Topics:

• Understanding AI Basics: What Scrum Masters Need to Know
• Introduction to AI Tools: Google AI Studio, Gemini – Gem Manager, Customised GPT, Claude, and Other User-Friendly Options
• AI Terminology for Non-Technical Users
• Ethical Considerations When Using AI in Team Contexts
• How AI Can Enhance the Scrum Master Role

AI Terminology Section:

• Large Language Models (LLMs): AI systems trained on vast amounts of text that can understand and generate human language
• Generative AI: Technology that can create new content like text, images, or ideas based on prompts
• Prompt: The input text given to an AI system that directs what kind of response you want
• AI Assistant: An AI system designed to help with specific tasks through conversation
• Tokens: The units of text that AI processes (roughly 4 characters or 3/4 of a word)
• Context Window: How much information an AI can "remember" during a conversation
• Hallucination: When AI generates information that sounds plausible but is incorrect or made up
• Fine-tuning: Adapting an AI model for specific purposes by training it on additional data

Ethical Considerations Section:

• Transparency: Being open with teams about how and when AI is being used
• Privacy: Ensuring team data used with AI respects confidentiality
• Bias awareness: Understanding that AI can reflect biases in its training data
• Human oversight: Maintaining human judgment for important decisions
• Consent: Getting team buy-in before implementing AI-assisted processes
• Clear boundaries: Defining what AI should and shouldn't do in your Scrum process