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Participatory prompting: a user-centric research method for eliciting AI assistance opportunities in knowledge workflows

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arxiv 2312.16633 v1 pith:EPM55CGF submitted 2023-12-27 cs.HC

classification cs.HC
keywords generativeworkflowsopportunitiespromptingend-usermethodparticipatoryeliciting
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Generative AI, such as image generation models and large language models, stands to provide tremendous value to end-user programmers in creative and knowledge workflows. Current research methods struggle to engage end-users in a realistic conversation that balances the actually existing capabilities of generative AI with the open-ended nature of user workflows and the many opportunities for the application of this technology. In this work-in-progress paper, we introduce participatory prompting, a method for eliciting opportunities for generative AI in end-user workflows. The participatory prompting method combines a contextual inquiry and a researcher-mediated interaction with a generative model, which helps study participants interact with a generative model without having to develop prompting strategies of their own. We discuss the ongoing development of a study whose aim will be to identify end-user programming opportunities for generative AI in data analysis workflows.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 3 citations worldwide. Full citation record

  1. What Does Success Look Like? Catalyzing Meeting Intentionality with AI-Assisted Prospective Reflection

    cs.HC 2025-05 conditional novelty 6.0 of 10

    A study with 18 employees found that a generative AI Meeting Purpose Assistant can help people clarify meeting goals, anticipate challenges, and change how they prepare, with social and technical barriers to adoption.

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