"In this volume I bring together some of my thinking new and old, on the subject of computers and automation. The old thinking is a description of the computer technology and its implications for management. The new thinking is an analysis of the economic implications of automation . . . . My research activities during the pas decade have brought me into contact with developments in the use of electronic digital computers. These computers are startling even in a world that takes atomic energy and the prospects of space travel in its stride. The computer and the new decision-making techniques associated with it are bringing changes in white-collar, executive, and professional work as momentous as those the introduction of machinery has brought to manual jobs. These essays record the product of my reflections about the organizational and social implications of these rapid technical developments." - Herbert A. Simon in the Preface.
I managed to work through some sections of this academic opinion piece, which republishes a few of the author's essays. The author's research is not laid out here, there are equations but no citations for the reader to follow. It felt like reading notes for a series of lectures, without the accompanying slides and speakers' inflection or pauses that would make it engaging.
The author's work, "The Sciences of the Artificial" is a cited source for the modern day "Design Thinking" fad; I read this book in the hopes that it would build on that work.
This might be entertaining to read in small sections with a group, from a historical perspective, if the group included people from that time period, who could contribute insights into the thinking of the time. For example, did people really take seriously those who suggested that computers would take away all jobs? Was that a credible position, or just out-of-touch academia? Who would fix the computers, mine their minerals, plant crops...? Were the computers going to ask the questions and develop equations, to solve them? Were computers to identify opportunities for improvement, then create the algorithms and plans to solve them? Certainly that is the conceit of many science fiction futures, but I found it difficult to take to heart the opinions attached to such a superficial world view. It is always a challenge to read predictions long after their intended target era, and while I suspect there may be gems and pearls of wisdom buried in this, the work itself did not give me adequate reason to keep digging for them.