This book's core argument is that an artificial intelligence that could equal or exceed human intelligence - sometimes called 'artificial general intelligence' (AGI) - is for mathematical reasons impossible. It offers two specific reasons for this claim:

1. Human intelligence is a capability of the human brain and central nervous system, which is a complex dynamic system

2. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer.

In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence from mathematics, physics, computer science, philosophy, linguistics, biology, and anthropology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "Artificial Intelligence" (AI)? And why, after more than 50 years, are our interactions with AI, for example with our bank's computers, still so unsatisfactory?

The First Edition was published the same week that ChatGPT was unleashed onto the world. In this Second Edition, shows how their arguments apply to new Large Language Models and bring up to date their other arguments relating to the limits of AI. They show why AI systems are best viewed as pieces of mathematics, which cannot think, feel, or will. They also demolish the idea that, with the help of AI, we could "solve physics" in a way that would allow us to create, in the cloud, a perfect simulation of reality in which we could enjoy digital immortality. Such ideas reveal a lack of understanding of physics, mathematics, human biology, and computers.

There is still, as they demonstrate in an updated final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, and which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society.

Key Changes to the Second Edition

Shows how the arguments of the First Edition apply also to new Large Language Models

Adds a treatment of human practical intelligence - of knowing how vs. knowing that - a topic that is ignored by the AI community

Demonstrates why "AI ethics" should be relabeled "ethics of human uses of AI"

Adds a new chapter showing the essential limitations of physics, providing a thorough grounding for the arguments of the book

Demolishes the idea that we might already be living in a simulation