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Tracking AI - Course Description

Prompt

Help me write a course description for a three-day course on understanding the exponential growth rate of AI and the strategic implications on organizations such as schools, colleges and universities as well as other businesses. Focus on how high-quality content generation is allowing almost anyone to generate text and images. Describe how most organizations that manage knowledge will be impacted. Include content that tracks AI capabilities such as AI benchmarks and question answering. Discuss the limitations of current LLMs and their lack of world models. Discuss how organizations are building generative AI centers of excellence to review ideas on how organizations can use AI to be more productive.

Exponential AI: Strategic Implications for Knowledge Organizations

Course Description

This three-day intensive course explores the exponential growth of artificial intelligence and its profound strategic implications for knowledge-based organizations including educational institutions and businesses. Participants will gain a comprehensive understanding of how generative AI is transforming content creation, knowledge management, and organizational productivity.

Target Audience

This course is targeting a general audience that has little knowledge of AI technologies. We are careful to clearly define new terms before they are used. There are no prerequisites for this course other than a curiousity of how AI works and how it will impact organizations that manage knowledge.

Day 1: Understanding AI's Exponential Growth

Morning: Foundations of AI Growth

  • AI capability trajectories: Historical perspective and acceleration patterns
  • Key AI benchmarks: From ImageNet to modern benchmarks like MMLU and HumanEval
  • Understanding both absolute and relative AI benchmarks
  • Key terminology for measuring AI tools - one shot, reasoning, agents
  • Objective capability measurement, accuracy, responsiveness, cost
  • Defining exponential growth in the context of AI development
  • Case studies of breakthrough moments in AI development

Afternoon: Content Generation Revolution

  • Text generation capabilities: From basic templates to human-level writing
  • Image generation evolution: DALL-E to Midjourney and beyond
  • Democratization of content creation tools
  • The dropping cost of AI tools: Open source and local tools
  • Hands-on workshop: Generating a graphic novel with Anthropic Claude and OpenAI DALL-E

Day 2: Organizational Impact Assessment

Integrating Organizational Knowledge

  • Definitions of public knowledge vs. private knowledge
  • Why LLMs contain public knowledge but not private knowledge
  • Types of private knowledge scope: personal, project, department and organization knowledge
  • Strategies for getting private knowledge into the context window
  • Protecting private knowledge
  • Case study: Family Educational Rights and Privacy Act (FERPA)

Afternoon Option 1: Educational Institution Impacts

  • Vision: the hyperpersonalized learning plan
  • Transforming teaching methodologies and curriculum development
  • Assessment challenges in an AI-assisted world - how do we measure the quality of a course, chapter, lesson plan, story or MicroSim?
  • Tracking reputable sources: research integrity and academic publishing considerations
  • Student skill development for an AI-augmented future

Afternoon Option 2: Business Transformation

  • Knowledge worker productivity shifts
  • AI and business process analysis
  • Customer service and engagement transformations
  • Product development acceleration
  • Strategic competitive advantages through AI adoption
  • Workshop: Impact assessment for your organization

Day 3: Strategic Response Planning

Morning: Limitations and Realistic Expectations

  • Current limitations of large language models
  • Predicting when limitations will no longer be a challenge
  • Understanding the absence of world models in current AI
  • Hallucination challenges and factual reliability
  • Ethical considerations and responsible AI deployment; bias and fairness measurements

Afternoon: Building AI Centers of Excellence

  • Organizational structures for AI integration - centralized vs. decentralized control models
  • Developing AI literacy across all organizational levels
  • Creating governance frameworks for responsible AI use
  • Implementation roadmapping and change management
  • Ethics Case Study: Is it ethical to deny student access to superior AI tools?
  • Workshop: Drafting your organization's AI strategy

Learning Outcomes

By completing this course, participants will:

  • Remember key AI terminology
  • Understand the exponential growth patterns of AI capabilities and their strategic implications
  • Apply AI to specific areas of your organization where AI will transform their organization's operations
  • Analyze the potentials and limitations of current AI technologies and predict future capabilities
  • Evaluate frameworks for establishing AI centers of excellence and customize these frameworks to the needs of your organization
  • Create preliminary strategic plans for AI integration in their organizations

Who Should Attend

  • Educational leaders and administrators
  • Business executives and strategic planners
  • Knowledge management professionals
  • Innovation and digital transformation leaders
  • Department heads responsible for organizational productivity

Limited to 30 participants to ensure interactive learning and personalized strategic planning assistance.