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