Course Overview
In this course, students will gain a comprehensive understanding of what algorithmic bias is and how it affects various AI systems. The course covers the 13 most common forms of AI bias, illustrated with real-world examples demonstrating how these biases manifest in different technologies. Students will also have an opportunity to identify different biases in a real example, to highlight the difficulty of spotting and mitigating bias in these everyday tools. Additionally, students will learn 9 effective strategies to reduce biases in AI.
Designed for learners from all backgrounds, this course requires no prerequisites and aims to provide a high-level understanding of AI bias and mitigation techniques. The curriculum includes pre-recorded lectures and a recording of a live lecture by instructor Jeffery Recker where he had open conversations with students. This is accompanied along with quizzes and additional resources to ensure a thorough grasp of the material. With a structured schedule, students can complete the course in about one weeks time.
About the instructor
Jeffery Recker, Co-Founder and Chief Operating Officer of BABL AI, has a background in social and environment sustainability and is a certified AI Auditor with years of experience in AI Auditing and Responsible AI Consulting.
In the course "Understanding Algorithmic Bias," he leverages his years of hands on expertise to teach students how to identify, analyze, and mitigate the wide varieties of biases in AI systems.
His leadership and real-world experience ensure that students gain practical skills and knowledge to develop ethical and unbiased AI solutions.
