Living Guide of AI in the Behavioural Research Process
AI can assist in multiple stages of the research process, from literature reviews to data analysis and report writing. It has the ability to enhance the work we are doing, making daily tasks simpler and less onerous, but there are some things to consider before starting a project.
Not sure where to start? If you do not have a specific research task or AI tool in mind, check out these resources:
- Caltech Science Exchange — what AI is and what it can do.
- AI and the future of behavioural science — LSE public event on how AI is already changing the field.
- Can Generative AI improve social science? — Bail (2024), PNAS.
Jump to a stage of your research
Each sub-page covers a specific stage of the research lifecycle, with tools, real examples, and key references.
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Background Research & Evidence Synthesis
Find and map relevant papers, then use AI responsibly in systematic reviews.
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Hypothesis Generation & Study Design
Refine research questions, generate hypotheses, and design surveys or interventions.
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Data Collection & Processing
Use chatbots, transcription tools, and synthetic data to collect and clean data.
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Data Analysis & Interpretation
Analyse qualitative and quantitative data with AI-powered tools and LLMs.
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Writing & Reporting
Draft, edit, cite, and disseminate research with AI support — responsibly.
A Note on Responsible Use
We advocate for a human-in-the-loop approach with thorough testing and careful evaluation of AI methods. Researchers should explore AI's capabilities responsibly, aware of benefits and inherent challenges — see Section 2 and the Section 5 BR-UK AI Statement for responsible use of AI.