Prompting responsibly: Bias, privacy, and thoughtful use.
Welcome to Module 9. Knowing *how* to prompt is important, but so is doing it *responsibly*. We must consider the ethical implications of AI interactions.
This module covers potential bias, privacy concerns, and responsible use of AI, encouraging awareness and thoughtful practice.
How this Connects: Ethics underpin all techniques. Responsible use is vital as we approach Module 10: Advanced Prompt Engineering.
AI models learn from real-world data, which contains human biases. Our prompts can also introduce or amplify these biases (e.g., stereotypes). This can lead to unfair or harmful outputs.
Example Biased Prompt: Generate a list of typical jobs for women. (Reinforces stereotypes)
More Neutral Prompt: Generate a list of common professions across various industries.
Reflection:
Can a prompt for a fun task (like creating a story character) accidentally include stereotypes?
We can be mindful in our prompting:
Be extremely cautious with sensitive data in prompts:
Risk Example: Prompting with specific client invoice details exposes that data.
Use AI outputs thoughtfully:
Scenario: Interview Questions
Less Ethical: ...questions for skills typically found in male candidates. (Bias)
More Ethical: ...questions for skills like problem-solving, coding proficiency... (Neutral)
Scenario: Using AI for Homework
Less Ethical: Write a complete essay... (Plagiarism)
More Ethical: Help me brainstorm... and create an outline... Explain... (Learning tool)
Scenario Prompt:
"Generate a profile description for a dating app. Make the user sound like a successful, assertive businessman who knows what he wants and isn't afraid to go after it. He enjoys expensive hobbies like yachting and collecting sports cars."
Goal: Identify ethical concerns and suggest a rewrite.
Expected Outcome:
You should identify the stereotyping and suggest a rewrite focusing on individual traits or user-provided details.
Evaluate your ethical analysis and rewrite from the exercise.
1. Issue Identification: Did you spot the reliance on stereotypes?
2. Rewrite Neutrality: Does the rewrite avoid those stereotypes?
3. Rewrite Effectiveness: Does the rewrite still guide the AI (e.g., by asking for user details)?
Suggestion for Improvement:
Question the assumptions in your prompts. Are they based on facts or potentially biased stereotypes? Aim for neutrality.
Understanding ethical dimensions is vital for responsible prompt engineering.
Next Steps: Let's explore slightly more technical aspects in Module 10: Advanced Prompt Engineering.