Your Model Is Unfair, Are You Even Aware? Inverse Relationship Between Comprehension and Trust in Explainability Visualizations of Biased ML Models
Fuente:
arXiv
Saved in:
| Main Authors: | Kaufman, Zhanna, Endres, Madeline, Bearfield, Cindy Xiong, Brun, Yuriy |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
My Model is Unfair, Do People Even Care? Visual Design Affects Trust and Perceived Bias in Machine Learning
by: Gaba, Aimen, et al.
Published: (2023)
by: Gaba, Aimen, et al.
Published: (2023)
Bias, Accuracy, and Trust: Gender-Diverse Perspectives on Large Language Models
by: Gaba, Aimen, et al.
Published: (2025)
by: Gaba, Aimen, et al.
Published: (2025)
Do You "Trust" This Visualization? An Inventory to Measure Trust in Visualizations
by: Wang, Huichen Will, et al.
Published: (2025)
by: Wang, Huichen Will, et al.
Published: (2025)
Write, Rank, or Rate: Comparing Methods for Studying Visualization Affordances
by: Stokes, Chase, et al.
Published: (2025)
by: Stokes, Chase, et al.
Published: (2025)
The Role of Text in Visualizations: How Annotations Shape Perceptions of Bias and Influence Predictions
by: Stokes, Chase, et al.
Published: (2024)
by: Stokes, Chase, et al.
Published: (2024)
Same Data, Diverging Perspectives: The Power of Visualizations to Elicit Competing Interpretations
by: Bearfield, Cindy Xiong, et al.
Published: (2024)
by: Bearfield, Cindy Xiong, et al.
Published: (2024)
Grid Labeling: Crowdsourcing Task-Specific Importance from Visualizations
by: Chang, Minsuk, et al.
Published: (2025)
by: Chang, Minsuk, et al.
Published: (2025)
Motion-based visual encoding can improve performance on perceptual tasks with dynamic time series
by: Hu, Songwen, et al.
Published: (2024)
by: Hu, Songwen, et al.
Published: (2024)
Gridlines Mitigate Sine Illusion in Line Charts
by: Knittel, Clayton, et al.
Published: (2024)
by: Knittel, Clayton, et al.
Published: (2024)
Perception-aware Sampling for Scatterplot Visualizations
by: Moumoulidou, Zafeiria, et al.
Published: (2025)
by: Moumoulidou, Zafeiria, et al.
Published: (2025)
Data-Induced Groupings and How To Find Them
by: Jiang, Yilan, et al.
Published: (2026)
by: Jiang, Yilan, et al.
Published: (2026)
Playing telephone with generative models: "verification disability," "compelled reliance," and accessibility in data visualization
by: Elavsky, Frank, et al.
Published: (2025)
by: Elavsky, Frank, et al.
Published: (2025)
From Perception to Decision: Assessing the Role of Chart Types Affordances in High-Level Decision Tasks
by: Li, Yixuan, et al.
Published: (2024)
by: Li, Yixuan, et al.
Published: (2024)
Efficiently Crowdsourcing Visual Importance with Punch-Hole Annotation
by: Chang, Minsuk, et al.
Published: (2024)
by: Chang, Minsuk, et al.
Published: (2024)
Tell Me Without Telling Me: Two-Way Prediction of Visualization Literacy and Visual Attention
by: Chang, Minsuk, et al.
Published: (2025)
by: Chang, Minsuk, et al.
Published: (2025)
Cognitive Trust in HRI: "Pay Attention to Me and I'll Trust You Even if You are Wrong"
by: Manor, Adi, et al.
Published: (2025)
by: Manor, Adi, et al.
Published: (2025)
How Aligned are Human Chart Takeaways and LLM Predictions? A Case Study on Bar Charts with Varying Layouts
by: Wang, Huichen Will, et al.
Published: (2024)
by: Wang, Huichen Will, et al.
Published: (2024)
Training Spatial Ability in Virtual Reality
by: Demetriou, Yiannos, et al.
Published: (2025)
by: Demetriou, Yiannos, et al.
Published: (2025)
Searching Through Complex Worlds: Visual Search and Spatial Regularity Memory in Mixed Reality
by: Lai, Lefan, et al.
Published: (2026)
by: Lai, Lefan, et al.
Published: (2026)
Trust Your Gut: Comparing Human and Machine Inference from Noisy Visualizations
by: Koonchanok, Ratanond, et al.
Published: (2024)
by: Koonchanok, Ratanond, et al.
Published: (2024)
Effects of Multimodal Explanations for Autonomous Driving on Driving Performance, Cognitive Load, Expertise, Confidence, and Trust
by: Kaufman, Robert, et al.
Published: (2024)
by: Kaufman, Robert, et al.
Published: (2024)
Raising Awareness of Location Information Vulnerabilities in Social Media Photos using LLMs
by: Ma, Ying, et al.
Published: (2025)
by: Ma, Ying, et al.
Published: (2025)
Why Would You Suggest That? Human Trust in Language Model Responses
by: Sharma, Manasi, et al.
Published: (2024)
by: Sharma, Manasi, et al.
Published: (2024)
Situationally-Induced Impairments and Disabilities Research
by: Sarsenbayeva, Zhanna, et al.
Published: (2019)
by: Sarsenbayeva, Zhanna, et al.
Published: (2019)
Hell is Paved with Good Intentions: The Intricate Relationship Between Cognitive Biases and Dark Patterns
by: Mildner, Thomas, et al.
Published: (2024)
by: Mildner, Thomas, et al.
Published: (2024)
Attack-Resilient Image Watermarking Using Stable Diffusion
by: Zhang, Lijun, et al.
Published: (2024)
by: Zhang, Lijun, et al.
Published: (2024)
Trust in Transparency: How Explainable AI Shapes User Perceptions
by: Sunny, Allen Daniel
Published: (2025)
by: Sunny, Allen Daniel
Published: (2025)
Are Cognitive Biases as Important as they Seem for Data Visualization?
by: Baigelenov, Ali, et al.
Published: (2025)
by: Baigelenov, Ali, et al.
Published: (2025)
Will You Be Aware? Eye Tracking-Based Modeling of Situational Awareness in Augmented Reality
by: Qu, Zhehan, et al.
Published: (2025)
by: Qu, Zhehan, et al.
Published: (2025)
Predicting Trust In Autonomous Vehicles: Modeling Young Adult Psychosocial Traits, Risk-Benefit Attitudes, And Driving Factors With Machine Learning
by: Kaufman, Robert, et al.
Published: (2024)
by: Kaufman, Robert, et al.
Published: (2024)
The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations
by: Chatzimparmpas, A., et al.
Published: (2022)
by: Chatzimparmpas, A., et al.
Published: (2022)
STL: Still Tricky Logic (for System Validation, Even When Showing Your Work)
by: Hurley, Isabelle, et al.
Published: (2024)
by: Hurley, Isabelle, et al.
Published: (2024)
Preliminary Quantitative Study on Explainability and Trust in AI Systems
by: Sunny, Allen Daniel
Published: (2025)
by: Sunny, Allen Daniel
Published: (2025)
Not Even Nice Work If You Can Get It; A Longitudinal Study of Uber's Algorithmic Pay and Pricing
by: Binns, Reuben, et al.
Published: (2025)
by: Binns, Reuben, et al.
Published: (2025)
Do You See What I See? A Qualitative Study Eliciting High-Level Visualization Comprehension
by: Quadri, Ghulam Jilani, et al.
Published: (2024)
by: Quadri, Ghulam Jilani, et al.
Published: (2024)
Developing Situational Awareness for Joint Action with Autonomous Vehicles
by: Kaufman, Robert, et al.
Published: (2024)
by: Kaufman, Robert, et al.
Published: (2024)
LLMs Corrupt Your Documents When You Delegate
by: Laban, Philippe, et al.
Published: (2026)
by: Laban, Philippe, et al.
Published: (2026)
TA-GNN: Physics Inspired Time-Agnostic Graph Neural Network for Finger Motion Prediction
by: Li, Tinghui, et al.
Published: (2025)
by: Li, Tinghui, et al.
Published: (2025)
The Impact of Uncertainty Visualization on Trust in Thematic Maps
by: Srivastava, Varun, et al.
Published: (2026)
by: Srivastava, Varun, et al.
Published: (2026)
How Can Explainable Artificial Intelligence Improve Trust and Transparency in Medical Diagnosis Systems?
by: Seitenov, Altynbek, et al.
Published: (2026)
by: Seitenov, Altynbek, et al.
Published: (2026)
Similar Items
-
My Model is Unfair, Do People Even Care? Visual Design Affects Trust and Perceived Bias in Machine Learning
by: Gaba, Aimen, et al.
Published: (2023) -
Bias, Accuracy, and Trust: Gender-Diverse Perspectives on Large Language Models
by: Gaba, Aimen, et al.
Published: (2025) -
Do You "Trust" This Visualization? An Inventory to Measure Trust in Visualizations
by: Wang, Huichen Will, et al.
Published: (2025) -
Write, Rank, or Rate: Comparing Methods for Studying Visualization Affordances
by: Stokes, Chase, et al.
Published: (2025) -
The Role of Text in Visualizations: How Annotations Shape Perceptions of Bias and Influence Predictions
by: Stokes, Chase, et al.
Published: (2024)