Quan Ze Chen

schoolUniversity Of Washingtonbar_chart#1261 Global Rank

Total Papers

HCI Rank

#1261

Research Areas

Years Active

Recent Publications

Botender: Supporting Communities in Collaboratively Designing AI Agents through Case-Based Provocations

AI agents, or bots, serve important roles in online communities. However, they are often designed by outsiders or a few tech-savvy members, leading to bots that may not align with the broader community's needs. How might communities collectively shape the behavior of community bots? We present Botender, a system that…

CHI '254th AuthorHuman-LLM Collaboration +1

End User Authoring of Personalized Content Classifiers: Comparing Example Labeling, Rule Writing, and LLM Prompting

Existing tools for laypeople to create personal classifiers often assume a motivated user working uninterrupted in a single, lengthy session. However, users tend to engage with social media casually, with many short sessions on an ongoing, daily basis. To make creating personal classifiers for content curation easier…

CHI '252nd AuthorSocial Platform Design & User Behavior +2

PolicyCraft: Supporting Collaborative and Participatory Policy Design through Case-Grounded Deliberation

Community and organizational policies are typically designed in a top-down, centralized fashion, with limited input from impacted stakeholders. This can result in policies that are misaligned with community needs or perceived as illegitimate. How can we support more collaborative, participatory approaches to policy de…

CSCW '233rd AuthorModeration I

Personalizing Content Moderation on Social Media: User Perspectives on Moderation Choices, Interface Design, and Labor

Social media platforms moderate content for each user by incorporating the outputs of both platform-wide content moderation systems and, in some cases, user-configured personal moderation preferences. However, it is unclear (1) how end users perceive the choices and affordances of different kinds of personal content m…

CSCW '231st AuthorCollaboration II

Judgment Sieve: Reducing Uncertainty in Group Judgments through Interventions Targeting Ambiguity versus Disagreement

When groups of people are tasked with making a judgment, the issue of uncertainty often arises. Existing methods to reduce uncertainty typically focus on iteratively improving specificity in the overall task instruction. However, uncertainty can arise from multiple sources, such as ambiguity of the item being judged d…

IUI '221st AuthorAI-Assisted Decision-Making & Automation +1

HINT: Integration Testing for AI-based features with Humans in the Loop

The dynamic nature of AI technologies makes testing human-AI interaction and collaboration challenging especially before such features are deployed in the wild. This presents a challenge for designers and AI practitioners as early feedback for iteration is often unavailable in the development phase. In this paper, we…

CHI '222nd AuthorOnline Harassment & Counter-Tools +1

Designing Word Filter Tools for Creator-led Comment Moderation

Online social platforms centered around content creators often allow comments on content, where creators moderate the comments they receive. As creators can face overwhelming numbers of comments, with some of them harassing or hateful, platforms typically provide tools such as word filters for creators to automate asp…

CSCW '211st AuthorCrowds and Collaboration

Goldilocks: Consistent Crowdsourced Scalar Annotations with Relative Uncertainty

Human ratings have become a crucial resource for training and evaluating machine learning systems. However, traditional elicitation methods for absolute and comparative rating suffer from issues with consistency and often do not distinguish between uncertainty due to disagreement between annotators and ambiguity inhe…

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