Here are 100 books that All-in On AI fans have personally recommended if you like
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As a professional statistician, I am naturally interested in AI and data science. However, in our current information age, everyone, in all segments of society, needs to understand the basics of AI and data science. These basics include such things as what these disciplines are, what they can contribute to society, and perhaps most importantly, what can go wrong. However, I have found that much of the literature on these topics is highly technical and beyond the reach of most readers. These books are specifically selected because they are readable by virtually everyone, and yet convey the key concepts needed to be data-literate in the 21st century. Enjoy!
A “Black Swan” is a highly unlikely event that occurs with massive consequences. Think of 9/11 or the astonishing success of Google or Amazon.
The main issue relative to Black Swans, as explained by Talib, is that after the fact people are drawn to concocting detailed explanations that make them seem less random, and more predictable. In other words, people develop causal explanations that are completely wrong, but sound reasonable, and will then use them to predict the future.
In the words of Nate Silver, they invent a “signal” to explain what is in reality “noise.” These explanations also create a false sense of security about our ability to predict future events. In short, we fool ourselves into thinking that we know more than we actually do.
The most influential book of the past seventy-five years: a groundbreaking exploration of everything we know about what we don’t know, now with a new section called “On Robustness and Fragility.”
A black swan is a highly improbable event with three principal characteristics: It is unpredictable; it carries a massive impact; and, after the fact, we concoct an explanation that makes it appear less random, and more predictable, than it was. The astonishing success of Google was a black swan; so was 9/11. For Nassim Nicholas Taleb, black swans underlie almost everything about our world, from the rise of religions…
I’m a mathematics professor who ended up writing the internationally bestselling novel The Death of Vishnu (along with two follow-ups) and became better known as an author. For the past decade and a half, I’ve been using my storytelling skills to make mathematics more accessible (and enjoyable!) to a broad audience. Being a novelist has helped me look at mathematics in a new light, and realize the subject is not so much about the calculations feared by so many, but rather, about ideas. We can all enjoy such ideas, and thereby learn to understand, appreciate, and even love math.
A primary reason to love math is because of its usefulness. This book shows two sides of math’s applicability, since it is so ubiquitously used in various algorithms.
On the one hand, such usage can be good, because statistical inferences can make our life easier and enrich it. On the other, when these are not properly designed or monitored, it can lead to catastrophic consequences. Mathematics is a powerful force, as powerful as wind or fire, and needs to be harnessed just as carefully.
Cathy O’Neil’s message in this book spoke deeply to me, reminding me that I need to be always vigilant about the subject I love not being deployed carelessly.
'A manual for the 21st-century citizen... accessible, refreshingly critical, relevant and urgent' - Financial Times
'Fascinating and deeply disturbing' - Yuval Noah Harari, Guardian Books of the Year
In this New York Times bestseller, Cathy O'Neil, one of the first champions of algorithmic accountability, sounds an alarm on the mathematical models that pervade modern life -- and threaten to rip apart our social fabric.
We live in the age of the algorithm. Increasingly, the decisions that affect our lives - where we go to school, whether we get a loan, how much we pay for insurance - are being made…
As a professional statistician, I am naturally interested in AI and data science. However, in our current information age, everyone, in all segments of society, needs to understand the basics of AI and data science. These basics include such things as what these disciplines are, what they can contribute to society, and perhaps most importantly, what can go wrong. However, I have found that much of the literature on these topics is highly technical and beyond the reach of most readers. These books are specifically selected because they are readable by virtually everyone, and yet convey the key concepts needed to be data-literate in the 21st century. Enjoy!
This book, by Nate Silver of 538 fame, explains in a straightforward manner why so many predictions by “experts,” from weather forecasts to sports outcomes to election polling to economics, ultimately prove wrong.
It relates to understanding the “signal,” the underlying science that is often revealed through trends and patterns in data, relative to the “noise,” the random or unpredictable variations always present in data. Silver also explains the concept of conditional probability, probability when provided with some relevant information, in an unusually clear manner.
The book reads more like a casual conversation with the author, rather than a statistics textbook.
UPDATED FOR 2020 WITH A NEW PREFACE BY NATE SILVER
"One of the more momentous books of the decade." —The New York Times Book Review
Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight.
Drawing on his own groundbreaking work, Silver examines the world of prediction,…
As a professional statistician, I am naturally interested in AI and data science. However, in our current information age, everyone, in all segments of society, needs to understand the basics of AI and data science. These basics include such things as what these disciplines are, what they can contribute to society, and perhaps most importantly, what can go wrong. However, I have found that much of the literature on these topics is highly technical and beyond the reach of most readers. These books are specifically selected because they are readable by virtually everyone, and yet convey the key concepts needed to be data-literate in the 21st century. Enjoy!
This book goes beyond the hype of data science, the details of machine learning methods, and the coding so closely associated with data science. Rather, it emphasizes the real types of problems for which data science may help, and explains the practical issues (“the real work”) that often lead to failure in data science projects.
These issues tend to be overlooked in more technical presentations of data science. They include such critical considerations as defining the right problem to begin with, understanding the “pedigree” (background and quality) of any data used, and ensuring that the right people are involved from the start.
The essential guide for data scientists and for leaders who must get more from their data science teams
The Economist boldly claims that data are now "the world's most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a…
I fell in love with technology when I wrote my first computer program at age 14 when there was no public Internet, no personal computers, no iPhone, no cloud. I have made technical contributions to every era of computing from mainframes, to PCs, Internet, Cloud, and now AI. I was recently elected to the National Academy of Engineering. AI currently surpasses my wildest imagination on the art of what’s possible. I'm still passionately working in technology at Google focused on how to live healthier lives. I believe we can make AI the telescope of the future, to helping everyone live long and healthy lives.
This book explores how AI is transforming healthcare and the potential benefits it can bring to patients and doctors.
The author, Eric, is a cardiologist with working knowledge of technology of AI. I love how he describes with clarity, the present and potential to make people healthier with AI First thinking. That is, how AI can make the business of health care human.
I love the premise and basis of Eric’ thinking that we can make healthcare personalized, proactive, anticipatory, helping people live healthier lives and reducing the cost of healthcare.
At the same time he is mindful that AI could be used to dehumanize healthcare and exacerbate existing inequalities.
A visit to a physician these days is cold: physicians spend most of their time typing at computers, making minimal eye contact. Appointments generally last only a few minutes, with scarce time for the doctor to connect to a patient's story, or explain how and why different procedures and treatments might be undertaken. As a result, errors abound: indeed, misdiagnosis is the fourth-leading cause of death in the United States, trailing only heart disease, cancer, and stroke. This is because, despite having access to more resources than ever, doctors are vulnerable not just to the economic demand to see more…
I have worked in the field of machine learning and predictive analytics for many years. Having started out as a technical specialist, I have become increasingly interested in the legal, ethical, and social aspects of these subjects. This is because it is these “soft issues” that often determine how successful these technologies are in practice and if they are viewed as a force for good or evil in wider society. This has led me to write several books focusing on the practical and cultural aspects of these subjects and how best to apply them for the benefit of business, individuals, and wider society.
Many writers have discussed the dangers that artificial intelligence and machine learning represent to our livelihoods, and how clever computers and autonomous robots will supplant us all in the workplace. What I like about this book is that it provides an alternative, and very optimistic, view of how these new technologies are being deployed. The authors present a future based on a partnership, in which artificial intelligence-based tools work in tandem with human workers, enhancing what individuals can do in the workplace rather than replacing them.
AI is radically transforming business. Are you ready?
Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on?
In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show…
I fell in love with technology when I wrote my first computer program at age 14 when there was no public Internet, no personal computers, no iPhone, no cloud. I have made technical contributions to every era of computing from mainframes, to PCs, Internet, Cloud, and now AI. I was recently elected to the National Academy of Engineering. AI currently surpasses my wildest imagination on the art of what’s possible. I'm still passionately working in technology at Google focused on how to live healthier lives. I believe we can make AI the telescope of the future, to helping everyone live long and healthy lives.
Parag is a clinician who covers the current and future state for using AI in several healthcare specialties like cardiology, pharmacy, orthopedics, radiology, and many more.
This is a book for generalists who want to understand how AI applies to a variety of medical disciplines. I enjoyed this book because it deepened my knowledge as an AI technologist on how to apply AI in areas of healthcare from the lens of a physician.
I am an economist who came to realize that the marketplace of ideas was a political doctrine, and not an empirical description of how we came to know what we think we know. Science has never functioned in the same manner across centuries; it was only during my lifetime that it became recast as a subset of market reality. I have spent a fair amount of effort exploring how economics sought to attain the status of a science; but now the tables have turned. It is now scientists who are trained to become first and foremost market actors, finally elevating the political dominance of the economists.
Edwards revealed how the very architecture of early computers owed a debt to the political structures of the Cold War. The innovation of a command/control/information infrastructure set the template for military regimentation, and subsequently for the surveillance society we currently inhabit. The story of how cybernetics—a field that never quite made the grade as pure science—nevertheless conquered the culture, is fascinating.
The Closed World offers a radically new alternative to the canonical histories of computers and cognitive science. Arguing that we can make sense of computers as tools only when we simultaneously grasp their roles as metaphors and political icons, Paul Edwards shows how Cold War social and cultural contexts shaped emerging computer technology―and were transformed, in turn, by information machines.
The Closed World explores three apparently disparate histories―the history of American global power, the history of computing machines, and the history of subjectivity in science and culture―through the lens of the American political imagination. In the process, it reveals intimate…
I’ve wanted to be a philosopher since I read Plato’s Phaedo when I was 17, a new immigrant in Canada. Since then, I’ve been fascinated with time, space, and quantum mechanics and involved in the great debates about their mysteries. I saw probability coming into play more and more in curious roles both in the sciences and in practical life. These five books led me on an exciting journey into the history of probability, the meaning of risk, and the use of probability to assess the possibility of harm. I was gripped, entertained, illuminated, and often amazed at what I was discovering.
I am laughing out loud, even now that I am rereading this book for the umpteenth time. Fraudsters are so clever, and so is advertising. And then there is sloppy journalism with its “wow” statistics.
I like his book enormously, not least because of its witty illustrations. It is subversive, comic, and provocative, and it makes me wise to seductive, misleading practices–and it does so with a light touch.
From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff's lively and engaging primer clarifies the basic principles of statistics and explains how they're used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.
I’ve always loved science fiction because it offers a hope, a dream, or a future that we just haven't seen yet. When I write my stories, I feel there is no better use of my imagination, than to contemplate a new world, a new civilization, or future technology. At the same time, I hope to entertain readers and spark young imaginations. Inside Modified, I reached into a distant future with off-world colonies that float in the clouds of Venus, while robots toil on the planet’s surface. Of course, in such a future, when advanced modifications and recursive designs are used, leads one to wonder if my robot can love too.
This book seems a bit strange at first, when the story begins with Moon-Watcher, the leader of a tribe of early ape-man, who struggles for survival during the brutal Pleistocene ice age. After an alien monolith appears, it seems to advance the way he thinks, leading him to develop crude weapons. When the same monolith is discovered in the future, we seem fated to find the answers behind the eerie structure. Skipping to a team of astronauts who travel aboard a ship to further investigate, things take an unexpected turn when the ship’s A.I. called HAL-9000, gets very confused about keeping secrets. Something about the way it remains so polite while it deceives the crew, is enough to give anyone a nightmare.
Written when landing on the moon was still a dream, and made into one of the most influential films of all time, 2001: A SPACE ODYSSEY remains a classic work of science fiction fifty years after its original publication.
The discovery of a black monolith on the moon leads to a manned expedition deep into the solar system, in the hope of establishing contact with an alien intelligence. Yet long before the crew can reach their destination, the voyage descends into disaster . . .
Brilliant, compulsive and prophetic, Arthur C. Clarke's timeless novel tackles the enduring theme of mankind's…
