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Course Outline

Course Outcomes

Passkey

Definition of Artificial Intelligence  

Importance of Ethics in AI  

Overview of Ethical Issues in AI  

Key Ethical Principles in AI  

Fairness and Non-Discrimination  

Understanding Bias in AI  

Strategies for Ensuring Fairness  

Transparency and Explainability  

The Importance of Explainable AI  

Tools and Techniques for Transparency  

Accountability and Responsibility  

Identifying Stakeholders in AI Development  

Establishing Accountability Frameworks  

Ethical Decision-Making Frameworks  

Utilitarianism and AI  

Cost-Benefit Analysis in AI Applications  

Balancing Outcomes and Stakeholder Impact  

Deontological Ethics  

Duty-Based Ethics in AI Development  

Rights and Obligations of AI Systems  

Virtue Ethics and AI  

Promoting Positive Values in AI Design  

Cultivating Ethical Awareness Among AI Practitioners  

Case Studies and Real-World Applications  

Ethical Dilemmas in AI Implementation  

Surveillance and Privacy Concerns  

Autonomous Systems and Ethical Decision-Making  

Best Practices for Ethical AI Development  

Guidelines from Industry Leaders  

Collaborative Approaches to Ethical AI  

Conclusion  

The Future of Ethics in AI  

Continuous Learning and Adaptation in Ethical AI Practices  

Assessment

Assessment Overview: “AI-Based Recruiting Tool” Scenario

Navigating Ethics in AI: A Comprehensive Introduction to Responsible Decision-Making  

A short course that introduces learners to Ethical Use of AI - Ensuring the fair, transparent, and responsible application of AI in decision-making and workflows.	AI adoption will continue to grow, and ethical use is key to avoiding biases, ensuring inclusivity, and building trust in AI-driven systems. The course should have an assessment component at the end that should take the learner around 1 hour to complete.