Artificial intelligence is a fascinating topic, and there are several different categories of AI literature to choose from: fiction, nonfiction, and technical books.
Our favorite Artificial Intelligence authors
Posing the question ‘how can I understand AI?’ is nearly as daunting as asking ‘what is the meaning of life?’
- James Vincent
I, Robot
By Isaac AsimovAsimov sets up and knocks down concerns about technology and gives the 21st century reader a welcome reminder that technology is supposed to free us to live life, rather than enslave us.
Neuromancer
By William GibsonA shocking vision that has challenged our assumptions about technology and ourselves, reinvented the way we speak and think, and forever altered the landscape of our imaginations.
Midnight Robber
By Nalo HopkinsonIt's Carnival time and the Caribbean-colonized planet of Toussaint is celebrating with music, dance, and pageantry. Masked "Midnight Robbers" waylay revelers with brandished weapons and spellbinding words.
Robopocalypse
By Daniel H. WilsonControlled by a childlike—yet massively powerful—artificial intelligence known as Archos, the global network of machines on which our world has grown dependent suddenly becomes an implacable, deadly foe.
The Master Algorithm
By Pedro DomingosPedro Domingos assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.
You Look Like a Thing and I Love You
By Janelle ShaneIn this smart, often hilarious introduction to the most interesting science of our time, Janelle Shane shows how these programs learn, fail, and adapt—and how they reflect the best and worst of humanity.
The Alignment Problem: Machine Learning and Human Values
By Brian Christian
A book examining the necessity of aligning the purpose of machines with our own purpose, and the book examines the different projects and methods that have taken place in order to best align these purposes.
The Singularity is Near
By Ray KurzweilRay Kurzweil examines the union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.
Race After Technology
By Ruha BenjaminLearn about the dangerous implications of AI built in a society that favors whiteness.
Deep Learning
By Ian Goodfellow, Yoshua Bengio and Aaron CourvilleDeep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts.
Reinforcement Learning
By Richard S. Sutton and Andrew G. BartoRichard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Foundations of Statistical Natural Language Processing
By Christopher ManningThis foundational text provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations.
Python Machine Learning
By Wei-Meng LeePython makes machine learning easy for beginners and experienced developers. There is no better time to learn machine learning using Python. Machine learning tasks that once required enormous processing power are now possible on desktop machines.
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