User Experience + Artificial Intelligence : Assessing the Qualities of AI-Infused Systems / Davide Spallazzo

Front Matter pp 2-8; 7 pages -- Introduction pp 9-15; 7 pages -- Making Sense of AI-Infused Systems. Framing Current Design Challenges pp 16-38; 23 pages -- UX Dimensions for AI. Past and Future Perspectives pp 39-65; 27 pages -- Unpacking AI-Infused Systems Qualities. Building a UX Evaluation Method pp 66-79; 14 pages -- AIXE. A Method to Evaluate the UX of Systems Integrating AI pp 80-95; 16 pages -- Applying AIXE to Compare Domestic Smart Speakers pp 96-109; 14 pages -- Conclusions pp 110-118; 9 pages.

This open access book addresses the thriving trend of embedding artificial intelligence (AI) and machine learning (ML) capabilities in products and services reaching the lay public, focusing on the user experience (UX) they prompt from a designerly perspective. It offers a UX evaluation method designed explicitly for AI-infused systems to answer one of the core problems affecting the relationship and interactions people have with such artefacts. The work investigates how people perceive and make sense of systems integrating AI capabilities, trying to understand how their meaning and significance can affect the experience of such products and what design challenges may arise. Given the fundamental premise that current UX methods cannot address AI-infused artefacts, it introduces the results of Meet-AI, a research project exploring specific ways to tackle these problems. The book then presents a comprehensive analysis of current UX methods, and a literature review focused on detecting possible gaps and the most suitable qualities to describe AI-infused systems, and summarizes the findings from all previous investigations into a UX evaluation scale: AIXE (AI user eXperience Evaluation). The book also portrays how the tool has been validated and expanded to become a more comprehensive method. It further describes how the scale has been applied to a comparative study of domestic smart speakers, and introduces a reversed interpretation of the outcomes, framing them as heuristics to inform the early phases of the design process and paving the way for future experimentations in the meta-design dimension.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2025. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.