mlsanityData to 14 Oct 2026

Understanding User Perceptions, Collaborative Experience and User Engagement in Different Human-AI Interaction Designs for Co-Creative Systems

arXiv 2204.13217 ↗First posted 27 Apr 2022cs.HC cs.AIcited by 8

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Abstract (arXiv)

Human-AI co-creativity involves humans and AI collaborating on a shared creative product as partners. In a creative collaboration, communication is an essential component among collaborators. In many existing co-creative systems users can communicate with the AI, usually using buttons or sliders. Typically, the AI in co-creative systems cannot communicate back to humans, limiting their potential to be perceived as partners rather than just a tool. This paper presents a study with 38 participants to explore the impact of two interaction designs, with and without AI-to-human communication, on user engagement, collaborative experience and user perception of a co-creative AI. The study involves user interaction with two prototypes of a co-creative system that contributes sketches as design inspirations during a design task. The results show improved collaborative experience and user engagement with the system incorporating AI-to-human communication. Users perceive co-creative AI as more reliable, personal, and intelligent when the AI communicates to users. The findings can be used to design effective co-creative systems, and the insights can be transferred to other fields involving human-AI interaction and collaboration.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 3 of its 42 references that are in the map. First posted on arXiv 27 Apr 2022.

Builds on

3 of 42 references.

References · 3

  1. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
  2. 2022Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systemscited by 59
  3. 2018Evaluating Creativity in Computational Co-Creative Systemscited by 9

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 4.

8 papers.