Intent Tagging: Exploring Micro-Prompting Interactions for Supporting Granular Human-GenAI Co-Creation Workflows

要旨

Despite Generative AI (GenAI) systems' potential for enhancing content creation, users often struggle to effectively integrate GenAI into their creative workflows. Core challenges include misalignment of AI-generated content with user intentions (intent elicitation and alignment), user uncertainty around how to best communicate their intents to the AI system (prompt formulation), and insufficient flexibility of AI systems to support diverse creative workflows (workflow flexibility). Motivated by these challenges, we created IntentTagger: a system for slide creation based on the notion of Intent Tags—small, atomic conceptual units that encapsulate user intent—for exploring granular and non-linear micro-prompting interactions for Human-GenAI co-creation workflows. Our user study with 12 participants provides insights into the value of flexibly expressing intent across varying levels of ambiguity, meta-intent elicitation, and the benefits and challenges of intent tag-driven workflows. We conclude by discussing the broader implications of our findings and design considerations for GenAI-supported content creation workflows.

著者
Frederic Gmeiner
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Nicolai Marquardt
Microsoft Research, Redmond, Washington, United States
Michael Bentley
Microsoft, Redmond, Washington, United States
Hugo Romat
Microsoft, Seattle, Washington, United States
Michel Pahud
Microsoft Research, Redmond, Washington, United States
David Brown
Microsoft Research, Redmond, Washington, United States
Asta Roseway
Microsoft Research, Redmond, Washington, United States
Nikolas Martelaro
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Kenneth Holstein
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Ken Hinckley
Microsoft Research, Redmond, Washington, United States
Nathalie Riche
Microsoft Research, Redmond, Washington, United States
DOI

10.1145/3706598.3713861

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713861

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Human-AI Collaboration

G304
7 件の発表
2025-05-01 01:20:00
2025-05-01 02:50:00
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