REVIEW 1 cited by
Participatory prompting: a user-centric research method for eliciting AI assistance opportunities in knowledge workflows
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original 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.
Forward citations
Cited by 1 Pith paper
-
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.
Discussion (0). Continue with ORCID to comment.