80 citations · 138 across the 8 of their papers we have counts for
11 papers
GUIDE: Generative Utility Inference and Decision Engine
Anagha Tiwari, Alexander G. Gray, Nick Feamster +3
Measuring the preferences of human users remains a fundamental challenge of AI alignment. Existing elicitation approaches struggle to efficiently discover multidimensional preferen…
VMC: A Grammar for Visualizing Statistical Model Checks
Ziyang Guo, Alex Kale, Matthew Kay +1
Visualizations play a critical role in validating and improving statistical models. However, the design space of model check visualizations is not well understood, making it diffic…
Underspecified Human Decision Experiments Considered Harmful
Jessica Hullman, Alex Kale, Jason Hartline
Decision-making with information displays is a key focus of research in areas like human-AI collaboration and data visualization. However, what constitutes a decision problem, and…
EVM: Incorporating Model Checking into Exploratory Visual Analysis
Alex Kale, Ziyang Guo, Xiao Li Qiao +2
Visual analytics (VA) tools support data exploration by helping analysts quickly and iteratively generate views of data which reveal interesting patterns. However, these tools seld…
MetaExplorer: Facilitating Reasoning with Epistemic Uncertainty in Meta-analysis
Alex Kale, Sarah Lee, Terrance Goan +2
Scientists often use meta-analysis to characterize the impact of an intervention on some outcome of interest across a body of literature. However, threats to the utility and validi…
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
Zijie J. Wang, Alex Kale, Harsha Nori +6
Machine learning (ML) interpretability techniques can reveal undesirable patterns in data that models exploit to make predictions--potentially causing harms once deployed. However,…
GAM Changer: Editing Generalized Additive Models with Interactive Visualization
Zijie J. Wang, Alex Kale, Harsha Nori +6
Recent strides in interpretable machine learning (ML) research reveal that models exploit undesirable patterns in the data to make predictions, which potentially causes harms in de…
Causal Support: Modeling Causal Inferences with Visualizations
Alex Kale, Yifan Wu, Jessica Hullman
Analysts often make visual causal inferences about possible data-generating models. However, visual analytics (VA) software tends to leave these models implicit in the mind of the…
Boba: Authoring and Visualizing Multiverse Analyses
Yang Liu, Alex Kale, Tim Althoff +1
Multiverse analysis is an approach to data analysis in which all "reasonable" analytic decisions are evaluated in parallel and interpreted collectively, in order to foster robustne…
Visual Reasoning Strategies for Effect Size Judgments and Decisions
Alex Kale, Matthew Kay, Jessica Hullman
Uncertainty visualizations often emphasize point estimates to support magnitude estimates or decisions through visual comparison. However, when design choices emphasize means, user…
Decision-Making Under Uncertainty in Research Synthesis: Designing for the Garden of Forking Paths
Alex Kale, Matthew Kay, Jessica Hullman
To make evidence-based recommendations to decision-makers, researchers conducting systematic reviews and meta-analyses must navigate a garden of forking paths: a series of analytic…