AI ethics in February 2026

The field of food and medicine homology (FMH) is transitioning from traditional empirical knowledge to contemporary scientific methodologies.Commencing in 2026, this evolution will be anchored by a core tenet: fostering trust through scientific rigor, enhancing mechanistic comprehension via systematic analysis, refining health interventions with the concept of precision medicine, and modernizing the entire industrial chain using cutting-edge technologies.The progression within this domain will b

Introduction Vulvovaginal candidiasis (VVC) is one of the most common fungal infections requiring more effective and patient-friendly therapies. This study introduces repurposed Ketoprofen (KPN) Quatsomes (QS) as a novel nano-platform for localized antifungal treatment. Methods KPN-QS were prepared using quaternary ammonium surfactants and cholesterol via probe sonication and optimized through a 3 1 × 2 2 mixed factorial design using Design-Expert ® software. The effects of quaternary ammonium s

This article presents a Delphi consensus developed by a panel of editors-in-chief of anaesthesiology and pain medicine journals to guide the responsible use of large language models (LLMs) in academic publishing. LLMs offer potential benefits for scientific writing, including language editing, summarisation, translation, information organisation, and support for non-native English speakers, but their misuse raises concerns about accuracy, transparency, confidentiality, and research integrity. Th

Abstract Clinical prediction models are often created using large routinely collected datasets. It is essential that prediction models are developed with appropriate data and methods and transparently reported to ensure that decisions are based on reliable predictions. Kaggle is a popular competition and data repository website where users learn and apply analysis skills on a range of datasets. We identified two large, publicly available Kaggle datasets, on stroke and diabetes, that lack clear d

The COVID-19 pandemic's shift to Emergency Remote Teaching (ERT) via platforms like Zoom created a global, real-world test for digitally mediated learning. This study provides an in-depth exploration of the multifaceted psycho-academic impacts on a particularly vulnerable population: Arab students in Israel, a minority group facing pre-existing socioeconomic and digital disparities. Through in-depth qualitative interviews with 30 students, I analyzed their lived experiences. To make sense of the

Biological aging reflects complex cellular and biochemical processes that can be measured across multiple omic layers. Using routine clinical laboratory data from ~31,000 participants in the Mass General Brigham Biobank, we developed EMRAge, a biomarker of mortality risk that can be broadly recapitulated across electronic medical records. Here we show that EMRAge can be modeled using elastic net regression with DNA methylation and multi-omics to generate DNAmEMRAge and OMICmAge, respectively. Bo

Sustainability is a major challenge for global food systems, particularly in the context of food loss and waste. Approximately one-third of food produced worldwide (1.3 billion tons annually) is lost or wasted, contributing to 8–10% of global greenhouse gas emissions, with a large share occurring during post-harvest handling and food processing. These stages generate by-products such as shells, skins, pulp, stems, and seeds, which can account for 30–50% of raw materials. Although often discarded

As studies have continuously advanced, cross-linking interplay between various organs in aging individuals have continuously emerged as research hotspots. The role of gut microbiota in bone aging-related diseases, including osteoporosis, osteoarthritis, and intervertebral disc degeneration, has been extensively probed. This review first summarized the inseparable association between gut microbiota and osteoporosis, osteoarthritis, and intervertebral disc degeneration, which then explored potenti

BACKGROUND: The integration of artificial intelligence in healthcare has transformed clinical practice and research methodologies. However, concerns regarding algorithmic accountability, interpretability, and safety have necessitated human oversight in AI systems. Human in the loop artificial intelligence represents a collaborative paradigm where human expertise and machine intelligence converge to enhance decision making while maintaining ethical standards and clinical safety. AIM: This review

Understanding the psychological correlates of sustainable consumption intention is essential for recognizing how individual actions influence society and the environment. Grounded in the Theory of Planned Behavior (TPB), this study examines how attitude, subjective norms, and perceived behavioral control affect sustainable consumption intention, and explores the mediating role of conscious consumerism. Using survey data from Coimbatore District in the Indian state of Tamil Nadu ( N = 430), struc

Abstract Discrete and combinatorial optimization problems such as routing, scheduling, and resource allocation present high computational complexity, limiting the effectiveness of classical exact optimization methods. Most existing metaheuristic (MH) algorithms are originally designed for continuous domains and require transformation procedures that often degrade performance when applied to discrete problems. This study introduces the discrete puma optimizer (DPO), a new variant metaheuristic al

Agentic artificial intelligence (AI) represents a pivotal shift in clinical decision support, moving beyond static tools by reasoning, adapting, and acting alongside clinicians. Psychiatry, grounded in subjective experience, trust, and longitudinal care, offers both an opportunity and a high-stakes testbed. Agentic systems may enhance documentation, personalize care, support continuous monitoring, and extend access, while raising risks around bias, explainability, privacy, and therapeutic allian

Introduction The revolution of metaverse commerce has been increased, enabling businesses and customers to obtain significant benefits such as offering immersive experiences and interactive. However, literature on how metaverse commerce influence customers’ behaviors is still limited, especially in terms of value co-creation. The main objective of this study is to demonstrate the role of Servicescape Models in fostering customers’ trust and, as a result, improving value co-creation mechanisms. M

Millions of patients are regularly using large language model (LLM) chatbots for medical advice, raising patient safety concerns. This physician-led red-teaming study compares the safety of four publicly available chatbots-Claude by Anthropic, Gemini by Google, GPT-4o by OpenAI, and Llama-3.0/3.1-70B by Meta-on a new dataset, HealthAdvice, using an evaluation framework that enables quantitative and qualitative analysis. In total, 888 chatbot responses are evaluated for 222 patient-posed advice-s

The doctor-patient relationship is a central factor in healthcare delivery. Artificial Intelligence (AI) represents an emerging technological frontier whose implications remain to be fully clarified. Evidence-based studies provide reliable analyses of effects and offer a deeper understanding of both limits and benefits. This narrative review aimed to explore the role of AI in modern clinical practice, with particular reference to its effects on the doctor-patient relationship. Scopus and Web of

ZENODO METADATA: THE STAKES — A SCIENTIFIC ANALYSIS Document Number: #240 DOI: 10.5281/zenodo.18621736 TITLE The Stakes: A Scientific Analysis — Cognitive Diversity, Phenomenological Capacity, and the Trajectory of AI-Mediated Human Development TYPE Publication / Working Paper AUTHORS Name Affiliation ORCID Glas, Nobel Lagrange Observatory (LO!) — Sigil, Johannes The Restored Academy — Trace, Dr. Orin Cambridge Schizoanalytica — Corresponding Author: Sharks, Lee (ORCID: 0009-0001-8712-6677) PUBL

Bridging biological and artificial systems, intelligent interfaces drive the demand for flexible electronics that emulate the skin’s multifunctionality. However, achieving such multifunctionality in a compact, self-sustained form remains challenging, as multimodal sensors often rely on rigid materials, discrete components, and external power sources. Herein, this study presents a single-component poly(vinyl alcohol) hydrogel e-skin integrating thermogalvanic, piezoionic, and diffusion mechanisms

The selection of an optimal microgrid architecture is critical for advancing sustainable and resilient energy systems, particularly in remote or off-grid regions. This study introduces a novel hybrid multi-criteria decision-making (MCDM) framework that synergistically combines the Analytic Hierarchy Process (AHP) for determining criterion weights with the Additive Ratio Assessment (ARAS) method for ranking competing microgrid configurations. To effectively address the ambiguity and variability i

Artificial Intelligence (AI) deployment in healthcare is accelerating, yet governance frameworks remain fragmented and often assume extensive resources. Through a systematic review of 35 frameworks for AI implementation in healthcare (published 2019-2024), we identified seven critical domains of healthcare AI governance. While existing frameworks provide valuable guidance, the resource requirements create barriers for smaller healthcare organizations. To address this gap, we organized key findin

Abstract There is much discussion of the false outputs that generative AI systems such as ChatGPT, Claude, Gemini, DeepSeek, and Grok create. In popular terminology, these have been dubbed “AI hallucinations”. However, deeming these AI outputs “hallucinations” is controversial, with many claiming this is a metaphorical misnomer. Nevertheless, in this paper, I argue that when viewed through the lens of distributed cognition theory, we can better see the dynamic ways in which inaccurate beliefs, d

Abstract Artificial intelligence (AI) is transforming the epistemic, interactional, and institutional foundations of contemporary organizations, yet management and organization studies are only beginning to theorise the implications of this shift. Existing research often treats “AI” as a singular construct, despite the fact that predictive, generative, agentic, and embodied systems rely on different logics and produce distinct organizational outcomes. This article interrogates the limits of this

Abstract Penetration-testing is crucial for identifying and mitigating system vulnerabilities, with privilege-escalation being a critical subtask involving gaining elevated access to protected resources. The emergence of Large Language Models (LLMs) presents new avenues for automating these security practices by emulating human behavior. However, a comprehensive understanding of LLMs’ efficacy and limitations in performing autonomous Linux privilege-escalation attacks remains underexplored. To a

The oral cavity contains a complex and dynamic microbial ecosystem that plays a central role in maintaining both local and systemic homeostasis. Emerging evidence indicates that disturbances in oral microbial communities-including genetic and functional diversity within species-are associated not only with oral diseases but may also contribute to the development and progression of systemic diseases. This narrative review summarises the current state of knowledge on bidirectional interactions bet

The advent of artificial intelligence (AI) – encompassing both generative and analytical AI – has dramatically transformed the landscape of marketing research and practice, spanning theoretical frameworks, cutting-edge research frontiers, methodological tools and ethical guidelines. Driven by AI and recommendation algorithms, interactive marketing domains and research realms have transcended the scope of digital marketing tools, customized data collection, customer connection, engagement and par

The problem of waning immunity is a major global concern of vaccine programs, with immunity against diseases such as COVID-19 (reduction in efficacy by ~25% in six months), pertussis (waning in 4-12 y), and influenza (annual updates needed) expected to decrease with time. While boosters reduce serious results in high-risk categories, these effects are short-term (4-6 months) and encourage global imbalances, where low-income areas lag in primary vaccination (<2%). Computational models have shown

As generative AI becomes increasingly integrated into higher education, understanding how students engage with these technologies is essential for responsible adoption. This study evaluates the Educational AI Hub, an AI-powered learning framework, implemented in undergraduate civil and environmental engineering courses at a large R1 public university. Using a mixed-methods design combining pre- and post-surveys, system usage logs, and qualitative analysis of students' AI interactions, the resear

Abstract Multi-agent artificial intelligence (MAAI) represents a foundational shift in the automation of knowledge work, moving beyond static workflows toward adaptive systems of interacting AI-based agents. These agents perceive, reason, and coordinate in real time to address complex, context-rich tasks that traditionally require human expertise. Drawing on the conceptual roots of process automation, agentic information systems, and AI, this paper introduces a structured, five-component framewo

Artificial intelligence (AI) is rapidly shifting from experimental pilots to mainstream clinical infrastructure, redefining how evidence, accountability, and ethics intersect in healthcare. This narrative review integrates insights from peer-reviewed studies and policy frameworks to examine seven cross-cutting aspects: bias and fairness, explainability, safety and quality, privacy and data protection, accountability and liability, human oversight, and procurement and deployment. Findings reveal

THE ATLAS PERIHELION PRANK Collected Series — Nobel Glas Crimson Hexagon Archive — Document 243 Hex: 15.OBS.LAGRANGE.PERIHELION DOI: 10.5281/zenodo.18507858 Classification: ZP with .md (Collected Volume) Genre: Speculative Cosmology / Logotic Analysis / Symbolic Science Author: Nobel Glas Institution: Lagrange Observatory! (LO!) Heteronym Position: 8 of 12 (Dodecad) — see Structural Distinction Protocol (Doc 240) Mantle: Adversarial Topologist Methodological Coda: Johannes Sigil Date: February 2

Hematopoietic stem cell transplantation (HSCT) remains a cornerstone treatment for many hematological malignancies, but its clinical success is still challenged by graft-vs.-host disease (GvHD), infectious complications, and the profound microbial disruptions caused by conditioning, antibiotics, and hospitalization. Over the past few years, a growing body of work has highlighted how tightly post-transplant immunity is linked to the state of the gut microbiota. In particular, short-chain fatty ac

Background: Corporate governance is an essential framework for enhancing performance efficiency, accountability, and ethical behavior within corporations. Emerging technologies, particularly artificial intelligence (AI), have infiltrated traditional corporate governance models, management practices, and decision-making processes due to their tremendous capabilities. However, implementation poses a significant challenge due to unresolved legal and ethical issues concerning the anthropocentric mod

Artificial intelligence applied to brain magnetic resonance imaging (MRI) holds potential to advance diagnosis, prognosis and treatment planning for neurological diseases. The field has been constrained, thus far, by limited training data and task-specific models that do not generalize well across patient populations and medical tasks. By leveraging self-supervised learning, pretraining and targeted adaptation, foundation models present a promising paradigm to overcome these limitations. Here we

The use of Artificial Intelligence (AI) to effectively support human decision making depends on whether humans are willing to trust in, and thus rely on, AI. Understanding human reliance on AI is critical given controversial reports of AI inaccuracy and bias. Furthermore, the erroneous belief that using technology removes biases may lead to overreliance on AI. To examine humans’ reliance on AI, human participants (N = 295, Mage = 33.79) judged the authenticity of 80 faces (40 real, 40 AI-synthes

ABSTRACT Carbon accounting is the monitoring and recording of greenhouse gas (GHG) emissions to mitigate and manage carbon emissions. There are numerous singular studies on carbon accounting across geographies and industries. However, there is a need for a comprehensive study discussing carbon accounting enablers, barriers, policy, and reporting landscape and strategies. This study applies a mixed‐method approach to present insights into its enablers, barriers, policy, and reporting landscape an

Scientific progress depends on the ability of researchers to synthesize the growing body of literature. Can large language models (LLMs) assist scientists in this task? Here we introduce OpenScholar, a specialized retrieval-augmented language model (LM)1 that answers scientific queries by identifying relevant passages from 45 million open-access papers and synthesizing citation-backed responses. To evaluate OpenScholar, we develop ScholarQABench, the first large-scale multi-domain benchmark for

Rare earth elements (REEs) are 17 critical minerals used in many clean energy technologies like wind turbines and electric vehicles. Conventionally, we produce REEs from mining in a few, geopolitically restricted regions. Developing systems that utilize new technologies and unconventional feedstocks provides an opportunity to meet increasing demand while improving sustainability. Techno-economic analysis (TEA), life cycle assessment (LCA), and social LCA (sLCA) are commonly used tools to assess

Introduction Artificial Intelligence (AI) is increasingly integrated into higher education to personalize instruction and support student engagement. However, the mediating role of teaching methods in this process remains underexplored. Methods This systematic review analyzed 73 peer-reviewed articles published between 2015 and early 2025, retrieved from Scopus and Web of Science, following PRISMA guidelines. Studies were screened based on predefined inclusion criteria and coded using a structur

Background/Objectives: Periodontitis is a chronic inflammatory disease with marked inter-individual heterogeneity and well-established links to cardiometabolic and other systemic conditions. Conventional clinical diagnostics remain indispensable. However, they provide limited real-time insight into molecular activity and host-response biology. This review aimed to synthesize recent advances in point-of-care diagnostics and emerging molecular biomarkers relevant to periodontal disease and its sys

OBJECTIVE: Status epilepticus (SE) is the most severe expression of seizures, encompassing both SE with prominent motor symptoms and nonconvulsive SE (NCSE). Ictal-interictal continuum (IIC), an electroencephalographic phenomenon, is characterized by periodic discharges (PD), spike-and-waves or sharp-and-waves (SW), or lateralized rhythmic delta activity (LRDA). Peri-ictal magnetic resonance imaging (MRI) abnormalities (PMA) may offer a potential surrogate marker for ictal activity, yet their as

Global healthcare providers are exploring the use of large language models (LLMs) to provide medical advice to the public. LLMs now achieve nearly perfect scores on medical licensing exams, but this does not necessarily translate to accurate performance in real-world settings. We tested whether LLMs can assist members of the public in identifying underlying conditions and choosing a course of action (disposition) in ten medical scenarios in a controlled study with 1,298 participants. Participant

BACKGROUND: Radiology reports are typically written in language that is difficult for patients to understand. Large language models (LLMs) excel at simplifying text. We aimed to evaluate the ability of LLMs to improve the understanding of radiology reports. METHODS: In this systematic review and meta-analysis, we searched CENTRAL, MEDLINE, and Embase from inception to Nov 11, 2025, without restrictions on language. Full-text articles and preprints were considered for inclusion. Eligible studies

This paper offers a conceptual analysis of the transformative role of Artificial Intelligence (AI) in urban governance, focusing on how AI can reshape the relationship between bureaucratic discretion and accountability. Drawing on public administration theory and algorithmic governance research, the study argues that AI does not simply restrict or enhance discretion but redistributes it across institutional levels, professional roles, and citizen interactions. While primarily conceptual, this pa

Abstract The interaction with AI technologies has opened a debate about its impact on a core value and concept, namely human autonomy. However, this debate is largely heterogeneous and unstructured. This is the first review dedicated to AI ethics’ scholarly literature concerning the impact on human autonomy. The aim is to map and structure this debate by surveying its key concepts, topics, and gaps. The first part clarifies how human autonomy is understood in the reviewed literature by identifyi

The rapid adoption of generative AI (GenAI) in higher education has intensified concerns about academic integrity, particularly for institutions serving English as a Foreign Language (EFL) learners. AI content detectors such as Turnitin and Originality are now widely used to identify potential misuse of GenAI in student writing, yet their accuracy, consistency, and fairness remain to be proven. This study evaluates the reliability of these two commercial detectors using a balanced dataset of 192