AI ethics in April 2025

Abstract The integration of artificial intelligence (AI) and machine learning (ML) into cybersecurity has driven a transformational shift, significantly enhancing the ability to detect, respond to, and mitigate complex cyber threats. Traditional defense mechanisms are increasingly inadequate against sophisticated attacks, necessitating the adoption of AI-driven security solutions. This review paper presents a novel, in-depth analysis of state-of-the-art AI and ML techniques applied to intrusion

Large language models (LLMs) show promise in mental health care for handling human-like conversations, but their effectiveness remains uncertain. This scoping review synthesizes existing research on LLM applications in mental health care, reviews model performance and clinical effectiveness, identifies gaps in current evaluation methods following a structured evaluation framework, and provides recommendations for future development. A systematic search identified 726 unique articles, of which 16

Importance: The primary objective of any newly developed medical device using artificial intelligence (AI) is to ensure its safe and effective use in broader clinical practice. Objective: To evaluate key characteristics of AI-enabled medical devices approved by the US Food and Drug Administration (FDA) that are relevant to their clinical generalizability and are reported in the public domain. Design, Setting, and Participants: This cross-sectional study collected information on all AI-enabled me

ABSTRACT The progression of differentiated thyroid carcinoma (DTC) poses significant clinical challenges, especially in determining the optimal time for intervention. To capture early signals of disease progression, we employed an optimized dynamic network biomarker (DNB) method—a systems biology approach that detects abrupt molecular changes indicating a critical transition signal. This analysis revealed that Stage II marks a critical transition in the disease trajectory. We further developed a

IMPORTANCE: The protocol of a randomised trial is the foundation for study planning, conduct, reporting, and external review. However, trial protocols vary in their completeness and often do not address key elements of design and conduct. The SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) statement was first published in 2013 as guidance to improve the completeness of trial protocols. Periodic updates incorporating the latest evidence and best practices are needed to

The protocol of a randomised trial is the foundation for study planning, conduct, reporting, and external review. However, trial protocols vary in their completeness and often do not address key elements of design and conduct. The SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) statement was first published in 2013 as guidance to improve the completeness of trial protocols. Periodic updates incorporating the latest evidence and best practices are needed to ensure that

Abstract Artificial intelligence (AI) technologies are advancing swiftly, both in terms of quantity and quality. Students must possess a solid understanding, abilities, and skills to successfully employ them. Therefore, the purpose of this quantitative study is to examine students’ AI literacy, including AI technological understanding, its practical application, critical appraisal, and its effects on students’ AI output quality, self-efficacy, and academic performance. Moreover, this research ex

Clinical pathogen diagnostics detect targets by qPCR (but with low sensitivity) or blood culturing (but time-consuming). Here we leverage a dual-stem-loop DNA amplifier to enhance non-specific collateral enzymatic cleavage of an oligonucleotide linker between a fluophore and its quencher by CRISPR-CasΦ, achieving ultrasensitive target detection. Specifically, the target pathogens are lysed to release DNA, which binds its complementary gRNA in CRISPR-CasΦ to activate the collateral DNA-cleavage c

The rise of Generative AI (GenAI) in knowledge workflows raises questions about its impact on critical thinking skills and practices.We survey 319 knowledge workers to investigate 1) when and how they perceive the enaction of critical thinking when using GenAI, and 2) when and why GenAI affects their effort to do so.Participants shared 936 first-hand examples of using GenAI in work tasks.Quantitatively, when considering both task-and user-specific factors, a user's task-specific self-confidence

Abstract Artificial intelligence (AI) holds significant potential for enhancing student learning. This reflection critically examines the promises and limitations of AI for cognitive learning processes and outcomes, drawing on empirical evidence and theoretical insights from research on AI-enhanced education and digital learning technologies. We critically discuss current publication trends in research on AI-enhanced learning and rather than assuming inherent benefits, we emphasize the role of i

Abstract As the demand for higher-order thinking skills continues to rise in the 21st century, the integration of Generative Artificial Intelligence (GAI) into educational practices has emerged as a promising tool. However, its full potential in enhancing collaborative problem-solving and team creativity within educational contexts, particularly in Digital Storytelling (DST), remains insufficiently explored. This study investigated the effects of GAI tools, including ChatGPT, Midjourney, and Run

ABSTRACT Legal practice has witnessed a sharp rise in products incorporating artificial intelligence (AI). Such tools are designed to assist with a wide range of core legal tasks, from search and summarization of caselaw to document drafting. However, the large language models used in these tools are prone to “hallucinate,” or make up false information, making their use risky in high‐stakes domains. Recently, certain legal research providers have touted methods such as retrieval‐augmented genera

Background: Digital health interventions have the potential to improve health at a large scale globally by improving access to healthcare services and health-related information, but they tend to benefit more affluent and privileged groups more than those less privileged.Methods: In this narrative review, we describe how this ‘digital health divide’ can manifest across three different levels reflecting inequalities in access, skills and benefits or outcomes (i.e. the first, second, and tertiary

El propósito de este estudio es analizar la aplicación de inteligencia artificial (IA) al personalizar a los estudiantes con necesidades educativas especiales (NEE). Desde la detección de la diversidad cognitiva y emocional social que caracteriza a este grupo de estudiantes, el estudio de las herramientas basadas en AIS se planteó como un eje central para adaptar el contenido, el ritmo, la estrategia y los formatos de aprendizaje a las características individuales de cada estudiante. El estudio

BACKGROUND: To analyze medical students' perceptions, trust, and attitudes toward artificial intelligence (AI) in medical education, and explore their willingness to integrate AI in learning and teaching practices. METHODS: This cross-sectional study was performed with undergraduate and postgraduate medical students from two medical universities in Beijing. Data were collected between October and early November 2024 via a self-designed questionnaire that covered seven main domains: Awareness of

Digital Twin (DT) technology has emerged as a transformative tool in various sectors, like agriculture, due to its potential to improve productivity, sustainability, and decision making processes. This paper provides a comprehensive review of the applications, challenges, and future directions of DT technology in agriculture. We explore the key concepts and architecture of DTs, focusing on the layering and classification of DT systems. The review delves into the various applications of DTs, such

The integration of Artificial Intelligence (AI) into financial services represents a developmental shift in the industry, presenting unprecedented opportunities and challenges. This scientometric review examines the evolution of AI in finance from 1989 to 2024, analyzing its pivotal applications in credit scoring, fraud detection, digital insurance, robo-advisory services, and financial inclusion. The analysis reveals significant trends, particularly the growing adoption of machine learning, nat

Large language models (LLMs) are artificial intelligence (AI) based computational models designed to understand and generate human like text. With billions of training parameters, LLMs excel in identifying intricate language patterns, enabling remarkable performance across a variety of natural language processing (NLP) tasks. After the introduction of transformer architectures, they are impacting the industry with their text generation capabilities. LLMs play an innovative role across various in

Generative artificial intelligence (AI) tools have been selectively adopted across the academic community to help researchers complete tasks in a more efficient manner. The widespread release of the Chat Generative Pre-trained Transformer (ChatGPT) platform in 2022 has made these tools more accessible to scholars around the world. Despite their tremendous potential, studies have uncovered that large language model (LLM)-based generative AI tools have issues with plagiarism, AI hallucinations, an

This is comment on: Hopewell S, et al. CONSORT 2025 explanation and elaboration: updated guideline for reporting randomised trials. BMJ. 2025 Apr 14;389:e081124. https://pubmed.ncbi.nlm.nih.gov/40228832 The CONSORT (2025) statement [1] writes about blinding as follows: “Unblinded outcome assessors may differentially assess subjective outcomes, and unblinded data analysts may introduce bias through the choice of analytical strategies, such as the selection of favourable time points or outcomes an

problems in student retention and critical thinking in 206 vocational education students in the Akwa Ibom State, Nigeria. The results showed that AI posed significant threats to the male students showing more concern than their female peers. While AI aids vocational education, it has the potential to reduce cognitive engagement because the students may accept passively the information provided by AI without critical scrutiny (Ododo et al., 2024). The study emphasizes the need for AI-powered lear

Engineering biology applies synthetic biology to address global environmental challenges like bioremediation, biosequestration, pollutant monitoring, and resource recovery. This perspective outlines innovations in engineering biology, its integration with other technologies (e.g., nanotechnology, IoT, AI), and commercial ventures leveraging these advancements. We also discuss commercialisation and scaling challenges, biosafety and biosecurity considerations including biocontainment strategies, s

Environmental, Social, and Governance (ESG) is highly consistent with the “Dual Carbon” goals proposed by China and has become an important indicator to measure enterprises’ high-quality development. This study explores the impact of intelligent manufacturing on corporate ESG performance and its potential mechanisms. Using the dataset of China’s A-share listed companies from 2009 to 2021, we treat the intelligent manufacturing pilot programs (IMPP) as a quasi-natural experiment and use the stagg

INTRODUCTION: The integration of artificial intelligence (AI) in healthcare has transformed clinical practices and medical education, with technologies like diagnostic algorithms and clinical decision support increasingly incorporated into curricula. However, there is still a gap in preparing future physicians to use these technologies effectively and ethically. OBJECTIVE: This scoping review maps the integration of artificial intelligence (AI) in undergraduate medical education (UME), focusing

Abstract At the heart of medicine lies physician–patient dialogue, where skillful history-taking enables effective diagnosis, management and enduring trust 1,2 . Artificial intelligence (AI) systems capable of diagnostic dialogue could increase accessibility and quality of care. However, approximating clinicians’ expertise is an outstanding challenge. Here we introduce AMIE (Articulate Medical Intelligence Explorer), a large language model (LLM)-based AI system optimized for diagnostic dialogue.

This systematic literature review rigorously evaluates the impact of Generative AI (GenAI) on academic integrity within higher education settings. The primary objective is to synthesize how GenAI technologies influence student behavior and academic honesty, assessing the benefits and risks associated with their integration. We defined clear inclusion and exclusion criteria, focusing on studies explicitly discussing GenAI’s role in higher education from January 2021 to December 2024. Databases in

The rising demand for energy requires high investments in network extensions and renewable sources, alongside replacing inefficient systems. Smart maintenance is important in minimizing unscheduled outages, reducing costs, improving network security, and increasing equipment’s life expectancy. The vast amount of data collected by sensors and measurements in energy networks makes it hard for humans to detect failures continuously. Thanks to recent breakthroughs in AI, the energy sector has booste

Cancer is a major global health concern. Therefore, new treatment options are needed. The phytochemicals have different chemical structures. It also exhibits several other biological activities. Therefore, these compounds are promising anticancer agents. This review aims to identify and assess new candidates for anticancer therapy. Researchers have identified these compounds among the well-studied plant chemicals and their actions. Thus, these compounds can be used in anticancer therapies. The p

The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While Large Language Models (LLMs) have shown promise in general domains, their effectiveness in BioNLP tasks remains unclear due to limited benchmarks and practical guidelines. We perform a systematic evaluation of four LLMs-GPT and LLaMA representatives-on 12 BioNLP benchmarks across six applications. We compare their zer

Large Language Models (LLMs) hold promise for medical applications but often lack domain-specific expertise. Retrieval Augmented Generation (RAG) enables customization by integrating specialized knowledge. This study assessed the accuracy, consistency, and safety of LLM-RAG models in determining surgical fitness and delivering preoperative instructions using 35 local and 23 international guidelines. Ten LLMs (e.g., GPT3.5, GPT4, GPT4o, Gemini, Llama2, and Llama3, Claude) were tested across 14 cl

INTRODUCTION: The rapid integration of digital technologies in healthcare requires healthcare professionals to be digitally ready and capable. This systematic review aims to identify interventions that improve digital readiness and capability among health professionals and to understand the barriers and facilitators they encounter during this digital transformation. METHODOLOGY: A mixed-methods systematic review was conducted following the Joanna Briggs Institute (JBI) guidelines. We searched fi

The emergence of generative artificial intelligence (GenAI) represents a watershed moment in the evolution of digital platforms. The capabilities of this AI technology go beyond traditional AI systems, enabling the autonomous generation of novel outcomes with significant implications for platform value creation, architecture, governance, and stakeholder interactions. We develop an integrative conceptual framework that identifies four key mechanisms through which GenAI transforms digital platform

The landscape of diagnostic testing is undergoing a significant transformation, driven by the integration of artificial intelligence (AI) and machine learning (ML) into decentralized, rapid, and accessible sensor platforms for point-of-care testing (POCT). The COVID-19 pandemic has accelerated the shift from centralized laboratory testing but also catalyzed the development of next-generation POCT platforms that leverage ML to enhance the accuracy, sensitivity, and overall efficiency of point-of-

Abstract With the growing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and sixth-generation (6G) communication networks has emerged as a transformative paradigm. By embedding AI capabilities across various network layers, this integration enables optimized resource allocation, improved efficiency, and enhanced system robust performance. This paper presents a comprehensive overview of AI and communication for 6G networks, with a f

Artificial intelligence chatbots driven by large language models (LLMs) have the potential to increase public science literacy and support scientific research, as they can quickly summarize complex scientific information in accessible terms. However, when summarizing scientific texts, LLMs may omit details that limit the scope of research conclusions, leading to generalizations of results broader than warranted by the original study. We tested 10 prominent LLMs, including ChatGPT-4o, ChatGPT-4.5