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PromptInfuser: Bringing User Interface Mock-ups to Life with Large Language Models

Published: 19 April 2023 Publication History

Abstract

Large Language Models have enabled novices without machine learning (ML) experience to quickly prototype ML functionalities with prompt programming. This paper investigates incorporating prompt-based prototyping into designing functional user interface (UI) mock-ups. To understand how infusing LLM prompts into UI mock-ups might affect the prototyping process, we conduct a exploratory study with five designers, and find that this capability might significantly speed up creating functional prototypes, inform designers earlier on how their designs will integrate ML, and enable user studies with functional prototypes earlier. From these findings, we built PromptInfuser, a Figma plugin for authoring LLM-infused mock-ups. PromptInfuser introduces two novel LLM-interactions: input-output, which makes content interactive and dynamic, and frame-change, which directs users to different frames depending on their natural language input. From initial observations, we find that PromptInfuser has the potential to transform the design process by tightly integrating UI and AI prototyping in a single interface.

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References

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[1] Daniel Adiwardana, Minh-Thang Luong, David R. So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, and Quoc V. Le. 2020. Towards a Human-like Open-Domain Chatbot. https://doi.org/10.48550/ARXIV.2001.09977
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[2] Eli Collins and Zoubin Ghahramani. 2021. LaMDA: our breakthrough conversation technology. https://blog.google/technology/ai/lamda/Accessed: 2023-01-11.
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[3] Matthew K. Hong, Adam Fourney, Derek DeBellis, and Saleema Amershi. 2021. Planning for Natural Language Failures with the AI Playbook. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 386, 11 pages. https://doi.org/10.1145/3411764.3445735
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[4] Ellen Jiang, Kristen Olson, Edwin Toh, Alejandra Molina, Aaron Donsbach, Michael Terry, and Carrie J Cai. 2022. PromptMaker: Prompt-Based Prototyping with Large Language Models. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA ’22). Association for Computing Machinery, New York, NY, USA, Article 35, 8 pages. https://doi.org/10.1145/3491101.3503564
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[5] Qian Yang, Aaron Steinfeld, Carolyn Rosé, and John Zimmerman. 2020. Re-Examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376301

Cited By

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  • (2024)Enhancing user experience in large language models through human-centered design: Integrating theoretical insights with an experimental study to meet diverse software learning needs with a single document knowledge baseComputing and Artificial Intelligence10.59400/cai.v2i1.5352:1(535)Online publication date: 19-Apr-2024
  • (2024)Exploring the Potential of Large Language Models in Radiological Imaging Systems: Improving User Interface Design and Functional CapabilitiesElectronics10.3390/electronics1311200213:11(2002)Online publication date: 21-May-2024
  • (2024)NLDesign: A UI Design Tool for Natural Language InterfacesProceedings of the ACM Turing Award Celebration Conference - China 202410.1145/3674399.3674455(153-158)Online publication date: 5-Jul-2024
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Published In

cover image ACM Conferences
CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
April 2023
3914 pages
ISBN:9781450394222
DOI:10.1145/3544549
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 April 2023

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Author Tags

  1. Design
  2. Generative AI
  3. Large Language Models
  4. Prototyping

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  • Work in progress
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  • Refereed limited

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CHI '23
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Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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CHI '25
CHI Conference on Human Factors in Computing Systems
April 26 - May 1, 2025
Yokohama , Japan

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Cited By

View all
  • (2024)Enhancing user experience in large language models through human-centered design: Integrating theoretical insights with an experimental study to meet diverse software learning needs with a single document knowledge baseComputing and Artificial Intelligence10.59400/cai.v2i1.5352:1(535)Online publication date: 19-Apr-2024
  • (2024)Exploring the Potential of Large Language Models in Radiological Imaging Systems: Improving User Interface Design and Functional CapabilitiesElectronics10.3390/electronics1311200213:11(2002)Online publication date: 21-May-2024
  • (2024)NLDesign: A UI Design Tool for Natural Language InterfacesProceedings of the ACM Turing Award Celebration Conference - China 202410.1145/3674399.3674455(153-158)Online publication date: 5-Jul-2024
  • (2024)PromptInfuser: How Tightly Coupling AI and UI Design Impacts Designers’ WorkflowsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661613(743-756)Online publication date: 1-Jul-2024
  • (2024)Not Just Novelty: A Longitudinal Study on Utility and Customization of an AI WorkflowProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661587(782-803)Online publication date: 1-Jul-2024
  • (2024)Enhancing AI-Assisted Group Decision Making through LLM-Powered Devil's AdvocateProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645199(103-119)Online publication date: 18-Mar-2024
  • (2024)Empirical Evidence on Conversational Control of GUI in Semantic AutomationProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645172(869-885)Online publication date: 18-Mar-2024
  • (2024)A Taxonomy for Human-LLM Interaction Modes: An Initial ExplorationExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650786(1-11)Online publication date: 11-May-2024
  • (2024)"We Need Structured Output": Towards User-centered Constraints on Large Language Model OutputExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650756(1-9)Online publication date: 11-May-2024
  • (2024)GenAICHI 2024: Generative AI and HCI at CHI 2024Extended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3636294(1-7)Online publication date: 11-May-2024
  • Show More Cited By

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