Foundations of AI: Bridging Mind, Brain and Machine

Strategic, non-technical guide to AI’s limits and potential. Master critical thinking about the nature of AI.

What you’ll learn
Distinguish between “Smart” and “Conscious”: Critically analyse whether AI is truly intelligent or just an advanced simulation.
Debate the “Hard Problem” of AI: Can machines ever feel emotions or possess a subjective “inner life”?
Navigate the Ethical Landscape: Assess who is responsible when AI fails and explore the profound implications of machine autonomy and free will.
Understand the “Blueprint” of Thinking: Compare how the human mind works vs. how AI systems are built, exploring the architectures used to mimic the brain.
Deconstruct AI Perception: Learn how machines “see” the world compared to humans, and why simple visual tasks for us are massive challenges for computers.
Identify AI’s Strengths & Blindspots: Use insights from cognitive science to see why AI models excel at patterns but struggle with common sense and meaning.

Requirements
No programming or technical experience required: You do not need to know how to code, and there is no advanced mathematics involved.
No prior background in AI or Neuroscience needed: We will start from the very beginning, defining every concept clearly as we go.
Just bring your curiosity: The only requirement is openness to abstract reasoning, conceptual discussions and a willingness to explore deep questions about the nature of intelligence, consciousness, and the future of humanity.

Description
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.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.

Who this course is for
Curious individuals who want to move beyond the media hype and understand the true philosophical and scientific foundations of Artificial Intelligence.
Managers, policy-makers, and writers who need a realistic, conceptual understanding of AI’s capabilities and limitations to make informed decisions without getting lost in technical jargon.
Students of psychology, philosophy, cognitve science and neuroscience who want to see how their knowledge of the human mind is being used to build modern AI systems.
Tech-adjacent professionals who want to understand the ‘blueprint’ of intelligent systems, like Neural Networks and Cognitive Architectures, but do not have a background in mathematics or programming.

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