Colleen Seifert

schoolUniversity of Michiganbar_chart#2356 Global Rank

Total Papers

HCI Rank

#2356

Research Areas

Years Active

Recent Publications

Bridging the Gulf of Envisioning: Cognitive Challenges in Prompt Based Interactions with LLMs

Large language models (LLMs) exhibit dynamic capabilities and appear to comprehend complex and ambiguous natural language prompts. However, calibrating LLM interactions is challenging for interface designers and end-users alike. A central issue is our limited grasp of how human cognitive processes begin with a goal an…

CHI '223rd AuthorHuman-LLM Collaboration +3

Solving Separation-of-Concerns Problems in Collaborative Design of Human-AI Systems through Leaky Abstractions

In conventional software development, user experience (UX) designers and engineers collaborate through separation of concerns (SoC): designers create human interface specifications, and engineers build to those specifications. However, we argue that Human-AI systems thwart SoC because human needs must shape the design…

DIS '212nd AuthorHuman-LLM Collaboration +1

Towards a Process Model for Co-Creating AI Experiences

Thinking of technology as a design material is appealing. It encourages designers to explore the material's properties to understand its capabilities and limitations--a prerequisite to generative design thinking. However, as a material, AI resists this approach because its properties only emerge as part of the user ex…

IUI '212nd AuthorGenerative AI (Text, Image, Music, Video) +2

ProtoAI: Model-Informed Prototyping for AI-Powered Interfaces

When prototyping AI-powered interfaces, designers seek to build useful and usable ways to support end-user tasks with AI capabilities. In the process, they need to consider the potential capabilities and constraints of the AI services and build interface adaptations such as explainability, error recovery, and feedback…

CHI '202nd AuthorBest PaperInteractive Data Visualization +1

texSketch: Active Diagramming through Pen-and-Ink Annotations

Learning from text is a constructive activity in which sentence-level information is combined by the reader to build coherent mental models. With increasingly complex texts, forming a mental model becomes challenging due to a lack of background knowledge, and limits in working memory and attention. To address this, we…

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