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Browsing by Author "Human-Centered Computing, School of Informatics and Computing"
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Item Academic Accomplices: Practical Strategies for Research Justice(ACM, 2019-06) Asad, Mariam; Dombrowski, Lynn; Costanza-Chock, Sasha; Erete, Sheena; Harrington, Christina; Human-Centered Computing, School of Informatics and ComputingThis workshop brings together folks currently or interested in becoming academic accomplices, or scholars committed to leveraging resources and power to support the justice work of their community collaborators. Academic accomplices are necessary for research justice-research that materially challenges inequity-and owe it to community partners to challenge underlying oppressive structure and practices as perpetuated through academic research. The goal of this workshop is to discuss concrete strategies for challenging oppression through research methodologies, physical or institutional resources, and/or pedagogy. This workshop will generate practical strategies for research justice for DIS and HCI scholars.Item Achieving Practical and Accurate Indoor Navigation for People with Visual Impairments(ACM, 2017) Ahmetovic, Dragan; Murata, Masayuki; Gleason, Cole; Brady, Erin; Takagi, Hironobu; Kitani, Kris; Asakawa, Chieko; Human-Centered Computing, School of Informatics and ComputingMethods that provide accurate navigation assistance to people with visual impairments often rely on instrumenting the environment with specialized hardware infrastructure. In particular, approaches that use sensor networks of Bluetooth Low Energy (BLE) beacons have been shown to achieve precise localization and accurate guidance while the structural modifications to the environment are kept at minimum. To install navigation infrastructure, however, a number of complex and time-critical activities must be performed. The BLE beacons need to be positioned correctly and samples of Bluetooth signal need to be collected across the whole environment. These tasks are performed by trained personnel and entail costs proportional to the size of the environment that needs to be instrumented. To reduce the instrumentation costs while maintaining a high accuracy, we improve over a traditional regression-based localization approach by introducing a novel, graph-based localization method using Pedestrian Dead Reckoning (PDR) and particle filter. We then study how the number and density of beacons and Bluetooth samples impact the balance between localization accuracy and set-up cost of the navigation environment. Studies with users show the impact that the increased accuracy has on the usability of our navigation application for the visually impaired.Item ActVirtual: Making Public Activism Accessible(ACM, 2017-10) Bora, Disha; Li, Hanlin; Salvi, Sagar; Brady, Erin; Human-Centered Computing, School of Informatics and ComputingTechnology-mediated public activism has grown popular in recent years with the high uptake of social media. Facebook and Twitter have become venues for activists to participate in online activism, or organize offline activism events. However, due to accessibility barriers in physical environments and accessibility issues in social media, people with disabilities continue to face challenges when they engage with such social movements. We interviewed 22 disabled activists about how they used technology to mediate civic engagement and barriers they faced. We present preliminary findings from these interviews and describe a potential solution named ActVirtual, a mobile platform for accessible activism. Our future work will include implementing and testing ActVirtual with users to make online and offline activism more accessible.Item "Alexa is a Toy": Exploring Older Adults' Reasons for Using, Limiting, and Abandoning Echo(ACM, 2020-04) Trajkova, Milka; Martin-Hammond, Aqueasha; Human-Centered Computing, School of Informatics and ComputingIntelligent voice assistants (IVAs) have the potential to support older adults' independent living. However, despite a growing body of research focusing on IVA use, we know little about why older adults become IVA non-users. This paper examines the reasons older adults use, limit, and abandon IVAs (i.e., Amazon Echo) in their homes. We conducted eight focus groups, with 38 older adults residing in a Life Plan Community. Thirty-six participants owned an Echo for at least a year, and two were considering adoption. Over time, most participants became non-users due to their difficulty finding valuable uses, beliefs associated with ability and IVA use, or challenges with use in shared spaces. However, we also found that participants saw the potential for future IVA support. We contribute a better understanding of the reasons older adults do not engage with IVAs and how IVAs might better support aging and independent living in the future.Item Assessing Demand for Transparency in Intelligent Systems Using Machine Learning(IEEE, 2018-07) Vorm, Eric S.; Miller, Andrew D.; Human-Centered Computing, School of Informatics and ComputingIntelligent systems offering decision support can lessen cognitive load and improve the efficiency of decision making in a variety of contexts. These systems assist users by evaluating multiple courses of action and recommending the right action at the right time. Modern intelligent systems using machine learning introduce new capabilities in decision support, but they can come at a cost. Machine learning models provide little explanation of their outputs or reasoning process, making it difficult to determine when it is appropriate to trust, or if not, what went wrong. In order to improve trust and ensure appropriate reliance on these systems, users must be afforded increased transparency, enabling an understanding of the systems reasoning, and an explanation of its predictions or classifications. Here we discuss the salient factors in designing transparent intelligent systems using machine learning, and present the results of a user-centered design study. We propose design guidelines derived from our study, and discuss next steps for designing for intelligent system transparency.Item Assessing the Value of Transparency in Recommender Systems: An End-User Perspective(ACM, 2018-10) Vorm, Eric S.; Miller, Andrew D.; Human-Centered Computing, School of Informatics and ComputingRecommender systems, especially those built on machine learning, are increasing in popularity, as well as complexity and scope. Systems that cannot explain their reasoning to end-users risk losing trust with users and failing to achieve acceptance. Users demand interfaces that afford them insights into internal workings, allowing them to build appropriate mental models and calibrated trust. Building interfaces that provide this level of transparency, however, is a significant design challenge, with many design features that compete, and little empirical research to guide implementation. We investigated how end-users of recommender systems value different categories of information to help in determining what to do with computer-generated recommendations in contexts involving high risk to themselves or others. Findings will inform future design of decision support in high-criticality contexts.Item Asymmetries in Online Job-Seeking: A Case Study of Muslim-American Women(ACM, 2021-10) Afnan, Tanisha; Rabaan, Hawra; Jones, Kyle M. L.; Dombrowski, Lynn; Human-Centered Computing, School of Informatics and ComputingAs job-seeking and recruiting processes transition into digital spaces, concerns about hiring discrimination in online spaces have developed. Historically, women of color, particularly those with marginalized religious identities, have more challenges in securing employment. We conducted 20 semi-structured interviews with Muslim-American women of color who had used online job platforms in the past two years to understand how they perceive digital hiring tools to be used in practice, how they navigate the US job market, and how hiring discrimination as a phenomenon is thought to relate to their intersecting social identities. Our findings allowed us to identify three major categories of asymmetries (i.e., the relationship between the computing algorithms' structures and their users' experiences): (1) process asymmetries, which is the lack of transparency in data collection processes of job applications; (2) information asymmetries, which refers to the asymmetry in data availability during online job-seeking; and (3) legacy asymmetries, which explains the cultural and historical factors impacting marginalized job applicants. We discuss design implications to support job seekers in identifying and securing positive employment outcomes.Item Attitudes About 'Fair Use' and Content Sharing in Social Media Applications(ACM, 2017-02) Faklaris, Cori; Hook, Sara Anne; Human-Centered Computing, School of Informatics and ComputingThe shift to Social Networking Services (SNSs) and mobile messaging apps such as Facebook, Instagram and Snapchat that rely on User-Generated Content (UGC) has challenged notions of fair use under U.S. copyright law. It remains unclear what understandings are common among these app users regarding legal and ethical norms in reusing artistic, journalistic and other types of content outside of online remixer spaces. Our online survey of N=106 users of N=48 SNS platforms and apps measured attitudes regarding fair use under U.S. copyright law and attribution for work that is shared. Participants reported a high level of agreement with more-restrictive conditions for content publishing and reuse. However, analyses of ratings and responses to open-ended questions reveal tension between issues of intellectual integrity and intellectual property.Item Beyond cute: exploring user types and design opportunities of virtual reality pet games(ACM, 2017-11) Lin, Chaolan; Dombrowski, Lynn; Faas, Travis; Brady, Erin; Human-Centered Computing, School of Informatics and ComputingVirtual pet games, such as handheld games like Tamagotchi or video games like Petz, provide players with artificial pet companions or entertaining pet-raising simulations. Prior research has found that virtual pets have the potential to promote learning, collaboration, and empathy among users. While virtual reality (VR) has become an increasingly popular game medium, litle is known about users' expectations regarding game avatars, gameplay, and environments for VR-enabled pet games. We surveyed 780 respondents in an online survey and interviewed 30 participants to understand users' motivation, preferences, and game behavior in pet games played on various medium, and their expectations for VR pet games. Based on our findings, we generated three user types that reflect users' preferences and gameplay styles in VR pet games. We use these types to highlight key design opportunities and recommendations for VR pet games.Item Bottom-Up Organizing with Tools from On High: Understanding the Data Practices of Labor Organizers(ACM, 2020-04) Khovanskaya, Vera; Sengers, Phoebe; Dombrowski, Lynn; Human-Centered Computing, School of Informatics and ComputingThis paper provides insight into the use of data tools in the American labor movement by analyzing the practices of staff employed by unions to organize alongside union members. We interviewed 23 field-level staff organizers about how they use data tools to evaluate membership. We find that organizers work around and outside of these tools to develop access to data for union members and calibrate data representations to meet local needs. Organizers mediate between local and central versions of the data, and draw on their contextual knowledge to challenge campaign strategy. We argue that networked data tools can compound field organizers' lack of discretion, making it more difficult for unions to assess and act on the will of union membership. We show how the use of networked data tools can lead to less accurate data, and discuss how bottom-up approaches to data gathering can support more accurate membership assessments.