We are delighted to share that Dr Yangting Li and Dr Aqib Siddiqui, LSE Fellows in Information Systems (IS), have been awarded the UK Academy for Information Systems (UKAIS) Early Career Researcher grant for their project, “Responsible LLM Use in Qualitative IS Research.”
“We are delighted and grateful to UKAIS for recognising the importance of this emerging area of research.” Dr Li said. “The grant gives us the opportunity to develop an early-stage idea into a more robust and evidence-informed contribution, while engaging with the wider IS community. For us, as early career researchers, this support is especially meaningful. It provides valuable validation, creates space for collaboration and helps us build a longer-term research agenda around responsible AI and qualitative research practice.”
The project explores what responsible large language models (LLM) use should look like in qualitative IS research. LLMs are increasingly being used in qualitative research, but there is still limited guidance on how researchers can benefit from these tools without obscuring interpretive decisions or weakening scholarly responsibility.
“This is important because the value of these technologies depends not only on what they can do, but also on whether researchers can explain, question and remain accountable for how their findings are produced.” Dr Li continued, “We hope [the project’s] findings will support our community in evaluating and reporting AI-assisted analysis with greater confidence.”
The project will help to establish clearer principles for responsible human-AI collaboration in qualitative research and, more broadly, contribute to ongoing discussions about research rigour, human judgement and responsible AI in academic practice.
The UKAIS aims to foster a better understanding of the IS field within the UK, providing a forum to discuss IS issues and lobby professional bodies.
The Early Career Researcher grant is designed to support early career researchers in developing their independent research profiles, building collaborative networks, and generating high-quality outputs that benefit scholarly knowledge, practice, policy, and the wider IS community.
Thursday 30 July 2026