Duration 1 day – 7 hrs
Overview
This course provides a foundational understanding of the ethical, social, and regulatory challenges surrounding the development and deployment of AI systems. Participants will explore core issues such as bias and fairness, explainable AI (XAI), and the broader ethical implications and emerging regulations impacting responsible AI use in both public and private sectors.
Objectives
- Identify and mitigate bias in AI systems
- Understand the principles and practices of fairness, transparency, and accountability in AI
- Explain how explainable AI (XAI) enhances trust and compliance
- Assess the ethical impact of AI technologies across industries
- Navigate regulatory frameworks and governance standards for ethical AI
Audience
- Business leaders, policymakers, and ethics officers
- AI developers, data scientists, and product managers
- Risk, compliance, and legal professionals working with AI solutions
- HR, marketing, and finance professionals exploring responsible AI adoption
Prerequisites
- General understanding of AI and machine learning applications
- No technical or programming background required
- Prior exposure to organizational policies or risk frameworks is helpful
Course Content
Session 1: Introduction to AI Ethics and Governance
- What is AI ethics?
- Key principles: fairness, transparency, accountability, and privacy
- Why governance matters in AI development and deployment
Session 2: Bias and Fairness in AI Systems
- Understanding algorithmic bias: causes and consequences
- Measuring and mitigating bias in data and models
- Case studies: real-world bias in hiring, lending, and law enforcement
Session 3: Explainable AI (XAI)
- What is explainability and why it matters
- Techniques for interpreting AI models
- XAI tools and frameworks
- Use cases: regulated industries, healthcare, finance
Session 4: Ethical Implications and Regulatory Landscape
- Social and legal impacts of AI adoption
- Overview of current and emerging regulations (EU AI Act, US NIST, Philippine Data Privacy Act)
- Building internal governance frameworks and responsible AI guidelines
- Discussion: Ethics boards, impact assessments, and stakeholder engagement
Session 5: Interactive Case Study and Workshop
- Group exercise: Identify ethical risks and propose governance strategies
- Build a Responsible AI Checklist for your organization
