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’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’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’m an Associate Professor in the University of Alabama’s Department of Philosophy. I worked as an FBI Special Agent before making the natural transition to academic philosophy. Being a professor was always a close second to Quantico, but that scene in Point Break in which Keanu Reeves and Patrick Swayze fight Anthony Kiedis on the beach made it seem like the FBI would be more fun than academia. In my current position as a professor at the University of Alabama, I teach in my department’s Jurisprudence Specialization. My primary research interests are at the intersection of philosophy of law, political philosophy, and criminal justice. I’ve written three books on policing.
I love this book because it reminds us of the many ways that technology can affect justice.
It is tempting to think sophisticated tactics such as “predictive policing” can solve all problems relating to human bias. However, Brayne shows that data and algorithms do not eliminate bias and discretion. Instead, high-tech police tools simply make bias less overt and visible, which erodes the public’s ability to hold the police accountable.
I especially enjoyed how the book flips the script, considering diverse ways to use these tools to help the public. For example, how can municipalities use technology to analyze the underlying factors that contribute to policing problems in the first place?
The scope of criminal justice surveillance, from the police to the prisons, has expanded rapidly in recent decades. At the same time, the use of big data has spread across a range of fields, including finance, politics, health, and marketing. While law enforcement's use of big data is hotly contested, very little is known about how the police actually use it in daily operations and with what consequences.
In Predict and Surveil, Sarah Brayne offers an unprecedented, inside look at how police use big data and new surveillance technologies, leveraging on-the-ground fieldwork with one of the most technologically advanced law…
A noted quantitative hedge fund manager and quant finance author, Ernie is the founder of QTS Capital Management and Predictnow.ai. Previously he has applied his expertise in machine learning at IBM T.J. Watson Research Center’s Human Language Technologies group, at Morgan Stanley’s Data Mining and Artificial Intelligence Group, and at Credit Suisse’s Horizon Trading Group. Ernie was quoted by Bloomberg, the Wall Street Journal, New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program. He is an adjunct faculty at Northwestern University’s Master’s in Data Science program and supervises student theses there. Ernie holds a Ph.D. in theoretical physics from Cornell University.
I have used this book to teach my Financial Risk Analytics course at Northwestern University for many years. As a textbook, it is surprisingly easy to read, and the abundant exercises are great. This would be a foundational text to read after you have read my own books. It puts you on solid ground to understand all the financial babble that you may read elsewhere. It includes extensive coverage of most basic topics important to a serious quantitative trader, while not being overly mathematical. Easily understandable if you have basic programming and math background from first year of university.
Everything is practical in this book, which isn’t what you would expect from a textbook! There is no math for math’s sake. I have used the techniques discussed in this book for real trading, and for creating features at my machine learning SaaS predictnow.ai. Examples: What’s the difference between net…
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code…
I’m a historian who’s spent far too much time thinking about how the color magenta contributed to climate change and why eighteenth-century humanitarians were obsessed with tobacco enemas. My favorite historical topics—like sensation, color, and truth—don’t initially seem historical, but that’s exactly why they need to be explored. I’ve learned that the things that seem like second nature are where our deepest cultural assumptions and unconscious biases hide. In addition to writing nonfiction, I’ve been lucky enough to grow up on a ranch, live in Paris, work as an interior design writer, teach high school and college, and help stray dogs get adopted.
I had never really given much thought to counting until I read this book, but in the very first chapter, Stone made me rethink everything I thought I knew about “one fish, two fish, red fish, blue fish.” She shows that every time we count, we’re making cultural assumptions. For example, what counts as a fish? And what makes the color of the fish more relevant than other features? Counting reveals that while these choices may seem intuitive, basic, and meaningless, they have very real impacts on people’s lives. Especially when we use numbers to measure things like merit, poverty, race, and productivity, those fundamental assumptions matter more than we care to admit.
Early in her extraordinary career, Deborah Stone wrote Policy Paradox, a landmark work on politics. Now, in Counting, she revolutionises how we approach numbers and shows how counting shapes the way we see the world. Most of us think of counting as a skill so basic that we see numbers as objective, indisputable facts. Not so, says Stone. In this playful-yet-probing work, Stone reveals the inescapable link between quantifying and classifying, and explains how counting determines almost every facet of our lives-from how we are evaluated at work to how our political opinions are polled to whether we get into…
In sixth grade, my teacher tried to teach the class how to read line charts – and something fell into place for me. Ever since then, I’ve tried to sort data into forms that we can use to make sense of it. As a researcher at Microsoft, I consulted with teams across the organization – from sales to legal; and from Excel to XBox – to help them understand their data. At Honeycomb, I design tools for software operations teams to diagnose their complex systems. These books each gave me an “ah-hah” moment that made me think differently about the craft of creating visualization. They now sit on my shelf in easy reach – I hope you find them fascinating too.
I learned Tukey’s name about as soon as I learned that data visualization existed as more than a menu in Excel and a personal obsession. Tukey coined the term “exploratory data analysis,” and so tapped into a passion for swimming around in all the interesting rows and columns. Tukey was working before computers were widespread, and so I got a view of how he saw data: working against the constraints of pencil and paper; keeping your hand moving as fast as possible. While the explorations we can do with gigabytes of memory and powerful rendering are very different, the goal of getting information into your head as fast as possible is unchanged.
This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearson.com/statistics-classics-series for a complete list of titles.
The approach in this introductory book is that of informal study of the data. Methods range from plotting picture-drawing techniques to rather elaborate numerical summaries. Several of the methods are the original creations of the author, and all can be carried out either with pencil or aided by hand-held calculator.
0134995457 / 9780134995458 EXPLORATORY DATA ANALYSIS (CLASSIC VERSION), 1/e
