1. Ensuring Transparency and Fairness in AI-Driven Decisions

• Explainability
  • AI systems should provide understandable and interpretable decisions.
  • Use techniques like SHAP or LIME to enhance transparency.
• Bias Mitigation
  • Identify and eliminate biases in training data.
  • Regularly audit AI models for discriminatory patterns.
  • Use diverse and representative datasets.
• Accountability
  • 2. Avoiding Over-Reliance on AI While Maintaining Human Oversight

• Human-in-the-Loop Approach
  • Ensure AI assists rather than replaces human decision-making.
  • Involve human experts in reviewing and approving AI outputs.
  • Balance automation with human expertise, especially in critical areas.
• Transparency in Decision-Making
  • Communicate AI’s role in decision-making processes.
  • Provide users with an option to appeal AI-based decisions.
  • Implement clear guidelines for human intervention.
• Risk Assessment
  • Regularly evaluate AI’s reliability, accuracy, and limitations.
  • Conduct stress tests and scenario analyses to identify potential failures.
  • Develop contingency plans for AI errors.
• Training & Education
  • Train employees and users on AI capabilities and ethical implications.
  • Encourage responsible AI usage and critical thinking.
  • 
    
• • 
    
  • 
    

1. Maintaining Integrity in Coaching Relationships

• Confidentiality
  • Respect all personal and professional details shared by mentees.
  • Do not disclose private information without explicit consent.
• Transparency
  • Be upfront about your coaching approach, structure, and expectations.
  • Set realistic goals and deliver on your commitments.

2. Promoting Fair Guidance & Non-Biased Support

• Inclusivity
  • Support learners from all backgrounds with equal respect and encouragement.
  • Avoid favoritism or judgment based on skill level or experience.
• Balanced Feedback
  • Give honest, constructive feedback without discouraging growth.
  • Encourage learners to challenge themselves and explore confidently.

3. Setting Boundaries and Professionalism

• Respectful Interaction
  • Maintain clear boundaries between personal and professional space.
  • Use positive language and maintain a mentor–mentee tone.
• Availability
  • Be consistent with response times and respect the learner’s schedule.
  • Set clear office hours and avoid burnout from 24/7 availability.

4. Encouraging Lifelong Learning

• Self-Improvement
  • Continue upgrading your own knowledge, certifications, and industry trends.
  • Model a mindset of continuous learning for your mentees.
• Empowerment
  • Coach your mentees to become independent, confident decision-makers.
  • Equip them with tools, not just answers.

1. Introduction to AI Tools for Agile & Scrum

• Overview of AI-driven tools for Agile teams.
• Benefits of using AI in Scrum workflows.
• Key tools covered: ChatGPT, Jira integrations, Trello Power-Ups.

2. Practical Walkthrough of Popular AI Tools

ChatGPT for Agile Teams

• Using AI for backlog refinement, sprint planning, and retrospectives.
• Automating meeting summaries and reports.
• Generating user stories and acceptance criteria.

Jira AI Integrations

• AI-powered ticket prioritization and estimation.
• Automating status updates and progress tracking.
• AI-based risk assessment for sprint planning.

3. Real-World Scenarios and Exercises

• Sprint Planning with AI: AI-generated user stories and prioritization.
• Daily Standups & Progress Tracking: Automating status updates and risk identification.
• Retrospectives & Continuous Improvement: AI-generated feedback analysis.

4. Hands-on Exercises & Case Studies

• Interactive AI tool demonstrations.
• Simulated Scrum ceremonies using AI support.
• Group exercises to implement AI-driven backlog management.

5. Best Practices & Implementation Tips

• Ensuring AI tools align with Agile principles.
• Avoiding over-reliance on AI—balancing human decision-making.
• Ethical considerations when using AI in Agile workflows.

.