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AI Ethics and Responsible Business Practices
New
110 students

AI Ethics and Responsible Business Practices

Master AI Governance, Mitigate Real-World Risks, and Implement the NIST AI Risk Management Framework in Business.
Created byImran Zakir
Last updated 10/2026
English
English [Auto],

What you'll learn

  • Analyze real-world AI failures in healthcare, coding, and business to identify ethical risks and root causes.
  • Apply the NIST AI Risk Management Framework (Map, Measure, Manage, Govern) to deploy AI systems responsibly.
  • Evaluate the core debates between immediate ethical harms (bias, data labor) and long-term existential AI risks.
  • Implement practical governance and human-in-the-loop oversight to maintain accountability in AI workflows.

Course content

4 sections • 15 lectures • 2h 20m total length

  • Defining AI: Analytical vs. Generative8:30

    Understanding AI as a set of tools designed to analyze information or generate new content based on learned patterns.

  • Generative AI (GenAI)9:04

    A specialized subset that produces textual, visual, and auditory outputs.

  • High-Stakes Applications5:39

    How AI systems now inform critical decisions in finance, health, HR, and public policy.

Requirements

  • No prior technical, coding, or AI background required; all concepts are explained clearly from the ground up.
  • A basic interest in Artificial Intelligence and how technology impacts business, ethics, and society.

Description

This course contains the use of artificial intelligence.

As Artificial Intelligence integrates rapidly into healthcare, hiring, finance, operations, and software development, organizations face a critical challenge: balancing cutting-edge AI power with real human responsibility. Deploying AI systems without proper oversight often leads to severe operational, financial, and ethical fallout.

This comprehensive, practical course demystifies AI ethics and equips you with actionable frameworks to govern and deploy technology responsibly. Moving past speculative science-fiction narratives, this course focuses on immediate, real-world challenges—such as algorithmic bias, unvetted autonomous agents, systematic errors, and data privacy concerns.

Through high-impact case studies, you will examine real-world AI failures—including diagnostic chatbots, automated insurance denials, and rogue coding agents—to understand why systems break down and how to prevent costly mistakes.

You will master the industry-standard NIST AI Risk Management Framework (AI RMF) using a clear, four-part blueprint:

  • Map: Identify operational contexts, target capabilities, and potential systemic risks before deployment.

  • Measure: Implement continuous monitoring to detect bias, inaccuracies, and performance drift.

  • Manage: Establish robust fallback mechanisms, override protocols, and rollback procedures.

  • Govern: Build an accountable culture with clear human-in-the-loop oversight and compliance policies.

Whether you are a business leader, manager, developer, or curious professional, this course provides the essential knowledge to navigate AI adoption safely, maintain customer trust, and lead responsible innovation in your organization.

Who this course is for:

  • Business professionals, managers, and entrepreneurs looking to implement AI tools safely and ethically.
  • Product managers, developers, and tech teams wanting a practical blueprint for AI risk management and governance.
  • Students, educators, and curious learners interested in the real-world impact and ethics of Artificial Intelligence.

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