Summary of Towards Explainable Artificial Intelligence (xai): a Data Mining Perspective, by Haoyi Xiong and Xuhong Li and Xiaofei Zhang and Jiamin Chen and Xinhao Sun and Yuchen Li and Zeyi Sun and Mengnan Du
Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective
by Haoyi Xiong, Xuhong Li, Xiaofei Zhang, Jiamin Chen, Xinhao Sun, Yuchen Li, Zeyi Sun, Mengnan Du
First submitted to arxiv on: 9 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research paper presents a novel approach to explainable AI (XAI) by examining the role of data collection, processing, and analysis in making deep neural networks more interpretable. The authors categorize existing work into three categories: interpretations of deep models, influences of training data, and insights of domain knowledge. They distill XAI methodologies into data mining operations on various data modalities, including images, text, and tabular data, as well as on training logs, checkpoints, and model behavior descriptors. This comprehensive study offers a data-centric examination of XAI from a lens of data mining methods and applications. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about making artificial intelligence (AI) more understandable. Right now, AI systems are very good at doing things like recognizing pictures or understanding speech, but we don’t really know how they do it. This study looks at the role that data plays in helping us understand why AI makes certain decisions. The authors group previous research into three categories: interpreting what AI is doing, looking at how the training data affects AI’s behavior, and using domain knowledge to gain new insights from AI. They also show how data mining techniques can be used to make AI more transparent. |
