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

arXiv: https://arxiv.org/abs/2204.13217 · HTML: https://mlsanity.com/paper/2204.13217/

## 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 (most cited first, 3 of 3)

- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systems](https://mlsanity.com/paper/2204.07666/) (2022)
- [Evaluating Creativity in Computational Co-Creative Systems](https://mlsanity.com/paper/1807.09886/) (2018)

## Built on by (most cited first, 8 of 8)

- [Human-Centered AI Communication in Co-Creativity: An Initial Framework and Insights](https://mlsanity.com/paper/2505.18385/) (2025)
- [Improving User Experience with FAICO: Towards a Framework for AI Communication in Human-AI Co-Creativity](https://mlsanity.com/paper/2504.02526/) (2025)
- [Human-Human-AI Triadic Programming: Uncovering the Role of AI Agent and the Value of Human Partner in Collaborative Learning](https://mlsanity.com/paper/2601.12134/) (2026)
- [Actionable AI: Enabling Non Experts to Understand and Configure AI Systems](https://mlsanity.com/paper/2503.06803/) (2025)
- [Toward AI standardization: A triadic human-ai collaboration framework for multi-level autonomous mobility](https://mlsanity.com/paper/2504.19120/) (2025)
- [Tinker Tales: A Tangible Dialogue System for Child-AI Co-Creative Storytelling](https://mlsanity.com/paper/2602.04109/) (2026)
- [Promoting Critical Thinking With Domain-Specific Generative AI Provocations](https://mlsanity.com/paper/2603.19975/) (2026)
- [No Pixel Left Behind: Filling Gaps in Anime Colorization](https://mlsanity.com/paper/2609.00800/) (2026)

## 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.