SciTech & AI Series: Literature Never Sleeps: Staying Ahead Without Burning Out

Welcome to Episode 2 of the SciTech Critical Evaluation of Literature and AI Series: “Literature Never Sleeps: Staying Ahead Without Burning Out"Literature never sleeps and neither do the challenges of keeping Medical Affairs teams up to date.Join experts from the MAPS Scientific & Technical Knowledge Domain to discover practical strategies for managing the deluge of data. We’ll explore how AI can accelerate evidence synthesis while highlighting its limitations and the critical role of human judgment. If you’re looking for smarter ways to stay current, this podcast is for you!Learning Objectives:Identify key challenges in keeping Medical Affairs teams currentUnderstand the impact of preprints, grey literature, bibliometrics, and predatory journals on evidence appraisal.Evaluate the role and limitations of AI in literature reviewRecognize how AI can accelerate evidence evaluation while appreciating the need for human judgment and safeguards against errors.Apply best practices for confidentiality and critical assessment of AI outputsLearn practical steps to ensure secure data handling and train teams to validate AI-generated insights effectively.Hear more from the Scientific & Technical Knowledge Domain through their position paper: "Safeguarding Scientific Rigor in the Critical Evaluation of Literature"