Louanne E. Boyd, Jazette Johnson, Franceli Linney Cibrian, Deanna Hughes, Eliza Delpizzo-Cheng, Karen Lotich, Sara A. Jones, Hollis E. Pass, Viseth Sean, Gillian R. Hayes
Some neurodivergent people prioritize visual details over the “big picture”. While excellent attention to detail has many advantages, some contexts require the rapid integration of global and local information. A local processing style can be so strong that local details interfere with the fluid integration of global information required for processing of information rapidly displayed on user interfaces. This disconnect between context of an interaction and processing style can be termed local interference. Personalization of visual stimuli can promote a more accessible computing experience. We describe how technological interventions can support shifting of visual attention from local to global features to make them more accessible. We present two empirical studies. One study with one autistic adult revealed a significant shift in eye gaze fixation, and the other study with 20 autistic children revealed filters that visually emphasize primary aspects encouraged more global comments about the image content.
{"title":"Global Filter: Augmenting Images to Support Seeing the “Big Picture” for People with Local Interference","authors":"Louanne E. Boyd, Jazette Johnson, Franceli Linney Cibrian, Deanna Hughes, Eliza Delpizzo-Cheng, Karen Lotich, Sara A. Jones, Hollis E. Pass, Viseth Sean, Gillian R. Hayes","doi":"10.1145/3571812","DOIUrl":"https://doi.org/10.1145/3571812","url":null,"abstract":"Some neurodivergent people prioritize visual details over the “big picture”. While excellent attention to detail has many advantages, some contexts require the rapid integration of global and local information. A local processing style can be so strong that local details interfere with the fluid integration of global information required for processing of information rapidly displayed on user interfaces. This disconnect between context of an interaction and processing style can be termed local interference. Personalization of visual stimuli can promote a more accessible computing experience. We describe how technological interventions can support shifting of visual attention from local to global features to make them more accessible. We present two empirical studies. One study with one autistic adult revealed a significant shift in eye gaze fixation, and the other study with 20 autistic children revealed filters that visually emphasize primary aspects encouraged more global comments about the image content.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":"30 1","pages":"1 - 28"},"PeriodicalIF":3.7,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43274433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
James Hodge, Sarah Foley, Daniel Lambton-Howard, L. Booi, Kyle Montague, Sandra Coulter, David S. Kirk, K. Morrissey
Recent HCI research has addressed emerging approaches for public engagement. One such public-facing method which has gained popularity over the previous decade has been open design events, or hackathons. In this article, we report on DemVR, a hackathon event that invited designers, technologists, and students of these disciplines to design Virtual Reality (VR) environments for people with dementia and their care partners. While our event gained reasonable attraction from designers and developers, this article unpacks the challenges in representing and involving people with dementia in these events, which had multiple knock-on effects on participant's outputs. Our analysis presents insights into participants’ motivations, challenges participants faced when constructing their “absent user”, and the design features teams developed to address the social context of the user. We conclude the article by proposing a set of commitments for collaborative design events, community building through design, and reification in design.
{"title":"Exploring Participants’ Representations and Shifting Sensitivities in a Hackathon for Dementia","authors":"James Hodge, Sarah Foley, Daniel Lambton-Howard, L. Booi, Kyle Montague, Sandra Coulter, David S. Kirk, K. Morrissey","doi":"10.1145/3571814","DOIUrl":"https://doi.org/10.1145/3571814","url":null,"abstract":"Recent HCI research has addressed emerging approaches for public engagement. One such public-facing method which has gained popularity over the previous decade has been open design events, or hackathons. In this article, we report on DemVR, a hackathon event that invited designers, technologists, and students of these disciplines to design Virtual Reality (VR) environments for people with dementia and their care partners. While our event gained reasonable attraction from designers and developers, this article unpacks the challenges in representing and involving people with dementia in these events, which had multiple knock-on effects on participant's outputs. Our analysis presents insights into participants’ motivations, challenges participants faced when constructing their “absent user”, and the design features teams developed to address the social context of the user. We conclude the article by proposing a set of commitments for collaborative design events, community building through design, and reification in design.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":"30 1","pages":"1 - 35"},"PeriodicalIF":3.7,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42417367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The need for AI systems to provide explanations for their behaviour is now widely recognised as key to their adoption. In this article, we examine the problem of trustworthy AI and explore what delivering this means in practice, with a focus on healthcare applications. Work in this area typically treats trustworthy AI as a problem of Human–Computer Interaction involving the individual user and an AI system. However, we argue here that this overlooks the important part played by organisational accountability in how people reason about and trust AI in socio-technical settings. To illustrate the importance of organisational accountability, we present findings from ethnographic studies of breast cancer screening and cancer treatment planning in multidisciplinary team meetings to show how participants made themselves accountable both to each other and to the organisations of which they are members. We use these findings to enrich existing understandings of the requirements for trustworthy AI and to outline some candidate solutions to the problems of making AI accountable both to individual users and organisationally. We conclude by outlining the implications of this for future work on the development of trustworthy AI, including ways in which our proposed solutions may be re-used in different application settings.
{"title":"Holding AI to Account: Challenges for the Delivery of Trustworthy AI in Healthcare","authors":"R. Procter, P. Tolmie, M. Rouncefield","doi":"10.1145/3577009","DOIUrl":"https://doi.org/10.1145/3577009","url":null,"abstract":"The need for AI systems to provide explanations for their behaviour is now widely recognised as key to their adoption. In this article, we examine the problem of trustworthy AI and explore what delivering this means in practice, with a focus on healthcare applications. Work in this area typically treats trustworthy AI as a problem of Human–Computer Interaction involving the individual user and an AI system. However, we argue here that this overlooks the important part played by organisational accountability in how people reason about and trust AI in socio-technical settings. To illustrate the importance of organisational accountability, we present findings from ethnographic studies of breast cancer screening and cancer treatment planning in multidisciplinary team meetings to show how participants made themselves accountable both to each other and to the organisations of which they are members. We use these findings to enrich existing understandings of the requirements for trustworthy AI and to outline some candidate solutions to the problems of making AI accountable both to individual users and organisationally. We conclude by outlining the implications of this for future work on the development of trustworthy AI, including ways in which our proposed solutions may be re-used in different application settings.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":"30 1","pages":"1 - 34"},"PeriodicalIF":3.7,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42210755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Research in HCI4D has continuously advanced a narrative of “lacks” and “gaps” of the African perspective in technoscience. In response to such misguided assumptions, this article attempts to reformulate the common and perhaps unfortunate thinking about African practices of design in HCI4D – i.e., largely as a function of African societal predicaments and Western technocratic resolutions. Through critical reflection on a range of issues associated with post-colonialism and post-development, I examine the possibilities that various historical tropes might offer to the reinvention of the African perspective on innovation. This leads to the consideration of how engaging in critical discussions about the future dimensions of African HCI can allow for grappling with the effect of the coloniality of being, power, and knowledge. Developing on the ideas of futuring as a way of dealing with the complexities of the present—in this case, the coloniality of the imagination—the article ends by discussing three tactical propositions for “remembering” future identities of African innovation where the values of autonomy are known and acted upon.
{"title":"No More “Solutionism” or “Saviourism” in Futuring African HCI: A Manyfesto","authors":"M. Adamu","doi":"10.1145/3571811","DOIUrl":"https://doi.org/10.1145/3571811","url":null,"abstract":"Research in HCI4D has continuously advanced a narrative of “lacks” and “gaps” of the African perspective in technoscience. In response to such misguided assumptions, this article attempts to reformulate the common and perhaps unfortunate thinking about African practices of design in HCI4D – i.e., largely as a function of African societal predicaments and Western technocratic resolutions. Through critical reflection on a range of issues associated with post-colonialism and post-development, I examine the possibilities that various historical tropes might offer to the reinvention of the African perspective on innovation. This leads to the consideration of how engaging in critical discussions about the future dimensions of African HCI can allow for grappling with the effect of the coloniality of being, power, and knowledge. Developing on the ideas of futuring as a way of dealing with the complexities of the present—in this case, the coloniality of the imagination—the article ends by discussing three tactical propositions for “remembering” future identities of African innovation where the values of autonomy are known and acted upon.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":" ","pages":"1 - 42"},"PeriodicalIF":3.7,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44384380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Color design has long benefited from the statistical analysis of public taste and, more recently, from crowdsourcing to discover fresh and popular ideas. However, the current color dictionary is considerably restricted in terms of the scope of expressible design concepts and the control of target demographics. We propose a search-engine-based color palette generator inspired by Natural Language Processing algorithms that filter and cluster semantically related words. The post-evaluation reveals that our results not only faithfully realize the given keywords but are notable indicators of inter-group dynamics; the differential recognition of the other group's identity colors reflects the direction of historic, geographic, or cultural influence.
{"title":"Color2Vec: Web-Based Modeling of Word-Color Association with Sociocultural Contexts","authors":"Long Xu, S. Park, Sangwon Lee","doi":"10.1145/3571816","DOIUrl":"https://doi.org/10.1145/3571816","url":null,"abstract":"Color design has long benefited from the statistical analysis of public taste and, more recently, from crowdsourcing to discover fresh and popular ideas. However, the current color dictionary is considerably restricted in terms of the scope of expressible design concepts and the control of target demographics. We propose a search-engine-based color palette generator inspired by Natural Language Processing algorithms that filter and cluster semantically related words. The post-evaluation reveals that our results not only faithfully realize the given keywords but are notable indicators of inter-group dynamics; the differential recognition of the other group's identity colors reflects the direction of historic, geographic, or cultural influence.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":" ","pages":"1 - 29"},"PeriodicalIF":3.7,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43845425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Robot Learning from Demonstration (RLfD) allows non-expert users to teach a robot new skills or tasks directly through demonstrations. Although modeled after human-human learning and teaching, existing RLfD methods make robots act as passive observers without the feedback of their learning statuses in the demonstration gathering stage. To facilitate a more transparent teaching process, we propose two mechanisms of Learning Engagement, Z2O-Mode and D2O-Mode, to dynamically adapt robots’ attentional and behavioral engagement expressions to their actual learning status. Through an online user experiment with 48 participants, we find that, compared with two baselines, the two kinds of Learning Engagement can lead to users’ more accurate mental models of the robot’s learning progress, more positive perceptions of the robot, and better teaching experience. Finally, we provide implications for leveraging engagement expression to facilitate transparent human-AI (robot) communication based on our key findings.
{"title":"Modeling Adaptive Expression of Robot Learning Engagement and Exploring its Effects on Human Teachers","authors":"Shuai Ma, Mingfei Sun, Xiaojuan Ma","doi":"10.1145/3571813","DOIUrl":"https://doi.org/10.1145/3571813","url":null,"abstract":"Robot Learning from Demonstration (RLfD) allows non-expert users to teach a robot new skills or tasks directly through demonstrations. Although modeled after human-human learning and teaching, existing RLfD methods make robots act as passive observers without the feedback of their learning statuses in the demonstration gathering stage. To facilitate a more transparent teaching process, we propose two mechanisms of Learning Engagement, Z2O-Mode and D2O-Mode, to dynamically adapt robots’ attentional and behavioral engagement expressions to their actual learning status. Through an online user experiment with 48 participants, we find that, compared with two baselines, the two kinds of Learning Engagement can lead to users’ more accurate mental models of the robot’s learning progress, more positive perceptions of the robot, and better teaching experience. Finally, we provide implications for leveraging engagement expression to facilitate transparent human-AI (robot) communication based on our key findings.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44339874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Public media and researchers in different areas have recently focused on perhaps unexpected problems that derive from an excessive and frequent use of technology, giving rise to a new kind of psychological “digital” wellbeing. Such a novel and pressing topic has fostered, both in the academia and in the industry, the emergence of a variety of digital self-control tools allowing users to self-regulate their technology use through interventions like timers and lock-out mechanisms. While these emerging technologies for behavior change hold great promise to support people’s digital wellbeing, we still have a limited understanding of their real effectiveness, as well as of how to best design and evaluate them. Aiming to guide future research in this important domain, this article presents a systematic review and a meta-analysis of current work on tools for digital self-control. We surface motivations, strategies, design choices, and challenges that characterize the design, development, and evaluation of digital self-control tools. Furthermore, we estimate their overall effect size on reducing (unwanted) technology use through a meta-analysis. By discussing our findings, we provide insights on how to (i) overcome a limited perspective that exclusively focuses on technology overuse and self-monitoring tools, (ii) evaluate digital self-control tools through long-term studies and standardized measures, and (iii) bring ethics in the digital wellbeing discourse and deal with the business model of contemporary tech companies.
{"title":"Achieving Digital Wellbeing Through Digital Self-control Tools: A Systematic Review and Meta-analysis","authors":"A. M. Roffarello, Luigi De Russis","doi":"10.1145/3571810","DOIUrl":"https://doi.org/10.1145/3571810","url":null,"abstract":"Public media and researchers in different areas have recently focused on perhaps unexpected problems that derive from an excessive and frequent use of technology, giving rise to a new kind of psychological “digital” wellbeing. Such a novel and pressing topic has fostered, both in the academia and in the industry, the emergence of a variety of digital self-control tools allowing users to self-regulate their technology use through interventions like timers and lock-out mechanisms. While these emerging technologies for behavior change hold great promise to support people’s digital wellbeing, we still have a limited understanding of their real effectiveness, as well as of how to best design and evaluate them. Aiming to guide future research in this important domain, this article presents a systematic review and a meta-analysis of current work on tools for digital self-control. We surface motivations, strategies, design choices, and challenges that characterize the design, development, and evaluation of digital self-control tools. Furthermore, we estimate their overall effect size on reducing (unwanted) technology use through a meta-analysis. By discussing our findings, we provide insights on how to (i) overcome a limited perspective that exclusively focuses on technology overuse and self-monitoring tools, (ii) evaluate digital self-control tools through long-term studies and standardized measures, and (iii) bring ethics in the digital wellbeing discourse and deal with the business model of contemporary tech companies.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":"30 1","pages":"1 - 66"},"PeriodicalIF":3.7,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48589109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Niels van Berkel, Maura Bellio, M. Skov, A. Blandford
Bringing AI technology into clinical practice has proved challenging for system designers and medical professionals alike. The academic literature has, for example, highlighted the dangers of black-box decision-making and biased datasets. Furthermore, end-users’ ability to validate a system’s performance often disappears following the introduction of AI decision-making. We present the MAP model to understand and describe the three stages through which medical observations are interpreted and handled by AI systems. These stages are Measurement, in which information is gathered and converted into data points that can be stored and processed; Algorithm, in which computational processes transform the collected data; and Presentation, where information is returned to the user for interpretation. For each stage, we highlight possible challenges that need to be overcome to develop Human-Centred AI systems. We illuminate our MAP model through complementary case studies on colonoscopy practice and dementia diagnosis, providing examples of the challenges encountered in real-world settings. By defining Human-AI interaction across these three stages, we untangle some of the inherent complexities in designing AI technology for clinical decision-making, and aim to overcome misalignment between medical end-users and AI researchers and developers.
{"title":"Measurements, Algorithms, and Presentations of Reality: Framing Interactions with AI-Enabled Decision Support","authors":"Niels van Berkel, Maura Bellio, M. Skov, A. Blandford","doi":"10.1145/3571815","DOIUrl":"https://doi.org/10.1145/3571815","url":null,"abstract":"Bringing AI technology into clinical practice has proved challenging for system designers and medical professionals alike. The academic literature has, for example, highlighted the dangers of black-box decision-making and biased datasets. Furthermore, end-users’ ability to validate a system’s performance often disappears following the introduction of AI decision-making. We present the MAP model to understand and describe the three stages through which medical observations are interpreted and handled by AI systems. These stages are Measurement, in which information is gathered and converted into data points that can be stored and processed; Algorithm, in which computational processes transform the collected data; and Presentation, where information is returned to the user for interpretation. For each stage, we highlight possible challenges that need to be overcome to develop Human-Centred AI systems. We illuminate our MAP model through complementary case studies on colonoscopy practice and dementia diagnosis, providing examples of the challenges encountered in real-world settings. By defining Human-AI interaction across these three stages, we untangle some of the inherent complexities in designing AI technology for clinical decision-making, and aim to overcome misalignment between medical end-users and AI researchers and developers.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":" ","pages":"1 - 33"},"PeriodicalIF":3.7,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47846018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Margaret E. Morris, Jennifer Brown, Paula S. nurius, Savanna Yee, Jennifer Mankoff, Sunny Consolvo
During the COVID-19 pandemic, risk negotiation became an important precursor to in-person contact. For young adults, social planning generally occurs through computer-mediated communication. Given the importance of social connectedness for mental health and academic engagement, we sought to understand how young adults plan in-person meetups over computer-mediated communication in the context of the pandemic. We present a qualitative study that explores young adults’ risk negotiation during the COVID-19 pandemic, a period of conflicting public health guidance. Inspired by cultural probe studies, we invited participants to express their preferred precautions for one week as they planned in-person meetups. We interviewed and surveyed participants about their experiences. Through qualitative analysis, we identify strategies for risk negotiation, social complexities that impede risk negotiation, and emotional consequences of risk negotiation. Our findings have implications for AI-mediated support for risk negotiation and assertive communication more generally. We explore tensions between risks and potential benefits of such systems.
{"title":"“I Just Wanted to Triple Check… They were all Vaccinated”: Supporting Risk Negotiation in the Context of COVID-19","authors":"Margaret E. Morris, Jennifer Brown, Paula S. nurius, Savanna Yee, Jennifer Mankoff, Sunny Consolvo","doi":"10.1145/3569938","DOIUrl":"https://doi.org/10.1145/3569938","url":null,"abstract":"During the COVID-19 pandemic, risk negotiation became an important precursor to in-person contact. For young adults, social planning generally occurs through computer-mediated communication. Given the importance of social connectedness for mental health and academic engagement, we sought to understand how young adults plan in-person meetups over computer-mediated communication in the context of the pandemic. We present a qualitative study that explores young adults’ risk negotiation during the COVID-19 pandemic, a period of conflicting public health guidance. Inspired by cultural probe studies, we invited participants to express their preferred precautions for one week as they planned in-person meetups. We interviewed and surveyed participants about their experiences. Through qualitative analysis, we identify strategies for risk negotiation, social complexities that impede risk negotiation, and emotional consequences of risk negotiation. Our findings have implications for AI-mediated support for risk negotiation and assertive communication more generally. We explore tensions between risks and potential benefits of such systems.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":" ","pages":"1 - 31"},"PeriodicalIF":3.7,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43396078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Most social media platforms implement content moderation to address interpersonal harms such as harassment. Content moderation relies on offender-centered, punitive approaches, e.g., bans and content removal. We consider an alternative justice framework, restorative justice, which aids victims in healing, supports offenders in repairing the harm, and engages community members in addressing the harm collectively. To assess the utility of restorative justice in addressing online harm, we interviewed 23 users from Overwatch gaming communities, including moderators, victims, and offenders; such communities are particularly susceptible to harm, with nearly three quarters of all online game players suffering from some form of online abuse. We study how the communities currently handle harm cases through the lens of restorative justice and examine their attitudes toward implementing restorative justice processes. Our analysis reveals that cultural, technical, and resource-related obstacles hinder implementation of restorative justice within the existing punitive framework despite online community needs and existing structures to support it. We discuss how current content moderation systems can embed restorative justice goals and practices and overcome these challenges.
{"title":"Addressing Interpersonal Harm in Online Gaming Communities: The Opportunities and Challenges for a Restorative Justice Approach","authors":"Sijia Xiao, Shagun Jhaver, Niloufar Salehi","doi":"10.1145/3603625","DOIUrl":"https://doi.org/10.1145/3603625","url":null,"abstract":"Most social media platforms implement content moderation to address interpersonal harms such as harassment. Content moderation relies on offender-centered, punitive approaches, e.g., bans and content removal. We consider an alternative justice framework, restorative justice, which aids victims in healing, supports offenders in repairing the harm, and engages community members in addressing the harm collectively. To assess the utility of restorative justice in addressing online harm, we interviewed 23 users from Overwatch gaming communities, including moderators, victims, and offenders; such communities are particularly susceptible to harm, with nearly three quarters of all online game players suffering from some form of online abuse. We study how the communities currently handle harm cases through the lens of restorative justice and examine their attitudes toward implementing restorative justice processes. Our analysis reveals that cultural, technical, and resource-related obstacles hinder implementation of restorative justice within the existing punitive framework despite online community needs and existing structures to support it. We discuss how current content moderation systems can embed restorative justice goals and practices and overcome these challenges.","PeriodicalId":50917,"journal":{"name":"ACM Transactions on Computer-Human Interaction","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46864965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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