How artificial intelligence is changing mental health, ethics, the environment and society — research-backed articles covering both the benefits and risks of AI.
Recent growth in the adoption of Agentic AI technology within organizational workflows and processes holds tremendous promise for productivity gains and the potential to drive disruptive innovation. Unlike traditional AI systems such as Large Language Models (LLMs) that are prompted by humans, Agent
BACKGROUND: Test-time scaling has emerged as a promising method to enhance the reasoning capabilities of large language models (LLMs) and vision-language models (VLMs) during inference without additional training. While foundational studies established scaling paradigms in general domains, their app
Recent growth in the adoption of Agentic AI technology within organizational workflows and processes holds tremendous promise for productivity gains and the potential to drive disruptive innovation. Unlike traditional AI systems such as Large Language Models (LLMs) that are prompted by humans, Agent
BACKGROUND: The aim of this study is to compare the performance of three large language models (ChatGPT 5, Microsoft Copilot, and Google Gemini 3), with that of dental students using their responses to multiple-choice questions (MCQs) in restorative dentistry. Accuracy of responses were analyzed acr
BACKGROUND: Medical and welfare facilities in the Noto region of Japan were severely affected by the 2024 Noto Peninsula earthquake and subsequent torrential rains. Staff working in these facilities were disaster survivors and frontline caregivers with limited psychological support. Nonverbal social
Artificial intelligence (AI) is deeply integrated into daily life. Emerging evidence suggests AI may help change the dynamics of social relationships by influencing social interactions, connectivity, and interpersonal relationships, and by providing new avenues for communication and contributing to
Recent growth in the adoption of Agentic AI technology within organizational workflows and processes holds tremendous promise for productivity gains and the potential to drive disruptive innovation. Unlike traditional AI systems such as Large Language Models (LLMs) that are prompted by humans, Agent
Generative and agentic AI is rapidly reshaping how knowledge workers think, learn, and produce — lifting productivity substantially, with the largest gains concentrated among novices and lower-skilled workers (Brynjolfsson et al., 2025). Yet the same dynamic raises a deeper question: if AI absorbs t
INTRODUCTION/BACKGROUND: To determine whether a prompting-based, interpretable artificial intelligence (AI) system, specifically a large language model (LLM) that applies structured radiographic criteria derived from radiographer training, can approximate Kuwaiti radiographer acceptance-rejection de