With the emergence of deep learning techniques, smartphone apps are now embedded on-device AI features for enabling advanced tasks like speech translation, to attract users and increase market competitiveness. A good interaction design is important to make an AI feature usable and understandable. However, AI features have their unique challenges like sensitiveness to the input, dynamic behaviours and output uncertainty. Existing guidelines and tools either do not cover AI features or consider mobile apps which are confirmed by our informal interview with professional designers. To address these issues, we conducted the first empirical study to explore user-AI-interaction in mobile apps. We aim to understand the status of on-device AI usage by investigating 176 AI apps from 62,822 apps. We identified 255 AI features and summarised 759 implementations into three primary interaction pattern types. We further implemented our findings into a multi-faceted search-enabled gallery. The results of the user study demonstrate the usefulness of our findings.

翻译：随着深度学习技术的兴起，智能手机应用现已嵌入端侧AI功能，用于实现语音翻译等高级任务，以吸引用户并提升市场竞争力。良好的交互设计对于使AI功能可用且易于理解至关重要。然而，AI功能具有其独特挑战，例如对输入的敏感性、动态行为以及输出不确定性。现有指南和工具要么未涵盖AI功能，要么未考虑移动应用——这已通过与专业设计师进行的非正式访谈得到确认。为解决这些问题，我们开展了首个实证研究，探究移动应用中的用户-AI交互。我们旨在通过调查62,822个应用中的176个AI应用，了解端侧AI的使用现状。我们识别出255个AI功能，并将759种实现归纳为三种主要交互模式类型。我们进一步将研究发现转化为一个支持多方面搜索的图库。用户研究的结果证明了我们研究成果的实用性。