MYTHS & MISCONCEPTIONS

• Myth: AI understands like a person.
  Reality: It predicts the next token using patterns; it has no beliefs or intent.
  
  

• Myth: AI is always right.
  Reality: It can be confidently wrong (“hallucinate”); verify important facts.
  
  

• Myth: AI has live internet access.
  Reality: Not by default; some tools add web/retrieval separately.
  
  

• Myth: More data automatically makes it smarter.
  Reality: Data quality, model design, compute, and alignment matter.
  
  

• Myth: AI is objective and bias-free.
  Reality: It can reflect biases in training data and prompts.
  
  

• Myth: Using AI is always cheating.
  Reality: It can be assistive when use is transparent and allowed and approved by the teacher. 

• Myth: AI replaces teachers.
  Reality: Appropriately integrated, it augments planning/feedback; freeing up time to keep a human in the loop.
  
  

• Myth: It’s safe to paste anything into AI.
  Reality: Don’t ever enter personal/student data or information into an AI model. 
  
  

• Myth: Detectors can prove AI-written text.
  Reality: Detectors are unreliable and shouldn't be used as sole determinant of academic integrity; process evidence and clear policy are recommended.
  
  

• Myth: You must know code to use AI.
  Reality: Clear natural-language prompts are enough. "Generate me an interactive game for me to practice my verbs in Spanish."

• Myth: There’s one “right” prompt.

Reality: Prompts are design choices. Push students to iterate, show their steps, and justify.