Though nowhere near as well known as the other John of Princeton's mathematics department, John Nash (and there are many more noted Johns in the field and department for sure), Conway's contributions might end up being significantly more impactful societally and definitely deeper mathematically. This book does a good job explaining the subject areas he worked in, mostly discrete mathematics, with strong combinatorial motivations, and bring visibility to his little-known private life, which he was hesitant to reveal. There's some tragedy to reading the text now, as although Conway still lives, he has been suffering from ill-health recently, which had manifested themselves more profoundly around the time this book was being written.
Like Nash, Conway did revolutionize a field called "Game Theory", more specifically, what is now known as combinatorial game theory, which as very little to do with the "Game Theory" of Economics that Nash's thesis touched. Though in this case, these works may end up influencing humanity much deeper and more directly through their contributions to AI, than the notion of the Nash Equilibrium, which however novel or clear from an academic sense, seems to be mostly a meaningless concept in either the practice of economics, or as a model of actual human behavior. Ironically, the notion is more relevant in application towards machine decision processes, like resource allocations within servers, than they are towards their original motivating problem. Besides that extra strange tidbit, the two seem totally different. Whereas John Nash could be characterized as a clean-cut square in his youth, Conway seems to have been a free-wheeling thinker with a mind far more open and accepting, especially in the social domains. His seminal work on the "Game of Life" which was done entirely with pen and paper, has gone on to propel the notion of cellular automata on the map, and has influenced works from a very wide swath of fields from computer scientist and applied mathematician Stephen Wolfram to late Nobel laureate Thomas Schelling.
Probably the first agent-based model built and conceived of, one also sees the kernels of the formalism of Markov Decision Processes and other subjects that would inform the current work on Reinforcement Learning as well. So in a real sense, simulations, robotics, machine learning, AI, and computational and synthetic biology, and social sciences owe a tremendous debt to what Conway started. Yet, one discovers in the text, it is the discovery he is least fond of, given that is has crowded out attention from his other works, which he believes are more impactful.
The book covers many of these as well. Including his contribution towards the classification of finite simple groups in algebra, a generational enterprise of which he is considered one of the central drivers. Yet, even in this endeavor, Conway is disappointed in the work, as he believes the classification, though correct, has failed to impart any deeper understanding of what this structure means, or why it exists. Here Conway makes a distinction between the technical process of "verifying" existence and understanding it, with his emphasis on the later. It is his opinion that mathematicians should seek to understand more and verifying is less important in this respect. Though not stated explicitly in the text, it would seem Conway might find sympathies among the constructivist school of thought in mathematics given these opinions.
This leads to another observation, Conways work has touched many of the subject matters in the field of mathematics, from including some logic with his work on surreal number system, that led toward the "arithmetic" of games, algebra, number theory, computing, and even in his later years, applied mathematical work in the foundations of Quantum Mechanics. Though many of his contributions are currently under-appreciated within these professions, it is likely their impact will grow as time progresses and connections are made to his findings with current interests in these respective fields.
Besides an overview of his technical works, the book also dedicates much to his personal life and behavioral peccadillos. Conway has been thrice married, with numerous flings, has 5 children, with a few of them also becoming mathematicians, and seems to have an egalitarian view on mathematics education. He believes most people could achieve his type of work if they were given the right teaching and mentoring experience, and Conway follows up this belief with long contributions to high school and collegiate math camps and enrichment programs. He put real action to those ideals.
What we get is a portrait of a singular individual, who though socially obtuse (purposefully), was indeed still a human being with ideas and is relatable. His relatability and capability of human connection also probably accounts for the wide net of his works. As another thing that is clear from this text is beside his deep individual contributions, he was at the center or and promoted the collaboration of many other mathematicians. Ultimately it maybe this trait that will probably give Conway's legacy a longer and greater legacy relative to other accomplished mathematicians who were either too pompous or socially incapable to collaborate well within their careers.
Overall a great read on a person more people should look into, and who has important works, some of which are fairly accessible to the general reader. Highly recommended