Here are 100 books that The Signal and the Noise 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…
Accurate and precise forecasting is essential for successful planning and policy from economics to epidemiology. We have been keen to understand why so many forecasts turn out to be highly inaccurate since making dreadful forecasts ourselves, and advising UK government agencies (Treasury, Parliament, Bank of England) during turbulent periods. As simple extrapolation often beats model-based forecasting, we have been developing improved methods that draw on the best aspects of both, and have published more than 60 articles and 6 books attracting more than 6000 citations by other scholars. Our recommended books cover a wide range of forecasting methods—suggesting there is no optimal way to look into the future.
This is a book that brings forecasters down to earth with a bang – we are not all super-forecasters! There is no magic involved in forecasting – seeing into the future is impossible. But Tetlock and Gardner show that good decision-making should be based on a set of guidelines that can be adapted to any situation. The writing is slick, given one of the authors is a science journalist, and it provides salutary reading for any would be practical forecaster.
'A manual for thinking clearly in an uncertain world. Read it.' Daniel Kahneman, author of Thinking, Fast and Slow _________________________ What if we could improve our ability to predict the future?
Everything we do involves forecasts about how the future will unfold. Whether buying a new house or changing job, designing a new product or getting married, our decisions are governed by implicit predictions of how things are likely to turn out. The problem is, we're not very good at it.
In a landmark, twenty-year study, Wharton professor Philip Tetlock showed that the average expert was only…
Accurate and precise forecasting is essential for successful planning and policy from economics to epidemiology. We have been keen to understand why so many forecasts turn out to be highly inaccurate since making dreadful forecasts ourselves, and advising UK government agencies (Treasury, Parliament, Bank of England) during turbulent periods. As simple extrapolation often beats model-based forecasting, we have been developing improved methods that draw on the best aspects of both, and have published more than 60 articles and 6 books attracting more than 6000 citations by other scholars. Our recommended books cover a wide range of forecasting methods—suggesting there is no optimal way to look into the future.
A wonderful read on how weather forecasting has improved so dramatically since Robert Fitzroy’s initial efforts in 1859. The amazing developments in mathematical modelling of the climate and advances in super-computers are excitedly and clearly described, starting from Blum wondering how one week ahead it was possible to forecast that Hurricane Sandy would strike New York.
'Revelatory ... convey[s] the technical brilliance and political significance of an achievement that hides in plain sight' Telegraph
From satellites circling the Earth, to weather stations far out in the ocean, through some of the most ingenious minds and advanced algorithms at work today - In this gripping investigation, Andrew Blum takes us on a global journey. Our destination: the simulated models weather scientists have constructed of our planet, which spin faster than time, turning chaos into prediction, offering glimpses of our future with eerie precision.
This collaborative invention spans the Earth and relies on continuous co-operation between all nations…
Accurate and precise forecasting is essential for successful planning and policy from economics to epidemiology. We have been keen to understand why so many forecasts turn out to be highly inaccurate since making dreadful forecasts ourselves, and advising UK government agencies (Treasury, Parliament, Bank of England) during turbulent periods. As simple extrapolation often beats model-based forecasting, we have been developing improved methods that draw on the best aspects of both, and have published more than 60 articles and 6 books attracting more than 6000 citations by other scholars. Our recommended books cover a wide range of forecasting methods—suggesting there is no optimal way to look into the future.
This is a readable tale of the rise of economic forecasters in the USA during the boom years of the 1920s, and their demise after failing to forecast the `Great Crash of 1929’ and ensuing Great Depression. Roger Babson did forewarn of a crash, but also failed after wrongly repeatedly forecasting an imminent recovery in the early 1930s. It holds many relevant lessons for our turbulent times, emphasizing that the future is always highly uncertain.
The period leading up to the Great Depression witnessed the rise of the economic forecasters, pioneers who sought to use the tools of science to predict the future, with the aim of profiting from their forecasts. This book chronicles the lives and careers of the men who defined this first wave of economic fortune tellers, men such as Roger Babson, Irving Fisher, John Moody, C. J. Bullock, and Warren Persons. They competed to sell their distinctive methods of prediction to investors and businesses, and thrived in the boom years that followed World War I. Yet, almost to a man, they…
Accurate and precise forecasting is essential for successful planning and policy from economics to epidemiology. We have been keen to understand why so many forecasts turn out to be highly inaccurate since making dreadful forecasts ourselves, and advising UK government agencies (Treasury, Parliament, Bank of England) during turbulent periods. As simple extrapolation often beats model-based forecasting, we have been developing improved methods that draw on the best aspects of both, and have published more than 60 articles and 6 books attracting more than 6000 citations by other scholars. Our recommended books cover a wide range of forecasting methods—suggesting there is no optimal way to look into the future.
When can we trust a forecast? Given how often forecasts end up being very wide of the mark, a degree of scepticism might well be warranted. Paul Goodwin provides an entertaining account of forecasting, arguing that intuition may serve us well in some settings, but that computer-based analysis of big data might be expected to prevail in others.
Whether it's an unforeseen financial crash, a shock election result or a washout summer that threatens to ruin a holiday in the sun, forecasts are part and parcel of our everyday lives. We rely wholeheartedly on them, and become outraged when things don't go exactly to plan.
But should we really put so much trust in predictions? Perhaps gut instincts can trump years of methodically compiled expert knowledge? And when exactly is a forecast not a forecast? Forewarned will answer all of these intriguing questions, and many more.
Packed with fun anecdotes and startling facts, Forewarned is a myth-busting guide…
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…
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!
Books on AI often go to extremes, either promoting it as the solution to all the world’s problems, or depicting it as an evil that will destroy humanity.
This book is much more practical, and based on experience using AI in actual business applications. It is the result of considerable research, involving investigation of applications not only in silicon-valley, but from various business sectors, such as Airbus, Ping, Progressive Insurance, and Capital One Bank.
Don’t let the title fool you; this book is not simply a promotion of AI, but addresses the practical issues that have to be considered if success is to be achieved. For example, they argue that “the most important aspect in AI success is not machinery, but human leadership, behavior, and change.”
A fascinating look at the trailblazing companies using artificial intelligence to create new competitive advantage, from the author of the business classic, Competing on Analytics, and the head of Deloitte's US AI practice.
Though most organizations are placing modest bets on artificial intelligence, there is a world-class group of companies that are going all-in on the technology and radically transforming their products, processes, strategies, customer relationships, and cultures.
Though these organizations represent less than 1 percent of large companies, they are all high performers in their industries. They have better business…
I’m a professor of psychology at Occidental College, where I direct the Thinking Lab. I hold degrees in psychology from Princeton and Harvard and have published several dozen scholarly articles on conceptual development and conceptual change. I’m interested in how people acquire new concepts and form new beliefs, especially within the domains of science and religion. My research investigates intuitions that guide our everyday understanding of the natural world and strategies for improving that understanding.
Science has revolutionized the way we live and the way we understand reality, but what accounts for its success? What method sets science apart from other forms of inquiry and ensures that it yields ever-more accurate theories of the world? Strevens argues that the scientific method is not a special kind of logic, like deriving hypotheses from first principles or narrowing hypotheses through falsification, but a simple commitment to arguing with evidence. Strevens shows, with historical case studies, how this commitment is seemingly irrational, as it provides no constraints on what counts as evidence or how evidence should be interpreted, but also incredibly powerful, fostering ingenuity and discovery.
* Why is science so powerful? * Why did it take so long-two thousand years after the invention of philosophy and mathematics-for the human race to start using science to learn the secrets of the universe?
In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument.
Like such classic works as Karl Popper's The Logic of Scientific Discovery and Thomas Kuhn's The Structure of…
I gradually shifted my statistics teaching from significance testing — traditional but bamboozling — to estimation (confidence intervals), which I called "the new statistics" because, although not new, relying on it would, for many researchers, be very new. It’s more informative, makes sense, and is a pleasure to teach and use. I "retired" to write Understanding the New Statistics. Then Open Science arrived—hooray! Robert Calin-Jageman joined me for an intro textbook with Open Science and The New Statistics all through. Our first edition came out in 2017. The second edition has wonderful new open-source software (‘esci’), which is also ideal for more advanced students and researchers. Enjoy!
Yes, this is a textbook, but if you are seeking a research design and methods text for psychology or a related discipline, this is easily my top choice.
There are lots of references to topical stories to keep everything relevant for students. There’s a truckload of valuable stuff online to support both teachers and learners. This fourth edition is right up-to-the-moment, Chapter 3 especially so, as it explains three types of scientific claims, and four types of validity that researchers should aim to achieve. That may sound forbidding, but Morling’s examples and explanations are pleasingly accessible.
Featuring an emphasis on future consumers of psychological research and examples drawn from popular media, Research Methods in Psychology: Evaluating a World of Information develops students' critical-thinking skills as they evaluate information in their everyday lives. The Fourth Edition of this best-selling text takes learning to a new level for both consumers and producers by offering new content, interactive learning, and online assessment to help them master the concepts.
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