AI-Systems Audit

Technical, ethical, regulatory and compliance review of you ML models and business.

Please refer to the following checklist for documents we require for conducting an AI-systemsaudit of your project. Please submit the following information to [e-mail] as soon as you have it available so the review process can start.

You can also access the table as Google Sheets here:

https://docs.google.com/spreadsheets/d/1FobNf9xRogBxD4grrUGsVrcC8a32nDEm80-L103lUBk/edit?usp=sharing

Note that you don't have to create new documents, however, the more information you provide, the more accurate our assessment of your project will be.

Audit process:

1. Review documentation, business logic, and strategy alignment of the Ml model implementation.

2. Close inspection of the raw data and a review of the code.

3. Reproduction of (parts of) the model training, testing, scoring and performance measures to understand and verify details of the model, its performance and reproducibility, as well as its fairness implications. This might include tests of the model’s behavior with manipulated data.

4. Compliance and legal regulation check.

If you have any questions about the AI audit process, please get in touch with [e-mail]