Why Machines Will Never Rule the World – Artificial Intelligence Without Fear

1st Edition

Book Description

The 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:

Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system.
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, and biology, 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 most common interactions with AI, for example with our bank’s computers, still so unsatisfactory?　

Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a 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, which are as impossible as AI systems that are intrinsically “evil” or able to “will” a takeover of human society.

Foreword

1. Introduction

1.1 The Singularity

1.2 Approach

1.3 Limits to the modelling of animate nature

1.4 The AI hype cycle

1.5 Why machines will not inherit the earth

1.6 How to read this book

Part I: Properties of the human mind

2. The human mind

2.1 Basic characteristics of the human mind

2.2 The mind-body problem: Monism and its varieties

3. Human and machine intelligence

3.1 Capabilities and dispositions

3.2 Intelligence

3.3 AI and human intelligence

4. The nature of human language

4.1 Why conversation matters

4.2 Aspects of human language

5. The variance and complexity of human language

5.1 Conversations: An overview

5.2 Levels of language production and interpretation

5.3 Conversation contexts

5.4 Discourse economy: implicit meaning

5.5 Structural elements of conversation

5.6 How humans pass the Turing test

6. Social and ethical behaviour

6.1 Can we engineer social capabilities?

6.2 Intersubjectivity

6.3 Social norms

6.4 Moral norms

6.5 Power

Part II: The limits of mathematical models

7. Complex systems

7.1 Models

7.2 Computability

7.3 Systems

7.4 The scope of extended Newtonian mathematics

7.5 Complex systems

7.6 Examples of complex systems

8. Mathematical models of complex systems

8.1 Multivariate distributions

8.2 Deterministic and stochastic computable system models

8.3 Newtonian limits of stochastic models of complex systems

8.4 Descriptive and interpretative models of complex systems

8.5 Predictive models of complex systems

8.6 Naïve approaches to complex system modelling

8.7 Refined approaches

8.8 The future of complex system modelling

Part III: The limits and potential of AI

9. Why there will be no machine intelligence

9.1 Brain emulation and machine evolution

9.2 Intentions and drivenness

9.3 Consciousness

9.4 Philosophy of mind, computation and AI

9.5 Objectifying intelligence and theoretical thinking

10. Why machines will not master human language

10.1 Language as a necessary condition for AGI

10.2 Why machine language production always falls short

10.3 AI conversation emulation

10.4 Mathematical models of human conversations

10.5 Why conversation machines are doomed to fail

11. Why machines will not master social interaction

11.1 No AI emulation of social behaviour

11.2 AI and legal norms

11.3 No machine emulation of morality

12. Digital immortality

12.1 Infinity stones

12.2 What is a mind?

12.3 Transhumanism

12.4 Back to Bostrom

13. AI spring eternal

13.1 AI for non-complex systems

13.2 AI for complex systems

Glossary

13.3 AI boundaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291

13.4 How AI will change the world . . . . . . . . . . . . . . . . . . . 293

Author(s)

Biography

Jobst Landgrebe is a scientist and entrepreneur with a background in philosophy, mathematics, neuroscience, and bioinformatics. Landgrebe is also the founder of Cognotekt, a German AI company which has since 2013 provided working systems used by companies in areas such as insurance claims management, real estate management, and medical billing. After more than 10 years in the AI industry, he has developed an exceptional understanding of the limits and potential of AI in the future.

Barry Smith is one of the most widely cited contemporary philosophers. He has made influential contributions to the foundations of ontology and data science, especially in the biomedical domain. Most recently, his work has led to the creation of an international standard in the ontology field (ISO/IEC 21838), which is the first example of a piece of philosophy that has been subjected to the ISO standardization process.

Reviews

“It’s a highly impressive piece of work that makes a new and vital contribution to the literature on AI and AGI. The rigor and depth with which the authors make their case is compelling, and the range of disciplinary and scientific knowledge they draw upon is particularly remarkable and truly novel.”

Shannon Vallor, Edinburgh Futures Institute, The University of Edinburgh