Co-Disclosing the Computer: LLM-Mediated Computing through Reflective Conversation
Mattias Rost
Abstract
Large language models (LLMs) are changing how we interact with computers. As they become capable of generating software dynamically, they invite a fundamental rethinking of the computer’s role in human activity. In this conceptual paper, we introduce LLM-mediated computing: a paradigm in which interaction is no longer structured around fixed applications, but emerges in real-time through human intent and LLM interpretation. We make three contributions: (1) we articulate a new interaction metaphor of reflective conversation to guide future design, (2) we use the lens of postphenomenology to understand the human-LLM-computer relation, and (3) we propose a new mode of computing based on co-disclosure, in which the computer is constituted in use. Together, they define a new mode of computing, provide a lens to analyze it, and offer a metaphor to design with.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext e3d9de89-eb3d-4bc6-9476-676ab0931fb9Builds on7
- Training language models to follow instructions with human feedbackLong Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida et al.NeurIPS 2022 · 24,707 citations
- Toolformer: Language Models Can Teach Themselves to Use ToolsTimo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu et al.NeurIPS 2023 · 5,989 citations
- Questioning the AI: Informing Design Practices for Explainable AI User ExperiencesQ. Vera Liao, Daniel M. Gruen, Sarah MillerCHI 2020 · 758 citations
- Manipulating and Measuring Model InterpretabilityForough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan et al.CHI 2021 · 663 citations
- Design Principles for Generative AI ApplicationsJustin D. Weisz, Jessica He, Michael J. Muller, Gabriela Hoefer et al.CHI 2024 · 221 citations
Related papers
- Partnering with Generative AI: Experimental Evaluation of Model-Led and Human-Led Interaction in Human-AI Co-CreationSebastian Maier, Manuel Schneider, Stefan FeuerriegelCHI 2026 · 5 citations
- Machine Eye: Designing Relational Engagement with Embodied Large Language ModelsAileen Ng, Nina Rajcic, Rowan PageCHI 2026 · 1 citation
- Privacy Control in Conversational LLM Platforms: A Walkthrough StudyZhuoyang Li, Yanlai Wu, Yao Li, Xinning Gui et al.CHI 2026 · 1 citation
- DuetUI: A Bidirectional Context Loop for Human-Agent Co-Generation of Task-Oriented InterfacesYuan Xu, Shaowen Xiang, Yizhi Song, Ruoting Sun et al.CHI 2026 · 2 citations
- SketchGPT: A Sketch-based Multimodal Interface for Application-Agnostic LLM InteractionZeyuan Huang, Cangjun Gao, Yaxian Shan, Haoxiang Hu et al.UIST 2025 · 8 citations
