helpResearch questionAlgorithmic Stigmatization and Social Harm
What types of perceived bias exist in AI companions?Direction: Fairness, Bias, and Research Governance
Algorithmic Stigmatization and Social Harm
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21 items
helpResearch questionAlgorithmic Stigmatization and Social Harm
How do users actively adjust AI companion values through interaction to reflect personal or community values?helpResearch questionAlgorithmic Stigmatization and Social Harm
What are the short-term effects and limitations of user-driven value adjustment strategies in real-world scenarios?lightbulbPractical problemAlgorithmic Stigmatization and Social Harm
Bias and harmful content in AI companions may cause psychological harm and social impact for users.lightbulbPractical problemAlgorithmic Stigmatization and Social Harm
Digital systems easily reinforce or exacerbate obesity discrimination, causing unfair treatment of larger-bodied groups.helpResearch questionAlgorithmic Stigmatization and Social Harm
How do algorithms cause stigmatization (algorithmic stigma) through labeling, stereotyping, segregation, and status loss/discrimination?helpResearch questionAlgorithmic Stigmatization and Social Harm
In algorithmic stigmatization, how do allocative and representational harms interact?helpResearch questionAlgorithmic Stigmatization and Social Harm
What social and technical intervention possibilities exist for algorithmic stigmatization?lightbulbPractical problemAlgorithmic Stigmatization and Social Harm
Algorithms may exacerbate social inequality through stigmatization, such as affecting higher education opportunities or mental health support.helpResearch questionAlgorithmic Stigmatization and Social Harm
Do media moral frames about mental health affect public stigmatizing attitudes toward mental illness?helpResearch questionAlgorithmic Stigmatization and Social Harm
On which moral dimensions do mental health narratives on Twitter and in news media differ?helpResearch questionAlgorithmic Stigmatization and Social Harm
How are positive and negative moral frames associated with the frequency of stigmatizing language in mental health narratives?lightbulbPractical problemAlgorithmic Stigmatization and Social Harm
Media coverage and social media often present mental health negatively, increasing stigmatization risk.helpResearch questionAlgorithmic Stigmatization and Social Harm
How do first-person and third-person narrative chatbots differ in reducing mental illness stigma?helpResearch questionAlgorithmic Stigmatization and Social Harm
How can chatbots promote self-disclosure and reduce mental illness stigma by simulating social contact?helpResearch questionAlgorithmic Stigmatization and Social Harm
Are chatbots effective at reducing responsibility attribution and social distance toward people with mental illness?lightbulbPractical problemAlgorithmic Stigmatization and Social Harm
Public stigma toward people with mental illness hinders their help-seeking and recovery.helpResearch questionAlgorithmic Stigmatization and Social Harm
How do users perceive bias in AI systems?helpResearch questionAlgorithmic Stigmatization and Social Harm
How do users' needs for bias and explanation differ in black-box AI systems?helpResearch questionAlgorithmic Stigmatization and Social Harm
How do users' needs for AI transparency and explainability differ between high-risk and low-risk application scenarios?lightbulbPractical problemAlgorithmic Stigmatization and Social Harm
Users lack awareness of AI bias sources and transparency, reducing trust.Related papers
CHI 2025
User-Driven Value Alignment: Understanding Users' Perceptions and Strategies for Addressing Biased and Discriminatory Statements in AI Companions
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Conceptualising Fatness within HCI: A Call for Fat Liberation
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Conceptualizing Algorithmic Stigmatization
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Moral Framing of Mental Health Discourse and Its Relationship to Stigma: A Comparison of Social Media and News
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Exploring Effects of Chatbot-based Social Contact on Reducing Mental Illness Stigma
YI-CHIEH LEE, Yichao Cui, Jack Jamieson
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Contextualizing User Perceptions about Biases for Human-Centered Explainable Artificial Intelligence
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