705 citations · 1.7k across the 20 of their papers we have counts for
5 papers · 1 filter
Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML
Shweta Narkar, Yunfeng Zhang, Q. Vera Liao +2
Automated Machine Learning (AutoML) is a rapidly growing set of technologies that automate the model development pipeline by searching model space and generating candidate models.…
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making
Charvi Rastogi, Yunfeng Zhang, Dennis Wei +3
Several strands of research have aimed to bridge the gap between artificial intelligence (AI) and human decision-makers in AI-assisted decision-making, where humans are the consume…
Measuring Social Biases of Crowd Workers using Counterfactual Queries
Bhavya Ghai, Q. Vera Liao, Yunfeng Zhang +1
Social biases based on gender, race, etc. have been shown to pollute machine learning (ML) pipeline predominantly via biased training datasets. Crowdsourcing, a popular cost-effect…
Explainable Active Learning (XAL): An Empirical Study of How Local Explanations Impact Annotator Experience
Bhavya Ghai, Q. Vera Liao, Yunfeng Zhang +2
The wide adoption of Machine Learning technologies has created a rapidly growing demand for people who can train ML models. Some advocated the term "machine teacher" to refer to th…
Explaining Models: An Empirical Study of How Explanations Impact Fairness Judgment
Jonathan Dodge, Q. Vera Liao, Yunfeng Zhang +2
Ensuring fairness of machine learning systems is a human-in-the-loop process. It relies on developers, users, and the general public to identify fairness problems and make improvem…