DWP - Artificial Intelligence (AI) for Managers 1 Day

Course Code: dwpaiman

Duration: 7 hours

Overview:

This comprehensive syllabus covers a wide range of topics relevant to AI in government, with a focus on practical applications and hands-on experience with various AI tools. It's designed to provide non-technical UK government employees with a solid understanding of AI and its potential applications in their work.

Format of the Course

Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.

Course Outline:

Introduction
- Welcome and course objectives
- Brief overview of AI's impact on government services
- UK's AI strategy and its importance in public sector innovation
Overview of Artificial Intelligence (AI)
- Defining AI: What it is and what it isn't
- Brief history of AI development
- Types of AI: Narrow AI vs. General AI
- Machine learning systems: A non-technical explanation
- Real-world examples of AI in government services (UK focus)
Exploring Applications for AI
- AI in the corporate context: Private sector use cases
- Government-specific AI applications:
  - Predictive analytics for policy-making
  - Chatbots for citizen services
  - Fraud detection in tax and welfare systems
  - AI-powered cybersecurity
- Case studies: Successful AI implementations in UK government departments
- Hands-on demonstrations of popular AI tools:
  - POE/ChatGPT: Generating reports and answering policy-related questions
  - Claude: Analyzing complex government documents
  - DALL-E: Creating visual aids for public communications
  - Midjourney: Generating concept art for urban planning projects
- Practical exercise: Using AI tools to draft a citizen communication
Learning About the Technology of AI
- Simplified explanation of key AI concepts:
  - Underfit and overfit: Balancing accuracy and generalization
  - Classification: Sorting data into categories
  - Regularization: Preventing overfitting
- Multi-layer perception (MLP) and deep learning: The basics
- Convolutional and recurrent neural networks: Applications in image and text processing
- Hands-on demo: Simple AI tools for non-technical users
- Interactive session: Comparing outputs from different AI models (e.g., GPT-3.5 vs GPT-4)
Assessing Strategic Approaches
- Commissioning or procurement (build or buy?):
  - Pros and cons of in-house development vs. outsourcing
  - UK government procurement guidelines for AI solutions
- AI maturity models for your organization:
  - Assessing current AI readiness
  - Planning for future AI integration
- Ethical considerations in government AI adoption
Working With Data in Your Organization
- Data readiness evaluation:
  - Assessing data quality and quantity
  - Data privacy and security in the public sector
- Word embeddings: Understanding textual data
- Training with artificial data:
  - Benefits and limitations
  - Ensuring data diversity and reducing bias
- GDPR and UK data protection laws in the context of AI
- Practical exercise: Using AI tools to analyze and visualize government datasets
Assessing AI Project Selection
- Key criteria for project selection:
  - Alignment with government priorities
  - Feasibility and resource requirements
  - Potential impact on citizens and public services
- Risk assessment and mitigation strategies
- Stakeholder engagement in AI project selection
Managing an AI Project
- Machine learning versus deep learning: Choosing the right approach
- Project management in the context of AI:
  - Lifecycle considerations
  - Realistic timescales for AI implementation
  - Agile methodology adapted for AI projects
- Operations, maintenance, and risk management:
  - Ensuring long-term success of AI implementations
  - Continuous monitoring and improvement
- Change management: Preparing government staff for AI adoption
Prompt Engineering for Government Applications
- Introduction to prompt engineering:
  - What it is and why it's important
  - The art of crafting effective prompts
- Best practices for prompt engineering in government contexts:
  - Clarity and specificity in prompts
  - Avoiding biases and ensuring fairness
  - Maintaining security and confidentiality
- Hands-on exercises with various AI tools:
  - ChatGPT: Crafting prompts for policy analysis
  - Claude: Engineering prompts for legal document summarization
  - GPT-4: Creating prompts for citizen service chatbots
  - DALL-E/Midjourney: Designing prompts for public awareness campaign visuals
- Practical applications in government work:
  - Using AI for draft legislation review
  - Generating public FAQs on new policies
  - Summarizing public feedback on proposed initiatives
- Ethical considerations in prompt engineering for government use
Gathering Feedback
- Implementing feedback methods:
  - Surveys, interviews, and focus groups
  - Digital platforms for citizen feedback
- Key stakeholders who will provide feedback:
  - Citizens
  - Government employees
  - Policy makers
  - AI ethics committees
- Analyzing results:
  - Quantitative and qualitative analysis techniques
  - Using feedback to improve AI systems and policies
- Demonstration: Using AI tools to analyze and categorize citizen feedback
AI Tools Workshop
- Deep dive into specific AI tools and their government applications:
  - Poe: Collaborative problem-solving for inter-departmental projects
  - ChatGPT: Drafting speeches and public statements
  - Claude: Analyzing and summarizing lengthy policy documents
  - DALL-E/Midjourney: Creating visual aids for public presentations
  - Anthropic's Constitutional AI: Understanding and applying ethical AI principles
- Hands-on exercises:
  - Using Poe for a mock interdepartmental brainstorming session
  - Employing ChatGPT to draft a public announcement on a new initiative
  - Utilizing Claude to analyze and summarize a complex piece of legislation
  - Creating infographics with DALL-E for a public health campaign
- Discussion: Potential integration of these tools in daily government operations
Summary and Conclusion
- Recap of key learnings
- Future of AI in UK government
- Resources for further learning and support
- Group activity: Participants share their most valuable takeaways and how they plan to apply AI tools in their work
- Q&A session