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Given the renewed attention on politics, values, and ethics within our field and the wider cultural milieu, now is the time to take stock of social justice research in HCI. We surveyed 124 papers explicitly pursuing social justice between 2009 and 2022 to better reflect on the current state of justice-oriented work within our discipline. We identified (1) how researchers understood the social justice-relevant harms and benefits, (2) the approaches researchers used to address harm, and (3) the tools that researchers leveraged to pursue justice. Our analysis highlights gaps in social justice work, such as the need for our community to conceptualize benefits, and identifies concrete steps the HCI community can take to pursue just futures. By providing a comprehensive overview of and reflection on HCI's current social justice landscape, we seek to help our research community strategize, collaborate, and collectively act toward justice.
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.
Homelessness is a humanitarian challenge affecting an estimated 1.6 billion people worldwide. In the face of rising homeless populations in developed nations and a strain on social services, government agencies are increasingly adopting data-driven models to determine one’s risk of experiencing homelessness and assigning scarce resources to those in need. We conducted a systematic literature review of 57 papers to understand the evolution of these decision-making algorithms. We investigated trends in computational methods, predictor variables, and target outcomes used to develop the models using a human-centered lens and found that only 9 papers (15.7%) investigated model fairness and bias. We uncovered tensions between explainability and ecological validity wherein predictive risk models (53.4%) unduly focused on reductive explainability while resource allocation models (25.9%) were dependent on unrealistic assumptions and simulated data that are not useful in practice. Further, we discuss research challenges and opportunities for developing human-centered algorithms in this area.