Automate This

Algorithms are transforming industries and professions at an accelerating pace, from Wall Street trading to medical diagnosis. In Automate This, Christopher Steiner traces the rise of algorithmic automation through key developments and personalities in technology, finance, and beyond. The book examines early breakthroughs in automation, including the first trading algorithms that changed Wall Street forever. Through interviews and research, Steiner documents how algorithms spread from finance into music composition, sports analytics, journalism, and healthcare. The narrative tracks both the technological advances and human impact as automation reshapes the professional landscape. Steiner explores what these changes mean for workers, companies, and society as algorithms take on increasingly complex tasks. This exploration of automation serves as a window into humanity's evolving relationship with artificial intelligence and machine learning. The book raises questions about the future of human expertise and creativity in an algorithmic world.

Readers describe the book as an accessible introduction to algorithmic automation, though many note it focuses more on finance and trading than the title suggests. Readers appreciated: - Clear explanations of complex concepts - Engaging storytelling and real-world examples - Historical context of automation development - Discussion of societal implications Common criticisms: - Too much emphasis on Wall Street/trading algorithms - Lacks technical depth - Becomes repetitive in later chapters - Some examples feel dated - Limited coverage of modern AI applications One reader noted: "The first half fascinated me but it lost steam discussing trading algorithms." Another commented: "Good primer for non-technical readers, but experts won't find new insights." Ratings: Goodreads: 3.8/5 (2,900+ ratings) Amazon: 4.2/5 (180+ ratings) Audible: 4.0/5 (300+ ratings) Several readers recommended the book for beginners interested in automation's impact on society, while those seeking technical details should look elsewhere.

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🔹 The book traces modern algorithmic trading back to Thomas Peterffy, who in the 1970s used early computers to generate more accurate options pricing sheets than traditional traders - leading to initial resistance but eventual transformation of Wall Street 🔹 Author Christopher Steiner was previously a technology staff writer at Forbes and holds a degree in civil engineering from the University of Illinois 🔹 The algorithms discussed in the book have expanded far beyond finance - they now compose music, write news articles, diagnose patients, and even predict hit songs with remarkable accuracy 🔹 One of the book's key examples is an algorithm developed by hedge fund manager David E. Shaw that detected price discrepancies between bonds and the underlying stocks they could be converted into - generating millions in profits 🔹 The book describes how a computer algorithm named "Bot Dylan" can analyze popular songs throughout history and predict with 85% accuracy whether a song will become a hit, based on mathematical patterns in the music