# AI in HCI Design and User Experience

arXiv: https://arxiv.org/abs/2301.00987 · HTML: https://mlsanity.com/paper/2301.00987/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 130 references that are in the map.
- First posted on arXiv 3 Jan 2023.

## Builds on (most cited first, 8 of 8)

- [Joint Deep Modeling of Users and Items Using Reviews for Recommendation](https://mlsanity.com/paper/1701.04783/) (2017)
- [Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks](https://mlsanity.com/paper/1706.04148/) (2017)
- [Photo-Realistic Monocular Gaze Redirection Using Generative Adversarial Networks](https://mlsanity.com/paper/1903.12530/) (2019)
- [Modeling Mobile Interface Tappability Using Crowdsourcing and Deep Learning](https://mlsanity.com/paper/1902.11247/) (2019)
- [Modeling Human Visual Search Performance on Realistic Webpages Using Analytical and Deep Learning Methods](https://mlsanity.com/paper/2005.03784/) (2020)
- [Co-evolutionary hybrid intelligence](https://mlsanity.com/paper/2112.04751/) (2021)
- [Maximizing the Value of Enterprise Human-Computer Interaction Standards: Strategies and Applications](https://mlsanity.com/paper/2105.05375/) (2021)
- [Guru, Partner, or Pencil Sharpener? Understanding Designers' Attitudes Towards Intelligent Creativity Support Tools](https://mlsanity.com/paper/2007.04848/) (2020)

## Abstract (arXiv)

In this chapter, we review and discuss the transformation of AI technology in HCI/UX work and assess how AI technology will change how we do the work. We first discuss how AI can be used to enhance the result of user research and design evaluation. We then discuss how AI technology can be used to enhance HCI/UX design. Finally, we discuss how AI-enabled capabilities can improve UX when users interact with computing systems, applications, and services.