Module 06 · AI Risks
Module check
11 statements, one from each chapter of the module. Call each one myth or fact. Take it once before the module and again after it: the difference is what the module taught you. Your scores stay in this browser.
- AI risk basically means hallucination. From The AI Risk Landscape
- If the assistant cites a source, the answer is supported by that source. From Accuracy, Hallucination and Reliability
- Removing gender and ethnicity from the data makes a model fair. From Bias and Fairness
- An approved enterprise AI platform means confidential data is safe. From Privacy and Confidential Data
- An attacker must interact with your AI system to inject instructions into it. From Security and AI Attacks
- If our AI tool created it and the provider's terms assign the output to us, the company owns the copyright. From Intellectual Property and Copyright
- A famous AI provider means low risk. From Model and Third-Party Risk
- If an AI system works well, the people beside it need less training. From Operational and Workforce Risk
- Human approval on every agent action is the safest design. From Agentic AI and Autonomous Actions
- Requiring a human to approve every AI output is enough to prevent harmful decisions. From Human Oversight and AI Incidents
- If the model is accurate in testing, the AI system is safe to deploy. From Module 06 Synthesis — Understanding AI Risk