Trustworthy AI: Managing Bias, Ethics, and Accountability
By External Provider
About this course
The course "Responsible AI and Ethics" explores the ethical, social, and technical aspects of artificial intelligence (AI) and machine learning (ML). It focuses on understanding bias in both human and machine systems and provides strategies for mitigating risks. By examining key issues such as fairness, accountability, and the regulatory landscape, learners will gain essential knowledge to navigate the ethical challenges in AI. Through case studies and real-world examples, students will explore the complexities of AI implementations, assessing their impact on society and industries. This course provides practical insights into responsible AI development, emphasizing both ethical decision-making and effective risk management. By the end of the course, learners will be equipped to lead AI projects that balance innovation with accountability, ensuring AI systems are fair, transparent, and sustainable. This unique combination of theoretical knowledge and real-world applications makes the course invaluable for anyone aiming to lead in the AI field.
What you will learn
- Understand the sources and trade-offs of bias in both human and AI systems, and learn strategies for mitigating these biases in AI implementations.
- Explore ethical frameworks for responsible AI, focusing on transparency, fairness, and accountability, and gain knowledge of laws surrounding AI.
- Analyze real-world AI case studies to identify strengths and weaknesses in AI adoption, and understand the considerations for managing AI projects.