most cited"It's like a rubber duck that talks back": Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Study

28 citations · 37 across the 3 of their papers we have counts for

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cs.HC20257 cited

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

Ava Elizabeth Scott, Lev Tankelevitch, Payod Panda +3

Despite decades of HCI and Meeting Science research, complaints about ineffective meetings are still pervasive. We argue that meeting technologies lack support for prospective refl…

cs.HC2024

The Future of Skill: What Is It to Be Skilled at Work?

Axel Niklasson, Sean Rintel, Stephann Makri +1

In this short paper, we introduce work that is aiming to purposefully venture into this mesh of questions from a different starting point. Interjecting into the conversation, we wa…

cs.HC202428 cited

"It's like a rubber duck that talks back": Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Study

Ian Drosos, Advait Sarkar, Xiaotong Xu +3

Generative AI tools can help users with many tasks. One such task is data analysis, which is notoriously challenging for non-expert end-users due to its expertise requirements, and…

cs.HC20241 cited

Mental Models of Meeting Goals: Supporting Intentionality in Meeting Technologies

Ava Elizabeth Scott, Lev Tankelevitch, Sean Rintel

Ineffective meetings due to unclear goals are major obstacles to productivity, yet support for intentionality is surprisingly scant in our meeting and allied workflow technologies.…

cs.HC20248 cited

Ironies of Generative AI: Understanding and mitigating productivity loss in human-AI interactions

Auste Simkute, Lev Tankelevitch, Viktor Kewenig +3

Generative AI (GenAI) systems offer opportunities to increase user productivity in many tasks, such as programming and writing. However, while they boost productivity in some studi…