Artificial Intelligence is transforming our world, but it is also surrounded by confusion and hype. Behind the headlines lie deep, unanswered questions: What does it really mean to be intelligent? Can a machine ever truly "understand"? And who is responsible when an autonomous system makes a mistake?

This course takes you beyond the buzzwords. It offers a clear, non-technical exploration of the philosophical, cognitive, and neuroscientific foundations of AI. By bridging the gap between the biological brain and silicon machines, you will gain the critical thinking skills to assess what today’s systems can and cannot do.

In this course you will:

• Cut Through the "Sentience" Hype: Instead of just asking "what a mind is," learn to critically evaluate the claims behind the headlines. You will explore the "Hard Problem" of consciousness to distinguish between a machine that truly feels versus one that is just an excellent simulator.

• Navigate the Ethics of Automation: Move beyond theory to the real-world impact of AI decision-making. We will examine the difficult questions leaders must answer: Who is responsible when an autonomous system fails? And how do we keep meaningful human control over powerful algorithms?

• Decode the "Black Box" of Intelligence: Understand the two main blueprints for building a mind: the logical, rule-based approach (Symbolic AI) versus the pattern-matching approach (Neural Networks). You will see why modern AI excels at learning from data but often lacks the common sense reasoning of the older systems.

• See the World Through Machine Eyes: Discover how machines "see" by comparing them to the ultimate vision system: the human brain. By tracing the path from raw data to meaningful perception, you will understand exactly why computer vision systems are powerful yet vulnerable to mistakes that humans would never make.

• Assess the Path to General Intelligence (AGI): Look ahead to the next wave of AI. We will explore "Hybrid" architectures that combine logic and learning, a leading approach for overcoming current limitations and potentially achieving human-level common sense.

Cut Through the "Sentience" Hype: Instead of just asking "what a mind is," learn to critically evaluate the claims behind the headlines. You will explore the "Hard Problem" of consciousness to distinguish between a machine that truly feels versus one that is just an excellent simulator.

Navigate the Ethics of Automation: Move beyond theory to the real-world impact of AI decision-making. We will examine the difficult questions leaders must answer: Who is responsible when an autonomous system fails? And how do we keep meaningful human control over powerful algorithms?

Decode the "Black Box" of Intelligence: Understand the two main blueprints for building a mind: the logical, rule-based approach (Symbolic AI) versus the pattern-matching approach (Neural Networks). You will see why modern AI excels at learning from data but often lacks the common sense reasoning of the older systems.

See the World Through Machine Eyes: Discover how machines "see" by comparing them to the ultimate vision system: the human brain. By tracing the path from raw data to meaningful perception, you will understand exactly why computer vision systems are powerful yet vulnerable to mistakes that humans would never make.

Assess the Path to General Intelligence (AGI): Look ahead to the next wave of AI. We will explore "Hybrid" architectures that combine logic and learning, a leading approach for overcoming current limitations and potentially achieving human-level common sense.

By the end of this course, you will be able to see past the hype and understand the real trade-offs behind today’s AI systems. You will possess the vocabulary to clearly articulate what AI is (and is not), understand the assumptions built into different technologies, and engage confidently in informed discussions about AGI, ethics, and the long-term impact of intelligent machines on society.