The Allure of Mechanical Life: Cybernetics, Artificial Life and the New AI

Citation

Ting, I. (2011), "The Allure of Mechanical Life: Cybernetics, Artificial Life and the New AI", Online Information Review, Vol. 35 No. 4, pp. 683-684. https://doi.org/10.1108/14684521111162007

In The Allure of Mechanical Life Johnston provides a comprehensive survey and history of “machinic life” in its various aspects – cybernetics, artificial life and artificial intelligence. As a young researcher in the area of artificial intelligence (AI), I have enjoyed reading this book to better understand the roadmap of “machinic life” and AI.

The book contains eight chapters organised into three sections. The three chapters in Section 1 range from cybernetics to “machinic philosophy”. Chapter 1 introduces cybernetics and the new complexity of machines. Chapter 2 discusses the mixing of machines, cybernetics and psychoanalysis. In the last chapter in this section the author uses a new term, “machinic philosophy”, to introduce the concept of assemblages, information and chaotic flow.

Although containing only two chapters, section 2 is my favourite part of the book. Chapter 4 presents the techniques of vital cells, which is the base of “machinic life”; issues in this chapter include automata, artificial life and autopoiesis. Many techniques are introduced in this chapter, and it also provides some very interesting examples. Chapter 5 discusses digital evolution and the emergence of complexity. Many interesting topics on artificial life and the concept and techniques of digital evolution are introduced here.

The last section includes three chapters, and the focus shifts from “machinic life” to “machinic intelligence”. Chapter 6 introduces the decoded couple of artificial intelligence and cognitive science. Chapter 7 discusses the new AI; three issues are treated:

1. 1.

   behaviour‐based robotics;

2. 2.

   autonomous agents; and

3. 3.

   artificial evolution.

This chapter is worth reading by those new to AI. In the final chapter the author shares his views on learning from neuroscience and discusses new prospects for building intelligent machines.

All chapters contain references for further reading, and a compilation of the references is also provided in an Appendix. In addition, the book provides a clear and detailed table of contents. I can recommend this book to researchers in AI as well as to those who want to learn more about “machinic life” and “machinic intelligence”.