Artificial Intelligence is increasingly integrating into everyday life and is becoming an increasingly pervasive reality. Domestic AI-enhanced devices are aggressively conquering new markets, nevertheless such products seem to respond to the taste for novelty rather than having a significant utility for the user, remaining confined to the dimension of the gadget or toy. Interestingly, although AI has been indicated as a new material for designers, the design discipline has not yet fully tackled this issue. Moving from these premises, the MeEt-AI research program aims at developing a new UX assessment method specifically addressed to AI-enhanced domestic devices and environments. Accordingly, we frame the project within the vast and variegated field of UX assessment methods, focusing on three main aspects of UX assessment –methodology, UX dimensions and analyzed objects – by looking at what current methods propose from the standpoint of AI-enhanced domestic products and environments. What emerges are general considerations that are at the basis of the positioning of the MeEt-AI research program.

Spallazzo, D., Sciannamè, M., Ceconello, M. (2020) Towards a UX Assessment Method for AI-Enabled Domestic Devices. HCI International 2020. https://doi.org/10.1007/978-3-030-50344-4_24 

The table has been developed within the Meet-AI project. It presents a wide-range critical analysis of 129 UX evaluation methods (both qualitative and quantitative). These are retrieved from articles published in the ACM Digital Library and Springer Link between 2000 and 2020. The results have then been confronted with the largest repository of UX evaluation methods available at the time of the study, namely All About UX website, to integrate methods eventually missed by the researchers. The evaluation methods are analyzed according to various criteria. Among them: the assessed UX dimension(s); the descriptors within the dimensions – here intended as the items describing the nuances of the overarching dimensions; the collection method(s); and the object(s) of analysis.

Spallazzo, Davide; Sciannamè, Martina; Ajovalasit, Marco; Ceconello, Mauro; Vitali, Ilaria; Arquilla, Venanzio (2021): UX Evaluation Methods Mapping. figshare. Dataset. https://doi.org/10.6084/m9.figshare.14350553.v1

The Meet-AI project focuses on the evaluation of AI-infused products, hardware devices in which AI systems are embedded. The table summarizes the responses to an exploratory survey addressed to a sample of advanced users (namely Digital Interaction Design students at Politecnico di Milano), aimed at collecting descriptors to specifically evaluate AI-infused produtcs under 8 UX dimensions (pragmatic, hedonic, aesthetic, affective, trustworthiness, conversational, intelligence, meaningfulness).

Spallazzo, Davide; Sciannamè, Martina (2021): UX Descriptors for AI-infused Products. figshare. Dataset. https://doi.org/10.6084/m9.figshare.14345498.v1

Aiming at developing a UX evaluation method for AI-infused products, the researchers involved in the Meet-AI project assessed the descriptors emerging from an exploratory survey (you can find the reference at the following link: https://figshare.com/s/bf5a997e78afc351e02b) according to their (i) consistency with the dimension in which they were proposed, and to their (ii) relevance for AI-infused products. Items emerging from a previously undertaken literature review and mapping of the existing UX evaluation methods are also evaluated according to their relevance. In the dataset, the 1 to 4 evaluations by the involved researchers are displayed.

Artificial Intelligence (AI) is entering our daily life and personal environments, as AI-infused products such as smart speakers are entering millions of houses worldwide. Despite the success and their potential to unleash Ambient Intelligence, they are still considered useless or close to a gadget dimension. Accordingly, we consider it mandatory for the design discipline to acknowledge those products, trying to understand and frame the User Experience (UX) they entail. The present study explores the UX dimensions that could describe and assess the experience enabled by such devices. It is the first step of a research program to create a novel UX evaluation method for AI-infused products. In the study, we employed a multi-method approach to (i) understand the main UX dimensions commonly assessed, (ii) identify specific UX dimensions for AI-infused products, and (iii) verify the assumptions with a sample of advanced users. The results are described, discussed, and framed within the current literature.

Spallazzo, D., Sciannamè, M., Ajovalasit, M., Ceconello, M., & Arquilla, V. (2022). Exploring AI-Infused Products Qualities to Unleash AmI. Ambient Intelligence – Software and Applications – 12th International Symposium on Ambient Intelligence, 483, 35–45. https://doi.org/10.1007/978-3-031-06894-2_4

Artificial intelligence is more-or-less covertly entering our lives and houses, embedded into products and services that are acquiring novel roles and agency on users. The design discipline and the Human-Computer Interaction (HCI) field are just beginning to explore the wicked relationship between Design and AI, looking for a definition of its borders, still blurred and ever changing. The book approaches this issue from a human-centered standpoint, proposing designerly reflections on AI-infused products. It addresses one main guiding question: what are the design implications of embedding intelligence into everyday objects?

Spallazzo, D., & Sciannamè, M. (Eds.). (2022). EMBEDDING INTELLIGENCE. Designerly reflections on AI-infused products. Franco Angeli Design International. https://series.francoangeli.it/index.php/oa/catalog/view/848/695/4914

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.

Sciannamè, M. & Spallazzo, D. AIXE. Building a scale to evaluate the UX of AI-infused products. IASDR 2023: Life-Changing Design. IASDR 2023: Life-Changing Design. https://doi.org/10.21606/iasdr.2023.355