mlsanityData to 14 Oct 2026

Toward General Design Principles for Generative AI Applications

arXiv 2301.05578 ↗First posted 13 Jan 2023cs.HC cs.AI cs.CYcited by 21

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Abstract (arXiv)

Generative AI technologies are growing in power, utility, and use. As generative technologies are being incorporated into mainstream applications, there is a need for guidance on how to design those applications to foster productive and safe use. Based on recent research on human-AI co-creation within the HCI and AI communities, we present a set of seven principles for the design of generative AI applications. These principles are grounded in an environment of generative variability. Six principles are focused on designing for characteristics of generative AI: multiple outcomes & imperfection; exploration & control; and mental models & explanations. In addition, we urge designers to design against potential harms that may be caused by a generative model's hazardous output, misuse, or potential for human displacement. We anticipate these principles to usefully inform design decisions made in the creation of novel human-AI applications, and we invite the community to apply, revise, and extend these principles to their own work.

Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Builds on 34 of its 123 references that are in the map. First posted on arXiv 13 Jan 2023.

Builds on

34 of 123 references.

References · 34

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22 more
  1. 2022Quantifying Memorization Across Neural Language Modelscited by 763
  2. 2021Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigmcited by 606
  3. 2020Unsupervised Translation of Programming Languagescited by 263
  4. 2020Questioning the AI: Informing Design Practices for Explainable AI User Experiencescited by 253
  5. 2021Design Guidelines for Prompt Engineering Text-to-Image Generative Modelscited by 218
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 9; 2024: 6; 2025: 4; 2026: 2.

21 papers.

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  1. 2023CoQuest: Exploring Research Question Co-Creation with an LLM-based Agentcited by 34
  2. 2023How Generative AI models such as ChatGPT can be (Mis)Used in SPC Practice, Education, and Research? An Exploratory Studycited by 16
  3. 2023Safety and Fairness for Content Moderation in Generative Modelscited by 16
  4. 2024One vs. Many: Comprehending Accurate Information from Multiple Erroneous and Inconsistent AI Generationscited by 13
  5. 2024Blessing or curse? A survey on the Impact of Generative AI on Fake Newscited by 12
  6. 2023Knowledge Engineering using Large Language Modelscited by 9
  7. 2023Scamming the Scammers: Using ChatGPT to Reply Mails for Wasting Time and Resourcescited by 8
  8. 2023Algorithmic Ghost in the Research Shell: Large Language Models and Academic Knowledge Creation in Management Researchcited by 6
  9. 2024Exploring the Design of Generative AI in Supporting Music-based Reminiscence for Older Adultscited by 4
  10. 2023PrefGen: Preference Guided Image Generation with Relative Attributescited by 2
  11. 2025Generative AI for Research Data Processing: Lessons Learnt From Three Use Casescited by 2
  12. 2023Generative AI May Prefer to Present National-level Characteristics of Cities Based on Stereotypical Geographic Impressions at the Continental Levelcited by 1
9 more
  1. 2024Boardwalk Empire: How Generative AI is Revolutionizing Economic Paradigmscited by 1
  2. 2024Traditional Chinese Medicine Case Analysis System for High-Level Semantic Abstraction: Optimized with Prompt and RAGcited by 1
  3. 2025Human-AI Interaction Design Standardscited by 1
  4. 2025GenAI-based Multi-Agent Reinforcement Learning towards Distributed Agent Intelligence: A Generative-RL Agent Perspectivecited by 1
  5. 2025AI-Assisted Music Production: A User Study on Text-to-Music Modelscited by 1
  6. 2023Conceptual Engineering Using Large Language Modelscited by 0
  7. 2024Physics-Informed Geometric Operators to Support Surrogate, Dimension Reduction and Generative Models for Engineering Designcited by 0
  8. 2026Comparing Socio-technical Design Principles with Guidelines for Human-centered AIcited by 0
  9. 2026Designing the Future of User Feedback for Generative AIcited by 0