Abstract

Despite the diffusion of artifacts integrating AI systems, current UX evaluation methods are not yet prepared nor comprehensive enough to include the unique traits characterizing them. That is the main premise of the [removed for blind review] project, which developed a new method to assess AI-infused artifacts. The contribution traces all the research steps that have been necessary to build AIXE, a specific and comprehensive scale framed as a questionnaire with 33 items, and aimed to support the understanding of the core UX qualities of this spreading technology. Specifically, it presents the three main phases of the research, which include: (i) the exploration of the state-of-the-art of current UX methods and reflections about AI-infused objects, (ii) the identification of dimensions and descriptors (second and first order variables) to construct an attitude scale using mixed methods sharing a human-centered approach, and (iii) the validation of the scale with an exploratory and a confirmatory factor analysis.

Keywords

AI-infused products, UX dimensions, UX evaluation method

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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Oct 9th, 9:00 AM

AIXE. Building a scale to evaluate the UX of AI-infused products

Despite the diffusion of artifacts integrating AI systems, current UX evaluation methods are not yet prepared nor comprehensive enough to include the unique traits characterizing them. That is the main premise of the [removed for blind review] project, which developed a new method to assess AI-infused artifacts. The contribution traces all the research steps that have been necessary to build AIXE, a specific and comprehensive scale framed as a questionnaire with 33 items, and aimed to support the understanding of the core UX qualities of this spreading technology. Specifically, it presents the three main phases of the research, which include: (i) the exploration of the state-of-the-art of current UX methods and reflections about AI-infused objects, (ii) the identification of dimensions and descriptors (second and first order variables) to construct an attitude scale using mixed methods sharing a human-centered approach, and (iii) the validation of the scale with an exploratory and a confirmatory factor analysis.

 

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