AI as Co-Pilot in Qualitative Research

Balance the use of AI across your workflow with established research and ethical standards. 

Qualitative social research generates rich, nuanced data, yet the manual burden of transcribing, coding, and synthesising hours of interviews often creates a significant bottleneck. This course provides a comprehensive overview of how researchers are using AI to augment the researcher’s interpretive power. You will explore a wide spectrum of AI applications that are changing and shaping qualitative research - from automated transcription and sentiment analysis to generative AI workflows and agentic AI tools that surface latent themes across vast datasets.

This programme provides an overview of the technical tools, but also moves beyond that overview to address the critical "AI-in-the-loop" necessity of ensuring researchers are positioned to safeguard the integrity and independence of qualitative research. AI brings particular interpretive risks and challenges when it comes to analysing and interpreting qualitative data out of context - and we will explore the implications of those risks for the future of high quality research. We will also explore data privacy, algorithmic bias, and the challenge of maintaining reflexive transparency in an AI-driven and market driven environment. Whether you are conducting ethnographies, focus groups, or policy evaluations, you will learn to assess when and how to use AI tools, and how best to ensure that AI-assisted outputs remain grounded in validity, context, and scholarly rigour.

Learning Outcomes

By attending this course, you will be able to:

• - Identify appropriate AI tools for different stages of the qualitative lifecycle, including data collection, transcription, and thematic analysis.
• - Test and trial prompt engineering for qualitative social research outcomes
• - Create, Evaluate and then Critique AI-generated outputs for qualitative research purposes
• - Understand how core research ethics principles can be adapted in an AI-driven research environment.

Who Will Benefit?

This course is designed for Mid-to-Senior Researchers, Insight Directors, and Data Strategists who already have a basic familiarity or understanding of how generative AI tools (like ChatGPT or Claude) work and are interested in how AI is likely to shape or change the future of the research in future. 

Learning Method

A highly interactive approach, combining hands-on software demonstrations, "clean-room" practice sessions with action learning sets, peer learning and exploring the ethics of AI assisted qualitative research through ‘Socratic dialogue’.

Course Delivery Mode

Online session that combines learning about AI use cases across qualitative social research with high-intensity, interactive, peer to peer action learning; as well as reflexive critical thinking about AI across qualitative social research.

Trainer Biography

Reema Patel has been researching the impacts of AI on sectors and industries since 2015. is a thought-leader in the fields of technology, data and AI ethics, and diversity, equity and inclusion. She founded and established Elgon Social Research, a cutting edge deliberative research agency.? She co-founded the Ada Lovelace Institute where she established its work on public engagement and participation. She is an author of several Ada Lovelace Institute’s reports, including Beyond Face Value, Rethinking Data, The Data Divide and Participatory Data Stewardship among others.