Jing Nathan Yan

schoolCornell Universitybar_chart#3866 Global Rank

Total Papers

HCI Rank

#3866

Research Areas

Years Active

Recent Publications

Fairness-in-the-Workflow: How Machine Learning Practitioners at Big Tech Companies Approach Fairness in Recommender Systems

Recommender systems (RS), which are widely deployed across high-stakes domains, are susceptible to biases that can cause large-scale societal impacts. Researchers have proposed methods to measure and mitigate such biases - but translating academic theory into practice is inherently challenging. Through a semi-structur…

CHI '211st AuthorInteractive Data Visualization +1

Tessera: Discretizing Data Analysis Workflows on a Task Level

Researchers have investigated a number of strategies for capturing and analyzing data analyst event logs in order to design better tools, identify failure points, and guide users. However, this remains challenging because individual- and session-level behavioral differences lead to an explosion of complexity and there…

CHI '201st AuthorAI Ethics, Fairness & Accountability +2

Silva: Interactively Assessing Machine Learning Fairness Using Causality

Machine learning models risk encoding unfairness on the part of their developers or data sources. However, assessing fairness is challenging as analysts might misidentify sources of bias, fail to notice them, or misapply metrics. In this paper we introduce Silva, a system for exploring potential sources of unfairness…

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