Introduction

This 5-day professional course on "Data Ethics and Responsible AI" is designed to provide participants with a comprehensive understanding of the ethical considerations involved in data collection, analysis, and artificial intelligence deployment. The course aims to equip professionals with the knowledge and skills necessary to ensure responsible use of AI technologies in their respective fields, promoting fairness, transparency, and accountability.

• Understand key principles of data ethics and their application.
• Identify and mitigate ethical risks associated with AI deployment.
• Promote fairness and accountability in AI systems.
• Implement practices for transparent and explainable AI methods.
• Explore real-life case studies of ethical dilemmas in AI.

Course Outlines

Day 1: Foundation of Data Ethics

• Introduction to ethics and moral philosophy
• Key principles of data ethics: privacy, consent, and ownership
• Regulatory frameworks and guidelines
• Understanding bias and discrimination in data
• Case studies on ethical data use

Day 2: Responsible AI Development

• Introduction to AI ethics
• Designing AI with ethical considerations
• Bias detection and mitigation techniques
• Human-in-the-loop systems for accountability
• Ensuring diversity and inclusivity in AI teams

Day 3: Fairness and Transparency in AI

• Defining fairness in AI systems
• Techniques for fairness measurement
• Transparent AI: challenges and solutions
• Explainable AI and interpretability
• Tools and frameworks for assessing AI transparency

Day 4: Implementing Ethical AI Practices

• Developing an ethical AI framework for organizations
• Guidelines for ethical data handling
• Role of AI ethics boards and committees
• Risk assessment and management in AI projects
• Best practices for ethical AI deployment

Day 5: Case Studies and Future Perspectives

• In-depth analysis of recent AI ethics case studies
• Learning from past ethical failures in AI
• Interactive group discussions and problem-solving
• Future trends in AI ethics: challenges and opportunities
• Developing a personal plan for ethical AI practice