Ethics of AI: Known Issues, Best Practices, and a Proposal Framework for Auditing.

1. Introduction 2. Background and Context 2.1 Historical Development of AI Ethics 2.2 Key Terminologies in AI Ethics 2.3 Importance of Ethics in AI 3. Known Ethical Issues 3.1 Bias and Discrimination in AI 3.2 Privacy Concerns in AI Utilization 3.3 Transparency and Explainability in AI 3.4 Accountability of AI Decisions 3.5 The Problem of AI Autonomy 4. Current Best Practices 4.1 Ethical AI Guidelines 4.2 Fairness in AI Algorithms 4.3 Enhancing AI Transparency 4.4 Strategies for AI Accountability 5. Case Studies 5.1 AI Ethics in Healthcare 5.2 AI in Criminal Justice Systems 5.3 AI in Autonomous Vehicles 6. Proposal Framework for Auditing 6.1 Objectives of AI Auditing Framework 6.2 Components of the Proposed Framework 6.3 Implementing the Auditing Framework 6.4 Challenges in the Auditing Process 7. Implications of the Framework 7.1 Long-term Benefits of AI Auditing 7.2 Potential Limitations and Criticisms 7.3 Adoption of the Framework in Industries 8. Conclusion and Future Directions 8.1 Summary of Key Findings 8.2 Recommendations for Future Research 8.3 Final Thoughts on AI Ethics