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AI+ Ethics Fundamentals™

Course code: NPAC120

Formerly known as AI+ Ethics™

Navigate the Intersection of AI and Ethics in Business Landscape

  • Responsible AI Focus: Master ethical AI practices aligned with both business objectives and broader societal values.
  • Risk Mitigation: Develop skills to manage compliance, transparency, and responsible AI decision-making.
  • Strategic Guidance: Embed ethical frameworks into AI adoption strategies and leadership approaches.
  • Reputation Builder: Strengthen organizational trust and credibility through responsible AI deployments.
75 EUR

91 EUR including VAT

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

Strategic Thinking

Learners will examine AI technologies and their commercial consequences, which involves planning strategically and make AI integration decisions for their organizations.

Ethical-Decision Making Skills

Students will learn to navigate AI's complex ethical issues by identifying ethical concerns, applying ethical decision-making frameworks, and ensuring accountability in AI initiatives.

Project Management

Participants will learn to develop, implement, and monitor AI initiatives while addressing bias, fairness, transparency, privacy, and security.

Compliance and Governance Norms and Practices

Students will learn about AI law and regulation, focusing on ensuring AI systems comply with legal requirements and applying governance best practices to mitigate risks, maintain transparency, and uphold accountability.

Course structure

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

Prerequisites

  • A basic knowledge of artificial intelligence, machine learning concepts, and their practical applications.
  • An understanding of the social, cultural, and political implications of AI technologies.
  • Familiarity with professional ethics, encompassing honesty, integrity, and accountability.
  • Exposure to real-world case studies highlighting ethical dilemmas in AI for practical context.
  • Ability to critically evaluate AI technologies and make informed ethical decisions across design, deployment, and management.
  • Familiarity with relevant laws, regulations, and industry standards governing AI usage.

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