AI Ethics & Responsible Use
Navigate the ethical dimensions of AI — bias, privacy, copyright, and societal impact.
Key Ethical Considerations
Bias: AI models reflect biases in their training data. Be aware that AI outputs may perpetuate stereotypes or systemic biases, especially in hiring, lending, healthcare, and criminal justice applications.
Privacy: Don't share others' personal information with AI tools without their consent. Be cautious with employee data, customer data, and any personally identifiable information.
Copyright: AI-generated content exists in a legal gray area. Don't represent AI-generated work as entirely your own in academic settings. Understand your organization's policy on AI-generated content.
Misinformation: AI can generate convincing false information at scale. Never use AI to deliberately create or spread misinformation.
Responsible AI Practices
1. Always disclose AI assistance when relevant (academic work, professional deliverables)
2. Verify before publishing — human review is essential for anything public-facing
3. Protect data — don't share sensitive information with AI tools unnecessarily
4. Consider impact — before automating a task, consider who might be affected
5. Stay informed — AI ethics and regulations evolve rapidly. Follow developments in your industry
6. Maintain skills — use AI to augment your abilities, not replace your thinking
Review your current AI usage. Are there areas where you should add human review? Are you sharing data you shouldn't? Write a personal AI usage policy for yourself.
- ✓AI reflects training data biases — be aware and mitigate
- ✓Protect privacy — don't share others' personal data with AI
- ✓Always disclose AI assistance where relevant
- ✓Use AI to augment your abilities, not replace your thinking