DAY 2 review podcast discussion Ongweso

Introduction

• Welcome to class! Students are encouraged to find a seat and help themselves to a Student Guide.

Classroom Policies

Syllabus Overview

• WiFi Connectivity & Device Usage:

  • Students must disable WiFi or put away devices when asked to ensure engagement and minimize distractions.

  • Minimize bathroom breaks to emergencies to respect fellow classmates and teacher.

Note-taking Recommendations

• Note-taking is crucial for class participation.

• Suggested materials include:

  • Old-fashioned composition notebook

  • Spiral notebook (with or without perforated edges)

• Notes can be shared among students, with a sign-up sheet circulated for this purpose.

Understanding Artificial Intelligence (AI)

Key Concepts in AI

• Artificial Intelligence: Technology that simulates human intelligence.

  • Data: Foundation for AI through statistical modeling.

  • Machine Learning: Utilization of big data to refine algorithms.

  • Deep Learning: Advanced machine learning with neural networks.

  • Generative AI: Focus on creating new content from learned data.

Essentials of AI Literacy

Point #1 - Understanding AI's Functionality

• Statistical Modeling of Data:

  • AI, especially chatbots, operates on large-scale statistical representations.

  • Example: Women's gymnastics evaluation through a trained AI model.

Point #2 - AI's Anthropomorphism

• AI often exhibits characteristics attributed to humans, as seen in various media.

  • Examples:

    • Westworld (TV series)

    • Klara and the Sun, Blade Runner (Philip K. Dick)

• Terminology: Learning, thinking, reasoning—all contribute to the public's perception of AI as science fiction.

Point #3 - Practical Use Cases of Generative AI

• Generative AI can be useful under specific circumstances, including:

  • Coding, Translation, Grammar checks, Organizing references.

• Limitations:

  • Generative AI is not a search engine and lacks reliability in verification and citation.

  • Concerns arise regarding its role in brainstorming and idea generation, highlighting its probabilistic nature.

Point #4 - Generative AI's Probabilistic Nature

• Normal Distribution & Bell Curve:

  • Understanding reliability through the lens of probabilistic mimicry.

  • “Stochastic Parrots” concept introduces concerns on model size and reliability.

Point #5 - Risks Associated with Generative Chatbots

• Potential Harms:

  • Data Theft, Surveillance and privacy issues.

  • Bias, Environmental Impact, Malicious Use, and Learning Loss.

  • The Eliza Effect: Overreliance on AI for emotional support and learning.

Current Matters in AI Development

Discussion and Engagement

• Reflect on the dynamics of power concentration in AI and its implications for privacy and data security.

Class Preparation & Expectations

Key Dates

• Thursday, January 23, 2025:

  • Engage with the podcast titled 404 Media Year in Review.

  • Expectations: Students should take notes, formulate questions and participate in class discussions about the podcast content.

Additional Reading

• Edward Ongweso’s substack article discussing AI discourse and perspectives within the AI debate.

  • Key Argument: Distinction between internal and external criticisms of AI highlights the complexity and realities of its impact on society.

AI in Business and Education

Diverging Perspectives

• Tensions exist between higher education goals and generative AI ambitions.

• Education's Focus: Promotes articulate and applied knowledge.

• Generative AI's Goal: Seeks quick economic productivity gains.

  • Observations on efficiency and productivity in AI development versus actual outputs in educational settings.