# Authoritative Readings and Resources

These resources extend the supplied learning chapters in **AINS6008 AI Project Management & Deployment**. They were selected because they are primary standards, official documentation, open textbooks, or authoritative institutional guidance—not unsourced link lists.

## How to Read Them

For each module, read the supplied chapter first. Then use the two linked resources at the end of that chapter to test terminology, compare the course's worked example with an authoritative treatment, and identify one point that should change or qualify your recommendation. Students are not expected to read every linked document cover to cover.

### 1. [NIST AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework)

Risk management across the AI lifecycle.

**Use with:** AI product discovery and scoping, Evaluation plans and acceptance criteria, MLOps and release management, Deployment business case.
### 2. [Google MLOps Guide](https://cloud.google.com/architecture/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning)

Continuous delivery and automation for ML systems.

**Use with:** AI product discovery and scoping, Stakeholders, requirements, and risk, MLOps and release management, Change management and adoption.
### 3. [Microsoft Responsible AI Standard](https://www.microsoft.com/en-us/ai/principles-and-approach)

Governance practices for responsible delivery.

**Use with:** Stakeholders, requirements, and risk, Agile delivery for AI uncertainty, Change management and adoption, Operations, monitoring, and governance.
### 4. [GAO AI Accountability Framework](https://www.gao.gov/products/gao-21-519sp)

Governance, data, performance, and monitoring evidence.

**Use with:** Agile delivery for AI uncertainty, Evaluation plans and acceptance criteria, Operations, monitoring, and governance, Deployment business case.

## Source-Use Standard

Assignments should distinguish among measured notebook evidence, course-provided synthetic evidence, claims supported by these sources, and the student's own professional judgment. Cite the specific page, section, control, or documentation topic used; a bare homepage link is not adequate evidence.