Duration 1 day – 7 hrs
Overview
This course provides professionals and organizations with a foundational understanding of how to use AI responsibly in the workplace. Covering key topics like ethical guidelines, governance frameworks, data privacy, compliance, and managing AI risks such as hallucinations and bias, this course equips participants with the knowledge to adopt AI safely and ethically across business functions.
Objectives
- Understand the principles of ethical AI use and governance in the workplace
- Identify and mitigate risks such as bias, hallucinations, and misinformation in AI outputs
- Apply data privacy and compliance practices, especially when using open-source and generative AI tools
- Establish workplace AI usage policies and best practices
- Promote trust, fairness, and accountability in AI-assisted decision-making
Audience
- HR leaders, compliance officers, risk managers, and IT policy makers
- Business leaders, department heads, and digital transformation officers
- AI tool users across marketing, HR, operations, and finance
- Anyone responsible for defining or following ethical standards for AI adoption
Prerequisites
- Basic understanding of AI tools (e.g., ChatGPT, Claude, Copilot)
- No technical or programming background required
- Prior exposure to company policies or compliance practices is helpful
Course Content
Session 1: Introduction to AI Governance and Responsible Use
- What is responsible AI?
- Overview of ethical principles: fairness, transparency, accountability
- AI usage policies in the workplace: why they matter
- Role of governance in AI adoption and risk management
Session 2: Workplace AI Usage Guidelines and Policies
- Defining acceptable use of GenAI tools in teams
- Setting internal AI policy frameworks
- Examples of real-world AI governance policies (Microsoft, Google, OECD, etc.)
- Drafting your own AI usage policy outline
Session 3: Data Privacy, Compliance & Open-Source Considerations
- Managing sensitive data with AI tools
- Understanding GDPR, HIPAA, and other regulatory obligations
- Using open-source AI (e.g., DeepSeek, LLaMA) responsibly
- Ensuring secure and compliant use of external APIs and cloud-based models
Session 4: Recognizing and Mitigating AI Hallucinations and Bias
- What are AI hallucinations and why they happen
- Understanding bias in model training and output
- Strategies to detect, reduce, and manage misleading or harmful AI outputs
- Evaluating AI-generated content for factual accuracy and ethical alignment
Session 5: Case Studies and Practical Applications
- Case review: AI misuse in hiring, marketing, or customer support
- Discussion: What would you do? Responding to ethical dilemmas with AI
- Building your AI Ethics checklist for your team or company
Final Hands-On Activity:
Participants will review a real-world AI use case, identify ethical concerns, suggest policy revisions, and present a responsible use guideline tailored to their department or company.
