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AI applications for social scientists (SPS-RE-AI-OLS-26)

SPS-RE-AI-OLS-26

Purpose

This course introduces researchers to the use of artificial intelligence tools in social science research, focusing especially on large language models. The first part of the course provides the conceptual background needed to understand and use AI in research. Participants will learn how large language models work in practice, how commercial and locally run models differ, and how choices about models, settings, data, and cost shape what these tools can be used for. 
The second part of the course is more applied. Participants will work with examples of how AI can be integrated into social science research workflows, including research design, data preparation, coding, writing, visualization, and text analysis. The course will also introduce practical ways of working with AI systems beyond standard chat interfaces, including APIs and local models. Across these examples, participants will consider how to assess the quality of AI outputs in practice. This includes checking outputs against other sources, comparing results across models and against human benchmarks, and documenting how AI has been used in the research process.
The course also considers broader questions of ethics, security, and research governance, including the use of sensitive or identifiable data, dependence on commercial providers, bias in model outputs, and the fact that models may change during the course of a project.
 

Description

Syllabus is available here.

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