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,…
It is April 1st, 2038. Day 60 of China's blockade of the rebel island of Taiwan.
The US government has agreed to provide Taiwan with a weapons system so advanced that it can disrupt the balance of power in the region. But what pilot would be crazy enough to run…
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…
A Duke with rigid opinions, a Lady whose beliefs conflict with his, a long disputed parcel of land, a conniving neighbour, a desperate collaboration, a failure of trust, a love found despite it all.
Alexander Cavendish, Duke of Ravensworth, returned from war to find that his father and brother had…
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…
The Duke's Christmas Redemption
by
Arietta Richmond,
A Duke who has rejected love, a Lady who dreams of a love match, an arranged marriage, a house full of secrets, a most unneighborly neighbor, a plot to destroy reputations, an unexpected love that redeems it all.
Lady Charlotte Wyndham, given in an arranged marriage to a man she…
I've had a long-time interest in two things: mathematics and social issues. This is why I got degrees in social work (Masters) and sociology (PhD) and eventually focused on the quantitative aspects of these two areas. Social Workers Count gave me the chance to marry these two interests by showing the role mathematics can play in illuminating a number of pressing social issues.
Jun Otsuka, a philosopher who also has training in statistics, zooms in on their philosophical foundations.
His book discusses the metaphysical, epistemological, and semantic assumptions on which Classical statistics, Bayesian statistics, predictive/classification AI models, and causal inference are based.
For those interested in these disciplines but who're also sensitive to the philosophical issues they raise, Otsuka's book is simply amazing. Run out and get a copy as soon as possible.
Simply stated, this book bridges the gap between statistics and philosophy. It does this by delineating the conceptual cores of various statistical methodologies (Bayesian/frequentist statistics, model selection, machine learning, causal inference, etc.) and drawing out their philosophical implications. Portraying statistical inference as an epistemic endeavor to justify hypotheses about a probabilistic model of a given empirical problem, the book explains the role of ontological, semantic, and epistemological assumptions that make such inductive inference possible. From this perspective, various statistical methodologies are characterized by their epistemological nature: Bayesian statistics by internalist epistemology, classical statistics by externalist epistemology, model selection by pragmatist…
I’m an applied statistician and academic researcher/lecturer at New Zealand’s oldest university – the University of Otago. R facilitates everything I do – research, academic publication, and teaching. It’s the latter part of my job that motivated my own book on R. From first-year statistics students who have never seen R to my own Ph.D. students using R to implement novel and highly complex statistical methods and models, my experience is that all ultimately love the ease with which the R language permits exploration, visualisation, analysis, and inference of one’s data. The ever-growing need in today’s society for skilled statisticians and data scientists means there's never been a better time to learn this essential language.
This provides a superb balance between technical aspects of R coding and the statistical methods that motivate its use. It's rare to find a book on topics like this that are written with Kabacoff's easygoing yet precise style, which makes it ideal for beginners. From my own experience, it is obvious the author has spent many years teaching this type of content, knowing where things deserve extra explanation up front and where other more technical details can be relegated to more advanced texts.
R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.
R in Action, Second Edition is language tutorial focused on practical problems. Written by a research methodologist, it takes a direct and modular approach to quickly give readers the information they need to produce useful results. Focusing on realistic data analyses and a comprehensive integration of graphics, it follows the steps that…
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…
This book follows the journey of a writer in search of wisdom as he narrates encounters with 12 distinguished American men over 80, including Paul Volcker, the former head of the Federal Reserve, and Denton Cooley, the world’s most famous heart surgeon.
In these and other intimate conversations, the book…
I currently teach in the management department of the London School of Economics, and I often need to communicate economic ideas to non-economists. Honestly, I was very nervous about writing (yet another) book about economics. Especially since there are so many around. Two things made me have a go. I really wanted to convey the key arguments with simplicity, translating often complicated and abstruse ideas into straightforward language in a way that didn’t dumb down. Second the world has changed so much in recent years that you need to keep up to date. Quantitative easing, modern monetary theory, and Bitcoin are ideas that just did not exist until recently.
All politicians should be forced to read this book. Anyone who reads a newspaper should be forced to read this book. My favourite radio programme in the world is Tim Harford’sMore or Less. And this book is every bit as good. Harford is clear, incisive, and always interesting. In a world crowded with disinformation and fake news, he shows you how to evaluate the numbers that are thrown at you. To read him is to become a little cleverer. Make this man prime minister someone.
'Tim Harford is one of my favourite writers in the world. His storytelling is gripping but never overdone, his intellectual honesty is rare and inspiring, and his ability to make complex things simple - but not simplistic - is exceptional. How to Make the World Add Up is another one of his gems. If you're looking for an addictive pageturner that will make you smarter, this is your book' Rutger Bregman, author of Humankind
'Tim Harford could well be Britain's Malcolm Gladwell' Alex Bellos, author of Alex's Adventures in Numberland
