Common AI myths (extended)

A longer myth-busting set beyond single-chapter callouts—useful as a Course 01 capstone literacy page.

What it is

A longer myth-busting set beyond single-chapter callouts—useful as a Course 01 capstone literacy page.

Myths drive bad buys, bad laws-of-coffee-shop, and bad personal risk decisions (scams).

⚠️ Myth: AI “knows” things like a person.: ✓ Reality: Systems compute outputs from training/objectives/tools—not lived understanding.
⚠️ Myth: Confident tone equals calibrated probability.: ✓ Reality: Fluency ≠ truth (Course 08).
⚠️ Myth: Open weights are always safer / closed always safer.: ✓ Reality: Safety is deployment + policy + ops (Course 25).
⚠️ Myth: One law or one vendor will “solve AI.”: ✓ Reality: Layered governance and engineering controls (Course 20/19).
⚠️ Myth: If a tool can do X in a demo, it can do X unsupervised at scale.: ✓ Reality: Reliability, permissions, and edge cases decide.

Collect three myths you’ve heard this month. Pair each with a chapter link from ANN Learn.