Book Review-Artificial Intelligence: A Guide for Thinking Humans By Melanie Mitchell

Ever since the explosion and proliferation of Chatbots in the AI sector, the superlatives and attacks on the idea of using AI have also proliferated. The fictional content of the announcements in social media and specialty media has been mind numbing. I had reached a point of not knowing what I could or could not believe.

I realized that what I needed was not what many are offering, their opinions disguised as informative articles on what AI entails, but a primer on the technologies that the articles are throwing out for public consumption. Many, like me, have become inured to the media content without ever understanding the technology, nor had I ever dug into the granularities which is fundamental to the technologies. I also desired a concise and precise history of how this revolution came about, which is my usual modus operandi when investigating a topic that was new to me. Although one cannot exist in the technology world without having been exposed to AI.

I had fortunately come upon Melanie Mitchell’s book in my endless wanderings in the vast spaces of the bookstore websites. This, was what I needed and wanted. It also didn’t hurt that Mitchell’s credentials are impeccable as far as the AI world is concerned. She did her PhD with the renowned Douglas Hofstadter of the University of Michigan and the authors of Gödel, Escher, Bach. She has created her own AI system as a part of her research. Finally, she has joint appointments at Portland State and the Santa Fe Institute.  

This book gave me everything I wanted; it demystified and explained all the buzzwords presently flying about in conversations about AI. She did so in chronological order, starting with the 1956 workshop organized by John McCarthy, who coined the misleading term Artificial Intelligence,  and held in Dartmouth. She laid out the evolution of AI, diving deep enough into the methods and algorithms of such topics as Symbolic AI, sub-symbolic AI, expert systems, Artificial Neural Network (ANN), Convolutional Neural Network (ConvNet), Deep Learning, Machine Learning, back propagation, large language model (LLM), reinforcement learning, etc.

She also introduced the readers to historical figures like John McCarthy, Marvin Minsky, Claude Shannon, Allen Newell, and Herbert Simon and discussed their contributions to the area. She also contemporary figures like Yann LeCun and Gary Marcus, and their recent contributions to the burgeoning field.

I particularly like the way she interposed history with concise but highly understandable explanations of how the technology evolved and developed, it gave the book a multi-dimensional appeal as each dimension reinforced the other dimensions without seeming chaotic and disorganized. On the contrary, the organization of the book was perfect for a relative novice to gain not only information and knowledge but also insight and understanding. I would highly recommend this book for those who are curious about this thing called AI and wish to be informed, and for those who are curious about the history of the technology and the people who are the historical innovators.