Ensure your AI solutions are safe and reliable with our comprehensive checklist.
| ID | Title | Source | Description |
|---|---|---|---|
| 1 | What’s the Worst That Could Happen? A Guide to AI Risks | Immuta Blog | Outlines various failure modes and risk factors in AI systems. |
| 2 | Errors + Graceful Failure | Google PAIR Guidebook | Discusses design strategies for managing AI errors and user mental models. |
| 3 | Understanding and Avoiding AI Failures: A Practical Guide | arXiv Paper | Framework for understanding AI failures and mitigation methods. |
| 4 | Analyzing AI Application Threat Models | NCC Group Blog | Analysis of threat models critical for mapping user–AI interaction risks. |
| 5 | Top Risks of Generative AI Systems | Google SAIF | Overview of key risks, failure modes, and mitigation strategies for generative AI. |
| 6 | Big Data and Machine Learning in Health Care | BMJ Article | Highlights how AI/ML are revolutionizing clinical decision-making. |
| 7 | Artificial Intelligence in Healthcare: Opportunities, Challenges... | AHRQ Report | Foundational insights into AI for healthcare quality and safety. |
| 8 | The Role of Artificial Intelligence in Graduate Medical Education | AAMC Report | Discusses AI in residency training, addressing safety and bias. |
| 9 | Enhancing Patient Safety in the Era of Artificial Intelligence | Joint Commission Perspective | Emphasizes patient safety standards for AI integration in clinical care. |
| 10 | Competency-Based Medical Education in the Age of Artificial Intelligence | ACGME Guidelines | Outlines integrating AI competencies into fellowship training. |
| 11 | Leveraging Artificial Intelligence to Enhance Patient Safety... | Stanford MedStar Safety Center | Advanced strategies for using AI to improve patient safety. |