AI and Machine Learning MOC
This Map of Content explores the rapidly evolving landscape of Artificial Intelligence (AI) and Machine Learning (ML), with a focus on foundational concepts, applications, ethical concerns, and pedagogical implications.
AI is not just a technical domainβit is a social, cultural, political, and epistemological force reshaping education, labor, identity, and power.
π§ Core Concepts
- Artificial Intelligence πΉ
- Machine Learning πΉ
- Neural Networks πΉ
- Deep Learning πΉ
- Natural Language Processing (NLP) πΉ
- Generative AI πΉ
- Large Language Models (LLMs) πΉ
- Supervised vs Unsupervised Learning πΉ
- Reinforcement Learning πΉ
- Computer Vision πΉ
π οΈ Applications & Tools
- AI in Education πΈ
- AI Writing Tools πΈ
- AI Image Generation Tools πΈ
- Voice Assistants and Smart Devices πΈ
- Facial Recognition Systems πΈ
- Predictive Policing πΈ
- Recommender Systems πΈ
- ChatGPT πΈ
- NotebookLM πΈ
- Google AI Studio πΈ
βοΈ Ethics & Societal Impact
- Bias in AI πΈ
- Algorithmic Accountability πΈ
- AI and Labor πΈ
- Surveillance AI πΈ
- AI and Democracy πΈ
- AI and Misinformation πΈ
- Ethics in AI πΉ
- Algorithmic Oppression πΈ
- Transparency vs Explainability πΈ
- Responsible AI Development πΉ
π Privacy & Security Concerns
- Privacy-Preserving AI πΈ
- Federated Learning πΈ
- Differential Privacy πΈ
- Homomorphic Encryption πΈ
- AI and Data Sovereignty πΈ
- AI and Cybersecurity πΈ
π Learning & Pedagogy
- Teaching AI Literacy πΉ
- AI in Kβ12 Education πΈ
- Ethical AI Curriculum πΈ
- Computational Thinking πΉ
- AI as Cognitive Amplifier πΈ
- AI for Inquiry-Based Learning πΈ
- Media Literacy and AI πΉ
π§ Critical & Interdisciplinary Perspectives
- Critical AI Studies πΈ
- Feminist AI πΈ
- Decolonizing AI πΈ
- Abolitionist Tech Futures πΈ
- AI and Climate Justice πΈ
- AI Narratives in Popular Culture πΉ