The challenges of regional regulatory disparities, systemic vulnerabilities identified through major health data breach case studies, and the potential of advanced technologies to enhance privacy protections are examined, focusing on the GDPR, CCPA, and POPIA.
This guideline summarizes updated safety data (2017–2025) and provides expert recommendations on the use of low intensity transcranial electrical stimulation (tES) in humans and recommends using screening and AE questionnaires in future controlled studies, in particular when planning to extend the stimulation parameters applied.
The role of DTs in personalized medicine, from pre-clinical research to post-marketing, while addressing technological, legal, and ethical challenges in implementation is explored.
This work investigates whether extraction of (in-copyright) training data remains a risk for production LLMs using a two-phase procedure, and measures extraction success with a score computed from a block-based approximation of longest common substring (nv-recall).
This work introduces CBR-RAG, where CBR cycle's initial retrieval stage, its indexing vocabulary, and similarity knowledge containers are used to enhance LLM queries with contextually relevant cases, and presents an evaluation of CBR-RAG.
This work develops a technique to measure memorization of books, and finds that most LLMs do not memorize most books -- either in whole or in part; however, there are notable exceptions.
This research explores how university settings that prioritise knowledge—real, shared, and thoughtfully managed—can help students become more aware of these dimensions and shows that when knowledge is genuinely valued, governance practices around AI tend to develop more clearly.
The use of HMWDs in clinical and research settings raises several ethical and legal concerns, ranging from patient safety to autonomy, justice, and data protection, which may lead to dehumanization and datafication of care relationships and further marginalization of vulnerable populations.
The research investigates epistemological and theological considerations related to the application of machine learning algorithms in interpreting sacred Islamic texts, proposing that AI applications adhere to principles of justice, transparency, and the preservation of human dignity and autonomy.
While GPT-4’s report is a step towards open discussions on LLMs, more extensive interdisciplinary reviews are essential for addressing bias, harm, and risk concerns, especially in high-risk domains.
This study advances the ongoing discourse on deepfake technology by providing stakeholders and policymakers with evidence-based recommendations aimed at mitigating the associated risks and harnessing potential benefits, and promotes a balanced and informed approach to navigating the complexities of this emerging technological challenge.
The need for collaboration among stakeholders and the development of comprehensive legal and regulatory frameworks to address the challenges and ensure the successful implementation of blockchain technology in various sectors is discussed.
A comprehensive global review of privacy legislation and enforcement mechanisms, shedding light on the challenges posed by the digital age, and investigates the effectiveness of enforcement mechanisms in ensuring compliance with privacy laws.
The goal in this article is to survey the key areas necessary to perform auditing and assurance and instigate the debate in this novel area of research and practice and anticipate the nature and scope of the auditing levels and framework presented will inform those interested in systems of governance and compliance with regulation/standards.
The regulatory landscape for MDSW and AI-driven MDSW is outlined, clarifying the responsibilities of laboratory professionals and manufacturers under the In Vitro Diagnostic Regulation (IVDR), ISO 15189:2022, and the Artificial Intelligence Act.
A participatory AI approach is adopted to derive key questions based on Article 52’s disclosure obligations to help inform future legal developments and interpretations of Article 52 and provide a starting point for Human-Computer Interaction research to (re-)examine disclosure transparency from a human-centered AI lens.
A three-phase lifecycle (training, real-world testing and post-marketing monitoring) to align regulatory burdens with AI maturity is proposed and a transparent protocol design with explicit data-use declarations is proposed, with particular attention to the early research phases.
A survey of the emerging field of legal alignment that aims to fill this gap and systematize research that studies how legal rules, principles, and methods can be leveraged to address problems of alignment and inform the design of AI systems that operate safely and ethically.
It is examined why utilization review has attracted so much AI innovation and why it is challenging to ensure responsible use of AI, and several steps that could be taken to help realize the benefits of AI use while minimizing risks.
A modular multi-agent framework that decomposes legal reasoning into distinct knowledge acquisition and application stages is introduced, suggesting that modular architectures with formalized knowledge representations can make sophisticated legal reasoning more accessible through computationally efficient models while enhancing consistency and explainability in AI legal reasoning.
In geology, AI’s potential for reducing drilling costs and improving safety, as well as its application to other areas like mining and construction, will drive significant advancements in scientific and industrial fields.
This paper examines ethical, legal, and social issues (ELSI) associated with healthcare digital twins (DTs) and provides practical recommendations for how this can be achieved, with specified stakeholder groups, to help build trustworthy and ethical DTs with demonstrable healthcare value.
Article Galaxy Pages is a free service from Research Solutions, a company that offers access to content in collaboration with publishing partners, online repositories and discovery services.