Towards Real Smart Apps: Investigating Human-AI Interactions in Smartphone On-Device AI Apps

• URL: http://arxiv.org/abs/2307.00756v1
• Date: Mon, 3 Jul 2023 05:04:34 GMT
• Title: Towards Real Smart Apps: Investigating Human-AI Interactions in Smartphone On-Device AI Apps
• Authors: Jason Ching Yuen Siu, Jieshan Chen, Yujin Huang, Zhenchang Xing, Chunyang Chen
• Abstract summary: A good interaction design is important to make an AI feature usable and understandable. Existing guidelines and tools either do not cover AI features or consider mobile apps. We conducted the first empirical study to explore user-AI-interaction in mobile apps.
• Score: 17.630597106970466
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

Related papers

• Survey of User Interface Design and Interaction Techniques in Generative AI Applications [79.55963742878684]
  We aim to create a compendium of different user-interaction patterns that can be used as a reference for designers and developers alike. We also strive to lower the entry barrier for those attempting to learn more about the design of generative AI applications.
  arXiv  Detail & Related papers  (2024-10-28T23:10:06Z)
• The Ethics of Advanced AI Assistants [53.89899371095332]
  This paper focuses on the opportunities and the ethical and societal risks posed by advanced AI assistants. We define advanced AI assistants as artificial agents with natural language interfaces, whose function is to plan and execute sequences of actions on behalf of a user. We consider the deployment of advanced assistants at a societal scale, focusing on cooperation, equity and access, misinformation, economic impact, the environment and how best to evaluate advanced AI assistants.
  arXiv  Detail & Related papers  (2024-04-24T23:18:46Z)
• Interrogating AI: Characterizing Emergent Playful Interactions with ChatGPT [10.907980864371213]
  This study focuses on playful interactions exhibited by users of a popular AI technology, ChatGPT. We found that more than half (54%) of user discourse revolved around playful interactions. It examines how these interactions can help users understand AI's agency, shape human-AI relationships, and provide insights for designing AI systems.
  arXiv  Detail & Related papers  (2024-01-16T14:44:13Z)
• An Empirical Study of AI Techniques in Mobile Applications [10.43634556488264]
  We conducted the most extensive empirical study on AI applications, exploring on-device ML apps, on-device DL apps, and AI service-supported (cloud-based) apps. Our study has strong implications for AI app developers, users, and AI R&D.
  arXiv  Detail & Related papers  (2022-12-03T15:31:34Z)
• AI-Assisted Authentication: State of the Art, Taxonomy and Future Roadmap [0.0]
  This paper focuses on the applications of artificial intelligence in authentication. With the emerging AI-assisted authentication schemes, our survey provides an overall understanding on a high level. In contrast to other relevant surveys, our research is the first of its kind to focus on the roles of AI in authentication.
  arXiv  Detail & Related papers  (2022-04-25T21:16:55Z)
• Cybertrust: From Explainable to Actionable and Interpretable AI (AI2) [58.981120701284816]
  Actionable and Interpretable AI (AI2) will incorporate explicit quantifications and visualizations of user confidence in AI recommendations. It will allow examining and testing of AI system predictions to establish a basis for trust in the systems' decision making.
  arXiv  Detail & Related papers  (2022-01-26T18:53:09Z)
• Trustworthy AI: A Computational Perspective [54.80482955088197]
  We focus on six of the most crucial dimensions in achieving trustworthy AI: (i) Safety & Robustness, (ii) Non-discrimination & Fairness, (iii) Explainability, (iv) Privacy, (v) Accountability & Auditability, and (vi) Environmental Well-Being. For each dimension, we review the recent related technologies according to a taxonomy and summarize their applications in real-world systems.
  arXiv  Detail & Related papers  (2021-07-12T14:21:46Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)
• Towards Tool-Support for Interactive-Machine Learning Applications in the Android Ecosystem [0.0]
  We believe there is a need for tool-support for AI engineers to address the challenges of implementing, testing, and deploying machine learning models. This paper presents preliminary results of a series of inquiries, including interviews with AI engineers and experiments for an interactive machine learning use case with a Smartwatch and Smartphone.
  arXiv  Detail & Related papers  (2021-03-27T09:28:40Z)
• Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things [98.10037444792444]
  We show how AI can empower the IoT to make it faster, smarter, greener, and safer. First, we present progress in AI research for IoT from four perspectives: perceiving, learning, reasoning, and behaving. Finally, we summarize some promising applications of AIoT that are likely to profoundly reshape our world.
  arXiv  Detail & Related papers  (2020-11-17T13:14:28Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.