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12.3 Ethics of Artificial Intelligence Development and Machine Learning

Learning Objectives

Ethical Governance and Regulations in Artificial Intelligence Systems and Products

Artificial Intelligence’s Impact on Fairness, Bias, Transparency, and Explainability

Careers in IS

Quizzes

Quiz: Fundamentals of AI Ethics

Quiz: Identifying Ethical Governance

Quiz: Understanding Fairness and Bias

Quiz: Recognizing Transparency and Explainability

Quiz: Comprehensive Ethics of AI

Course Survey and Feedback

Course Evaluation Survey

Learner Feedback

Build trustworthy AI from the ground up. Ethical AI Development: Governance, Fairness, and Transparency is a practical, outcomes-driven course designed for professionals who create, deploy, or oversee AI systems. You will learn how to translate ethical principles into concrete practices across the AI lifecycle—from data collection and model training to evaluation, monitoring, and post-deployment governance. Using real-world scenarios, you will explore emerging regulations, organizational risk frameworks, and hands-on methods for mitigating bias while improving transparency and explainability. The curriculum covers responsible data sourcing, model documentation, auditability, and human-in-the-loop controls, alongside techniques like fairness metrics, disparate impact analysis, interpretability tools, and transparent reporting. You will also examine how governance boards, impact assessments, and policy playbooks reduce risk and build stakeholder trust. Quizzes and reflections reinforce core concepts and help you identify practical next steps for your organization. By the end, you will have a clear blueprint to align AI capabilities with ethical standards, regulatory expectations, and business goals—so you can deliver AI that is legal, safe, and worthy of user confidence.

CH 12.3: Ethical AI Development: Governance, Fairness, and Transparency

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            <p>The rapid integration of artificial intelligence into daily life and business operations has brought the ethics of machine learning to the forefront of modern technology discussions. This course explores the critical intersection of innovation and responsibility, focusing on the governance and regulations that guide the creation of AI systems and products. By examining the frameworks necessary for ethical oversight, participants will understand how to navigate the complex legal and moral landscapes that define contemporary AI development.</p>

<p>Beyond high-level governance, the curriculum delves into the practical challenges of ensuring fairness and mitigating bias within algorithmic decision-making. A significant portion of the study is dedicated to the principles of transparency and explainability, ensuring that AI systems are not just effective, but also accountable and understandable to their users. Finally, the course highlights the evolving career opportunities within Information Systems (IS), preparing professionals to lead with integrity in an increasingly automated world through rigorous analysis and ethical practice.</p>
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