Course outline for
AI and Critical Thinking

Session One: Course Overview

Course Overview

Learning Objectives

Pre-Assignment

Pre-Course Assessment

Session Two: Introduction to AI

Artificial Intelligence

Ethics and Social Implications of AI

Case Study: Real-World Example of AI Bias

Session Three: Critical Thinking with AI

Critical Thinking

Evaluating an AI News Article or Product Claim

Session Four: Machine Learning and Algorithms

How Machine Learning Works

Overview of Algorithms Commonly Used in AI

The Practical Applications and Challenges of Machine Learning

Session Five: Advanced Ethics and AI Safety

Detailed Discussion on Data Privacy and AI Security

The Role of AI in Surveillance and Personal Freedoms

Balancing Innovation with Ethical Concerns

Session Six: Case Studies of AI Implementations

AI in Various Industries: Opportunities and Challenges

Case Study: AI Implementation in Supply Chain Management by DHL

AI Implementations

Session Seven: Philosophical and Future Aspects of AI

AI and Consciousness: Philosophical Debates

The Potential for Artificial General Intelligence (AGI)

The Future Impact of AI on Society

Philosophical And Future Aspects of AI

Session Eight: AI Guidelines and Policies

Developing Draft AI Guidelines and Policies: A Collaborative Starting Point

Defining Core Principles for AI Ethics Guidelines

Session Nine: Critical Evaluation of AI Systems

Understanding AI Robustness, Reliability, and Limitations

Reliability In AI Systems: Importance and Maintenance

Areas Where AI Can Be Helpful in Critical Thinking

Personal Action Plan

Course Summary

Post-Course Assessment

Pre- and Post-Course Assessment Answer Key

Pre-Course Assessment

Post-Course Assessment

Assignment Answer Key

Session Two: Introduction to AI

Session Three: Critical Thinking with AI

Session Four: Machine Learning and Algorithms

Session Five: Advanced Ethics and AI Safety