Human-Centered Computing Works
Permanent URI for this collection
Working papers, posters, reports, presentations and other works authored by members of the Department of Human-Centered Computing.
Browse
Recent Submissions
Item Indy Postcard Collector - Dec. 2024(Indianapolis Postcard Club, 2024-12) Hook , Sara AnneThe December 2024 issue of Indy Postcard Collector, published by the Indianapolis Postcard Club, edited by Sara Anne Hook, Professor EmeritaItem Designing for Culturally Sensitive Cultural Change: A case study of designing for the visibility of Saudi women in the digital media(Association for Computing Machinery, 2022) Alshehri, Taghreed; Kirkham, Reuben; Dombrowski, Lynn; Olivier, Patrick; Human-Centered Computing, Luddy School of Informatics, Computing, and EngineeringOnline self-presentation is recognized as a global phenomenon largely influenced by and sensitive to users’ cultural norms. However, incorporating cultural understanding into the design process can be challenging. Designing for culture creates dilemmas between designing for a pre-existing cultural ‘status quo’ or for cultural change. We argue that culturally sensitive design should not be a tool for (i) perpetuating existing cultural inequalities or (ii) empowering the individual isolated from their wider cultural milieu. We propose “designing for culturally sensitive cultural change”—a process in which we support creating a trajectory departing from the status quo, to bridge the gap between people's aspirations and practices related to cultural change. We demonstrate this in a case study on designing for Saudi women's self-presentation in digital media. We conclude with reflections on cultural sensitivity in designing for cultural change and broader implications for HCI.Item Indy Postcard Collector, October 2024(Indianapolis Postcard Club, 2024-10) Hook, Sara AnneThe October 2024 issue of Indy Postcard Collector, published by the Indianapolis Postcard Club, edited by Sara Anne Hook, Professor Emerita.Item Parental Acceptance of Children’s Storytelling Robots: A Projection of the Uncanny Valley of AI(Frontiers Media, 2021-05-19) Lin, Chaolan; Šabanović, Selma; Dombrowski, Lynn; Miller, Andrew D.; Brady, Erin; MacDorman, Karl F.; Human-Centered Computing, Luddy School of Informatics, Computing, and EngineeringParent–child story time is an important ritual of contemporary parenting. Recently, robots with artificial intelligence (AI) have become common. Parental acceptance of children’s storytelling robots, however, has received scant attention. To address this, we conducted a qualitative study with 18 parents using the research technique design fiction. Overall, parents held mixed, though generally positive, attitudes toward children’s storytelling robots. In their estimation, these robots would outperform screen-based technologies for children’s story time. However, the robots’ potential to adapt and to express emotion caused some parents to feel ambivalent about the robots, which might hinder their adoption. We found three predictors of parental acceptance of these robots: context of use, perceived agency, and perceived intelligence. Parents’ speculation revealed an uncanny valley of AI: a nonlinear relation between the human likeness of the artificial agent’s mind and affinity for the agent. Finally, we consider the implications of children’s storytelling robots, including how they could enhance equity in children’s access to education, and propose directions for research on their design to benefit family well-being.Item Indy Postcard Collector - August 2024(Indianapolis Postcard Club, 2024-08) Hook , Sara AnneThe August 2024 issue of Indy Postcard Collector, published by the Indianapolis Postcard Club, edited by Sara Anne Hook, Professor Emerita.Item Indy Postcard Collector, June 2024(Indianapolis Postcard Club, 2024-06) Hook , Sara AnneThe June 2024 issue of Indy Postcard Collector, published by the Indianapolis Postcard Club, edited by Sara Anne Hook, Professor Emerita.Item Does mind perception explain the uncanny valley effect? A meta-regression analysis and (de)humanization experiment.(Elsevier, 2024) MacDorman, Karl F.Gray and Wegner (2012) proposed that when robots look human, their appearance prompts attributions of experience, including sensations and feelings, which is uncanny. This theory, confusingly termed mind perception, differs from perceptual theories of the uncanny valley in that the robots' eeriness is not stimulus-driven. To explore this seminal theory, we conducted a meta-regression analysis of 10 experiments and a (de)humanization experiment. In the first part, experiments were identified in the literature that manipulated artificial entity's experience using descriptions. However, experiments with no observable stimuli yielded larger effects for experience and eeriness than those with robots and virtual reality characters. This finding undermines a theory that purports to explain how a robot's human likeness causes eeriness. Further, a second issue concerns Gray and Wegner's protocol based on a vignette design. Reading about an entity with experience activates thoughts that may not be activated when encountering it, and these thoughts may increase its eeriness. Therefore, the paper's second part focuses on an experiment we conducted with a novel humanization–dehumanization protocol. Participants' attitudes on robots' similarity to humans were gradually shifted to manipulate robots' perceived humanness, experience, and agency. However, the manipulation's effect on eeriness and coldness was mostly nonsignificant or counter to prediction. Differences in the robots' physical appearance had a much larger effect on their eeriness and coldness. In fact, as a mediator, experience mitigated the stimulus's overall effect of increasing eeriness. These results favor perceptual theories, rather than mind perception, in explaining the uncanny valley.Item A two-branch multi-scale residual attention network for single image super-resolution in remote sensing imagery(IEEE, 2024) Patnaik, Allen; Bhuyan, Manas K.; MacDorman, Karl F.High-resolution remote sensing imagery finds applications in diverse fields, such as land-use mapping, crop planning, and disaster surveillance. To offer detailed and precise insights, reconstructing edges, textures, and other features is crucial. Despite recent advances in detail enhancement through deep learning, disparities between original and reconstructed images persist. To address this challenge, we propose a two-branch multiscale residual attention network for single-image super-resolution reconstruction. The network gathers complex information about input images from two branches with convolution layers of different kernel sizes. The two branches extract both low-level and high-level features from the input image. The network incorporates multiscale efficient channel attention and spatial attention blocks to capture channel and spatial dependencies in the feature maps. This results in more discriminative features and more accurate predictions. Moreover, residual modules with skip connections can help to overcome the vanishing gradient problem. We trained the proposed model on the WHU-RS19 dataset, collated from Google Earth satellite imagery, and validated it on the UC Merced, RSSCN7, AID, and real-world satellite datasets. The experimental results show that our network uses features at different levels of detail more effectively than state-of-the-art models.Item Designing Conversational Assistants to Support Older Adults’ Personal Health Record Access(Springer, 2022) Karimi, Pegah; Ballard, Kallista; Vazirani, Pooja; Jorigay, Ravi Teja Narasimha; Martin-Hammond, Aqueasha; Human-Centered Computing, Luddy School of Informatics, Computing, and EngineeringOlder adults often rely on information provided during doctors’ visits or online to manage their health but can experience challenges accessing this information at home. Recently, conversational assistants are being explored to aid navigation of health information included in online portals, but we still know little about users’ perceptions of using these tools for managing personal health information. In this paper, we conducted a wizard-of-oz study to better understand older adults’ perceptions of a conversational assistant, MIHA, to help with navigating personal health information. Participants saw value in using a tool such as MIHA to help facilitate access to their personal health information and to help them become more engaged in their health. Participants believed MIHA’s features helped build confidence in the responses returned, but made suggestions for improving the interactions. We share insights of potential uses and design implications for conversational assistants that help older adults navigate personal health information.Item Examining Identity as a Variable of Health Technology Research for Older Adults: A Systematic Review(ACM, 2022) Harrington, Christina N.; Martin-Hammond, Aqueasha; Bray, Kirsten; Human-Centered Computing, Luddy School of Informatics, Computing, and EngineeringInnovations in HCI research of health-related pervasive and ubiquitous technologies can potentially improve older adults’ access to healthcare resources and support long-term independence in the home. Despite efforts to include their voices in technology research and design, many older adults have yet to actualize these health benefits, with barriers of access and proficiency actually widening the gap of health inequities. We reviewed 174 HCI publications through a systematic review to examine who is engaged in the design of health technologies for older adults, methods used to engage them, and how different types of participation might impact design directions. Findings highlight that thus far, many identity dimensions have not been explored in HCI aging research. We identify research gaps and implications to promote expanding research engagement with these dimensions as a way to support the design of health technologies that see better adoption among marginalized populations.