The Illusion Engine

The Quest for Machine Consciousness

What does it mean for a machine to think? Can an artificial intelligence system ever experience the world as we do? The Illusion Engine: The Quest for Machine Consciousness explores these deep questions at the intersection of philosophy, neuroscience, and artificial intelligence.

If you’ve ever wondered…

  • Can a machine be conscious, or is it all illusion?
  • Is subjective experience reducible to neural computation?
  • What can philosophical thought experiments tell us about AI?
  • What can AI engineering and neural network architectures tell us about philosophy?

…this book is for you.

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Whether you’re a philosopher, AI researcher, student, or simply curious about the nature of consciousness in the age of machines, The Illusion Engine: The Quest for Machine Consciousness offers a deeply engaging and intellectually rigorous exploration.

For a draft version for research perusal, please contact me.

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Table of Contents

1

Introduction

2

The Mind and the Body

3

Let’s Get Physical

4

Cybernetics

5

Artificial General Intelligence

6

The Imitation Game

7

Computation

8

Neural Networks and Machine Learning

9

Deep Learning

10

Large Language Models

11

Consciousness

12

Hallucinations

13

Machine Consciousness

14

Explaining AI

15

Quantum Minds

16

Artificial Minds, Human Ethics

17

Hard Problem of Consciousnesses

  • About the Author

Kristina Šekrst is a researcher and engineer working at the crossroads of logic, artificial intelligence, and cognitive science. With a Ph.D. in logic and a background spanning philosophy, linguistics, and computer science, she explores questions about mind, meaning, and machine cognition – particularly how artificial systems process language, reason, and simulate thought.

Her interests include the philosophy of mind and language, cognitive modeling, explainable AI, and astrobiology. In industry, Kristina serves as a principal software engineer and was part of the team that first identified prompt injection vulnerabilities in large language models. She continues to apply her technical skills to practical and ethical challenges in AI. Bringing together theory and practice, Kristina works to better understand the foundations of intelligence – both human and artificial.