Research Article
Elevating User-Centered Design with AI: A Comprehensive Exploration using the AI-UCD Algorithm Framework
@ARTICLE{10.4108/eetcasa.4211, author={Waralak Vongdoiwang Siricharoien}, title={Elevating User-Centered Design with AI: A Comprehensive Exploration using the AI-UCD Algorithm Framework}, journal={EAI Endorsed Transactions on Contex-aware Systems and Applications}, volume={10}, number={1}, publisher={EAI}, journal_a={CASA}, year={2024}, month={12}, keywords={Artificial intelligence, User-Centered Design (UCD), AI-UCD Framework, Human Centered Design, User Experience (UX)}, doi={10.4108/eetcasa.4211} }- Waralak Vongdoiwang Siricharoien
Year: 2024
Elevating User-Centered Design with AI: A Comprehensive Exploration using the AI-UCD Algorithm Framework
CASA
EAI
DOI: 10.4108/eetcasa.4211
Abstract
This paper presents a comprehensive exploration of the synergistic relationship between User-Centered Design (UCD) and Artificial Intelligence (AI) within the context of the AI-UCD Algorithm Framework. With the growing influence of AI in digital interfaces, the need to prioritize user needs and preferences has become paramount. The AI-UCD Framework, consisting of nine pivotal steps, acts as a structured guide for integrating AI into user interfaces while ensuring a user-centric, data-driven, and ethical approach. The exploration begins by highlighting the importance of understanding user needs and context through robust user research and contextual inquiry. It then delves into the process of defining AI integration objectives and brainstorming AI-enhanced solutions, emphasizing the creative aspects of UCD in tandem with AI capabilities. Subsequently, the paper discusses the critical role of designing AI-driven interfaces, from information architecture to user flow design, ensuring seamless integration of AI features.Implementation and testing of AI features are addressed, highlighting the collaboration between UI/UX designers and AI developers. The paper emphasizes the iterative nature of the framework, relying on usability testing and user feedback to drive continuous improvements. Moreover, it considers user training and assistance, a vital aspect of introducing users to AI features.The framework's data-driven aspect is covered by discussing data collection, analysis, and performance monitoring to ensure AI features are meeting objectives and KPIs. Additionally, the exploration addresses AI's role in personalization, adapting to user behavior and preferences. It recognizes the ethical dimensions of AI, promoting transparency, fairness, and accessibility.The paper then presents a five-step AI-UCD Validation Model, designed to verify the framework's effectiveness in real-world applications. These validation steps encompass user testing and feedback, data analysis, ethical audits, iterative improvements, and compliance with industry standards. Examples of how these steps work in practice are provided.
Copyright © 2024 Siricharoen et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
