Cautions & HITL
Understanding Common A.I. Risks
Students learn where A.I. can go wrong such as generating incorrect information, misunderstanding context, or confidently giving false answers (hallucinations).
Bias, Fairness & Ethical Concerns
Explore how A.I. can reflect biased data for example, an A.I. tool favoring certain resumes or making uneven recommendations, highlighting the importance of human review.
Humans are Essential for Accuracy & Trust
Learn how people must validate A.I. outputs like a manager approving A.I.-generated reports or a developer reviewing A.I.-written code before deployment.
Using AI Safely & Responsibly
We discuss simple guidelines such as double-checking critical information, protecting sensitive data, and knowing when not to rely fully on A.I. to reduce risks and improve outcomes.
