83 citations · 358 across the 21 of their papers we have counts for
17 papers · 1 filter
Intelligent Reasoning Cues: A Framework and Case Study of the Roles of AI Information in Complex Decisions
Venkatesh Sivaraman, Eric P. Mason, Mengfan Ellen Li +4
Artificial intelligence (AI)-based decision support systems can be highly accurate yet still fail to support users or improve decisions. Existing theories of AI-assisted decision-m…
TempoQL: A Readable, Precise, and Portable Query System for Electronic Health Record Data
Ziyong Ma, Richard D. Boyce, Adam Perer +1
Electronic health record (EHR) data is an essential data source for machine learning for health, but researchers and clinicians face steep barriers in extracting and validating EHR…
Design Patterns of Human-AI Interfaces in Healthcare
Rui Sheng, Chuhan Shi, Sobhan Lotfi +4
Human-AI interfaces play a pivotal role in integrating clinicians' expertise with artificial intelligence to enhance both healthcare practice and research. However, designing effec…
Tempo: Helping Data Scientists and Domain Experts Collaboratively Specify Predictive Modeling Tasks
Venkatesh Sivaraman, Anika Vaishampayan, Xiaotong Li +4
Temporal predictive models have the potential to improve decisions in health care, public services, and other domains, yet they often fail to effectively support decision-makers. P…
Static Algorithm, Evolving Epidemic: Understanding the Potential of Human-AI Risk Assessment to Support Regional Overdose Prevention
Venkatesh Sivaraman, Yejun Kwak, Courtney Kuza +6
Drug overdose deaths, including those due to prescription opioids, represent a critical public health issue in the United States and worldwide. Artificial intelligence (AI) approac…
Divisi: Interactive Search and Visualization for Scalable Exploratory Subgroup Analysis
Venkatesh Sivaraman, Zexuan Li, Adam Perer
Analyzing data subgroups is a common data science task to build intuition about a dataset and identify areas to improve model performance. However, subgroup analysis is prohibitive…
Sketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Unit
Nur Yildirim, Susanna Zlotnikov, Deniz Sayar +14
Advances in artificial intelligence (AI) have enabled unprecedented capabilities, yet innovation teams struggle when envisioning AI concepts. Data science teams think of innovation…
The Impact of Imperfect XAI on Human-AI Decision-Making
Katelyn Morrison, Philipp Spitzer, Violet Turri +3
Explainability techniques are rapidly being developed to improve human-AI decision-making across various cooperative work settings. Consequently, previous research has evaluated ho…
Zeno: An Interactive Framework for Behavioral Evaluation of Machine Learning
Ángel Alexander Cabrera, Erica Fu, Donald Bertucci +4
Machine learning models with high accuracy on test data can still produce systematic failures, such as harmful biases and safety issues, when deployed in the real world. To detect…
Ignore, Trust, or Negotiate: Understanding Clinician Acceptance of AI-Based Treatment Recommendations in Health Care
Venkatesh Sivaraman, Leigh A. Bukowski, Joel Levin +2
Artificial intelligence (AI) in healthcare has the potential to improve patient outcomes, but clinician acceptance remains a critical barrier. We developed a novel decision support…
Improving Human-AI Collaboration With Descriptions of AI Behavior
Ángel Alexander Cabrera, Adam Perer, Jason I. Hong
People work with AI systems to improve their decision making, but often under- or over-rely on AI predictions and perform worse than they would have unassisted. To help people appr…
"Public(s)-in-the-Loop": Facilitating Deliberation of Algorithmic Decisions in Contentious Public Policy Domains
Hong Shen, Ángel Alexander Cabrera, Adam Perer +1
This position paper offers a framework to think about how to better involve human influence in algorithmic decision-making of contentious public policy issues. Drawing from insight…
Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support
Anna Kawakami, Venkatesh Sivaraman, Hao-Fei Cheng +7
AI-based decision support tools (ADS) are increasingly used to augment human decision-making in high-stakes, social contexts. As public sector agencies begin to adopt ADS, it is cr…
Emblaze: Illuminating Machine Learning Representations through Interactive Comparison of Embedding Spaces
Venkatesh Sivaraman, Yiwei Wu, Adam Perer
Modern machine learning techniques commonly rely on complex, high-dimensional embedding representations to capture underlying structure in the data and improve performance. In orde…
Characterizing Human Explanation Strategies to Inform the Design of Explainable AI for Building Damage Assessment
Donghoon Shin, Sachin Grover, Kenneth Holstein +1
Explainable AI (XAI) is a promising means of supporting human-AI collaborations for high-stakes visual detection tasks, such as damage detection tasks from satellite imageries, as…
Discovering and Validating AI Errors With Crowdsourced Failure Reports
Ángel Alexander Cabrera, Abraham J. Druck, Jason I. Hong +1
AI systems can fail to learn important behaviors, leading to real-world issues like safety concerns and biases. Discovering these systematic failures often requires significant dev…
Ablate, Variate, and Contemplate: Visual Analytics for Discovering Neural Architectures
Dylan Cashman, Adam Perer, Remco Chang +1
Deep learning models require the configuration of many layers and parameters in order to get good results. However, there are currently few systematic guidelines for how to configu…