Mathematics has always been driven by human curiosity and insight. But a quiet revolution is underway: artificial intelligence is beginning to help mathematicians discover new ideas, find hidden patterns, and even prove theorems.

In this talk, I will share some of the most exciting recent developments at the intersection of AI and mathematics — including my own research experience — and explore what this means for the future of discovery.

No technical background is required. This is a story for anyone curious about where one of the oldest sciences is heading in the age of intelligent machines.

Foundation models, including large language models, have very great potential for innovation in STEM subjects. This talk introduces research with examples from the field of medical AI physical sciences, including the uses of AI throughout the pipeline of STEM research: hypothesis generation, methodological research, and technology-transfer into real-world applications.

The role of AI in social sciences and humanities research is contested today. While many see AI as useful for conducting data analyses, literature reviews, and manuscript editing, students and scholars need to be aware of several significant ethical considerations when using AI in social sciences and humanities.

This presentation examines ethical risks involved with using AI in the social sciences and humanities. After providing an overview of some of the major ethical issues involved in using AI in conducting research in the social sciences and humanities, final reflections are provided regarding best practices in research and research training.

Generative AI (GenAI) has become an integral tool across the research lifecycle, prompting universities and organizations worldwide to develop GenAI-related guidelines and frameworks. However, significant gaps remain between awareness, policy development, and governance.

Drawing from current frameworks and emerging governance approaches, this talk explores the evolving landscape of GenAI and Responsible Conduct of Research (RCR), with insights from institutional experiences in the Southeast Asia region. This talk will examine key governance challenges, while reflecting on how institutions may begin translating broad policy frameworks into meaningful and responsible research practice.

Generative artificial intelligence (GenAI) is increasingly reshaping scholarly publishing, from translation and language editing to summarisation, drafting, formatting, and editorial workflow support. While GenAI tools promise efficiency and accessibility, their disruptive capacity to draw on training data and sources (sometimes of uncertain quality or copyright status) to generate content that mimics the conventions of scholarly work raises urgent ethical questions.

This session will examine four interconnected themes: responsible and ethical use of GenAI; transparency and disclosure; impact on editorial and peer review standards; and use of detection tools. Potential benefits, as well as risks such as breaches of confidentiality and privacy, bias and misinformation, misappropriation, over‑automation, false accusations, and inequitable access will be considered. By situating GenAI within COPE’s roles of promoting integrity, transparency, and accountability, the session will highlight governance frameworks and practical strategies to responsibly integrate GenAI into workflows and ensure it strengthens rather than undermines the values underpinning scholarly and research publication.

The overarching principle is clear: GenAI should be treated as a supportive tool that complements, but never replaces, human judgement or ethical conduct. Authorship, peer review, editorial decisions, and integrity determinations must remain human responsibilities, carried out with honesty, fairness, and accountability.