Open challenges of XAI
As briefly discussed, there have been some significant advances in the field of XAI. XAI is no longer just a topic of academic research; the availability of XAI frameworks has made XAI an essential tool for industrial practitioners. But are these frameworks sufficient to increase AI adoption? Unfortunately, the answer is no. XAI is yet to mature further as there are certain open challenges that, once resolved, can significantly bridge the gap between AI and the end user. Let's discuss these open challenges next:
- Shifting focus between the model developer and the end user: After exploring many XAI frameworks throughout this book, you might have also felt that the explainability provided by most of the frameworks requires technical knowledge of ML, mathematics, or statistics to truly understand the working of the model. This is because the explainability methods or algorithms were primarily designed for ML experts or model developers.
As more...