AI ethics on Friday, 9 January 2026

Introduction: Artificial intelligence (AI) technology has significantly changed human work. Increasingly, organizations are promoting the integration of AI into employees' work processes. While existing research has explored AI applications in the workplace, relatively little attention has been devoted to understanding how organizational AI adoption influences employees' motivational reactions and the subsequent impacts. Drawing on approach-avoidance motivational theory, this research explores t

This manifesto presents the theoretical and operational foundation of the Ze System—a radical framework for the scientific investigation of latent reality. Moving beyond the paradigm of passive observation, it posits that a substantial portion of reality exists in an unmanifested, wave-like state of potentialities, statistical shadows, and distributed correlations. Ze redefines scientific inquiry as an active, provocative engagement with this latent field. Its core thesis is that the hidden is n

As AI-based technologies such as ChatGPT are increasingly used across various sectors, understanding how people conceptualize artificial intelligence (AI) is crucial for anticipating public response and developing AI technologies responsibly 1. We hypothesize that public perceptions of AI are rapidly evolving, and that these perceptions inform not only how people use AI, but also the extent to which they trust it and the role they believe it should play in their lives - if at all. However, belie

Background: Diabetic kidney disease (DKD) is a major microvascular complication of diabetes, often progressing silently and leading to end-stage kidney disease (ESKD) and cardiovascular morbidity. Early identification and risk-adapted intervention are crucial to improving long-term outcomes, yet existing clinical workflows are limited by delayed diagnosis and underutilization of available therapies. Methods: We propose and evaluate a multimodal, risk-driven framework for the early recognition an

Abstract Exponential growth in scientific literature has heightened the demand for efficient evidence-based synthesis, driving the rise of the field of automated meta-analysis (AMA) powered by natural language processing and machine learning. This PRISMA systematic review introduces a structured framework for assessing the current state of AMA, based on screening 13,216 papers (2006–2024) and analyzing 61 studies across diverse domains. Findings reveal a predominant focus on automating data proc

The severe shortage of donor organs and limitations of current disease models highlight the urgent need for transformative strategies in tissue engineering (TE) and regenerative medicine (RM). Bioprinting has emerged as a powerful approach for creating functional tissues and organs, yet current workflows remain labor-intensive, variable, and challenging to scale. The convergence of artificial intelligence (AI), advanced bioprinting technologies, robotics, biosensing, and cutting-edge biological

Over the last 15 years, mixture risk assessment for food xenobiotics has evolved from conceptual discussions and simple screening tools, such as the Hazard Index (HI), towards operational, component-based and probabilistic frameworks embedded in major food-safety institutions. This review synthesizes methodological and regulatory advances in cumulative risk assessment for dietary "cocktails" of pesticides, contaminants and other xenobiotics, with a specific focus on food-relevant exposure scenar