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Short abstract

A creative intervention that embeds critical AI literacy and ethics into postgraduate research methods training. Through reflective exercises such as data flow mapping and speculative futures research design, it examines assumption of neutrality, expertise and technosolutionist attitudes.

Long abstract

This creative intervention aims at embedding critical AI literacy and AI ethics into a research method training context. Research students across levels currently turn to AI tools in order to automate aspects of the entirety of the research process, from undergrads who dive deep into research design when they tackle a dissertation, or more researchers are lured by the ease of automation. As higher education policies focus on adoption (AI as set of tools) and plagiarism (AI as cheating), there is less time and energy spent in understanding the critical issues that underlie AI use, its ethics and epistemological implications. This intervention addresses the need to enhance awareness of AI as an actor in the production of knowledge, and to develop literacy about the ideological, political and economic stakes of AI infrastructure globally. It consists of a pilot lasting for one term in a postgrad setting (MA in Strategic Communication) in a course on applied research methods. The critical AI exercises are reflective and structured around milestones, while the collection of data concern three pillars: assumptions of neutrality, perceptions of expertise, and attitudes of technosolutionism. The exercises include a mapping of data flows and a speculative futures research design (where participants create a future research pipeline scenario with and without use of AI). The aim is to create an AI ethics and critical skills toolkit that can be adapted more widely in research training across disciplines. In the EEAST session, my focus will be on introducing this replicable framework.