5 Great AI books to read in 2020

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Artificial intelligence (AI) has expanded into one of the most important technologies in human history. It comes with so many benefits, from improving the efficiency of simple, basic tasks to helping to solve advanced problems by quickly analyzing large data sets.

As such, AI is being used in a wide range of industries. Examples include Netflix recommendation engines to help you choose your next series indulgence, to chatbots that help you find information quickly without waiting for an agent to help.

With this in mind, it’s important to understand what AI is so you get a better grasp on how modern technology works.

So, no matter if you’re new to the subject or you’re an expert in artificial intelligence, here are 5 great AI books to read in 2020 that will help you start thinking deeper and improve your overall understanding.

1. Rebooting AI: Building Artificial Intelligence We Can Trust Gary; Marcus and Ernest Davis

This first AI book to read addresses the and concerns about implementing AI into society and business, particularly with the use of deep learning and big data.

AI is a very powerful tool. However, if it is to be trusted, it must be able to explain itself to us, understand the world in which it exists and understand the consequences of its actions. These criteria are what Marcus and Ernest Davis describe as deep understanding and is a subject that scientists must consider more as the technology advances.


Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence.

2. Thinking, Fast And Slow; Daniel Kahneman

Nobel laureate Daniel Kahneman studied why and how humans make decisions. This book is an account of their findings. How you may think we come to rational decisions may not come about using such logical processes.

AI cannot replicate irrationality. That said, there is still an awful lot to learn about human psychology that it will be interesting to see if AI at least comes close.


Why is there more chance we'll believe something if it's in a bold typeface? Why are judges more likely to deny parole before lunch? Why do we assume a good-looking person will be more competent? The answer lies in the two ways we make choices: fast, intuitive thinking, and slow, rational thinking. This book reveals how our minds are tripped up by error and prejudice (even when we think we are being logical), and gives you practical techniques for slower, smarter thinking. It will enable you to make better decisions at work, at home, and in everything you do.

3. The Feeling Of What Happens: Body And Emotion In The Making Of Consciousness; Antonio Damasio

This next great AI book to read in 2020 delves into the realms of neuroscience. Damasio describes the relationships between the mind, feelings and emotions. It’s worth looking at this because if AI can learn to feel emotions, how can they be considered different than humans? It’s a fascinating subject.

Of course, it’s unlikely that machines will develop consciousness any time soon, but reading Damasio’s book will have you wonder what it really means to be human.


At its core, human consciousness is awareness of the feeling, experiencing self, the 'very thought of' oneself. Brilliantly wide-ranging in his scope, leading expert on the neurophysiology of emotions Antonio Damasio illustrates his thesis with fascinating and illuminating neurological case studies that are both stimulating and provocative.

4. The Age of Surveillance Capitalism: The Fight For A Human Future At The New Frontier Of Power; Shoshana Zuboff

Next up on this list of best AI books to read in 2020 addresses many people’s fear: living in the age of robots and AI. Now, it can be argued that current technology poses just as much as a threat to the future - and this book shows how injustice and inequality are promoted by computer technology.

Considering what’s been going on all over the world in recent times, this AI book has more meaning than ever. Every citizen, including digital scientists, have a responsibility to ensure this does not happen now and ever again.


The challenges to humanity posed by the digital future, the first detailed examination of the unprecedented form of power called "surveillance capitalism," and the quest by powerful corporations to predict and control us. The heady optimism of the Internet's early days is gone. Technologies that were meant to liberate us have deepened inequality and stoked divisions. Tech companies gather our information online and sell it to the highest bidder, whether government or retailer. Profits now depend not only on predicting our behaviour but modifying it too. How will this fusion of capitalism and the digital shape our values and define our future?

5. HAL’s Legacy: 2001’s Computer As Dream And Reality; Davis G. Stork

It’s always good to look at the past. HAL’s Legacy is a review of HAL 9000 in 2001: A Space Odyssey. This may have been a science fiction novel, but considering the time of its release, Arthur C. Clarke’s imagination did a remarkable job at depicting future AI.

Stork’s book is a comparison of HAL 9000 and artificial intelligence in twenty years’ time.

One of HAL’s main flaws is exactly what modern AI still lacks: it was not able to understand the consequences of its actions. For now, this is a key distinction between human and machine, but who knows what will happen in the future?


Inspired by HAL's self-proclaimed birth date, HAL's Legacy reflects upon science fiction's most famous computer and explores the relationship between science fantasy and technological fact. The informative, nontechnical chapters written especially for this book describe many of the areas of computer science critical to the design of intelligent machines, discuss whether scientists in the 1960s were accurate about the prospects for advancement in their fields, and look at how HAL has influenced scientific research.