> For the complete documentation index, see [llms.txt](https://maheshwarappa-a.gitbook.io/explainable-ai-1/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://maheshwarappa-a.gitbook.io/explainable-ai-1/explainable-systems-and-black-box-systems.md).

# Explainable systems and Black box systems

White Box vs Black Box

### Types of AI system/Models 

There are two types of AI systems that can be defined 

1. Explainable systems or White box systems
2. Black Box systems

### Explainable systems / White Box systems (models)

![White Box](https://1181649628-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-M5Vxy9PzQFOZjhyK8YP%2F-Mg3EiBNANSh7TOR6IY-%2F-Mg3J-FgrNZZA_cuLjTG%2Fwhite%20box%20model.png?alt=media\&token=502080d5-738d-4ae6-b76d-6f5caf588dd8)

These are the AI systems or Models where one can easily map the input to the output. One knows what is happening during the training phase and how the system makes the appropriate choice.

Examples: Linear Regression and Decision Tree

### **Black Box systems**

![Black Box](https://1181649628-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-M5Vxy9PzQFOZjhyK8YP%2F-Mg3EiBNANSh7TOR6IY-%2F-Mg3K8iEDUDnz48LUEiI%2F02.Black%20box%20model.png?alt=media\&token=d025445c-9e34-45ca-a0cf-3e913a83c99d)

These are the AI systems or Models where one can not map the input to the output. You do not know what is happening within the system.

Example: Deep Learning and Computer Vision Models