With great AI power comes great responsibility. Ethical considerations for AI-augmented development.

Key Ethical Principles

• 🔍 Transparency: Disclose when code/content is AI-generated
• ⚖️ Fairness: Detect and mitigate bias in AI outputs
• 🔒 Privacy: Never send sensitive data to public LLMs
• 👤 Accountability: Human always responsible for AI output
• 🌍 Sustainability: Consider energy cost of AI training/inference

Questions to Ask

• • Whose data trained this? Was it ethically sourced?
• • What are unintended consequences? Who might be harmed?
• • Is this explainable? Can we justify AI decisions?
• • Am I over-relying? Maintaining my skills?

Best Practices

• ✓ Review all AI output - you're accountable
• ✓ Mark AI contributions in commits/PRs
• ✓ Use privacy modes for proprietary code
• ✓ Stay informed on AI ethics developments