AI+ Ethics (AIET)

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AI+ Ethics (AIET)

Fast Lane Institute for Knowledge Transfer GmbH
Logo Fast Lane Institute for Knowledge Transfer GmbH
Provider rating: starstarstarstarstar_half 9.0 Fast Lane Institute for Knowledge Transfer GmbH has an average rating of 9.0 (out of 34 reviews)

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Starting dates and places
placeFrankfurt
9 Sep 2026
placeHamburg
2 Dec 2026
Description

Voraussetzungen

  • Basic grasp of ethical principles and moral reasoning
  • Interest in how AI impacts society and daily life, and openness to change
  • Willingness to understand AI ethical frameworks and guidelines

Detaillierter Kursinhalt

Module 1: Overview of AI Ethics & Societal Impact

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

Module 2: Bias and Fairness in AI

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

Module 3: Transparency and Explainable AI

  • 3.1 Importance of Transparent AI Syste…

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Didn't find what you were looking for? See also: Ethics, Certified Ethical Hacker (CEH), EC-Council, CompTIA A+ / Network+ / Security+, and IT Security.

Voraussetzungen

  • Basic grasp of ethical principles and moral reasoning
  • Interest in how AI impacts society and daily life, and openness to change
  • Willingness to understand AI ethical frameworks and guidelines

Detaillierter Kursinhalt

Module 1: Overview of AI Ethics & Societal Impact

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

Module 2: Bias and Fairness in AI

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

Module 3: Transparency and Explainable AI

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

Module 4: Privacy and Security Issues in AI

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

Module 5: Accountability and Responsibility

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

Module 6: Legal and Regulatory Issues

  • 6.1 Overview of Relevant Laws and Regulations Pertaining to AI
  • 6.2 Understanding the Global Regulatory Issues for AI Technologies
  • 6.3 Case Studies: GDPR Compliance
  • 6.4 Legal Compliance of AI Tools

Module 7: Ethical Decision-Making Frameworks

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

Module 8: AI Governance & Best Practices

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

Module 9: Global AI Ethics Standards

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