Here are 100 books that How Data Happened fans have personally recommended if you like
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I’ve been fascinated by information technology since I was a child–whether in the form of books, libraries, computers, or cell phones! Living through a massive expansion in the volume of data, I believe it is essential to study the long history of information to make sense of our current data-driven times–which is why I became a historian of data, which I teach and write about full time. Here are some of the most informative and insightful books that have helped me make sense of our issues, ranging from information overload and artificial intelligence to privacy and data justice.
How and why do states keep secrets? Soll provides powerful and, at times, surprising answers to this question by turning to the absolutist governments of early modern Europe, and specifically the administrator Jean-Baptiste Colbert.
As the key minister of state under King Louis XIV, Colbert built a powerful system of information collection and control that, in many ways, anticipated the modern national security state. If you want to make sense of government collection of data and state secrecy today, Soll’s book is a must-read.
Jean-Baptiste Colbert saw governance of the state not as the inherent ability of the king, but as a form of mechanical mastery of subjects such as medieval legal history, physics, navigation, and the price lists of nails, sails, and gunpowder. In The Information Master, Jacob Soll shows how the legacy of Colbert's encyclopedic tradition lies at the very center of the rise of the modern state.
This innovative book argues that Colbert's practice of collecting knowledge originated in Renaissance Italy, where merchants recognized the power to be gained from merging scholarship and trade. By connecting historical literatures-archives, libraries, merchant techniques,…
I’ve been fascinated by information technology since I was a child–whether in the form of books, libraries, computers, or cell phones! Living through a massive expansion in the volume of data, I believe it is essential to study the long history of information to make sense of our current data-driven times–which is why I became a historian of data, which I teach and write about full time. Here are some of the most informative and insightful books that have helped me make sense of our issues, ranging from information overload and artificial intelligence to privacy and data justice.
Today, archives are places where we go to research and learn about the past. But as Popper’s fascinating book shows, in the sixteenth and seventeenth centuries, governments used archives like we use computers and databases today as facilities for storing information they considered immediately relevant to solving political problems.
Just like we use computers today, governments mobilized archives to collect, organize, and redeploy information to advance their specific policy objectives. While the early modern world might seem quite distant from our own, Popper shows us that the problem of using information to exert political power is a very old one.
An exploration of the proliferation of paper in early modern Britain and its far-reaching effects on politics and society.
We are used to thinking of ourselves as living in a time when more information is more available than ever before. In The Specter of the Archive, Nicholas Popper shows that earlier eras had to grapple with the same problem-how to deal with too much information at their fingertips.
He reveals that early modern Britain was a society newly drowning in paper, a light and durable technology whose spread allowed statesmen to record drafts, memoranda, and other ephemera that might otherwise…
I’ve been fascinated by information technology since I was a child–whether in the form of books, libraries, computers, or cell phones! Living through a massive expansion in the volume of data, I believe it is essential to study the long history of information to make sense of our current data-driven times–which is why I became a historian of data, which I teach and write about full time. Here are some of the most informative and insightful books that have helped me make sense of our issues, ranging from information overload and artificial intelligence to privacy and data justice.
How do citizens learn to accept violence perpetuated by their own governments? Answering this profoundly relevant and timely question lies at the heart of Linstrum’s book–and data lies at the crux of the answer. He shows how, despite massive amounts of data about colonial violence circulating in postwar Britain, British people found ways to accommodate and justify that violence.
This book is a sobering challenge to the belief that better information produces better and more empathetic societies, showing that the connection between knowledge and enlightened behavior is not nearly as straightforward as we may want to believe.
An eye-opening account of how violence was experienced not just on the frontlines of colonial terror but at home in imperial Britain.
When uprisings against colonial rule broke out across the world after 1945, Britain responded with overwhelming and brutal force. Although this period has conventionally been dubbed "postwar," it was punctuated by a succession of hard-fought, long-running conflicts that were geographically diffuse, morally ambiguous, and impervious to neat endings or declarations of victory. Ruthless counterinsurgencies in Malaya, Kenya, and Cyprus rippled through British society, molding a home front defined not by the mass mobilization of resources, but by sentiments…
I’ve been fascinated by information technology since I was a child–whether in the form of books, libraries, computers, or cell phones! Living through a massive expansion in the volume of data, I believe it is essential to study the long history of information to make sense of our current data-driven times–which is why I became a historian of data, which I teach and write about full time. Here are some of the most informative and insightful books that have helped me make sense of our issues, ranging from information overload and artificial intelligence to privacy and data justice.
If you love NPR as much as I do, then this is the book for you! Shepperd tells the fascinating story of how public radio came into being in the US during the mid-twentieth century–and how public radio played a crucial role in defining Americans’ expectations about what they have the right to know about their government’s activities.
If you want to make sense of the historical relationship between democracy and data, then this is the book for you!
Winner of the 2024 BEA Book Award
Runner-up in the History Division of the Association for Education in Journalism and Mass Communication (AEJMC)
Runner-up for the AJHA Book of the Year (American Journalism Historians Association).
Despite uncertain beginnings, public broadcasting emerged as a noncommercial media industry that transformed American culture. Josh Shepperd looks at the people, institutions, and influences behind the media reform movement and clearinghouse the National Association of Educational Broadcasters (NAEB) in the drive to create what became the Public Broadcasting Service and National Public Radio.
Founded in 1934, the NAEB began as a disorganized collection of undersupported…
I’m an economics professor, but I also have a column in Australia’s leading financial newspaper so I really appreciate authors who can tackle complex topics in an accessible manner. I’m also both extremely interested in and do academic research on topics to do with technologies like two-sided platforms, cryptocurrencies, blockchain, and artificial intelligence. All these books made me think harder about the big issues in these areas, and how to combine rigorous research with what is actually happening—often at breakneck speed—in the real-world digital economy.
This book helped me understand why advances in artificial intelligence are going to have a big impact on productivity and economic growth. I loved the analogies to old technologies like electrification of factories, and newer examples like how Team New Zealand used simulations to change racing tactics and boat design.
The book has an important, big idea at its heart. That idea is that AI helps organizations make better predications, and those better predictions allow organizations to be fundamentally redesigned to take advantage of this. This is where the AI productivity revolution comes from.
"What does AI mean for your business? Read this book to find out." -- Hal Varian, Chief Economist, Google Artificial intelligence does the seemingly impossible, magically bringing machines to life--driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.
But in Prediction Machines, three eminent economists recast the rise of AI…
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 started my career as a research scientist building machine learning algorithms for weather forecasting. Twenty years later, I found myself at a precision agriculture startup creating models that provided guidance to farmers on when to plant, what to plant, etc. So, I am part of the movement from academia to industry. Now, at Google Cloud, my team builds cross-industry solutions and I see firsthand what our customers need in their data science teams. This set of books is what I suggest when a CTO asks how to upskill their workforce, or when a graduate student asks me how to break into the industry.
What if you are faced with a problem for which a standard approach doesn’t yet exist? In such a case, you will need to be able to figure out the approach from the first principles. This book will help you learn how to derive insights starting from raw data.
'A statistical national treasure' Jeremy Vine, BBC Radio 2
'Required reading for all politicians, journalists, medics and anyone who tries to influence people (or is influenced) by statistics. A tour de force' Popular Science
Do busier hospitals have higher survival rates? How many trees are there on the planet? Why do old men have big ears? David Spiegelhalter reveals the answers to these and many other questions - questions that can only be addressed using statistical science.
Statistics has played a leading role in our scientific understanding of the world for centuries, yet we are all familiar with the way…
I taught for 45 years at Ithaca College broken by two years as Fulbright Professor in West Africa at the University of Liberia. During my years in academia, I developed several new courses including a popular “Math in Africa” class and the first U.S. course for college credit in chess theory. I’ve always had a passion for and continue to have strong interests in (1) national educational and social issues concerning equal access to math education for all and (2) teaching others about the power of mathematics and statistics to help one more deeply understand social issues.
This book is kind of a fun crash course in statistics which covers all the basic concepts at an introductory level.
The cartoons are a little bit dated, but still entertaining. There are lots of pictures and graphs which are a pleasure if you are a visual learner. The reader will come away with many useful tools to help understand real world problems.
I’m a retired math professor, but still got a real kick out of this book and especially appreciated the many good examples referenced such as gender discrimination in salaries and racial discrimination in jury selection. I recommended it to many of my struggling students.
Updated version featuring all new material. If you have ever looked for P-values by shopping at P mart, tried to watch the Bernoulli Trails on "People's Court," or think that the standard deviation is a criminal offense in six states, then you need The Cartoon Guide to Statistics to put you on the road to statistical literacy. The Cartoon Guide to Statistics covers all the central ideas of modern statistics: the summary and display of data, probability in gambling and medicine, random variables, Bernoulli Trails, the Central Limit Theorem, hypothesis testing, confidence interval estimation, and much more-all explained in simple,…
In my career as an academic librarian, I was often asked to teach students to think about the credibility of the information they incorporate into their academic, professional, personal, and civic lives. In my teaching and writing, I have struggled to make sense of the complex and nuanced factors that make some information more credible and other information less so. I don’t have all the answers for dealing with problematic information, but I try hard to convince people to think carefully about the information they encounter before accepting any of it as credible or dismissing any of it as non-credible.
I constantly recommend The Data Detective because it serves as an unmatched handbook for making sense of the statistical data to which we are constantly exposed.
What I like about it, besides its lively, readable style, is that the book convincingly and clearly explains 1) why we need statistical data to make informed decisions, 2) the factors that go into producing reliable statistics, 3) the factors that can produce unreliable statistics, and 4) how any statistics, reliable or not, can be misused to deceive us.
The author, Tim Harford, is an economist who writes for the Financial Times and hosts the brilliant podcast Cautionary Tales.
From “one of the great (greatest?) contemporary popular writers on economics” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics.
Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us.” If we can toss…
I am the Fletcher Jones Professor of Economics at Pomona College. I started out as a macroeconomist but, early on, discovered stats and stocks—which have long been fertile fields for data torturing and data mining. My book, Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics is a compilation of a variety of dubious and misleading statistical practices. More recently, I have written several books on AI, which has a long history of overpromising and underdelivering because it is essentially data mining on steroids. No matter how loudly statisticians shout correlation is not causation, some will not hear.
The title is provocative but justified because so much of the “evidence” that we are bombarded with daily is bullshit. This is a wonderful compilation of statistical mistakes and misuses that are intended to persuade readers to be skeptical and to show them how to recognize bullshit when they see it.
Bullshit isn’t what it used to be. Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data.
“A modern classic . . . a straight-talking survival guide to the mean streets of a dying democracy and a global pandemic.”—Wired
Misinformation, disinformation, and fake news abound and it’s increasingly difficult to know what’s true. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based…
