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User-centric AI: evaluating the usability of generative AI applications through user reviews on app stores
1Information Technology Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia.
Peerj. Computer Science
|December 9, 2024
Summary
This study evaluated generative AI apps using user reviews, finding ChatGPT most usable. Gemini AI and Da Vinci AI showed lower usability, highlighting areas for improvement in AI tool design.
Area of Science:
- Human-Computer Interaction
- Artificial Intelligence Usability
- Software Engineering
Background:
- Real-world usability of generative AI tools remains under-researched.
- User reviews from digital marketplaces offer valuable insights into AI application performance.
- Existing research lacks comprehensive usability evaluations based on large-scale user feedback.
Purpose of the Study:
- To conduct a usability evaluation and comparison of leading generative AI applications.
- To analyze user reviews from the Apple App Store and Google Play for insights into AI tool effectiveness, efficiency, and satisfaction.
- To identify specific usability issues and provide recommendations for enhancing generative AI user experience.
Main Methods:
- Extracted and analyzed 11,549 user reviews for five generative AI apps (ChatGPT, Bing AI, Microsoft Copilot, Gemini AI, Da Vinci AI) from January to March 2024.
- Applied ISO 9241 usability standards, focusing on effectiveness, efficiency, and user satisfaction.
- Utilized user feedback data to assess compound usability and satisfaction scores across Android and iOS platforms.
Main Results:
- ChatGPT demonstrated the highest compound usability scores (0.504 Android, 0.462 iOS) and user satisfaction (0.590 Android, 0.565 iOS).
- Gemini AI recorded the lowest usability (0.016 Android) and satisfaction (-0.138 Android) among analyzed Android apps.
- Da Vinci AI showed the lowest usability among analyzed iOS apps (0.275), indicating platform-specific user experience variations.
Conclusions:
- User satisfaction is a critical factor in the overall usability of generative AI applications.
- Identified common usability challenges include ease of use, functionality, and reliability.
- Actionable recommendations are proposed to improve the design and user experience of generative AI tools.
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