AI Ethics

The course spans industry, policy-making, academia, and society at large, covering principles of AI ethics, strategies to foster fair and equitable AI systems, approaches to minimize biases, and methods to address key issues and establish user trust.

Ethical Principles and Challenges

Throughout the course, you will learn about the core principles of ethical AI and expand your understanding of common challenges and opportunities in the field of AI ethics. Through hands-on exercises, you will build your skills to craft ethical AI by design. Begin Learning today!

• Define data and AI ethics, and explain their importance in real-world applications.
• Differentiate ethical principles from laws, regulations, and societal norms in the context of data use.
• Identify ethical risks and responsibilities across the entire data lifecycle.
• Apply principles of transparency, consent, and ownership to support ethical AI practices.
• Evaluate ethical implications of data sharing, bias, and AI impact on society and sustainability.

1. Approaching AI Ethics

   Understand the foundations of AI Ethics and observe some of the challenges of the ethical use of AI.

    

2. Below the Surface: AI Ethics

   Unpack the core principles of AI Ethics and discover a promising technique, explainable AI (XAI), that can integrate these principles into many AI systems.

    

3. The Way Forward: AI Ethics

   Discover the value ethical frameworks present to organizations of all sizes and prepare yourself to tackle tomorow's ethical challenges with AI ethics by design.