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.
Participatory prompting: a user-centric research method for eliciting AI assistance opportunities in knowledge workflows
1 Pith paper cite this work, alongside 3 external citations. Polarity classification is still indexing.
abstract
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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cs.HC 1years
2025 1verdicts
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unclear 1representative citing papers
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What Does Success Look Like? Catalyzing Meeting Intentionality with AI-Assisted Prospective Reflection
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.