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Participatory prompting: a user-centric research method for eliciting AI assistance opportunities in knowledge workflows (2312.16633v1)

Published 27 Dec 2023 in cs.HC

Abstract: Generative AI, such as image generation models and LLMs, 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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Authors (8)
  1. Advait Sarkar (25 papers)
  2. Ian Drosos (9 papers)
  3. Rob Deline (1 paper)
  4. Andrew D. Gordon (16 papers)
  5. Carina Negreanu (13 papers)
  6. Sean Rintel (14 papers)
  7. Jack Williams (11 papers)
  8. Benjamin Zorn (7 papers)
Citations (4)
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