8 citations · 15 across the 14 of their papers we have counts for
16 papers
Learning Checklists to Reduce Lottery Effects in Scientific Peer Review
Xuanyou Liu, Ziyang Guo, Jason Hartline +1
Reviewer lottery error describes error due to a small set of peer reviews attending to only some of the issues with a paper that a larger pool of eligible reviewers would raise. We…
Calibrating LLM Explanations to Human Decisions with Reinforcement Learning
Dong Shu, Ziyang Guo, Negar Kamali +2
Explanations of LLM outputs are considered an important way to make model behavior legible, helping human users make good decisions on downstream tasks. However, default training a…
Generative AI Literacy Training Improves Intelligence Analysts' Discrimination of Real and AI-Generated Images
Negar Kamali, Candice Rockell Gerstner, Jessica Hullman +1
Across social and online platforms, people are increasingly exposed to AI-generated images. As a consequence, the task of distinguishing AI-generated from authentic images is becom…
Hypothesizing an effect size by considering individual variation
Andrew Gelman, Amy Krefman, Lauren Kennedy +1
When designing and evaluating an experiment or observational study, it is useful to have a realistic hypothesis regarding the average treatment effect. We present an approach to co…
This human study did not involve human subjects: Validating LLM simulations as behavioral evidence
Jessica Hullman, David Broska, Huaman Sun +1
A growing literature uses large language models (LLMs) as synthetic participants to generate cost-effective and nearly instantaneous responses in social science experiments. Howeve…
Behavioral Study of Dashboard Mechanisms
Paula Kayongo, Jessica Hullman, Jason Hartline
Visualization dashboards are increasingly used in strategic settings like auctions to enhance decision-making and reduce strategic confusion. This paper presents behavioral experim…
Bridging Prediction and Intervention Problems in Social Systems
Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou +32
Many automated decision systems (ADS) are designed to solve prediction problems -- where the goal is to learn patterns from a sample of the population and apply them to individuals…
Explanations are a Means to an End: Decision Theoretic Explanation Evaluation
Ziyang Guo, Berk Ustun, Jessica Hullman
Explanations of model behavior are commonly evaluated via proxy properties weakly tied to the purposes explanations serve in practice. We contribute a decision theoretic framework…
Conformal Prediction and Human Decision Making
Jessica Hullman, Yifan Wu, Dawei Xie +2
Methods to quantify uncertainty in predictions from arbitrary models are in demand in high-stakes domains like medicine and finance. Conformal prediction has emerged as a popular m…
Seeing Eye to AI? Applying Deep-Feature-Based Similarity Metrics to Information Visualization
Sheng Long, Angelos Chatzimparmpas, Emma Alexander +2
Judging the similarity of visualizations is crucial to various applications, such as visualization-based search and visualization recommendation systems. Recent studies show deep-f…
Characterizing Photorealism and Artifacts in Diffusion Model-Generated Images
Negar Kamali, Karyn Nakamura, Aakriti Kumar +3
Diffusion model-generated images can appear indistinguishable from authentic photographs, but these images often contain artifacts and implausibilities that reveal their AI-generat…
Explaining and Improving Information Complementarities in Multi-Agent Decision-making
Ziyang Guo, Yifan Wu, Jason Hartline +1
Multiple agents are increasingly combined to make decisions with the expectation of achieving complementary performance, where the decisions they make together outperform those mad…
What to Consider When Considering Differential Privacy for Policy
Priyanka Nanayakkara, Jessica Hullman
Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to variou…
Automating the Practice of Science -- Opportunities, Challenges, and Implications
Sebastian Musslick, Laura K. Bartlett, Suyog H. Chandramouli +11
Automation transformed various aspects of our human civilization, revolutionizing industries and streamlining processes. In the domain of scientific inquiry, automated approaches e…
How to Distinguish AI-Generated Images from Authentic Photographs
Negar Kamali, Karyn Nakamura, Angelos Chatzimparmpas +2
The high level of photorealism in state-of-the-art diffusion models like Midjourney, Stable Diffusion, and Firefly makes it difficult for untrained humans to distinguish between re…
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…