AI Ethics and Bias Micro-Credential

AI Ethics and Bias Micro-Credential

Duration: 2 Hours

Description

This micro-credential explores how bias arises in AI systems and its impact on fairness and accountability. Participants examine real-world cases, analyze datasets for hidden biases, and investigate the “black box” nature of algorithms. Through hands-on labs and discussions, they learn mitigation techniques, apply ethical frameworks, and practice human-in-the-loop approaches to build transparent, responsible, and explainable AI solutions.

Audience

This course is for anyone who uses or works with AI, from developers and data scientists to business leaders and everyday users.

Objectives

  • Identify different types of bias in AI systems
  • Understand the sources of bias, from data to design
  • Analyze the societal impact of biased AI on individuals and groups
  • Apply practical strategies to mitigate and address ethical challenges

Prerequisites

No prior technical knowledge is required, but a basic understanding of AI concepts is helpful.

Course Outline

Module 1: The Problem of Bias

  • Bias in a Nutshell
  • Real-World Examples
  • The Data is the Key
  • Lab – Analyze a Dataset to Identify Potential Sources of Bias

Module 2: From Bias to Unfairness

  • Algorithmic Bias
  • The Black Box Problem
  • Fairness and Accountability
  • Lab – Discuss Ethical Dilemmas Relates to AI Systems

Module 3: Building a Responsible Future

  • Mitigation Strategies
  • Explainable AI
  • Ethical Frameworks
  • The Human in the Loop