Marc Hassenzahl

Kuntal Ghosh, Marc Hassenzahl, Shadan Sadeghian

Human-AI collaboration is considered the most promising way to incorporate AI in the workplace. What remains unexplored are the experiential consequences of this teaming. More specifically, in a team with AI, how humans perceive themselves (self-perception) and how they are perceived by their coworkers (peer perception) in terms of work ownership and job meaningfulness. In a 2x2x2 vignette study (n=50), participants rated perceptions of ownership, affect, job meaningfulness and satisfaction, and role dynamics across two levels (low/high) of AI proactivity and AI competency as within-subject factors, with point-of-view (self perception/peer perception) as between-subjects. Our results showed that AI with low competency or low proactivity generally improved feelings related to ownership, meaningfulness, satisfaction, and role dynamics, and also increased positive affect while reducing negative affect. However, these effects were often influenced by point-of-view. For instance, low AI proactivity resulted in higher job satisfaction from self-perception rather than peer perception. Based on our findings, we argue that designing AI for the future of work solely around performance metrics may not be adequate. Highly competent and proactive AI-driven systems can have undesirable impacts on perceptions of ownership, job identity, social image and team dynamics, and consequently, job meaningfulness.

Kuntal Ghosh, Marc Hassenzahl, Shadan Sadeghian

The proliferation of Artificial Intelligence (AI) in workplaces is transforming how we work. While existing research on human-AI collaboration at work often prioritizes performance, less is known about their experiential outcomes. Through interviews with 24 employees across Information Technology (IT), service-based, and healthcare sectors, this paper examines AI's impact on job satisfaction via perceptions of job decency and meaningfulness, now and in the future. Our results reveal that the anticipated impact of AI on overall job satisfaction varies with the occupational domain, with differing perceptions of its underlying decency and meaningfulness. For instance, IT and healthcare anticipate increased satisfaction with decency aspects like working hours but decreased satisfaction with meaningfulness aspects like social image due to misconceptions about AI handling most of their tasks. Conversely, service workers foresee no improvement in their working hours but a higher social standing due to the perceived status boost associated with working with AI.

Judith Dörrenbächer, Matthias Laschke, Diana Löffler et al.

Design Fiction is known for its provocative and often dystopian speculations about the future. In this paper, we present an alternative approach that focuses primarily on the positive. We propose to imagine, enact, and evaluate utopia with participants. By doing so, we react to four main critiques concerning Design Fiction: (1) its negativity, (2) its contextlessness, (3) its elitist authorship, and (4) its missing evaluation methods.

Alarith Uhde, Marc Hassenzahl

Social acceptability is an important consideration for HCI designers who develop technologies for social contexts. However, the current theoretical foundations of social acceptability research do not account for the complex interactions among the actors in social situations and the specific role of technology. In order to improve the understanding of how context shapes and is shaped by situated technology interactions, we suggest to reframe the social space as a dynamic bundle of social practices and explore it with simulation studies using agent-based modeling. We outline possible research directions that focus on specific interactions among practices as well as regularities in emerging patterns.

Alarith Uhde, Marc Hassenzahl

Social contexts play an important role in understanding acceptance and use of technology. However, current approaches used in HCI to describe contextual influence do not capture it appropriately. On the one hand, the often used Technology Acceptance Model and related frameworks are too rigid to account for the nuanced variations of social situations. On the other hand, Goffman's dramaturgical model of social interactions emphasizes interpersonal relations but mostly overlooks the material (e.g., technology) that is central to HCI. As an alternative, we suggest an approach based on Social Practice Theory. We conceptualize social context as interactions between co-located social practices and acceptability as a matter of their (in)compatibilities. Finally, we outline how this approach provides designers with a better understanding of different types of social acceptability problems and helps finding appropriate solutions.

Alarith Uhde, Matthias Laschke, Marc Hassenzahl

Shift scheduling impacts healthcare workers' well-being because it sets the frame for their social life and recreational activities. Since it is complex and time-consuming, it has become a target for automation. However, existing systems mostly focus on improving efficiency. The workers' needs and their active participation do not play a pronounced role. Contrasting this trend, we designed a social practice-based, worker-centered, and well-being-oriented self-scheduling system which gives healthcare workers more control during shift planning. In a following nine month appropriation study, we found that workers who were cautious about their social standing in the group or who had a more spontaneous personal lifestyle used our system less often than others. Moreover, we revealed several conflict prevention practices and suggest to shift the focus away from a competitive shift distribution paradigm towards supporting these pro-social practices. We conclude with guidelines to support individual planning practices, self-leadership, and for dealing with conflicts.

Holger Klapperich, Alarith Uhde, Marc Hassenzahl

Nowadays, automation not only permeates industry but also becomes a substantial part of our private, everyday lives. Driven by the idea of increased convenience and more time for the "important things in life," automation relieves us from many daily chores - robots vacuum floors and automated coffee makers produce supposedly barista-quality coffee on the press of a button. In many cases, these offers are embraced by people without further questioning. However, while we save time by delegating more and more everyday activities to automation, we also may lose chances for enjoyable and meaningful experiences. In two field studies, we demonstrate that a manual process has experiential benefits over more automated processes by using the example of coffee-making. We present a way to account for potential experiential costs of everyday automation and strategies of how to design interaction with automation to reconcile experience with the advantages of a more and more powerful automation.

Sarah Janboecke, Alina Gawlitta, Judith Doerrenbaecher et al.

Time and its lack of play a central role in our everyday lives. Despite increasing productivity, many people experience time stress, exhaustion and a longing for time affluence, and at the same time, a fear of not being busy enough. All this leads to a neglect of natural time, especially the patterns and rhythms created by physiological processes, subsumed under the heading of chronobiology. The present paper presents and evaluates a calendar application, which uses chronobiological knowledge to support people s planning activities. Participants found our calendar to be interesting and engaging. It especially made them think more about their bodies and appropriate times for particular activities. All in all, it supported participants in negotiating. external demands and personal health and wellbeing. This shows that technology does not necessarily has to be neutral or even further current (mal-)practices. Our calendar cares about changing perspectives and thus about enhancing users wellbeing.

Sarah Janboecke, Diana Loeffler, Marc Hassenzahl

When discussing the future of work and in detail the concerns of workers within and beyond established workplace settings, technology-wise we act on rather new ground. Especially preserving a meaningful work environment gains new importance when introducing disruptive technologies. We sometimes do not even have the technology which effects we are willing to discuss. To measure implications for employees and thus create meaningful design variants we need to test systems and their effects before developing them. Confronted with the same problem we used the experimental vignette method to study the effects of AI use in work contexts. During the workshop, we will report our experiences.

Matthias Laschke, Alarith Uhde, Marc Hassenzahl

Work is a rich source of meaning. However, beyond organizational changes, most approaches in the research field of Meaningful Work neglected the power of work-related technology to increase meaning. Using two cases as examples, this paper proposes a wellbeing-driven approach to the design of work-related technology. Despite the positive results of our cases, we argue that the use of technology as a means of increasing meaning in the workplace is still in its infancy.

Holger Klapperich, Alarith Uhde, Marc Hassenzahl

Nowadays, automation not only dominates industry but becomes more and more a part of our private, everyday lives. Following the notion of increased convenience and more time for the "important things in life", automation relieves us from many daily household chores - robots vacuum floors and automated coffeemakers produce supposedly barista-quality coffee on the press of a button. In many cases these offers are embraced by people without further questioning. Of course, automation frees us from many unloved activities, but we may also lose something by delegating more and more everyday activities to automation. In a series of four studies, we explored the experiential costs of everyday automation and strategies of how to design technology to reconcile experience with the advantages of ever more powerful automation.