Length: 2 days
This 2-day course provides a comprehensive understanding of responsible AI practices, focusing on their application in defense settings. Participants will learn about the principles of ethical AI, explore frameworks and guidelines, and gain practical skills in implementing responsible AI solutions.
Learning Objectives
- Understand the principles and importance of responsible AI.
- Explore ethical frameworks and guidelines for AI in defense.
- Gain practical skills in developing and implementing responsible AI solutions.
- Learn to ensure compliance with ethical standards and regulatory requirements.
Target Audience
- Defense personnel involved in AI development and deployment.
- IT professionals and analysts working in defense-related fields.
- AI researchers and practitioners.
Day 1: Understanding Responsible AI
8:00 AM – 9:00 AM: Registration and Welcome
- Registration
- Course introduction and objectives
- Overview of the agenda
9:00 AM – 10:30 AM: Session 1 – Introduction to Responsible AI
- What is responsible AI?
- Importance of ethical AI in defense applications
- Overview of ethical principles: fairness, accountability, transparency, and privacy
- Case studies of AI misuse and ethical dilemmas
10:30 AM – 10:45 AM: Break
10:45 AM – 12:15 PM: Session 2 – Ethical Frameworks and Guidelines
- Overview of DIU’s Responsible AI Guidelines
- Other ethical frameworks and standards (e.g., IEEE, OECD, EU)
- Comparison of different frameworks
- Case study: Applying ethical frameworks to defense AI projects
12:15 PM – 1:15 PM: Lunch Break
1:15 PM – 2:45 PM: Session 3 – Bias and Fairness in AI
- Understanding bias in AI systems
- Techniques for detecting and mitigating bias
- Ensuring fairness in AI models
- Practical exercise: Identifying and addressing bias in AI datasets
2:45 PM – 3:00 PM: Break
3:00 PM – 4:30 PM: Session 4 – Accountability and Governance
- Establishing accountability in AI development and deployment
- Role of governance structures in responsible AI
- Implementing AI audit and compliance processes
- Case study: Governance best practices in defense AI projects
4:30 PM – 5:00 PM: Q&A and Day 1 Wrap-up
- Recap of key points
- Q&A session
Day 2: Implementing and Ensuring Responsible AI
8:00 AM – 9:00 AM: Recap and Day 2 Introduction
- Recap of Day 1
- Overview of Day 2 agenda
9:00 AM – 10:30 AM: Session 5 – Transparency and Explainability
- Importance of transparency in AI systems
- Techniques for making AI models explainable
- Communicating AI decisions to stakeholders
- Practical exercise: Implementing explainability in AI models
10:30 AM – 10:45 AM: Break
10:45 AM – 12:15 PM: Session 6 – Privacy and Security in AI
- Ensuring data privacy in AI applications
- Techniques for secure AI development and deployment
- Handling sensitive data in defense AI projects
- Practical exercise: Implementing privacy-preserving AI techniques
12:15 PM – 1:15 PM: Lunch Break
1:15 PM – 2:45 PM: Session 7 – Implementing Responsible AI Solutions
- Integrating responsible AI principles into the AI lifecycle
- Tools and best practices for responsible AI development
- Case study: Successful implementation of responsible AI in defense projects
- Practical exercise: Developing a responsible AI implementation plan
2:45 PM – 3:00 PM: Break
3:00 PM – 4:30 PM: Session 8 – Compliance and Continuous Improvement
- Ensuring compliance with ethical standards and regulatory requirements
- Monitoring and auditing AI systems for ongoing compliance
- Strategies for continuous improvement in responsible AI practices
- Practical exercise: Conducting an AI ethics audit
4:30 PM – 5:00 PM: Course Wrap-up and Certification
- Final Q&A session
- Course wrap-up and key takeaways
- Distribution of certificates of completion
Course Materials
- Slide deck covering all sessions
- Hands-on lab manuals for practical exercises
- Access to ethical AI tools and frameworks
- DIU’s Responsible AI Guidelines documentation
Assessment and Certification
Participants will receive a certificate of completion upon successfully attending the full course and participating in practical exercises. An optional assessment can be provided to test the knowledge gained during the course.