Are you still searching for the right reading material for next year? Choosing a book can be very subjective, and it’s easy to make the wrong choice. Perhaps something useful on artificial intelligence (AI)? It would be great to finally understand the hype around AI to join the conversation and invest in the future. But you want something engaging without too much math? Walking into a bookstore or searching online can be overwhelming due to the sheer number of books available.
Here are five recommendations: a fictional biography, a new type of atlas, an interactive book for learning and experimenting, a book on the math of AI understandable to non-mathematicians, and a classic for those who want to know everything in detail.
How It All Began: Maniac
BenjamÃn Labatut, Maniac
Let’s start with context and history: The AI era didn’t begin with ChatGPT. The connection between AI, mathematical logic, military research, the atomic bomb, the Cold War, and game theory is less known. In “Maniac,” BenjamÃn Labatut weaves these themes into a fictional biography of John von Neumann, the inventor of modern computer architecture. The book takes you on a journey through recent history, ending with the duel between human and machine: the Korean Go champion Lee Sedol versus AI AlphaGo.
The Environment: Atlas of AI
Kate Crawford, Atlas of AI
If you’re interested in the impact of modern AI and want to see beyond the tech industry’s promises, this book is essential. Kate Crawford reveals that AI is more than just a miraculous and intangible form of machine intelligence. In “Atlas of AI,” we learn about the tangible, material side of the AI industry: from lithium mines to data preparation factories in the global south, automated workplaces, vast data archives, AI training camps, and the Pentagon’s algorithmic warfare team. According to Crawford, AI is primarily an “extraction technology,” profiting from minerals, cheap labor, and vast amounts of data.
The Mathematics: Why Machines Learn
Anil Ananthaswamy, Why Machines Learn
If you want to know how machine learning works, this book is highly recommended. Yes, it involves math, but it’s relatively simple. Anil Ananthaswamy repeats concepts from different perspectives, helping you understand why and how machines learn.
Learning Through Play: Understanding Artificial Intelligence
Pit Noack, Sophia Sanner, Understanding Artificial Intelligence
What happens when an artist, musician, and software developer writes a book on AI basics? You get a book that’s far from boring, despite the technical subject. The engaging texts, cartoons, and infographics by Sophia Sanner are complemented by numerous online example programs. You can experiment with different methods, see how simple scripts piece together texts, and explore what language models do when you tweak their parameters.
The Textbook: AI, A Modern Approach
Peter Norvig, Stuart Russell, Artificial Intelligence, A Modern Approach
The textbook by Norvig and Russell may seem intimidating with its 1,000 pages, but it covers much more than machine learning and neural networks. It starts with search algorithms, as search is also AI. Now, it begins with agents, but it also covers AI history and ethical questions. This comprehensive work is a widely cited university textbook.