11 citations · 13 across the 5 of their papers we have counts for
8 papers
Vibe Analysis: Exploring LLM Adoption by Data Visualization Practitioners
Shani C Spivak, Aditi Krishna, Mahsan Nourani +1
Large language models (LLMs) are enticing in their promise to support data visualization (Vis) through faster and simpler workflows for data prep, analysis, and visualization creat…
Human-in-the-Loop User Feedback Affects Perceived Accuracy and Trust, but Task Subjectivity Matters
Donald R. Honeycutt, Mahsan Nourani, Eric D. Ragan
While ML can produce complex models beyond those that a human could produce manually, incorporating human input can often improve performance beyond purely data-driven models. Whil…
"Trust Junk" Leads to Unjustified Support for Highly Discriminatory Predictive Models
Michael Correll, Lucy Havens, Mahsan Nourani
The persuasive power of data visualizations can go awry: for instance, in an explainable AI (XAI) context, visualizations can produce over-trust of predictive models. In this paper…
Amplifying Rural Educators' Perspectives: A Qualitative Study of Generative AI's Impact in Rural U.S. High Schools
Shira Michel, Benjamin Taylor, Sabrina Parra Díaz +3
Recent breakthroughs in Generative AI (GenAI) are reshaping educational landscapes, presenting challenges and opportunities. While all contexts present unique challenges, rural sch…
Soliciting Human-in-the-Loop User Feedback for Interactive Machine Learning Reduces User Trust and Impressions of Model Accuracy
Donald R. Honeycutt, Mahsan Nourani, Eric D. Ragan
Mixed-initiative systems allow users to interactively provide feedback to potentially improve system performance. Human feedback can correct model errors and update model parameter…
The Role of Domain Expertise in User Trust and the Impact of First Impressions with Intelligent Systems
Mahsan Nourani, Joanie T. King, Eric D. Ragan
Domain-specific intelligent systems are meant to help system users in their decision-making process. Many systems aim to simultaneously support different users with varying levels…
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition
Mahsan Nourani, Chiradeep Roy, Tahrima Rahman +3
Explainable machine learning and artificial intelligence models have been used to justify a model's decision-making process. This added transparency aims to help improve user perfo…
SplitStreams: A Visual Metaphor for Evolving Hierarchies
Fabian Bolte, Mahsan Nourani, Eric D. Ragan +1
The visualization of hierarchically structured data over time is an ongoing challenge and several approaches exist trying to solve it. Techniques such as animated or juxtaposed tre…