Generative AI in research lights, shadows and key competencies скачать в хорошем качестве

Generative AI in research lights, shadows and key competencies

During this session, participants will learn best practices for integrating AI into their workflows while critically assessing its ethical, methodological, and epistemological implications. Through practical examples and discussions, the session will provide a balanced perspective on how AI is reshaping research practices across disciplines. Key topics covered Understanding the role of generative AI in research Learn how AI can assist with literature reviews, data analysis, and writing support in academic work. Applying best practices for AI integration Discover effective strategies for using AI while maintaining academic rigor and research integrity. Critically assessing AI-generated content Develop skills to evaluate the reliability, biases, and limitations of AI-generated outputs. Navigating ethical and epistemological challenges Explore key ethical concerns, including authorship, transparency, and misinformation in AI-assisted research. Exploring future directions Discuss how AI is evolving in academic research and identify areas where human expertise remains essential. Lecturers Filippo Chiarello, University of Pisa Jelena Dzakula, King's College London