# Topic5:  Verifiable Trustworthy AI 

## Motivation:

- Many aspects of trustworthy  AI (or responsible AI), such as robustness, backdoor-free, fairness, privacy protection capabilities, and accountability, have gradually attracted the attention of the industry and academia.
- Scholars' understanding and research on the attributes of trustworthy AI are mostly empirical, and there are few theoretical studies. The verifiable and certifiable analysis, tuning, and evaluation methods of trustworthy AI attributes and bounds, and their relation to explainable AI, require theoretical guidance.

## Target:

​	Propose verifiable and certifiable research mechanism and evaluation system on trustworthy AI.

## Method:

​	We expect the applicant can conduct Verifiable Trustworthy AI research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and  provide you with the most powerful technical support.

## How To Join

1. Submit an issue/PR based on community discussion for consultation or claim on related topics
2. Submit your proposal to us by email xxx@huawei.com