Explainable AI and User Experience. Prototyping and Evaluating an UX-Optimized XAI Interface in Computer Vision

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(as of Dec 25,2024 01:03:28 UTC – Details)

Publisher ‏ : ‎ Grin Verlag (May 7, 2023)
Language ‏ : ‎ English
Paperback ‏ : ‎ 156 pages
ISBN-10 ‏ : ‎ 3346874192
ISBN-13 ‏ : ‎ 978-3346874191
Item Weight ‏ : ‎ 7.5 ounces
Dimensions ‏ : ‎ 5.83 x 0.36 x 8.27 inches

Explainable AI and User Experience: Prototyping and Evaluating an UX-Optimized XAI Interface in Computer Vision

In recent years, there has been a growing interest in developing Explainable AI (XAI) systems that can provide users with insights into how AI algorithms make decisions. This is particularly important in applications like computer vision, where AI systems are used to analyze and interpret visual data.

One key challenge in designing XAI systems is ensuring that they are user-friendly and intuitive. Users need to be able to easily understand and interact with the explanations provided by the AI system. This is where User Experience (UX) design comes into play.

In this post, we will explore the process of prototyping and evaluating an UX-optimized XAI interface in the context of computer vision. By focusing on the user’s needs and preferences, we can create a more effective and engaging XAI system.

The first step in designing an UX-optimized XAI interface is to understand the needs and preferences of the target users. This can be done through user research, such as interviews, surveys, and usability testing. By gathering insights from users, we can identify their expectations and pain points when interacting with XAI systems.

Next, we can start prototyping the XAI interface, using tools like wireframes and mockups to visualize the layout and functionality of the system. During this stage, it is important to consider the clarity and simplicity of the explanations provided by the AI system. The interface should be designed in a way that helps users easily understand and trust the decisions made by the AI algorithms.

Once the prototype is ready, we can move on to evaluating the UX of the XAI interface. This can be done through usability testing, where users are asked to perform tasks with the system and provide feedback on their experience. By observing how users interact with the interface, we can identify any usability issues and make improvements to enhance the overall user experience.

By following this iterative process of prototyping and evaluating, we can create an UX-optimized XAI interface that effectively communicates the decisions made by AI algorithms in computer vision applications. This not only helps users better understand and trust the AI system, but also enhances their overall experience with the technology.
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