Here’s a clear, simple, and concise summary of Ethical AI Practice and its Types 👇—✅ Summary: Ethical AI Practice

Ethical AI Practice refers to designing, building, and deploying artificial intelligence systems in a responsible, fair, safe, and transparent manner.It ensures AI benefits people, avoids harm, respects privacy, and supports accountability in decision-making.Ethical AI focuses on preventing bias, protecting human rights, and making sure AI systems work reliably for society.—

✅ Types of Ethical AI Practice

1. Fairness & Bias Prevention

Ensuring AI treats all groups equally and does not discriminate based on race, gender, age, or background.

2. Transparency & Explainability

AI systems should be understandable — users must know how decisions are made and what data was used.

3. Privacy & Data Protection Protecting user data, limiting data collection, and following legal standards like GDPR.

4. Accountability & Governance Clear responsibility for AI outcomes.Teams should monitor systems and address issues quickly.

5. Safety & Reliability Ensuring AI operates safely, avoids harmful actions, and performs consistently in real-world scenarios.

6. Human-Centric Design. AI should support human values, enhance human decision-making, and avoid replacing essential human roles where harmful.

7. Sustainability Designing AI with minimal environmental impact by reducing energy consumption and responsible use of computing resources.—