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 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.
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.
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.
It is found that most LLMs do not memorize most books -- either in whole or in part, but it is also found that Llama 3.1 70B entirely memorizes some books, like the first Harry Potter book and 1984.
Using cadaveric images in anatomy textbooks is appropriate, and no additional consent should be necessary, and such usage falls within the good faith of professionals using these invaluable gifts.
A synthesis of 141 binding policies applicable to AI in healthcare and population health in the EU and 10 European countries is presented, which has already formed a baseline regulatory framework for AI in health.
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.
Although there is a consensus that RAI practices are a necessity, their implementation in real-world is still in its early day and the involvement of all relevant stakeholders is irreplaceable in driving and shaping RAI practices.
This paper proposes CoTaEval, an evaluation framework to assess the effectiveness of copyright takedown methods, the impact on the model's ability to retain uncopyrightable factual knowledge from the training data whose recitation is embargoed, and how well the model maintains its general utility and efficiency.
A typology is proposed that distinguishes the different stages of the AI life-cycle, the high-level ethical principles that should govern their implementation, and the tools with the potential to foster compliance with these principles, encompassing both technical and conceptual resources.
It is posits that the banking sector must embrace a holistic and adaptive approach to cybersecurity, underscored by strategic investments in technology, education, and collaboration to navigate the evolving cyber threat landscape effectively.
This paper analyses the implications of AI penetration in the public sector, as well as the challenges that these technological developments pose to SAIs to improve effectiveness and efficiency in their auditing tasks.
Critical analysis from various perspectives with a recurring theme of the growing impact that generative deep learning techniques are beginning to have on FDeID and related areas such as gait de-identification are offered.
This study conducts a systematic analysis of existing Data Governance Frameworks, identifying the crucial assets as well as components, and provides a mapping between them to set a base that enables the development of a comprehensive Data Governance Framework tailored specifically for Data Trusts.
The document outlines the directions for scientific-expert, normative activities, and international cooperation, and it explores collaborative agreements with scientific and regulatory institutions, paving the way for innovative practices that further improve public health outcomes and safety standards.
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.
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.
It is recommended that educators introduce AI as one tool among many in the designer’s toolkit and encourage it to be used as a process tool rather than for generating final design deliverables.
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