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What Did My AI Learn? How Data Scientists Make Sense of Model Behavior

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-031-02197-8openalex-snapshot
HCI Theory
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Snorkel: rapid training data creation with weak supervision.
inferredcites →https://doi.org/10.1007/s10916-011-9718-xopenalex-snapshot
Extracting Insights from Electronic Health Records: Case Studies, a Visual Analytics Process Model, and Design Recommendations
inferredcites →https://doi.org/10.1007/s13398-014-0173-7.2openalex-snapshot
Democracy Barometer. Methodology. Version 4.
inferredcites →https://doi.org/10.1038/515151aopenalex-snapshot
Interactive notebooks: Sharing the code
inferredcites →https://doi.org/10.1038/s41586-019-1138-yopenalex-snapshot
Machine behaviour
inferredcites →https://doi.org/10.1109/cvpr.1993openalex-snapshot
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2019.00453openalex-snapshot
A Style-Based Generator Architecture for Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00871openalex-snapshot
High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/esem.2019.8870157openalex-snapshot
Understanding Development Process of Machine Learning Systems: Challenges and Solutions
inferredcites →https://doi.org/10.1109/icdar.2017.157openalex-snapshot
Total-Text: A Comprehensive Dataset for Scene Text Detection and Recognition
inferredcites →https://doi.org/10.1109/icde.2019.00139openalex-snapshot
Slice Finder: Automated Data Slicing for Model Validation
inferredcites →https://doi.org/10.1109/icse-seip.2019.00042openalex-snapshot
Software Engineering for Machine Learning: A Case Study
inferredcites →https://doi.org/10.1109/tse.2017.2754374openalex-snapshot
Data Scientists in Software Teams: State of the Art and Challenges
inferredcites →https://doi.org/10.1109/tse.2019.2937083openalex-snapshot
How does Machine Learning Change Software Development Practices?
inferredcites →https://doi.org/10.1109/tse.2019.2962027openalex-snapshot
Machine Learning Testing: Survey, Landscapes and Horizons
inferredcites →https://doi.org/10.1109/tvcg.2013.186openalex-snapshot
ScatterBlogs2: Real-Time Monitoring of Microblog Messages through User-Guided Filtering
inferredcites →https://doi.org/10.1109/tvcg.2016.2598828openalex-snapshot
Squares: Supporting Interactive Performance Analysis for Multiclass Classifiers
inferredcites →https://doi.org/10.1109/tvcg.2019.2934619openalex-snapshot
The What-If Tool: Interactive Probing of Machine Learning Models
inferredcites →https://doi.org/10.1109/tvcg.2020.3012063openalex-snapshot
ConfusionFlow: A Model-Agnostic Visualization for Temporal Analysis of Classifier Confusion
inferredcites →https://doi.org/10.1109/tvcg.2020.3030443openalex-snapshot
CAVA: A Visual Analytics System for Exploratory Columnar Data Augmentation Using Knowledge Graphs
inferredcites →https://doi.org/10.1109/vast47406.2019.8986948openalex-snapshot
FAIRVIS: Visual Analytics for Discovering Intersectional Bias in Machine Learning
inferredcites →https://doi.org/10.1145/169059.169209openalex-snapshot
The cost structure of sensemaking
inferredcites →https://doi.org/10.1145/1978942.1978967openalex-snapshot
Apolo
inferredcites →https://doi.org/10.1145/2147783.2147788openalex-snapshot
End-user debugging strategies
inferredcites →https://doi.org/10.1145/2207676.2207711openalex-snapshot
Distributed sensemaking
inferredcites →https://doi.org/10.1145/2531602.2531644openalex-snapshot
Standing on the schemas of giants
inferredcites →https://doi.org/10.1145/2702123.2702509openalex-snapshot
ModelTracker
inferredcites →https://doi.org/10.1145/2702123.2702561openalex-snapshot
Real-World Affinity Diagramming Practices
inferredcites →https://doi.org/10.1145/288392.288596openalex-snapshot
Data mountain
inferredcites →https://doi.org/10.1145/2939502.2939503openalex-snapshot
Visual exploration of machine learning results using data cube analysis
inferredcites →https://doi.org/10.1145/3134680openalex-snapshot
Novice and Expert Sensemaking of Crowdsourced Design Feedback
inferredcites →https://doi.org/10.1145/3172944.3172950openalex-snapshot
AnchorViz
inferredcites →https://doi.org/10.1145/3180155.3180220openalex-snapshot
DeepTest
inferredcites →https://doi.org/10.1145/3196709.3196729openalex-snapshot
Grounding Interactive Machine Learning Tool Design in How Non-Experts Actually Build Models
inferredcites →https://doi.org/10.1145/3238147.3238187openalex-snapshot
DeepRoad: GAN-based metamorphic testing and input validation framework for autonomous driving systems
inferredcites →https://doi.org/10.1145/3274357openalex-snapshot
The Misgendering Machines
inferredcites →https://doi.org/10.1145/3274374openalex-snapshot
CrowdIA
inferredcites →https://doi.org/10.1145/3287560.3287596openalex-snapshot
Model Cards for Model Reporting
inferredcites →https://doi.org/10.1145/3290605.3300356openalex-snapshot
How Data Science Workers Work with Data
inferredcites →https://doi.org/10.1145/3290605.3300830openalex-snapshot
Improving Fairness in Machine Learning Systems
inferredcites →https://doi.org/10.1145/3308561.3354629openalex-snapshot
Twitter A11y
inferredcites →https://doi.org/10.1145/3313831.3376177openalex-snapshot
Understanding and Visualizing Data Iteration in Machine Learning
inferredcites →https://doi.org/10.1145/3313831.3376445openalex-snapshot
Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI
inferredcites →https://doi.org/10.1145/3351095.3375624openalex-snapshot
Explainable machine learning in deployment
inferredcites →https://doi.org/10.1145/3366423.3380306openalex-snapshot
Towards Hybrid Human-AI Workflows for Unknown Unknown Detection
inferredcites →https://doi.org/10.1145/3368555.3384468openalex-snapshot
Hidden stratification causes clinically meaningful failures in machine learning for medical imaging
inferredcites →https://doi.org/10.1145/3377811.3380339openalex-snapshot
Structure-invariant testing for machine translation
inferredcites →https://doi.org/10.1145/3379337.3415865openalex-snapshot
Mesh
inferredcites →https://doi.org/10.1145/3382494.3410681openalex-snapshot
Adoption and Effects of Software Engineering Best Practices in Machine Learning
inferredcites →https://doi.org/10.1145/3392878openalex-snapshot
Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs
inferredcites →https://doi.org/10.1145/3411764.3445518openalex-snapshot
“Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI
inferredcites →https://doi.org/10.1145/3411764.3445735openalex-snapshot
Planning for Natural Language Failures with the AI Playbook
inferredcites →https://doi.org/10.1145/3415224openalex-snapshot
Designing Alternative Representations of Confusion Matrices to Support Non-Expert Public Understanding of Algorithm Performance
inferredcites →https://doi.org/10.1145/3449205openalex-snapshot
How AI Developers Overcome Communication Challenges in a Multidisciplinary Team
inferredcites →https://doi.org/10.1145/3458723openalex-snapshot
Datasheets for datasets
inferredcites →https://doi.org/10.1145/3461702.3462527openalex-snapshot
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development
inferredcites →https://doi.org/10.1145/3479569openalex-snapshot
Discovering and Validating AI Errors With Crowdsourced Failure Reports
inferredcites →https://doi.org/10.1145/3491102.3501823openalex-snapshot
Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labels
inferredcites →https://doi.org/10.1145/3491102.3502102openalex-snapshot
Symphony: Composing Interactive Interfaces for Machine Learning
inferredcites →https://doi.org/10.1145/3531146.3533108openalex-snapshot
Interactive Model Cards: A Human-Centered Approach to Model Documentation
inferredcites →https://doi.org/10.1145/3531146.3533135openalex-snapshot
Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theory
inferredcites →https://doi.org/10.1145/3531146.3533240openalex-snapshot
The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models
inferredcites →https://doi.org/10.1145/989863.989865openalex-snapshot
Designing interaction, not interfaces
inferredcites →https://doi.org/10.1147/jrd.2019.2942288openalex-snapshot
FactSheets: Increasing trust in AI services through supplier's declarations of conformity
inferredcites →https://doi.org/10.1177/0149206312457823openalex-snapshot
Life After Business Failure
inferredcites →https://doi.org/10.1177/0735275112457914openalex-snapshot
Theory Construction in Qualitative Research
inferredcites →https://doi.org/10.1186/s40537-019-0197-0openalex-snapshot
A survey on Image Data Augmentation for Deep Learning
inferredcites →https://doi.org/10.1287/orsc.1050.0133openalex-snapshot
Organizing and the Process of Sensemaking
inferredcites →https://doi.org/10.1287/orsc.5.3.309openalex-snapshot
Organizational Culture and Individual Sensemaking: A Schema-Based Perspective
inferredcites →https://doi.org/10.14778/3157794.3157797openalex-snapshot
Snorkel
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.442openalex-snapshot
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList
inferredcites →https://doi.org/10.18653/v1/2021.naacl-demos.6openalex-snapshot
Robustness Gym: Unifying the NLP Evaluation Landscape
inferredcites →https://doi.org/10.18653/v1/2023.eacl-mainopenalex-snapshot
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
inferredcites →https://doi.org/10.18653/v1/p19-1073openalex-snapshot
Errudite: Scalable, Reproducible, and Testable Error Analysis
inferredcites →https://doi.org/10.2307/259169openalex-snapshot
Sensemaking in Organizations
inferredcites →https://doi.org/10.2307/2655359openalex-snapshot
Grounded Theory in Practice
inferredcites →https://doi.org/10.4135/9781483368924.n320openalex-snapshot
National Transportation Safety Board
inferredcites →https://doi.org/10.48550/arxiv.1412.6572openalex-snapshot
Explaining and Harnessing Adversarial Examples
inferredcites →https://doi.org/10.48550/arxiv.1910.03156openalex-snapshot
Software Engineering Practice in the Development of Deep Learning Applications
inferredcites →https://doi.org/10.48550/arxiv.2203.14960openalex-snapshot
Domino: Discovering Systematic Errors with Cross-Modal Embeddings
inferredcites →https://doi.org/10.5465/19416520.2014.873177openalex-snapshot
Sensemaking in Organizations: Taking Stock and Moving Forward
inferredcites →https://doi.org/10.5465/amj.2008.0843openalex-snapshot
Ecological Sensemaking
inferredcites →https://doi.org/10.5465/amle.2011.0007openalex-snapshot
The Handbook for Teaching Leadership: Knowing, Doing & BeingThe Handbook for Teaching Leadership: Knowing, Doing & Being, edited by SnookScott A., KhuranaRakesh, and NohriaNitin. Thousand Oaks, CA: SAGE. Forthcoming October 2011. 917 pages. E-book option.

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Human-Centered and Participatory AI Auditing
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Human-Centered and Participatory AI Auditing
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The Technique of Inverse Multidimensional Scaling for the Synthesis of Machine Learning Models
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Multi-Class Bias Mitigation Methods for Classification Without Discrimination
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The AI interface: Designing for the ideal machine-human experience
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Counterfactual explanations with varying parameter control: Effects on mental-model formation and explanation satisfaction
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A review of deep learning in dentistry
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Data-Driven E-Commerce UI Personalization: Going Beyond Product Recommendations
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One Size Does Not Fit All: Multivariant User Interface Personalization in E-Commerce
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Data Extraction, Visualization, and Prediction Through Natural Language Processing
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VLSlice: Interactive Vision-and-Language Slice Discovery
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Building Smart Systems to Satisfice User Intention in Situ: A Look Back to the Future*
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Making Sense of AI Systems Development
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Embodying the Algorithm
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fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks
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Zeno: An Interactive Framework for Behavioral Evaluation of Machine Learning
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ESCAPE: Countering Systematic Errors from Machine’s Blind Spots via Interactive Visual Analysis
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Improving Human-AI Collaboration With Descriptions of AI Behavior
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ScatterShot: Interactive In-context Example Curation for Text Transformation
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Supporting Human-AI Collaboration in Auditing LLMs with LLMs
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AIMEE: An Exploratory Study of How Rules Support AI Developers to Explain and Edit Models
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The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology
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VIME: Visual Interactive Model Explorer for Identifying Capabilities and Limitations of Machine Learning Models for Sequential Decision-Making
inferred← citeshttps://doi.org/10.1145/3691620.3695033openalex-snapshot
What Is Wrong with My Model? Identifying Systematic Problems with Semantic Data Slicing
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How Do HCI Researchers Study Cognitive Biases? A Scoping Review
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