AI+ Ethics Fundamentals™

Formerly known as AI+ Ethics™ <br> <br> Navigate the Intersection of AI and Ethics in Business Landscape

  • Responsible AI Focus: Master ethical AI use aligned with business and societal values
  • Risk Mitigation: Learn to manage compliance, transparency, and AI decision-making
  • Strategic Guidance: Integrate ethical practices into AI adoption and leadership
  • Reputation Builder: Build organisational trust and credibility in AI deployments

 

Duur: 1 dag(en)

  • Ethics Professionals:Enhance your expertise in AI ethics to guide responsible AI deployment. 
  • AI & Data Enthusiasts:Learn how to apply ethical frameworks in AI decision-making processes. 
  • Compliance Officers:Ensure AI technologies comply with legal and ethical standards to mitigate risks. 
  • Technology Leaders:Drive ethical AI strategies and lead responsible AI initiatives within organizations. 
  • Students & New Graduates:Gain a competitive edge in the rapidly growing field of AI ethics. 
  • In-Depth Ethical Understanding:Understand ethical considerations and social impacts of AI for responsible decision-making.
  • Bias Mitigation and Fairness:Learn strategies to identify and prevent biases in AI systems, ensuring fairness and transparency.
  • Privacy and Security Assurance:Explore strategies to safeguard privacy and secure AI systems and data.
  • Legal and Regulatory Compliance:Understand global AI regulations to ensure compliance with legal and ethical standards.

Inhoud

Course Overview
Module 1: Overview of AI Ethics & Societal Impact
  • 1.1 Introduction to Ethical Considerations in AI Preview
  • 1.2 Understanding The Societal Impact of AI Technologies Preview
  • 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 Preview
  • 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 Preview
  • 3.2 Techniques for Explaining AI Models to Diverse Stakeholders Preview
  • 3.3 Guided Projects on Designing and Analysis of AI Systems with Ethical Considerations
Module 4: Privacy and Security Issues in AI
  • Study frameworks for holding organizations accountable for the ethical use of AI.
  • Why it matters: Ensures ethical AI deployment and helps mitigate the consequences of potential misuse or harm.
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: IEEE’s Ethically Aligned Design
  • 9.2 Comparative Case Studies on Standard Implementations
  • 9.3 Tools for Evaluating AI Systems Against Global Standards
Optional Module: AI Agents for Ethics and Its Implications
  • 1. Understanding AI Agents
  • 2. Case Studies
  • 3. Hands-On Practice with AI Agents
Tools you will explore
  • AI4People (Atomium – European Institute for Science, Media, and Democracy)
  • IBM – AI Fairness 360
  • IBM – AI Explainability 360
  • European Commission High-Level Expert Group on AI

Lesmethode

Instructor-led OR Self-paced course + Official exam + Digital badge

Kenmerken

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Access to all materials and exams is provided for 365 days after delivery.

Voorkennis

  • Basic knowledge of artificial intelligence, machine learning concepts, Python familiarity, fundamental AI/ML concepts

 895,00 excl. BTW