AI Fundamentals & Generative AI Overview
Digital Competency Framework (DQ Institute)
8 digital skills × 3 maturity levels ⇒ 24 competencies (knowledge, skills, attitudes, values)
Technological Paradigm Shifts
1960s Mainframes (large computers)
1970\text{-}1980s Minicomputers / Personal Computers
1990s Internet connectivity & e-commerce
2000s Cloud computing (anywhere, anytime data)
2010s→present Mobile, Social Media, IoT, Artificial Intelligence
AI Literacy Principles
Know core AI functions → apply responsibly
Continuously evaluate output accuracy
Prioritise ethics: avoid misuse, misinformation, copyright issues
Everyday AI Examples
Facial recognition (phones, security)
Noise cancellation (headphones)
Route optimisation (Google Maps)
Targeted online advertising
Self-driving vehicles
Voice assistants (Siri, Google Assistant)
Smart farming analytics
Common Application Areas
Virtual assistants (voice control, scheduling)
Social media content/recommendations
Online shopping suggestions & price checks
Streaming personalisation (Netflix, Spotify, YouTube)
Travel/route assistants
AI Fundamentals & Hierarchy
Artificial Intelligence (AI): machines mimic human cognition
Machine Learning (ML): AI subset, learns from data
Deep Learning (DL): ML subset, neural-network based
Large Language Models (LLM): DL models that process & generate language
Generative AI (GenAI): creates new content from learned data
Bloom’s Taxonomy Parallel
AI progresses from remembering data → creating new content (highest level)
Technology Adoption to 50 M Users
Airplane 68 years
Internet 7 years
Facebook 3 years
Generative AI 5 weeks
Generative-AI Startup Surge
Rapid increase in companies building proprietary GenAI tools
Seven Core Generative-AI Types
Text generation (LLMs)
Image generation (text→image: Adobe Firefly, Freepik, Google Imagen)
Code generation & analysis (GitHub Copilot, Google Gemini)
3-D object generation (text→3D)
Music generation (e.g., Suno)
Audio generation / text-to-speech (VoiceoverMaker)
Video generation (text→video)
Prompt Engineering
Prompt = instruction given to AI
Prompt Engineer: crafts precise, effective prompts; blends AI knowledge & problem-solving skills
Additional GenAI Use-Cases
Weather modelling & forecasting
Stock-market trend prediction
Consumer-trend & demand analysis
Auto-generated game levels
Automated product design
Handwriting & character recognition
Advanced facial recognition
Educator’s Perspective
AI cannot replace teachers’ expertise, creativity, or pedagogy
Acts as a powerful tool to enhance and personalise teaching & learning