Over the past few years, with the advent of ChatGPT, generative artificial intelligence (GenAI) has been at the centre of numerous discussions regarding generative and creative power, especially with the hope that it will enhance human creativity and, consequently, transformative power. Creativity, especially human creativity, has long been studied, particularly by psychologists and design scientists, who have revealed the difficulty of overcoming the fixation effect. This effect can hinder creativity and has not yet been explored in relation to GenAI, even though it is of major importance for understanding creative issues. In this work, we propose leveraging the rich body of literature on design creativity and creativity management to shed light on the fixation effect related to GenAI tools, which are considered partners in the design process, and possible defixation techniques. To study this issue, we propose a twofold methodology: a first, in-depth qualitative step with design theory experts, leading to the formulation of hypotheses, and a second, experimental step based on the well-documented egg task in creativity to test the hypotheses. Ultimately, we show that the use of GenAI tools in creative endeavours results in a greater number of generated ideas and that it does not prevent the fixation effect but can foster idea exploration and thus help with second-order defixation. These results consequently show the importance of considering a cocreativity regime involving both humans and GenAI, and they extend knowledge on the fixation effect in this context. They also indicate the capacity of GenAI in creative processes, thus suggesting some relevant use cases to leverage these tools.

The establishment of BIM raises issues at the transition between sketches, still mostly used in ideation, and project digital models. With the latest AI evolution, one way of supporting this transition is to provide sketch interpretation software generating digital representations. However, the question arises as to whether these two modes of representation can co-exist, and whether digital representations can provide a resource for designers in the preliminary phase. In this paper, we investigate the impact of auto-generated representations on the preliminary design activity of architects. We implement a Wizard of Oz protocol with nine participants sketching their design and being provided with CAD plans, 3D models and inspirational images. We study reflexive conversations by analyzing and categorizing behavior patterns preceding and following the reception of self-generated representations. We identify 23 patterns, and show the flexible role of the digital representations, having a strong impact on the process.

As global populations age, ensuring safe and independent mobility for older adults is a critical priority for urban planning and public health. Mobility in the built environment involves complex, moment-to-moment interactions, yet current assessment methods often rely on subjective surveys or static geospatial data that fail to capture dynamic human responses. Furthermore, these methods rarely address the specific needs of vulnerable individuals, such as those with knee osteoarthritis or a history of falls, who are most sensitive to environmental barriers. Hence, there is a lack of high-resolution, objective tools capable of quantifying how micro-scale built environmental features directly influence the physiological and kinematic states of these populations. Here we present an automated multimodal framework that integrates wearable motion sensors, physiological monitors, eye-tracking, and dual-perspective video to reconstruct a holistic profile of the walking experience. The framework employs SLAM and computer vision techniques to achieve precise tracking and environmental profiling. By synchronizing these inputs, the framework maps physiological and kinematic responses to specific built environment features. This overcomes the limitations of GNSS-denied settings and manual annotation, revealing micro-scale adaptations, including gait speed changes on slopes or during road crossings, that are often missed by conventional aggregate analyses. The resulting multimodal dataset captures the nuanced interplay between the built environment and vulnerable older adults. The computational pipelines and a specialized walkway surface material dataset are made publicly available. This work lays the foundation for large-scale, data-driven assessments of urban walkability, informing evidence-based design interventions to enhance safety and social engagement for aging societies.

One of the most exciting moments in a prenatal ultrasound session is learning the sex of the baby.Following a conversation analysis perspective, we present a multimodal analysis of sequences of interaction between patient and practitioner at the time the foetus’ sex is the focus of attention. Based on video data collected from maternity wards and private practitioners, we report on two types of sequences, which illustrate the different ways of responding to the perceptually-occasioned formulation of the foetus’ sex: as a telling or as a noticing (in which case participants orient towards jointly seeing). While the possibility of both response is inherent to the sequential properties of noticing-based claims in general, we will discuss how the production of both types of sequences is sensitive and articulated to the distribution of epistemic authority as a practical achievement in this medical setting, along two dimensions: expert versus ordinary knowledge, and professional vision versus lay gaze.