtering, making the process slow and non-interactive....
Coden: Efficient Temporal Graph Neural Networks for Continuous Prediction
arXiv:2602.12613v1 Announce Type: new Abstract: Temporal Graph Neural Networks (TGNNs) are pivotal in processing dynamic graphs. However, existing TGNNs primarily target one-time predictions for a given temporal span, whereas many practical applications require continuous predictions, that predictions are issued frequently...
Formalizing the Sampling Design Space of Diffusion-Based Generative Models via Adaptive Solvers and Wasserstein-Bounded Timesteps
arXiv:2602.12624v1 Announce Type: new Abstract: Diffusion-based generative models have achieved remarkable performance across various domains, yet their practical deployment is often limited by high sampling costs. While prior work focuses on training objectives or individual solvers, the holistic design of...
The Jean Monnet Program – The NYU Institutes On The Park
The NYU Institutes On The Park