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The rapid advancement of Artificial Intelligence (AI) technologies has significantly transformed the work environment, affecting employee motivation and well-being. Techno-work engagement emphasizes the employee well-being linked to technology use in the workplace, since the technological advancements reconfigure the socio-technical dynamics in the work practices. This study aims to explore the impact of AI tools on techno-work engagement among user experience design (UXD) professionals through the lens of self-determination theory (SDT). SDT addresses three fundamental psychological needs: autonomy, competence, and relatedness, and how they relate to motivation and engagement at work. Qualitative data was collected through retrospective interviews with seven UXD professionals, and analyzed abductively using reflexive thematic analysis, which generated five key themes illuminating the relationships between AI tools and techno-work engagement. It was revealed when AI tools align with UXD professionals’ workflows and values, these tools enhance motivation and engagement by streamlining tasks and offering new perspectives during the design process. However, AI tools are most effective as supplements to, rather than replacements for, human creativity. Thus, AI tools can potentially enhance techno-work engagement among UXD professionals, provided they align with their values and workflows. We hopefully contribute to the broader conversation on how AI technologies reconfigures the future of work.

Large knowledge gaps exist regarding how enabling technologies, such as robotics, automation, and AI, impact the digital work environment in the ongoing industrial revolution. While these technologies must align with work tasks, they also have the potential to enhance meaningfulness at work by fulfilling human needs for competence, autonomy, and self-realization. However, the development of laboratory automation has mainly been technology-driven, underscoring the need for a human-centered approach here called Laboratory 5.0. This paper presents an empirical UX evaluation of a semi-automated robot used in inhalator testing by five chemists in a pharmaceutical lab. Data collection included think-aloud protocols, questionnaires, observations, and interviews, analyzed through triangulation. The findings revealed that while the robot streamlined tasks and increased flexibility, it also introduced physical and cognitive work environment challenges, such as ergonomic strain, cognitive load, unclear process feedback, and workflow interruptions. These insights will guide the redesign and implementation of a mobile lab robot, addressing user experience and interaction challenges in the laboratory context. By improving UX in human-robot interaction, this research aims to contribute to a more sustainable, meaningful and engaging digital work environment in Laboratory 5.0, which will benefit chemists and workers in similar domains.

In Industry 4.0 and 5.0, humans and robots share physical and social spaces, making sustainable workplaces essential. While mobile, flexible, and collaborative robots offer new possibilities, challenges remain. Effective human-robot interaction relies on mutual recognition of actions and intentions for efficiency, safety, and smooth collaboration. Awareness of user experience (UX) is growing, as it influences work satisfaction, engagement, and well-being. This paper identifies UX issues when mobile robots are introduced on the shop floor alongside operators and truck drivers. The study, conducted at a large manufacturing plant, examined mobile robots delivering heavy parts to the assembly line and navigating a busy warehouse corridor and production area. Two months after field testing, a post-evaluation took place, with data collected from eight participants, four operators and four truck drivers, who had frequently interacted with the robots. Participants completed a questionnaire and an interview. Key findings show: a) differences between operators and truck drivers, b) higher UX assessments for operators, c) more and greater challenges for truck drivers, and d) neither group seeing major personal benefits but recognizing advantages for the company. Both physical and cognitive work environment problems were identified.

This paper contributes to the long-ongoing research on control room work by exploring the work practices of traffic controllers and information officers in the domain of train traffic. This study examines how distributed, socially, spatially, and temporally dynamic work activities are enacted within train traffic control rooms. By exploring the situated knowledge of traffic controllers and information officers, we identify the challenge of maintaining remote engagement with, and attachment to, places beyond the control room. By employing a workplace study approach, the paper illustrates how the workers manage the demands of being distributed and dependent on artefacts, as well as their acquired ability to ‘see’ the rail, while physically present elsewhere. We introduce the concept of ‘sense of place’ to better understand the remote aspects of work and how workers develop and maintain their engagement with railway operations in locations far from their own. To conceptualise this phenomenon, we introduce a new term—remote situatedness. This concept integrates cognitive and technological aspects of enhanced seeing with the sense of place, capturing professionals’ ability to engage with distant locations. Our findings highlight three key examples: Mutually enacted situated seeing, Mediated sense of place, and Failed sense of place. These illustrate how remote situatedness is enacted, technologically mediated, and challenged. In conclusion, the paper highlights the need to put the workers’ engagement with their material and social environment at the core of control room research and suggests future research directions for studying work practices from a holistic perspective.

Lantbrukets digitalisering är sammankopplad med de samhälleliga och globala utmaningarna. Behovet av att nå de globala målen inom en snar framtid för att kunna hålla oss inom vår planets begränsade resurser på ett hållbart sätt är akut, vilket medför att lantbruket behöver föda fler människor samtidigt som det påverkas av pågående klimatförändringar.

The human-robot interaction (HRI) field goes beyond the mere technical aspects of developing robots, often investigating how humans perceive robots. Human perceptions and behavior are determined, in part, by expectations. Given the impact of expectations on behavior, it is important to understand what expectations individuals bring into HRI settings and how those expectations may affect their interactions with the robot over time. For many people, social robots are not a common part of their experiences, thus any expectations they have of social robots are likely shaped by other sources. As a result, individual expectations coming into HRI settings may be highly variable. Although there has been some recent interest in expectations within the field, there is an overall lack of empirical investigation into its impacts on HRI, especially in-person robot interactions. To this end, a within-subject in-person study (N=31\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=31$$\end{document}) was performed where participants were instructed to engage in open conversation with the social robot Pepper during two 2.5 min sessions. The robot was equipped with a custom dialogue system based on the GPT-3 large language model, allowing autonomous responses to verbal input. Participants' affective changes towards the robot were assessed using three questionnaires, NARS, RAS, commonly used in HRI studies, and Closeness, based on the IOS scale. In addition to the three standard questionnaires, a custom question was administered to capture participants' views on robot capabilities. All measures were collected three times, before the interaction with the robot, after the first interaction with the robot, and after the second interaction with the robot. Results revealed that participants to large degrees stayed with the expectations they had coming into the study, and in contrast to our hypothesis, none of the measured scales moved towards a common mean. Moreover, previous experience with robots was revealed to be a major factor of how participants experienced the robot in the study. These results could be interpreted as implying that expectations of robots are to large degrees decided before interactions with the robot, and that these expectations do not necessarily change as a result of the interaction. Results reveal a strong connection to how expectations are studied in social psychology and human-human interaction, underpinning its relevance for HRI research.

In this paper, we promote and motivate research on user experience (UX) in the domain of rail, more specifically for the workers engaged in the daily operational parts of executing train traffic. UX aspects have often been overlooked in the design and use of technology within the workplace, particularly in safety-critical work domains. Here, we provide an overview of current UX research at work and outline a roadmap with seven facets for future research within the domain of operational train traffic that is in alignment with the need for further investigation into UX at work. We hope future research will contribute to a deeper understanding of how positive experience at work provides additional means of enhancing engagement and improving safety management in workplaces in general and for the work in operational train traffic specifically.

This paper explores the complex and time-critical work practices within operational train traffic in Sweden by reporting on an incident causing an infrastructure breakdown and large traffic disruptions. Based on a workplace study approach, we report on how the control room workers – train traffic controllers and information officers – grasp, make sense of, and handle the consequences of the incident as it unfolds in realtime. We portray how the workers develop and acquire a sense of place in relation to the incident’s severity which is essential for successfully handling the situation. By introducing the ‘sense of place’ concept originally derived from the field of natural resources to the domain of operational train traffic, we provide a deepened understanding of the challenges characterising remote control work from a safety-critical socio-technical systems perspective. Finally, reflections on the application of the ‘sense of place’ concept, safety aspects and directions for future research are provided.

Increased use of robotization, automation, and artificial intelligence (AI) highlights the need for theory development of the digital work environment since such technologies are likely to significantly alter or even totally change human work practices. This paper focuses on how these technologies influence people’s digital work engagement. In an ongoing project, we study how support from these technologies changes the socio-technical work dynamics and how work engagement can be facilitated in such digital workplaces. The project aims to develop a digital work engagement framework based on input across multiple work domains. The present paper reports on an initial characterization of digital work engagement and presents a synthesis of findings from the first iteration of the envisioned framework. Finally, a discussion on the opportunities and challenges of enabling technologies for the future of work practices is provided.