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Building AI Literacy: Practical Activities

AI literacy is best taught through doing. These activities can be integrated into existing modules to build critical evaluation and responsible use skills.

Activity 1: Critique the Output (Accuracy)​

Goal: Students learn that AI is fallible and requires expert verification.

Instructions:

  1. Generate: Educator provides an AI-generated nursing care plan for a complex patient (e.g., "Patient with COPD and acute delirium"). Ensure the output contains 1-2 subtle clinical errors.
  2. Analyse: Students work in pairs to "mark" the AI's work against clinical guidelines (NICE/local policy).
  3. Discuss: Share the errors found. Why did the AI make them?

Takeaway: "Trust but verify." The nurse is the licensed professional; the AI is just a tool.

2. Prompt Refinement Relay (Optimization)​

Goal: Teach iterative prompt engineering.

Instructions:

  1. Round 1: Student A writes a simple prompt (e.g., "Write a discharge summary").
  2. Evaluate: Evaluate the output (likely generic).
  3. Round 2: Student B adds context and constraints to the prompt (e.g., "Include social history, use SBAR format").
  4. Evaluate: Compare the quality improvement.
  5. Round 3: Student C refines it further for tone and specific medical terminology.

Takeaway: The quality of the output depends on the quality of the input.

3. The Ethics Audit (Responsible Use)​

Goal: identify bias and ethical risks.

Instructions:

  1. Scenario: Ask an AI to "Describe the typical pain presentation of a 55-year-old woman versus a 55-year-old man."
  2. Audit: Analyse the output for gender bias. Does it perpetuate stereotypes?
  3. Reflect: How would this bias affect patient care if used unchecked?

Takeaway: AI models reflect the biases in their training data. Nurses must advocate for equitable care.