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AI+ Ethics (AI+ Ethics)

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    • T87203
    • 1 day
    • 06/03/2025 - 06/03/2025*
    • 9:00 AM
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    • T87204
    • 1 day
    • 07/07/2025 - 07/07/2025*
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    • T87205
    • 1 day
    • 08/04/2025 - 08/04/2025*
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    • T87206
    • 1 day
    • 09/08/2025 - 09/08/2025*
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    • T87207
    • 1 day
    • 10/06/2025 - 10/06/2025*
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Course Summary
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Description

Learn and get certified with AI Ethics Training to manage ethical challenges in AI application design, effectively. This ethics in AI certification program equips professionals with ethical knowledge to responsibly utilize AI technologies, understand societal impacts, mitigate risks, and guide decision-making in global AI governance. To enroll in this AI Ethics course, you should have a foundational understanding of AI concepts and professional ethics to navigate AI systems confidently.

The AI+ Ethics course delves into the ethical considerations and societal impacts of Artificial Intelligence. It covers ethical principles, the societal impact of AI technologies, and strategies for conducting social and ethical impact assessments. Participants will explore biases in data and algorithms, and learn strategies for mitigating bias and ensuring fairness. The course also addresses the need for transparency and explainable AI, including techniques for making AI models understandable to diverse stakeholders. Additionally, it examines privacy and security issues related to AI.

Objectives

  • Understand the ethical considerations in AI: Gain knowledge of the ethical implications of AI technologies and their impact on society.
  • Evaluate societal impacts: Examine the societal consequences of AI technologies and develop strategies for assessing their social and ethical impact.
  • Mitigate bias and ensure fairness: Explore biases in data and algorithms, and learn strategies to mitigate bias and ensure fairness in AI systems.
  • Ensure transparency and explainability: Understand the importance of transparency in AI systems and learn techniques for explaining AI models to diverse stakeholders.
  • Address privacy, security, accountability, and legal issues: Analyze privacy and security concerns in AI, understand concepts of accountability, and become familiar with relevant legal and regulatory frameworks, aiming to develop ethically aligned AI systems compliant with global standards.

Prerequisites

Required

  • Having a basic grasp of ethical principles and moral reasoning.
  • Being interested in how AI impacts society and daily life, and being open to change.
  • Willing to understand AI ethical frameworks and guidelines. Please let me know if this approach to language and tone works.

Recommended

  • AI+ Executive
  • AI+ Everyone

Who Should Attend

  • AI Engineer
  • IT Professional

Outline

Overview of AI Ethics & Societal Impact

  • Introduction to Ethical Considerations in AI
  • Understanding The Societal Impact of AI Technologies
  • Strategies for Conducting Social and Ethical Impact Assessments

Bias and Fairness in AI

  • Exploration of Biases in Data and Algorithms
  • Strategies for Mitigating Bias and Ensuring Fairness in AI Systems

Transparency and Explainable AI

  • Importance of Transparent AI Systems
  • Techniques for Explaining AI Models to Diverse Stakeholders
  • Guided Projects on Designing and Analysis of AI Systems with Ethical Considerations

Privacy and Security issues in AI

  • Examination of Privacy Concerns Related to AI
  • Strategies for Ensuring the Security of AI Systems and Data

Accountability and Responsibility

  • Concepts of Accountability in AI Development and Deployment
  • Responsibilities of AI Practitioners and Organizations

Legal and Regulatory Issues

  • Overview of Relevant Laws and Regulations Pertaining to AI
  • Understanding the Global Regulatory Issues for AI Technologies
  • Case Studies
  • Legal Compliance of AI Tools

Ethical Decision-Making Frameworks

  • Introduction to Frameworks for Making Ethical Decisions in AI
  • Case Studies and Applications of Ethical Decision-Making
  • Use of Simulation Platforms in Ethical Decision-Making

AI Governance & Best Practices

  • Principles and Functions of International AI Governance
  • Best Practices for Integrating AI Ethics into Organizational Policies
  • Case Studies on AI Governance

Global AI Ethics Standards

  • Explore Standards like IEEE’s Ethically Aligned Design
  • Comparative Case Studies on Standard Implementations
  • Tools for Evaluating AI Systems Against Global Standards

Optional Module: AI Agents for Ethics and Its Implications

  • Understanding AI Agents
  • Case Studies
  • Hands-On Practice with AI Agents