AiLab Reading List

  • Navigating & learning Artificial Intelligence
  • Twitter: @_AiLab

Knowing which reading material to choose to learn more about Artificial Intelligence can be difficult due to the range and scope of brilliant resources available. That’s why we’ve created a list of AiLab reading recommendations.

Our list includes introductory subjects in AI (such as neural networks), as well as subject matter focused around philosophy and biology – which relate closely to current problems being tackled within the field of AI.

This is by no means a comprehensive list of suitable reading material, but it should provide a good introduction. We’re always on the lookout for exceptional books, papers and journals, so if you have any recommendations please get in touch and let us know about your favourites (or drop us a message on twitter: @_AiLab).

Artificial Intelligence

  • Prediction Machines: The Simple Economics of Artificial Intelligence, Ajay Agrawal, Joshua Gans and Avi Goldfarb, (2018), Harvard Business Review Press Beginner
  • Top Pick Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig, (2016), 3rd Edition, Pearson Beginner
  • Superintelligence: Paths, Dangers, Strategies, Nick Bostrom, (2016), Oxford University Press Beginner
  • Surviving AI: The Promise and Peril of Artificial Intelligence, Callum Chace, (2015), Three Cs Beginner
  • Artificial Intelligence: Structures and Strategies for Complex Problem Solving, George Luger, (2008), 6th Edition, Pearson Beginner
  • Artificial Intelligence, Rob Callan, (2003), Palgrave Beginner
  • Artificial Intelligence (Handbook Of Perception And Cognition), Margaret A. Boden, (1996), Academic Press Beginner

Machine Learning

  • Make Your Own Neural Network, Tariq Rashid, (2016), CreateSpace Beginner
  • Top Pick Deep Learning, Ian Goodfellow, Yoshua Bengio and Aaron Courville, (2016), The MIT Press Advanced
  • The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, Pedro Domingos, (2015), Basic Books Beginner
  • Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks, Russell Reed and Robert Marks II, (1999), MIT Press Intermediate
  • The Essence of Neural Networks, Rob Callan, (1998), Prentice Hall Beginner
  • An Introduction To Neural Networks, James Anderson, (1995), MIT Press Beginner
  • Associative Engines: Connectionism, Concepts, and Representational Change, Andy Clark, (1993), MIT Press Advanced

Brains & Minds (Cognition)

  • The Book of Why: The New Science of Cause and Effect, Judea Pearl, (2018), Basic Books Intermediate
  • How to Create a Mind: The Secret of Human Thought Revealed, Ray Kurzweil, (2014), Duckworth Overlook Intermediate
  • How the Mind Works, Steven Pinker, (2009), W. W. Norton & Company Beginner
  • The Stuff of Thought: Language as a Window into Human Nature, Steven Pinker, (2005), Penguin Books Beginner
  • Mind: A Brief Introduction, John Searle, (2005), Oxford University Press Beginner
  • The Emperor's New Mind: Concerning Computers, Minds and the Laws of Physics, Roger Penrose and Martin Gardner, (2002), Oxford University Press Intermediate
  • Top Pick Minds, Brains, and Computers: An Historical Introduction to the Foundations of Cognitive Science, Eds: Robert Harnish and Denise Cummins, (1999), Wiley-Blackwell Beginner
  • The Conscious Mind: In Search of a Fundamental Theory, David Chalmers, (1997), Oxford University Press Intermediate
  • Kinds Of Minds: Toward An Understanding Of Consciousness, Daniel Dennett, (1997), Basic Books Intermediate
  • Connectionism and cognitive architecture: A critical analysis, Jerry Fodor and Zenon Pylyshyn, (1988), In: Pinker, S and Mehler, J., (Eds), Connections and Symbols, pp3-71, MIT Press, Cambridge, MA. Advanced
  • Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol 1: Foundations, David Rumelhart and James McClelland, (1986), MIT Press, Cambridge, MA. Advanced
  • Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol 2: Psychological and Biological Models, David Rumelhart and James McClelland, (1986), MIT Press, Cambridge, MA. Advanced


  • Top Pick The Language Instinct, Steven Pinker, (2007), Harper Perennial Beginner
  • Understanding Natural Language, Terry Winograd, (1972), Academic Press Intermediate

Science Fiction

  • The Complete Robot, Isaac Asimov, (2018), HarperCollins. [Complete collection of Asimov's Robot stories] Beginner
  • Speak, Louisa Hall, (2015), Ecco Beginner
  • Do Androids Dream of Electric Sheep?, Philip Dick, (1968), Doubleday Beginner
  • 2001: A Space Odyssey, Arthur C. Clarke, (1968), Hutchinson Beginner
  • Top Pick I, Robot, Isaac Asimov, (1950), Gnome Press. [Also In: The Complete Robot] Beginner