Introduction/Overview

Artificial intelligence (AI) is changing social research, offering powerful tools for data collection, analysis, and interpretation. In the current context, there is a significant risk that the integrity of social research as a discipline is compromised by the imperative for speed, efficiency and innovation. There are significant implications in particular for quality control and assurance, as well as for inclusive social research. This training session examines the impacts AI is having on social research and aims to equip social researchers with the toolkits and the frameworks to work with AI reflexively and responsibly.

Critical thinking: We will begin with the foundational principles for social research - and walk through the social researcher’s responsibility for critical thinking and quality assurance, for thoughtful and responsible data stewardship, before considering transparency, compliance and implications for the use of AI in sensitive settings and contexts.

Risk assessment: We will explore the different emergent uses of AI, and implications for its role in social research. Moving beyond those applications and uses, we will walk through protocols for risk assessment for the use of AI in social research - understanding how to assess high, medium and low risk applications.

Research ethics and inclusive research: We will also explore foundational ethical challenges in social research: such as protecting privacy and confidentiality, assessing and mitigating risks, understanding potential social and individual impacts and harms, and ensuring equity in who benefits and who may be affected. In particular, we will look at what it means to centre care and consideration for participants, ensuring inclusive research design in the age of AI.

As this is a fast moving field, this session will combine theory with peer-based action learning sets, that simulate a range of scenarios and involve dynamic peer to peer learning, with structured input from the trainer. Participants will be expected to bring examples of how they have used AI in social research (or seen how AI has been used in social research), to be shared under strict terms of confidentiality.

Topics

The course will cover:

• A recap of the core principles of social research
• An overview of AI’s implications for social research
• Frameworks for thinking critically about the use of AI day to day
• Risk assessment frameworks for evaluating the use of AI in social research
• Implications of AI’s uses for social research ethics
• Dynamic peer to peer sharing and learning of use cases
• Action learning sets, walking through anonymised scenarios, for participants to share how they would manage, assess or evaluate the use of AI in high risk settings

Learning outcomes

By the end of the workshop, participants will:

• Learn to critically evaluate the strengths, limitations, and risks of AI-enabled research methods.
• Apply principles of critical thinking and quality assurance to the use of AI in research processes.
• Demonstrate and exercise the principles of responsible data stewardship, which includes care and stewardship of social research data that will interact with AI systems
• Conduct a structured risk assessment for AI use and management within a social research project.
• Identify and assess ethical risks associated with AI use, particularly in sensitive settings and contexts (‘high risk use cases’), and where appropriate understand where to draw red lines or secure appropriate safeguards in place.
• Recognise and mitigate potential sources of bias, discrimination, and inequity in AI systems and datasets.

Who will benefit?

This course is run as a real-time online tutored course. It combines ‘tutor-led’ sessions, illustrations and case studies, peer mentoring, and practical (breakout group) exercises, and a series of online supporting resources. It is aimed at those with at least a basic understanding of social research methods but who are new to the use of AI in social research.

Course tutor

Reema Patel is a researcher specialising in AI governance, public policy, participation and inclusion, and the responsible use of emerging technologies and founder/director of Elgon Social Research. Reema has worked at the coal face of AI governance since 2016 at the RSA and the Ada Lovelace Institute, later moving into a social research roles at Ipsos UK as their Head of Deliberative Engagement.

She is writing a forthcoming book about AI accountability, (Palgrave MacMillan/Springer, 2026) and is an advisor to the ESRC Digital Good Network and the UKRI funded Sciencewise public engagement programme.

  This course contributes 6 hours to the MRS CPD programme

n.b. This course runs over two consecutive days:

Part 1 - 7 September - 10.00 am to 4.00 pm

Part 2 - 8 September - 10.00 am to 4.00 pm

Looking to book for four or more people from your organisation? Please let us know before booking by emailing: [email protected]