In the rapidly evolving landscape of artificial intelligence, ensuring that generative AI systems adhere to robust standards is crucial. The National Institute of Standards and Technology (NIST), for example, has developed the Generative AI Intelligence Profile, a comprehensive framework designed to guide the development and deployment of generative AI technologies.

In the fast-evolving biopharmaceutical industry, the integration of artificial intelligence (AI) into clinical documentation processes presents an unprecedented opportunity to enhance efficiency and accuracy across the entire value chain. By adopting a technology-agnostic AI system, biopharma companies can significantly streamline operations, reduce costs, and accelerate drug development, ultimately delivering innovative therapies to patients more quickly.

As artificial intelligence (AI) permeates various aspects of life and business, the importance of explainable AI (XAI) grows, particularly in content creation tools—especially when those are being used in a regulated environment. Explainable AI enhances user trust by making the workings of AI systems transparent and comprehensible.

In recent years, lean authoring principles have emerged as a cornerstone for efficient and effective communication. These principles, which emphasize planning, avoiding redundancy, and using precise language, are especially relevant in technical and professional writing.

The World Health Organization (WHO) has long been a guiding force in global health issues, setting standards and offering recommendations to ensure the well-being and safety of populations worldwide.

Artificial intelligence (AI) systems are increasingly integrated into various sectors, including healthcare, finance, and customer service, making their reliability and accuracy critical. However, one lesser-known issue that can arise with AI systems is confabulation (aka hallucinations, fabrications).