In the current digital landscape, humans take center stage. This has caused a paradigm shift in the realm of intelligent technologies, prompting researchers and (industry) practitioners to reflect on the challenges and complexities involved in understanding the (potential) users of the technologies they develop. In this chapter, we provide an overview of human factors in user modeling, a core component of human-centered intelligent solutions. We discuss critical concepts, dimensions, and theories that inform the design of user models that are more attuned to human characteristics. Additionally, we emphasize the need for a comprehensive user model that simultaneously considers multiple factors to represent the intricacies of individuals’ interests and behaviors. Such a holistic model can, in turn, shape the design of intelligent solutions that are better able to adapt and cater to a wide range of user groups.@en

Information Retrieval (IR) remains an active, fast-paced area of research. However, most advances in IR have predominantly benefited the so-called “classical” users, e.g., English-speaking adults. We envision IR4U2as a forum to spotlight efforts that, while sparse, consider diverse, and often understudied, user groups when designing, developing, assessing, and deploying the IR technologies that directly impact them. The key objectives for IR4U2 are: (1) raise awareness about ongoing efforts focused on IR technologies designed for and used by often understudied user groups, (2) identify challenges and open issues impacting this area of research, (3) ignite discussions to identify common frameworks for future research, and (4) enable cross-fertilization and community-building by sharing lessons learned from research catering to different audiences by researchers and (industry) practitioners across various disciplines.

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This special issue highlights state-of-the-art research in intelligent systems and technology for people with diverse abilities. To control scope, we pay particular attention to cognitive diversity, including but not limited to, neurodevelopmental disorders and autism, cognitive and learningdisabilities, and dementia. We introduce the papers in this special issue by contextualizing them according to different research areas. By curating leading-edge contributions in this area, we aim to raise awareness about research challenges and requirements inherent in the development and assessment of systems designed for these categories of users.

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