HCMar 5, 2025
De-skilling, Cognitive Offloading, and Misplaced Responsibilities: Potential Ironies of AI-Assisted DesignPrakash Shukla, Phuong Bui, Sean S Levy et al.
The rapid adoption of generative AI (GenAI) in design has sparked discussions about its benefits and unintended consequences. While AI is often framed as a tool for enhancing productivity by automating routine tasks, historical research on automation warns of paradoxical effects, such as de-skilling and misplaced responsibilities. To assess UX practitioners' perceptions of AI, we analyzed over 120 articles and discussions from UX-focused subreddits. Our findings indicate that while practitioners express optimism about AI reducing repetitive work and augmenting creativity, they also highlight concerns about over-reliance, cognitive offloading, and the erosion of critical design skills. Drawing from human-automation interaction literature, we discuss how these perspectives align with well-documented automation ironies and function allocation challenges. We argue that UX professionals should critically evaluate AI's role beyond immediate productivity gains and consider its long-term implications for creative autonomy and expertise. This study contributes empirical insights into practitioners' perspectives and links them to broader debates on automation in design.
HCMay 13, 2025
Tracing the Invisible: Understanding Students' Judgment in AI-Supported Design WorkSuchismita Naik, Prakash Shukla, Ike Obi et al.
As generative AI tools become integrated into design workflows, students increasingly engage with these tools not just as aids, but as collaborators. This study analyzes reflections from 33 student teams in an HCI design course to examine the kinds of judgments students make when using AI tools. We found both established forms of design judgment (e.g., instrumental, appreciative, quality) and emergent types: agency-distribution judgment and reliability judgment. These new forms capture how students negotiate creative responsibility with AI and assess the trustworthiness of its outputs. Our findings suggest that generative AI introduces new layers of complexity into design reasoning, prompting students to reflect not only on what AI produces, but also on how and when to rely on it. By foregrounding these judgments, we offer a conceptual lens for understanding how students engage in co-creative sensemaking with AI in design contexts.
HCAug 17, 2021
Understanding Data Visualization Design PracticePaul Parsons
Professional roles for data visualization designers are growing in popularity, and interest in relationships between the academic research and professional practice communities is gaining traction. However, despite the potential for knowledge sharing between these communities, we have little understanding of the ways in which practitioners design in real-world, professional settings. Inquiry in numerous design disciplines indicates that practitioners approach complex situations in ways that are fundamentally different from those of researchers. In this work, I take a practice-led approach to understanding visualization design practice on its own terms. Twenty data visualization practitioners were interviewed and asked about their design process, including the steps they take, how they make decisions, and the methods they use. Findings suggest that practitioners do not follow highly systematic processes, but instead rely on situated forms of knowing and acting in which they draw from precedent and use methods and principles that are determined appropriate in the moment. These findings have implications for how visualization researchers understand and engage with practitioners, and how educators approach the training of future data visualization designers.
HCAug 14, 2021
Fixation and Creativity in Data Visualization Design: Experiences and Perspectives of PractitionersPaul Parsons, Prakash Shukla, Chorong Park
Data visualization design often requires creativity, and research is needed to understand its nature and means for promoting it. The current visualization literature on creativity is not well developed, especially with respect to the experiences of professional data visualization designers. We conducted semi-structured interviews with 15 data visualization practitioners, focusing on a specific aspect of creativity known as design fixation. Fixation occurs when designers adhere blindly or prematurely to a set of ideas that limit creative outcomes. We present practitioners' experiences and perspectives from their own design practice, specifically focusing on their views of (i) the nature of fixation, (ii) factors encouraging fixation, and (iii) factors discouraging fixation. We identify opportunities for future research related to chart recommendations, inspiration, and perspective shifts in data visualization design.
HCSep 29, 2020
How do Visualization Designers Think? Design Cognition as a Core Aspect of Visualization PsychologyPaul Parsons
There are numerous opportunities for engaging in research at the intersection of psychology and visualization. While most opportunities taken up by the VIS community will likely focus on the psychology of users, there are also opportunities for studying the psychology of designers. In this position paper, I argue the importance of studying design cognition as a necessary component of a holistic program of research on visualization psychology. I provide a brief overview of research on design cognition in other disciplines, and discuss opportunities for VIS to build an analogous research program. Doing so can lead to a stronger integration of research and design practice, can provide a better understanding of how to educate and train future designers, and will likely surface both challenges and opportunities for future research.
HCSep 6, 2020
Data Visualization Practitioners' Perspectives on ChartjunkPaul Parsons, Prakash Shukla
Chartjunk is a popular yet contentious topic. Previous studies have shown that extreme minimalism is not always best, and that visual embellishments can be useful depending on the context. While more knowledge is being developed regarding the effects of embellishments on users, less attention has been given to the perspectives of practitioners regarding how they design with embellishments. We conducted semi-structured interviews with 20 data visualization practitioners, investigating how they understand chartjunk and the factors that influence how and when they make use of embellishments. Our investigation uncovers a broad and pluralistic understanding of chartjunk among practitioners, and foregrounds a variety of personal and situated factors that influence the use of chartjunk beyond context. We highlight the personal nature of design practice, and discuss the need for more practice-led research to better understand the ways in which concepts like chartjunk are interpreted and used by practitioners.
HCSep 6, 2020
Design Judgment in Data Visualization PracticePaul Parsons, Colin M. Gray, Ali Baigelenov et al.
Data visualization is becoming an increasingly popular field of design practice. Although many studies have highlighted the knowledge required for effective data visualization design, their focus has largely been on formal knowledge and logical decision-making processes that can be abstracted and codified. Less attention has been paid to the more situated and personal ways of knowing that are prevalent in all design activity. In this study, we conducted semi-structured interviews with data visualization practitioners during which they were asked to describe the practical and situated aspects of their design processes. Using a philosophical framework of design judgment from Nelson and Stolterman [23], we analyzed the transcripts to describe the volume and complex layering of design judgments that are used by data visualization practitioners as they describe and interrogate their work. We identify aspects of data visualization practice that require further investigation beyond notions of rational, model- or principle-directed decision-making processes.
HCJul 9, 2020
Hack.VR: A Programming Game in Virtual RealityDominic Kao, Christos Mousas, Alejandra J. Magana et al.
In this article we describe Hack.VR, an object-oriented programming game in virtual reality. Hack.VR uses a VR programming language in which nodes represent functions and node connections represent data flow. Using this programming framework, players reprogram VR objects such as elevators, robots, and switches. Hack.VR has been designed to be highly interactable both physically and semantically.