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If Then: How the Simulmatics Corporation Invented the Future
The Simulmatics Corporation, launched during the Cold War, mined data, targeted voters, manipulated consumers, destabilized politics, and disordered knowledge—decades before Facebook, Google, and Cambridge Analytica. Jill Lepore, best-selling author of These Truths, came across the company’s papers in MIT’s archives and set out to tell this forgotten history, the long-lost backstory to the methods, and the arrogance, of Silicon Valley.
Founded in 1959 by some of the nation’s leading social scientists—“the best and the brightest, fatally brilliant, Icaruses with wings of feathers and wax, flying to the sun”—Simulmatics proposed to predict and manipulate the future by way of the computer simulation of human behavior. In summers, with their wives and children in tow, the company’s scientists met on the beach in Long Island under a geodesic, honeycombed dome, where they built a “People Machine” that aimed to model everything from buying a dishwasher to counterinsurgency to casting a vote. Deploying their “People Machine” from New York, Washington, Cambridge, and even Saigon, Simulmatics’ clients included the John F. Kennedy presidential campaign, the New York Times, the Department of Defense, and dozens of major manufacturers: Simulmatics had a hand in everything from political races to the Vietnam War to the Johnson administration’s ill-fated attempt to predict race riots. The company’s collapse was almost as rapid as its ascent, a collapse that involved failed marriages, a suspicious death, and bankruptcy. Exposed for false claims, and even accused of war crimes, it closed its doors in 1970 and all but vanished. Until Lepore came across the records of its remains.
The scientists of Simulmatics believed they had invented “the A-bomb of the social sciences.” They did not predict that it would take decades to detonate, like a long-buried grenade. But, in the early years of the twenty-first century, that bomb did detonate, creating a world in which corporations collect data and model behavior and target messages about the most ordinary of decisions, leaving people all over the world, long before the global pandemic, crushed by feelings of helplessness. This history has a past; If Then is its cautionary tale.
Founded in 1959 by some of the nation’s leading social scientists—“the best and the brightest, fatally brilliant, Icaruses with wings of feathers and wax, flying to the sun”—Simulmatics proposed to predict and manipulate the future by way of the computer simulation of human behavior. In summers, with their wives and children in tow, the company’s scientists met on the beach in Long Island under a geodesic, honeycombed dome, where they built a “People Machine” that aimed to model everything from buying a dishwasher to counterinsurgency to casting a vote. Deploying their “People Machine” from New York, Washington, Cambridge, and even Saigon, Simulmatics’ clients included the John F. Kennedy presidential campaign, the New York Times, the Department of Defense, and dozens of major manufacturers: Simulmatics had a hand in everything from political races to the Vietnam War to the Johnson administration’s ill-fated attempt to predict race riots. The company’s collapse was almost as rapid as its ascent, a collapse that involved failed marriages, a suspicious death, and bankruptcy. Exposed for false claims, and even accused of war crimes, it closed its doors in 1970 and all but vanished. Until Lepore came across the records of its remains.
The scientists of Simulmatics believed they had invented “the A-bomb of the social sciences.” They did not predict that it would take decades to detonate, like a long-buried grenade. But, in the early years of the twenty-first century, that bomb did detonate, creating a world in which corporations collect data and model behavior and target messages about the most ordinary of decisions, leaving people all over the world, long before the global pandemic, crushed by feelings of helplessness. This history has a past; If Then is its cautionary tale.
432 pages, Hardcover
First published September 15, 2020
About the author
Jill Lepore
47 books1,141 followersJill Lepore is the David Woods Kemper ’41 Professor of American History, Harvard College Professor, and chair of Harvard's History and Literature Program. She is also a staff writer at The New Yorker.
Winner of the Anisfield-Wolf Award for the best non-fiction book on race, and a finalist for the Pulitzer Prize; The Name of War (Knopf, 1998), winner of the Bancroft Prize, the Ralph Waldo Emerson Prize, and the Berkshire Prize and a finalist for the J. Anthony Lukas Award.
A co-founder of the magazine Common-place, Lepore’s essays and reviews have also appeared in the New York Times, the Times Literary Supplement, American Scholar, the Los Angeles Times, the Washington Post, The Daily Beast, the Journal of American History and American Quarterly. Her research has been funded by the National Endowment for the Humanities, the Pew Foundation, the Gilder Lehrman Institute, the Charles Warren Center, and the Woodrow Wilson Foundation. She has served as a consultant for the National Park Service and currently serves on the boards of the National Portrait Gallery and the Society of American Historians.
Jill lives in Cambridge,Massachusetts.
Winner of the Anisfield-Wolf Award for the best non-fiction book on race, and a finalist for the Pulitzer Prize; The Name of War (Knopf, 1998), winner of the Bancroft Prize, the Ralph Waldo Emerson Prize, and the Berkshire Prize and a finalist for the J. Anthony Lukas Award.
A co-founder of the magazine Common-place, Lepore’s essays and reviews have also appeared in the New York Times, the Times Literary Supplement, American Scholar, the Los Angeles Times, the Washington Post, The Daily Beast, the Journal of American History and American Quarterly. Her research has been funded by the National Endowment for the Humanities, the Pew Foundation, the Gilder Lehrman Institute, the Charles Warren Center, and the Woodrow Wilson Foundation. She has served as a consultant for the National Park Service and currently serves on the boards of the National Portrait Gallery and the Society of American Historians.
Jill lives in Cambridge,Massachusetts.
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Displaying 1 - 30 of 360 reviews
October 19, 2020
Much more a rough history of the political landscape of the 1950s and 60s than of Simulatics. Makes you think now and then but then obliterates any useful thoughts with a mound of random tangents and pieces of trivia. The actual history of Simulatics is probably a third or less of the book. Pretty disappointing.
June 17, 2020
Absolutely fascinating! Historian Jill Lepore has put her scholarly research skills to use and brought out of the archives the history of an obscure company, Simulmatics, that was the forerunner for today's Silicon Valley start-ups. The young men who rule Silicon Valley may believe they are unique and that history is inconsequential to their goals, but Lepore is here to tell them otherwise. Founded in 1959 and bankrupt in just over a decade, Simulmatics used early computers to gather and analyze data in order to predict and channel human behavior. Early on, there were those who found what this company did immoral, but she details the actors who set the stage for the lack of government regulation even today. I loved her Epilogue in which she masterfully dispenses with the hubris and arrogant indifference to history of those young men in Silicon Valley. Here is a master at the top of her game!
My thanks to Edelweiss and the publisher for a digital ARC. Also thanks to Library Journal for their "day of dialog" for librarians and authors, through which I heard Jill Lepore talk about this book.
My thanks to Edelweiss and the publisher for a digital ARC. Also thanks to Library Journal for their "day of dialog" for librarians and authors, through which I heard Jill Lepore talk about this book.
October 7, 2020
I confess: I have a brain crush on Ms Lepore. I enjoy her books, her articles in The New Yorker, and her new podcast, The Last Archive ("a show about how we know what we know and why it seems, lately, as if we don’t know anything at all"). If I could have coffee with any public intellectual, she'd be right at the top of the list. Her intelligence, wit, and breadth of knowledge are simply wonderful.
"If Then," her latest book, is ostensibly the story of the Simulmatics Corporation. In fact, what it's really about is the birth of the world we inhabit today. Though hardly anyone remembers them today, Simulmatics was everywhere in mid-century America. They claimed credit for the election of John F. Kennedy. They secured countless contracts with private businesses and federal agencies, and even (as Lepore shows in some detail) were instrumental in formulating American strategy in the Vietnam War. They were geniuses and drunks, academics and admen, hubristic great promisers but poor deliverers, particularly bad as husbands, more than a little unbalanced. Their mission, as Lepore puts it, was nothing less than to invent a computer program designed to predict and manipulate human behavior, all sorts of human behavior, from buying a dishwasher to countering an insurgency to casting a vote. They called it the People Machine.
The Simulmatics men (how clunky the name sounds to modern ears, but back then it probably sounded futuristic, like something from "The Jetsons" TV show -- which I suspect many readers of this review will have to Google) were convinced that every aspect of human behavior could be expressed precisely in mathematical terms and thus could be as predictable as any other natural process. Lepore shows us their lives and their times in this era of Mad Men with their chain-smoked cigarettes and ubiquitous cocktails, blinkered vision and collapsing marriages. The Simulmatics Era gave birth to our own age.
The book begins with the first use of a computer, UNIVAC, to predict the outcome of a presidential election on live TV. It didn't go well, and the Why of it makes for a good story, with the added bonus of her captivating description of how newspapers reported election results before computers. But out of that misstep a new world was born in which data became ever more refined and precise and ever more central to critically important currents in our lives, particularly in the menage a trois between marketing, politics, and computers.
Lepore notes, the 1935 Manhattan phone book listed ten public relations firms. By the mid-50s there were more than 700. Politicians had always been packaged and marketed, but that all reached a whole other level beginning in the '50s and '60s. Democrat Adlai Stevenson ran his campaigns as an intellectual, believing he could address American voters with intelligence and rational discourse rather than lower himself to something as demeaning as TV advertisements -- a medium used to sell coffee, soap, and cigarettes, not something as serious as the office of the President of the United States . His Republican opponent, Dwight Eisenhower, however, was more pragmatic. He recognized the impact of 30-second ads that could put out a message quickly and efficiently to millions of viewers and could even be designed specifically for particular markets. To handle this part of his campaign, Ike hired the ad man who was to later write the immortal words, "M&Ms melt in your mouth, not in your hand."
This was the culture in which Simulmatics was birthed. These "Computermen," admen, and quantifiers came from the best American universities. They were smart and awfully sure of themselves and their genius. Their vision was, needless to say, less than perfect (though many of them were, in fact, geniuses). As Lepore says with characteristic wry economy, they were "mid-century white liberals in an era when white liberals were not expected to understand people who weren't white or liberal," and "they did not consider the intelligence of woman to be intelligence; they did not consider a female understanding of human behavior to be knowledge." There was, in fact, a great deal these men couldn't see or understand.
"If Then" is simultaneously a history of Simulmatics, a portrait of the time -- the second half of the twentieth century -- and an exploration of how we got where we are. Of the spread of and growing reliance on technology that ran side-by-side with mounting distrust of technology and its impact on culture and democracy. Of newspapers struggling to compete with new means of communication. It looks too at the Cold War and the Civil Rights movement and the backlash it engendered, and the anti-war movement. Of the short-lived idea of something called the National Data Center that would bring information about Americans that was currently stored in countless organizations and offices, all together in one place where it could be easily accessed. (The NDC idea may have been short-lived, but as we know, it came back -- to stay and grow.) Of growing links between elite universities and the Department of Defense. Of a technology that grew, infiltrating more and more of our lives, with virtually no government oversight, no protection of privacy.
The book covers a lot of ground, too much to summarize here.One thing that really struck me: how the Simulmatics men convinced the Department of Defense to send them to Vietnam so they could conduct interviews about a place whose culture and history they knew nothing about, interviews in which the Vietnamese translators changed the questions they in fact asked and the answers that were given. One of the key figures in the endeavor was a man named Walter Slote, a man with no qualifications for the job and not enough self-awareness to admit it. The cost, in dollars and deaths, was awful. Vietnamese men women, and children were dying, starving, being shot, bombed, burned, and napalmed. American soldiers were being shipped home in boxes, coffins, and bags. And the U.S. government was paying an Upper West Side Freudian analyst to explain that the Vietnamese, as a people, had Oedipal issues.
The story of Simulmatics is the story of Facebook and Google, Cambridge Analytics and AI. It is a story we may be learning too late. Lepore writes in language that is representative of the sadness and anger that propel much of "If Then" and define our times: In twenty-first-century Silicon Valley, the meaninglessness of the past and the uselessness of history became articles of faith, gleefully performed arrogance. "The only thing that matters is the future," said the Google and Uber self-driving car designer Anthony Levandowski in 2018. "I don't even know why we study history. It's entertaining, I guess -- the dinosaurs and the Neanderthals and the Industrial Revolution and stuff like that. But what already happened doesn't really matter. You don't need to know history to build on what they made. In technology, all that matters is tomorrow."
Simulmatics closed its doors in 1970, and its principals went on to other things. But their legacy! Lepore lays it out very clearly: the scientists of this long-vanished American corporation helped build the machine in which humanity would, by the twenty-first century, find itself trapped and tormented: stripped bare, driven to distraction, deprived of its senses, interrupted, exploited, directed, connected and disconnected, bought and sold, alienated and coerced, confused, misinformed, and even govern. They never meant to hurt anyone.
"If Then," her latest book, is ostensibly the story of the Simulmatics Corporation. In fact, what it's really about is the birth of the world we inhabit today. Though hardly anyone remembers them today, Simulmatics was everywhere in mid-century America. They claimed credit for the election of John F. Kennedy. They secured countless contracts with private businesses and federal agencies, and even (as Lepore shows in some detail) were instrumental in formulating American strategy in the Vietnam War. They were geniuses and drunks, academics and admen, hubristic great promisers but poor deliverers, particularly bad as husbands, more than a little unbalanced. Their mission, as Lepore puts it, was nothing less than to invent a computer program designed to predict and manipulate human behavior, all sorts of human behavior, from buying a dishwasher to countering an insurgency to casting a vote. They called it the People Machine.
The Simulmatics men (how clunky the name sounds to modern ears, but back then it probably sounded futuristic, like something from "The Jetsons" TV show -- which I suspect many readers of this review will have to Google) were convinced that every aspect of human behavior could be expressed precisely in mathematical terms and thus could be as predictable as any other natural process. Lepore shows us their lives and their times in this era of Mad Men with their chain-smoked cigarettes and ubiquitous cocktails, blinkered vision and collapsing marriages. The Simulmatics Era gave birth to our own age.
The book begins with the first use of a computer, UNIVAC, to predict the outcome of a presidential election on live TV. It didn't go well, and the Why of it makes for a good story, with the added bonus of her captivating description of how newspapers reported election results before computers. But out of that misstep a new world was born in which data became ever more refined and precise and ever more central to critically important currents in our lives, particularly in the menage a trois between marketing, politics, and computers.
Lepore notes, the 1935 Manhattan phone book listed ten public relations firms. By the mid-50s there were more than 700. Politicians had always been packaged and marketed, but that all reached a whole other level beginning in the '50s and '60s. Democrat Adlai Stevenson ran his campaigns as an intellectual, believing he could address American voters with intelligence and rational discourse rather than lower himself to something as demeaning as TV advertisements -- a medium used to sell coffee, soap, and cigarettes, not something as serious as the office of the President of the United States . His Republican opponent, Dwight Eisenhower, however, was more pragmatic. He recognized the impact of 30-second ads that could put out a message quickly and efficiently to millions of viewers and could even be designed specifically for particular markets. To handle this part of his campaign, Ike hired the ad man who was to later write the immortal words, "M&Ms melt in your mouth, not in your hand."
This was the culture in which Simulmatics was birthed. These "Computermen," admen, and quantifiers came from the best American universities. They were smart and awfully sure of themselves and their genius. Their vision was, needless to say, less than perfect (though many of them were, in fact, geniuses). As Lepore says with characteristic wry economy, they were "mid-century white liberals in an era when white liberals were not expected to understand people who weren't white or liberal," and "they did not consider the intelligence of woman to be intelligence; they did not consider a female understanding of human behavior to be knowledge." There was, in fact, a great deal these men couldn't see or understand.
"If Then" is simultaneously a history of Simulmatics, a portrait of the time -- the second half of the twentieth century -- and an exploration of how we got where we are. Of the spread of and growing reliance on technology that ran side-by-side with mounting distrust of technology and its impact on culture and democracy. Of newspapers struggling to compete with new means of communication. It looks too at the Cold War and the Civil Rights movement and the backlash it engendered, and the anti-war movement. Of the short-lived idea of something called the National Data Center that would bring information about Americans that was currently stored in countless organizations and offices, all together in one place where it could be easily accessed. (The NDC idea may have been short-lived, but as we know, it came back -- to stay and grow.) Of growing links between elite universities and the Department of Defense. Of a technology that grew, infiltrating more and more of our lives, with virtually no government oversight, no protection of privacy.
The book covers a lot of ground, too much to summarize here.One thing that really struck me: how the Simulmatics men convinced the Department of Defense to send them to Vietnam so they could conduct interviews about a place whose culture and history they knew nothing about, interviews in which the Vietnamese translators changed the questions they in fact asked and the answers that were given. One of the key figures in the endeavor was a man named Walter Slote, a man with no qualifications for the job and not enough self-awareness to admit it. The cost, in dollars and deaths, was awful. Vietnamese men women, and children were dying, starving, being shot, bombed, burned, and napalmed. American soldiers were being shipped home in boxes, coffins, and bags. And the U.S. government was paying an Upper West Side Freudian analyst to explain that the Vietnamese, as a people, had Oedipal issues.
The story of Simulmatics is the story of Facebook and Google, Cambridge Analytics and AI. It is a story we may be learning too late. Lepore writes in language that is representative of the sadness and anger that propel much of "If Then" and define our times: In twenty-first-century Silicon Valley, the meaninglessness of the past and the uselessness of history became articles of faith, gleefully performed arrogance. "The only thing that matters is the future," said the Google and Uber self-driving car designer Anthony Levandowski in 2018. "I don't even know why we study history. It's entertaining, I guess -- the dinosaurs and the Neanderthals and the Industrial Revolution and stuff like that. But what already happened doesn't really matter. You don't need to know history to build on what they made. In technology, all that matters is tomorrow."
Simulmatics closed its doors in 1970, and its principals went on to other things. But their legacy! Lepore lays it out very clearly: the scientists of this long-vanished American corporation helped build the machine in which humanity would, by the twenty-first century, find itself trapped and tormented: stripped bare, driven to distraction, deprived of its senses, interrupted, exploited, directed, connected and disconnected, bought and sold, alienated and coerced, confused, misinformed, and even govern. They never meant to hurt anyone.
October 16, 2020
Wow, not sure how a topic I’m DEEPLY interested in can be written about in a way that’s so boring. I have 80 pages left and not sure I’m going to finish. Its jsut too many names and unimportant details - I was expecting more of an interesting discussion about how predictions have altered our modern society and 3/4 of the way through we’ve progressed from 1960 to 1968. 2 starts because I enjoyed reading about jfk and his brush with predictive analytics especially as our presidential election shitstorm is happening!
October 22, 2020
I have a great deal of respect for jill lepore. I’ve read two other books she wrote, and I definitely agree with her position on the current state of affairs in america.
This book, on the history of the simulatics corporation, was boring. I kept waiting for the hook, but it just kept droning on about this company which is loosely tied to the dawn of ARPANET (the earliest internet), and some crossover between the players and concepts of simulmatics and of ARPA. But there was really nothing compelling or interesting about the history of simulmatics corp, including its unweildy name. Maybe some gossipy tidbits about the founders’ failed marriages - who cares?
In the final chapter, there is a bit of synthesis, a thread that runs between the first 310 pages and the point we find ourselves at today with predictive data being used in politics and marketing and business development. It was mildly interesting, but not enough to justify the bore that went before.
If I didn’t have so much respect for Ms. Lepore and the high quality of her writing and research, this would have been a 2-star review.
This book, on the history of the simulatics corporation, was boring. I kept waiting for the hook, but it just kept droning on about this company which is loosely tied to the dawn of ARPANET (the earliest internet), and some crossover between the players and concepts of simulmatics and of ARPA. But there was really nothing compelling or interesting about the history of simulmatics corp, including its unweildy name. Maybe some gossipy tidbits about the founders’ failed marriages - who cares?
In the final chapter, there is a bit of synthesis, a thread that runs between the first 310 pages and the point we find ourselves at today with predictive data being used in politics and marketing and business development. It was mildly interesting, but not enough to justify the bore that went before.
If I didn’t have so much respect for Ms. Lepore and the high quality of her writing and research, this would have been a 2-star review.
December 23, 2020
Jill Lepore is a very good writer. I realized this is the fourth of her books I have read. She is also an eminent American historian. This was a fascinating look at the early events leading up to the internet as we know it today. Because she is an historian she has lots of details and names that needed recording but at times left me near yawning. I understand the mission though and am glad she included the parts I was not astute enough to acknowledge as important. She ties everything together toward the end of the book. The last chapter and her epilogue was the big red bow on the book. Almost anyone with a computer, facebook account or other interaction in today's world (everyone) should enjoy this history.
June 6, 2021
Long before political campaigns manipulated people with Facebook and Cambridge Analytica, there was another company trying the same thing. Simulmatics built what they called a "People Machine" to try to predict how people would respond to various scenarios. They claimed success in helping JFK win the presidency. They went on to have much less success predicting the outcomes of strategies in the war in Vietman and predicting riots in the USA. (Their work in Vietnam was particularly bad.) The company went boom and bust in about 10 years. While it was controversial in its day, spawning protests and inspiring SF books like Simulacron 3 and The 480, they are mostly forgotten today.
I found it fascinating to read about people trying to do this sort of thing with computers using punch cards, magnetic tape, and getting data from opinion surveys. It was also interesting to see how much presidential campaigns have changed. Back in the time of JFK, the votes in primaries were considered merely as opinion polls; the real decision was made at the convention. The presumed democratic nominee for 1960, Adlai Stevenson, wouldn't even state whether he was or was not running until the day of the convention.
This gave me more information about Simulmatics than I really needed. A book half as long would have been better for me. But that is just my preference. Jill Lepore did us all a great service by putting together this history.
I found it fascinating to read about people trying to do this sort of thing with computers using punch cards, magnetic tape, and getting data from opinion surveys. It was also interesting to see how much presidential campaigns have changed. Back in the time of JFK, the votes in primaries were considered merely as opinion polls; the real decision was made at the convention. The presumed democratic nominee for 1960, Adlai Stevenson, wouldn't even state whether he was or was not running until the day of the convention.
This gave me more information about Simulmatics than I really needed. A book half as long would have been better for me. But that is just my preference. Jill Lepore did us all a great service by putting together this history.
December 14, 2020
I'm not convinced the Simulmatics Corporation accomplished much of anything. This book rambles off historical events that Simulmatics was tied to, but at best only portrays this company and group of people as incompetent. I was thinking this 50 pages into the book, and the rest of the book only confirmed this to be true.
If you're looking for a history of companies, computers, and social scientists' involvement in swaying public opinion and decision making, this isn't it. I considered writing that this book was more of a guide of what not to do for future corporations looking to influence a population, but I didn't get that impression either. It was simply the story of a group of people that were more interested in making money and perhaps gaining some notoriety, while pretending to be social scientists and computer wizards.
The book is promoted as being a backstory to the Silicon Valley companies of today, but the author spends more time identifying all of the ways Simulmatics failed, and failed miserably. This is at least acknowledged in the last chapter, but then quickly overshadowed by the idea that these folks created the early version of some phycological-warfare machine we are prisoners of today. If anything, Simulmatics was a blip - a failed company in the list of attention merchants of time gone by. I'm not convinced this is a history of much at all besides greed.
I've rated the book so low for a few reasons. First, it truly felt like the author was trying to make a story out of nothing, and then never actually made the case that Simulmatics accomplished anything at all. Second, the author writes 330 pages filled with details that either derail the flow of the book or are just completely irrelevant, telling a story that could have been done in a podcast episode. Finally, the story the author was trying to convey never actually came across. When I finished the book, I went and re-read the flaps, and quite frankly, they were the most interesting part of the book. I encourage potential readers to skip this one.
If you're looking for a history of companies, computers, and social scientists' involvement in swaying public opinion and decision making, this isn't it. I considered writing that this book was more of a guide of what not to do for future corporations looking to influence a population, but I didn't get that impression either. It was simply the story of a group of people that were more interested in making money and perhaps gaining some notoriety, while pretending to be social scientists and computer wizards.
The book is promoted as being a backstory to the Silicon Valley companies of today, but the author spends more time identifying all of the ways Simulmatics failed, and failed miserably. This is at least acknowledged in the last chapter, but then quickly overshadowed by the idea that these folks created the early version of some phycological-warfare machine we are prisoners of today. If anything, Simulmatics was a blip - a failed company in the list of attention merchants of time gone by. I'm not convinced this is a history of much at all besides greed.
I've rated the book so low for a few reasons. First, it truly felt like the author was trying to make a story out of nothing, and then never actually made the case that Simulmatics accomplished anything at all. Second, the author writes 330 pages filled with details that either derail the flow of the book or are just completely irrelevant, telling a story that could have been done in a podcast episode. Finally, the story the author was trying to convey never actually came across. When I finished the book, I went and re-read the flaps, and quite frankly, they were the most interesting part of the book. I encourage potential readers to skip this one.
December 15, 2022
Fantastic. Jill Lepore traces the use of 1950s and 1960s era mainframe computers (they fill a whole room! They use reel-to-reel magnetic tape as storage medium!) from their use as network TV gimmicks to project winners of Presidential elections, to their use by Presidential candidates (JFK was the first) to gauge the response of the electorate to certain planned public statements on the "big issues" and on "policy matters" (such as JFKs Catholicism or the Civil Rights policy planning to court the "black vote").
The theory of the book is that there is a direct line that can be drawn from computer projections of election results, to the advent of "big data," and to the predicted creation of (and now the actuality of) customized and networked circles of friends that form communities of similar minded people. Sound familiar? Sound like the dystopian hellscape of today that was played like a fiddle by Trump on social media?
The book's theory is that horrific and uncontrollable societal peril is put into play by the ability of machines, pre-loaded with actual, publicly available personal data on millions of people (like age, income, race, creed, color, zip code, shopping habits, political party affiliation, level of education), can predict how certain groups of the population, or "customized circles of friends or similar minded people" will behave, based on past actual data, when these like minded people are confronted with a given set of future variables (the election of a black man to the White House, for example).
This book will blow your mind. The factional, fragmented, walled-off silos of discontent and solidified (and often ill-founded) opinion holders that are degrading the social discourse today (Anti-vaxxer Fox News watchers, this means you) were predicted back then, when Ike was President, and when Adlai Stevenson, JFK, LBJ and Nixon were all mere potential candidates for the Presidency.
Eerie, accurate, and all too true. 5 Stars! Read this book!
The theory of the book is that there is a direct line that can be drawn from computer projections of election results, to the advent of "big data," and to the predicted creation of (and now the actuality of) customized and networked circles of friends that form communities of similar minded people. Sound familiar? Sound like the dystopian hellscape of today that was played like a fiddle by Trump on social media?
The book's theory is that horrific and uncontrollable societal peril is put into play by the ability of machines, pre-loaded with actual, publicly available personal data on millions of people (like age, income, race, creed, color, zip code, shopping habits, political party affiliation, level of education), can predict how certain groups of the population, or "customized circles of friends or similar minded people" will behave, based on past actual data, when these like minded people are confronted with a given set of future variables (the election of a black man to the White House, for example).
This book will blow your mind. The factional, fragmented, walled-off silos of discontent and solidified (and often ill-founded) opinion holders that are degrading the social discourse today (Anti-vaxxer Fox News watchers, this means you) were predicted back then, when Ike was President, and when Adlai Stevenson, JFK, LBJ and Nixon were all mere potential candidates for the Presidency.
Eerie, accurate, and all too true. 5 Stars! Read this book!
September 22, 2020
This book could have easily been subtitled as “The Age of Surveillance Capitalism: The Prequel” - or something similar, like “The Internet Behaving Badly, The Prequel”.
Jill Lepore provides a history of the Simulmatics Corp. which went into business to use data analysis to forecast the results of political campaigns and elections, so that candidates could learn about their electorate in detail on key issues and then fashion predictions about the results of speeches and other interventions. Get it? Use computer analyzed data to advantage and for a fee. This activity could potentially be expanded to a range of other activities, such as pacification programs in Vietnam, riot prediction and prevention in Vietnam, and even what types of products customers are likely to want and then purchase. Sounds promising, only these days were talk about the Internet, Big Data, and the broad tool kit of “Data Analytics”.
Professor Lepore tells the story of some enterprising behavioral scientists who worked on government related research projects in the Cold War era and then sought to apply their skills to serve other clients. The intent was to eliminate the guess work out of working with larger social groups and thus improve the results of new program initiatives and new products. The promise of the computer loomed large at the time, the work was engaging, and there was even potential for monetary rewards. A number of really extraordinary scholars were looped into this effort and Simulmatics seemed to be on the verge of defining key parts of American life in the Kennedy Administration. For books of the times, think “The Ugly American” and for movies think “Dr. Strangelove” and “Fail Safe”. This is the Cold War America before Vietnam, about which much was written on organization men, hidden persuaders, and other catch phrases. The principal characters in the book also come across as highly driven but also highly eccentric - not that different from the profiles of many more recent high technology pioneers.
Things did not work out as planned and Simulmatics did not become a legendary firm, as the FAANG companies have. In trying to figure out the train wreck, there appear to be multiple causes. A first issue was data - especially finding sufficient quantities of the right types and at reasonable expense. There were other issues as well.
A second problem is that academics, including enterprising ones, are not always very handy or concerned with the operational details of projects. To have much of a chance for success, the firm’s projects needed much more funding and scale.
A third problem was one of theory. The presumption of these projects (and lots of projects today) is that the facts will speak for themselves. That has never been the case, such that when an analysis is completed, determining what it means and what to do about results is unclear. Solving this problem involves working with actual decision makers and actually understanding some really complex statistical techniques, of which regression analysis is just a beginning. The details of prediction / simulation models matter.
A fourth problem was competition. The analytic knowledge and capabilities were widely enough disbursed and more than a few firms had some datasets that could prove valuable. High margins were not likely to be sustainable.
Finally, in retrospect it is clear that a well functioning network of linked computers was necessary and that particular data centers were not going to be successful. This includes the power of the computers as well, and nobody was talking about “Moore’s Law” back in the 1950s and 1960s. The technology was not up to the task; the time was not right.
This story is interesting on its own terms but I especially like how Professor Lepore ties together the Simulmatics story with the subsequent development of the Internet and the tech boom that is still reshaping the world today. A key part of the story is the growth of public sentiment against Simulmatics and its analytic ambitions in the course of its work with DoD during the Vietnam war. It is fascinating how these public concerns newer quite went away, although they were somewhat attenuated, and have recently re-emerges with concerns about the growing and unchecked power of the FAANG firms, the integrity of US elections, and the loss of personal data primacy. There is a clear continuity between Simulmatics and the present and Professor Lepore is effective at elaborating it.
In reading the book, I wondered if there were any parallel stories that developed along with the story of Simulmatics. What comes to mind is the story of the “Whiz Kids”, profiled by John Byrne in a 1983 book, who worked with the military in WW2 to apply techniques of what became operations research and then applied it to large industrial firms (Ford) with mixed results. These stories would come together under Robert McNamara in Vietnam.
I am glad Professor Lepore is so prolific and look forward to her books.
Jill Lepore provides a history of the Simulmatics Corp. which went into business to use data analysis to forecast the results of political campaigns and elections, so that candidates could learn about their electorate in detail on key issues and then fashion predictions about the results of speeches and other interventions. Get it? Use computer analyzed data to advantage and for a fee. This activity could potentially be expanded to a range of other activities, such as pacification programs in Vietnam, riot prediction and prevention in Vietnam, and even what types of products customers are likely to want and then purchase. Sounds promising, only these days were talk about the Internet, Big Data, and the broad tool kit of “Data Analytics”.
Professor Lepore tells the story of some enterprising behavioral scientists who worked on government related research projects in the Cold War era and then sought to apply their skills to serve other clients. The intent was to eliminate the guess work out of working with larger social groups and thus improve the results of new program initiatives and new products. The promise of the computer loomed large at the time, the work was engaging, and there was even potential for monetary rewards. A number of really extraordinary scholars were looped into this effort and Simulmatics seemed to be on the verge of defining key parts of American life in the Kennedy Administration. For books of the times, think “The Ugly American” and for movies think “Dr. Strangelove” and “Fail Safe”. This is the Cold War America before Vietnam, about which much was written on organization men, hidden persuaders, and other catch phrases. The principal characters in the book also come across as highly driven but also highly eccentric - not that different from the profiles of many more recent high technology pioneers.
Things did not work out as planned and Simulmatics did not become a legendary firm, as the FAANG companies have. In trying to figure out the train wreck, there appear to be multiple causes. A first issue was data - especially finding sufficient quantities of the right types and at reasonable expense. There were other issues as well.
A second problem is that academics, including enterprising ones, are not always very handy or concerned with the operational details of projects. To have much of a chance for success, the firm’s projects needed much more funding and scale.
A third problem was one of theory. The presumption of these projects (and lots of projects today) is that the facts will speak for themselves. That has never been the case, such that when an analysis is completed, determining what it means and what to do about results is unclear. Solving this problem involves working with actual decision makers and actually understanding some really complex statistical techniques, of which regression analysis is just a beginning. The details of prediction / simulation models matter.
A fourth problem was competition. The analytic knowledge and capabilities were widely enough disbursed and more than a few firms had some datasets that could prove valuable. High margins were not likely to be sustainable.
Finally, in retrospect it is clear that a well functioning network of linked computers was necessary and that particular data centers were not going to be successful. This includes the power of the computers as well, and nobody was talking about “Moore’s Law” back in the 1950s and 1960s. The technology was not up to the task; the time was not right.
This story is interesting on its own terms but I especially like how Professor Lepore ties together the Simulmatics story with the subsequent development of the Internet and the tech boom that is still reshaping the world today. A key part of the story is the growth of public sentiment against Simulmatics and its analytic ambitions in the course of its work with DoD during the Vietnam war. It is fascinating how these public concerns newer quite went away, although they were somewhat attenuated, and have recently re-emerges with concerns about the growing and unchecked power of the FAANG firms, the integrity of US elections, and the loss of personal data primacy. There is a clear continuity between Simulmatics and the present and Professor Lepore is effective at elaborating it.
In reading the book, I wondered if there were any parallel stories that developed along with the story of Simulmatics. What comes to mind is the story of the “Whiz Kids”, profiled by John Byrne in a 1983 book, who worked with the military in WW2 to apply techniques of what became operations research and then applied it to large industrial firms (Ford) with mixed results. These stories would come together under Robert McNamara in Vietnam.
I am glad Professor Lepore is so prolific and look forward to her books.
May 4, 2020
This traces the rise and fall of Simulmatics Corp., a fascinating slice of political, sociological, and computational history that I had never heard of. Which is interesting because I know a few things about all three sectors, but this data science startup, launched in the 1950s and bankrupt by the end of the '60s, was a new piece of the puzzle for me. And it really is, literally a piece of a lot of bigger things—algorithms, advertising, the big elections of the 1960s, efforts to quantify the Vietnam War and race riots, and the genealogy of big data and Cambridge Analytica, among other aspects. Very, very interesting and engaging.
November 16, 2020
This book was a real struggle to complete. I did so because of author Jill Lepore's excellent reputation as a writer. The book has stellar moments, particularly the epilogue. But much of it is completely useless trivia, irrelevant to the supposed thrust of the book. It felt like a couple of magazine articles bulked up (poorly) to book length. Cannot recommend.
November 18, 2020
The US media hailed the 2008 Obama Presidential campaign as the one that began the era of social media in political campaigns. Obama’s team deployed multiple social networking applications like Twitter and Facebook as part of their campaign outreach. These applications became a vehicle to raise money and target voters at a micro-level to get out the vote. Social media became a powerful medium to counter smear campaigns. It enabled Obama to topple the Clinton challenge in the primaries and then John McCain in the presidential election. Eight years later, Donald Trump won in 2016 against all predictions of a comfortable win for Hillary Clinton. It shocked the Democrats, and they laid the blame on Russian hackers and a British political consulting firm called Cambridge Analytica. What was Cambridge Analytica’s crime? It harvested private information from the Facebook profiles of over fifty million users, making it one of the largest data heist in Facebook’s history. It let Cambridge Analytica mine the private social media activity of these American citizens. With algorithms developed at Cambridge Analytica, they helped the Trump campaign in 2016. Like Obama in 2008, Cambridge Analytica claimed they helped Trump win.
How accurate are the claims of the Obama campaign and Cambridge Analytica that their social media initiatives propelled their clients to victory? We cannot conclusively prove that social media outreach made a crucial difference. Other explanations could be equally valid. Perhaps Americans, tired of eight years of war in Afghanistan and Iraq, were ready for a change. They may have voted for Obama even without the social media campaign. In 2016, we know that a majority of white conservatives, poor working-class men, and rural Americans voted for Trump. They may have found the eight years of Obama as inimical to their future and were ready to turn up in numbers and vote Trump to power. They could have felt they were facing an existential dilemma. The outreach of Cambridge Analytica may have been superfluous. However, in the minds of people, all the commotion about Cambridge Analytica and Facebook made social media a superpower in electioneering. Democrats started clamoring for keeping Facebook and Twitter in check so we can protect democracy and stop manipulating the minds of voters. Most people now believe there is a new, sinister turn of democracy since social media arrived on the scene. Jill Lepore, author of this book, says this is nothing new. Gathering large amounts of data on voters, storing them on computers, applying algorithms to predict voter behavior, and advising political campaigns is not new. The Kennedy campaign against Nixon used it in 1960!
Back in 1954, in the early days of computers, Eugene Burdick and Harold Lasswell, two political scientists, studied the mathematics of mass persuasion. They tried to model the behavior of the American voter as a television-watching, shopping-cart pushing, Coke, or Pepsi drinking, Eisenhower-Nixon voter. In 1959, Ed Greenfield and Ithiel de Sola Pool co-founded a data science company called the Simulmatics Corporation. Its scientists had a grand, over-arching ambition of simulating human behavior and predicting the future. They wanted to achieve it by developing a computer program called ‘The People Machine’. It would work on a massive amount of data collected from a vast population. By running computer simulations on this data, Simulmatics wanted to predict election outcomes and forecast outcomes of wars. They hoped to predict race riots (it was the 1960s!), avert disasters, and affect consumer behavior. In short, they called it the ‘A-bomb of the social sciences’. The company’s first major project was to advise the Kennedy campaign in its 1960 bid for the presidency.
Ithiel de Sola Pool and Bill McPhee, the chief data scientists of Simulmatics, collected data from a hundred thousand surveys of Gallup and Roper. They focused on data between 1952 and 1958 at an interval of two years. The voters in these surveys were divided into 480 voter types, such as Midwestern, rural, Protestant, female, and more. They sorted the questions in the surveys into ‘fifty issue attitudes’ that included election returns from each of those years. The goal was to use this dataset of voters and issues as a macroscope. They called this program the ‘People Machine’. We could ask it any question about a move that a candidate might make. It would reply with how voters would respond to such a move, down to the tiniest segment of the electorate,
The 1960 election was a close one between Kennedy and Nixon. Race prejudice against Blacks and JFK’s Catholic religion were key issues. The People Machine advised JFK that he must confront the religious issue head-on. It might lose him some Protestant votes but gain Catholic and minority voters. It advised JFK to make a straightforward attack on race prejudice to get the Black vote. On the TV debates, Simulmatics prompted JFK to use his personable traits such as good looks, fervor, and humor to advantage. In November 1960, when JFK won narrowly by just about 18000 popular votes, Simulmatics claimed the People Machine made the difference in the JFK win. However, JFK’s close circle of advisers pointed out that the suggestions of ‘People Machine’ were commonplace political wisdom with the Kennedy team. But the publicity blitz ensured the People Machine got notoriety for getting JFK elected. Soon, questions arose about the dangers of so much of data collection to manipulate voters. What does it mean for democracy? What about privacy in an age of big data? Is information the actual power? The anxieties of today regarding social media were already echoing sixty years ago.
Notwithstanding the skepticism of Simulmatics’ impact in the JFK election, the obsession with data and prediction persisted. Ithiel de Sola Pool, co-founder of Simulmatics, used his connections and got a major contract for his company from the Pentagon. It was to assess the Pentagon’s counterinsurgency efforts to win the ‘hearts and minds’ of the South Vietnamese. After much effort, Simulmatics produced its assessments. But the Pentagon didn’t see substantial value in it and ended the contract. Simulmatics, however, persisted in its work by moving into the areas of counterinsurgency and the study of urban problems. They aimed to solve the ‘Black problem’ in American cities by building simulation models, called the Riot Prediction Machine. They tried to forecast possible urban riots in Harlem and Rochester, NY. The results were dubious here too. The company went bankrupt in 1970. With hindsight, one can say Simulmatics had only limited success in its ventures because the amount of data was insufficient. Besides, the computers were too slow for extensive simulation, and modeling of reality was incomplete. And then there was the fundamental problem of simulating human behavior and predicting the future based on this exercise!
Despite the mixed results from Simulmatics, acquisition of vast amounts of data, its analysis, and making predictions continued. The Defense departments inherited the approach. Bob McNamara, Secretary of Defense, was a quantitative specialist from Harvard. His team collected vast amounts of data on the war in Vietnam. It included the number of troops, ships, planes, helicopters, the size of the population, the body count, and the death ratio of soldiers in combat. Even the density of the Vietnamese mind and the price of rice were gathered! One day in 1967, McNamara’s men fed all this data into their program on the giant computer in the Pentagon. Then they asked, ‘when will the US win in Vietnam?’. After humming and hawing for a long while, the computer output ‘The US won in 1965’! So much for simulating human behavior and the prediction of the Future!
In early 1971, the US Army collected data and conducted surveillance on civil rights figures, anti-Vietnam war activists, and political dissidents. They stored the data on computers, treating American citizens as foreign combatants. The US Army seems to have done what the NSA did thirty years later. There was no Edward Snowden to expose it in the 1970s. But there was Daniel Ellsberg, who exposed the truth on the Vietnam War with the Pentagon Papers.
We would be mistaken if we conclude Simulmatics was a total failure. The company had many bright engineers and scientists. Its founders did pioneering things in using computers in the social sciences. They pioneered pattern detection and prediction in political campaigns. In advertising, they launched targeting consumers with customized messages. Fifty years on, the field of ‘predictive analysis’ today is in effect a rebranding of the methods used by Simulmatics. The field was worth a market size of $4.6 billion in 2017 and expected to grow to reach $12.4 billion by 2022.
Ithiel de Sola Pool, as part of his work in Simulmatics, predicted the coming communication revolution. He foresaw information like tax returns, social security records, criminal and hospital records, and credit ratings being stored digitally and processed in the next few decades. Pool also envisaged computers communicating with one another over a vast international network. He said people could find out anything about anyone without leaving their desks in fifty years - i.e., by 2018! Pool was not alone in being prescient in the 1960s about such technology. Paul Baran, a computer scientist with the RAND Corporation, testified in the Congressional hearings of Cornelius Gallagher on Data Privacy. He predicted data would in the future get aggregated into ‘big data’ with or without the federal government. He explained computers would all be connected in future into a vast network of networks. So, it wouldn’t matter whether we hold data in one node or elsewhere across the country. Baran prophetically advised Congress to set up ethical guidelines, safeguards, and rules regarding ownership of data. It is important to identify who owns the data, the obligations of the holder, whether they can share it or sell it. It is amazing to see that Paul Baran was such a visionary in 1966.
Though the book deals with the rise and fall of the Simulmatics Corporation, it includes historical accounts of the United States of the 1950s and 60s. It has brief profiles of Adlai Stevenson, Richard Nixon, and JFK as part of this narrative. Stevenson emerges as a decent, intellectual leader and politician while Nixon and JFK fare worse. They appear ruthless, crafty, and somewhat opportunistic politicians. The book covers the Vietnam war in some detail, along with the anti-war protests and demonstrations in the late 1960s. The civil rights movement and the race riots in US cities also find their due. I found the tales and descriptions of those times highly educational and fascinating.
Author Jill Lepore closes the book with some profound observations about the arrogance of ignoring history and trumpeting how important the future is. Silicon Valley technocrats today talk about the irrelevance of history in technology. They believe the only thing that matters is the future. Jill Lepore says sharply that this is a cockeyed idea and not even original. She follows with, “it is a creaky, bankrupt Cold-War idea, an exhausted and discredited idea. Inventing the future has a history, decades-old, dilapidated. Simulmatics is its cautionary tale, a time-worn fable. Because tomorrow is not all that matters. Nor is technology, or the next president. What matters would be what remains, endures and cures”.
I loved reading this gripping book and strongly recommend it for everyone interested in technology, history, social science, or behavioral science.
How accurate are the claims of the Obama campaign and Cambridge Analytica that their social media initiatives propelled their clients to victory? We cannot conclusively prove that social media outreach made a crucial difference. Other explanations could be equally valid. Perhaps Americans, tired of eight years of war in Afghanistan and Iraq, were ready for a change. They may have voted for Obama even without the social media campaign. In 2016, we know that a majority of white conservatives, poor working-class men, and rural Americans voted for Trump. They may have found the eight years of Obama as inimical to their future and were ready to turn up in numbers and vote Trump to power. They could have felt they were facing an existential dilemma. The outreach of Cambridge Analytica may have been superfluous. However, in the minds of people, all the commotion about Cambridge Analytica and Facebook made social media a superpower in electioneering. Democrats started clamoring for keeping Facebook and Twitter in check so we can protect democracy and stop manipulating the minds of voters. Most people now believe there is a new, sinister turn of democracy since social media arrived on the scene. Jill Lepore, author of this book, says this is nothing new. Gathering large amounts of data on voters, storing them on computers, applying algorithms to predict voter behavior, and advising political campaigns is not new. The Kennedy campaign against Nixon used it in 1960!
Back in 1954, in the early days of computers, Eugene Burdick and Harold Lasswell, two political scientists, studied the mathematics of mass persuasion. They tried to model the behavior of the American voter as a television-watching, shopping-cart pushing, Coke, or Pepsi drinking, Eisenhower-Nixon voter. In 1959, Ed Greenfield and Ithiel de Sola Pool co-founded a data science company called the Simulmatics Corporation. Its scientists had a grand, over-arching ambition of simulating human behavior and predicting the future. They wanted to achieve it by developing a computer program called ‘The People Machine’. It would work on a massive amount of data collected from a vast population. By running computer simulations on this data, Simulmatics wanted to predict election outcomes and forecast outcomes of wars. They hoped to predict race riots (it was the 1960s!), avert disasters, and affect consumer behavior. In short, they called it the ‘A-bomb of the social sciences’. The company’s first major project was to advise the Kennedy campaign in its 1960 bid for the presidency.
Ithiel de Sola Pool and Bill McPhee, the chief data scientists of Simulmatics, collected data from a hundred thousand surveys of Gallup and Roper. They focused on data between 1952 and 1958 at an interval of two years. The voters in these surveys were divided into 480 voter types, such as Midwestern, rural, Protestant, female, and more. They sorted the questions in the surveys into ‘fifty issue attitudes’ that included election returns from each of those years. The goal was to use this dataset of voters and issues as a macroscope. They called this program the ‘People Machine’. We could ask it any question about a move that a candidate might make. It would reply with how voters would respond to such a move, down to the tiniest segment of the electorate,
The 1960 election was a close one between Kennedy and Nixon. Race prejudice against Blacks and JFK’s Catholic religion were key issues. The People Machine advised JFK that he must confront the religious issue head-on. It might lose him some Protestant votes but gain Catholic and minority voters. It advised JFK to make a straightforward attack on race prejudice to get the Black vote. On the TV debates, Simulmatics prompted JFK to use his personable traits such as good looks, fervor, and humor to advantage. In November 1960, when JFK won narrowly by just about 18000 popular votes, Simulmatics claimed the People Machine made the difference in the JFK win. However, JFK’s close circle of advisers pointed out that the suggestions of ‘People Machine’ were commonplace political wisdom with the Kennedy team. But the publicity blitz ensured the People Machine got notoriety for getting JFK elected. Soon, questions arose about the dangers of so much of data collection to manipulate voters. What does it mean for democracy? What about privacy in an age of big data? Is information the actual power? The anxieties of today regarding social media were already echoing sixty years ago.
Notwithstanding the skepticism of Simulmatics’ impact in the JFK election, the obsession with data and prediction persisted. Ithiel de Sola Pool, co-founder of Simulmatics, used his connections and got a major contract for his company from the Pentagon. It was to assess the Pentagon’s counterinsurgency efforts to win the ‘hearts and minds’ of the South Vietnamese. After much effort, Simulmatics produced its assessments. But the Pentagon didn’t see substantial value in it and ended the contract. Simulmatics, however, persisted in its work by moving into the areas of counterinsurgency and the study of urban problems. They aimed to solve the ‘Black problem’ in American cities by building simulation models, called the Riot Prediction Machine. They tried to forecast possible urban riots in Harlem and Rochester, NY. The results were dubious here too. The company went bankrupt in 1970. With hindsight, one can say Simulmatics had only limited success in its ventures because the amount of data was insufficient. Besides, the computers were too slow for extensive simulation, and modeling of reality was incomplete. And then there was the fundamental problem of simulating human behavior and predicting the future based on this exercise!
Despite the mixed results from Simulmatics, acquisition of vast amounts of data, its analysis, and making predictions continued. The Defense departments inherited the approach. Bob McNamara, Secretary of Defense, was a quantitative specialist from Harvard. His team collected vast amounts of data on the war in Vietnam. It included the number of troops, ships, planes, helicopters, the size of the population, the body count, and the death ratio of soldiers in combat. Even the density of the Vietnamese mind and the price of rice were gathered! One day in 1967, McNamara’s men fed all this data into their program on the giant computer in the Pentagon. Then they asked, ‘when will the US win in Vietnam?’. After humming and hawing for a long while, the computer output ‘The US won in 1965’! So much for simulating human behavior and the prediction of the Future!
In early 1971, the US Army collected data and conducted surveillance on civil rights figures, anti-Vietnam war activists, and political dissidents. They stored the data on computers, treating American citizens as foreign combatants. The US Army seems to have done what the NSA did thirty years later. There was no Edward Snowden to expose it in the 1970s. But there was Daniel Ellsberg, who exposed the truth on the Vietnam War with the Pentagon Papers.
We would be mistaken if we conclude Simulmatics was a total failure. The company had many bright engineers and scientists. Its founders did pioneering things in using computers in the social sciences. They pioneered pattern detection and prediction in political campaigns. In advertising, they launched targeting consumers with customized messages. Fifty years on, the field of ‘predictive analysis’ today is in effect a rebranding of the methods used by Simulmatics. The field was worth a market size of $4.6 billion in 2017 and expected to grow to reach $12.4 billion by 2022.
Ithiel de Sola Pool, as part of his work in Simulmatics, predicted the coming communication revolution. He foresaw information like tax returns, social security records, criminal and hospital records, and credit ratings being stored digitally and processed in the next few decades. Pool also envisaged computers communicating with one another over a vast international network. He said people could find out anything about anyone without leaving their desks in fifty years - i.e., by 2018! Pool was not alone in being prescient in the 1960s about such technology. Paul Baran, a computer scientist with the RAND Corporation, testified in the Congressional hearings of Cornelius Gallagher on Data Privacy. He predicted data would in the future get aggregated into ‘big data’ with or without the federal government. He explained computers would all be connected in future into a vast network of networks. So, it wouldn’t matter whether we hold data in one node or elsewhere across the country. Baran prophetically advised Congress to set up ethical guidelines, safeguards, and rules regarding ownership of data. It is important to identify who owns the data, the obligations of the holder, whether they can share it or sell it. It is amazing to see that Paul Baran was such a visionary in 1966.
Though the book deals with the rise and fall of the Simulmatics Corporation, it includes historical accounts of the United States of the 1950s and 60s. It has brief profiles of Adlai Stevenson, Richard Nixon, and JFK as part of this narrative. Stevenson emerges as a decent, intellectual leader and politician while Nixon and JFK fare worse. They appear ruthless, crafty, and somewhat opportunistic politicians. The book covers the Vietnam war in some detail, along with the anti-war protests and demonstrations in the late 1960s. The civil rights movement and the race riots in US cities also find their due. I found the tales and descriptions of those times highly educational and fascinating.
Author Jill Lepore closes the book with some profound observations about the arrogance of ignoring history and trumpeting how important the future is. Silicon Valley technocrats today talk about the irrelevance of history in technology. They believe the only thing that matters is the future. Jill Lepore says sharply that this is a cockeyed idea and not even original. She follows with, “it is a creaky, bankrupt Cold-War idea, an exhausted and discredited idea. Inventing the future has a history, decades-old, dilapidated. Simulmatics is its cautionary tale, a time-worn fable. Because tomorrow is not all that matters. Nor is technology, or the next president. What matters would be what remains, endures and cures”.
I loved reading this gripping book and strongly recommend it for everyone interested in technology, history, social science, or behavioral science.
January 7, 2022
Read this because I’m moving towards doing research in social game theory and thought I should understand some of the history. I spent a summer writing simulations of social norms evolving in populations so, well, this was pretty topical. The MIT media lab, which Lepore criticizes, is actually one of the places I applied to work, and the person I did research with in college has a lot of collaborators there.
So I feel kind of conflicted? I don’t have any deep insights about the truth of what Lepore says, and there are beaucoup du citations, so it’s all true. Is it lightly spiced up and not just pure analysis? Definitely. But it felt very carefully done. I actually think this book has taught me a huge amount about the 60s as a whole, given Simulmatics was so government tied.
Kind of sad that all these people in social science didn’t just … do science? Apparently Simulmatic’s had absolutely trash methods, as in they were just bad scientists, which honestly protected the world because Simulmatics just never delivered on their wild promises. Maybe if they just … did science, instead off trying to make money and influence high level US politics, then they would have made the world better, instead of worse? Or was their whole line of thinking pathological from the start?
I think this did impress upon me that computational tools have been on the verge of “doing everything” for a while. Lepore has a great quote from Marvin Minsky that he thought artificial general intelligence would be possible in a couple years, which he said in the 50s. I wonder if we’re currently repeating that little slice of history.
One thing I will say, and this is a paraphrase from the absolutely wonderful postdoc I worked with on my research in college, is that what we were doing, pure math research loosely inspired by social science, was basically art. It wasn’t really predictive, I mean no idea how you’d find the parameters for those models, it was more just qualitative. I like to think it was pretty fundamentally optimistic research too, as we were trying to find ways to induce the evolution of cooperation in populations of selfish agents. I wonder whether that sort of research will end up like Simulmatics. Hopefully not.
Sorry for the rant!
P. S. Wow these power hungry, egotistical men of Simulmatics were on a personal level just … terrible?
So I feel kind of conflicted? I don’t have any deep insights about the truth of what Lepore says, and there are beaucoup du citations, so it’s all true. Is it lightly spiced up and not just pure analysis? Definitely. But it felt very carefully done. I actually think this book has taught me a huge amount about the 60s as a whole, given Simulmatics was so government tied.
Kind of sad that all these people in social science didn’t just … do science? Apparently Simulmatic’s had absolutely trash methods, as in they were just bad scientists, which honestly protected the world because Simulmatics just never delivered on their wild promises. Maybe if they just … did science, instead off trying to make money and influence high level US politics, then they would have made the world better, instead of worse? Or was their whole line of thinking pathological from the start?
I think this did impress upon me that computational tools have been on the verge of “doing everything” for a while. Lepore has a great quote from Marvin Minsky that he thought artificial general intelligence would be possible in a couple years, which he said in the 50s. I wonder if we’re currently repeating that little slice of history.
One thing I will say, and this is a paraphrase from the absolutely wonderful postdoc I worked with on my research in college, is that what we were doing, pure math research loosely inspired by social science, was basically art. It wasn’t really predictive, I mean no idea how you’d find the parameters for those models, it was more just qualitative. I like to think it was pretty fundamentally optimistic research too, as we were trying to find ways to induce the evolution of cooperation in populations of selfish agents. I wonder whether that sort of research will end up like Simulmatics. Hopefully not.
Sorry for the rant!
P. S. Wow these power hungry, egotistical men of Simulmatics were on a personal level just … terrible?
November 10, 2021
Lepore tells a bracing tale of the mid century American liberals who first framed of the idea of creating computer simulations to model human behavior, using the comet-like rise and fall of the long-forgotten Simulmatics Corporation as the through-line on which to hang her narrative. The book is at its strongest on two fronts. First, Lepore excels in creating acid pen portraits of the men in question, from Ed Greenfield, the Madison Avenue advertising empresario who would be Simulmatics’ bibulous and financially reckless CEO; to Ithiel de Sola Pool, the DoD consultant and visionary of unregulated technology, the child of a rabbi who swapped his Old Testament religion for the new religion of muscular Cold War liberalism; to Eugene Burdick, the glamorous Berkeley political scientist and creator of romans à clef for liberal idealists. Her strength here lies above all in tying these men’s professional ambitions, habits and blindspots back to their blinkered domestic lives, with typically postwar “Feminine Mystique”-struggling wives who they mainly ignored, abused, or cheated on. While Lepore’s narrative is about the world the men tried to make, her sympathetic view of how it all looked to their wives, who themselves are sensitively portrayed, is a major thing that sets this book apart. As a portrait of the dreams and ultimately crippling contradictions of postwar (especially white male intellectual elite) liberals, there may be no better book.
Second, Lepore does a marvelous job of capturing the peculiar simultaneities of the postwar era, with the Montgomery Bus Boycott, for example, unfolding in the same summer as the legendary Dartmouth summer seminar that coined the term “artificial intelligence”; or the parallel hotel events in 1972 in Washington, one which involves Nixon’s men burglarizing the Watergate headquarters of the DNC and the other at the Hilton where the first public demo of ARPANET took place. The parallels capture the way in which different historical patterns are always unfolding in parallel, and that what seems momentous at the time may turn out to be fading headline, while was ignored at the time turns out to have been prophetic. Methodologically, moreover, these simultaneities underscore that deep and perhaps impossible challenge associated with trying to do long term prediction via simulation: what is the relevant data that one should be feeding into the models? The answer to which has to do with (always fallible) judgments about what in the present do we believe will be most important in the future.
On a less positive note, however, the book is framed around a normative conceit which is dubious to say the least and arguably a form of special pleading. Lepore argues that what the Simulmatics crew was trying to do would ultimately be realized in horrifying form in what her even more polemical Harvard colleague Shoshona Zuboff calls “The Age of Surveillance Capitalism.” And alas, WHAT IF suffers from the same fatal intellectual problem as Zuboff’s screed: the formal and utterly unjustified assertion of anthropocentric exceptionalism. Lepore concedes that modeling is great for improving everything from weather forecasting to aircraft safety to public health, but insists (on no basis), that, “The study of the human condition is not the same as the study of the spread of viruses and the density of clouds and the movement of the stars. Human nature does not follow laws like the law of gravity, and to believe that does is to take the oath to a new religion.” To which one must reply: this is only true insofar as what Lepore is doing is even more accurately portrayed as a defense of an OLD religion.
This claim also confuses two things: it is one thing to say that building machines that are completely able to predict our behavior creates terrible possibilities of political control (possibilities she rightly points out that her historical characters looked forward to with great hope, as promising a way for elites to guide the unreliable masses); it is altogether another and much more dubious thing to assert that such predictions are impossible because humans in fact are radically different from every other sort of thing in the world — which is precisely the old religion that Lepore (and Zuboff) quite explicitly defends. As it doesn’t for Zuboff, never does it seem to occur to Lepore that the alleged threat of the former — that is, a society of total control through machines — is only possible if the latter is in fact false, or conversely that if human behavior is in fact NOT modellable and simulatable, then the fears of totalitarian control through these models is not something we need to worry about, since human unruliness will always exceed the machine. In other words, you can’t have it both ways, but the assertion of human exceptionalism traps you in trying to.
In the end, however, these normative contradictions don’t detract much from the rollicking good tale that Lepore tells about a series of at once technically visionary and socially blinkered men who indeed both spyed and limned the simulation-directed future that we all live in today.
Second, Lepore does a marvelous job of capturing the peculiar simultaneities of the postwar era, with the Montgomery Bus Boycott, for example, unfolding in the same summer as the legendary Dartmouth summer seminar that coined the term “artificial intelligence”; or the parallel hotel events in 1972 in Washington, one which involves Nixon’s men burglarizing the Watergate headquarters of the DNC and the other at the Hilton where the first public demo of ARPANET took place. The parallels capture the way in which different historical patterns are always unfolding in parallel, and that what seems momentous at the time may turn out to be fading headline, while was ignored at the time turns out to have been prophetic. Methodologically, moreover, these simultaneities underscore that deep and perhaps impossible challenge associated with trying to do long term prediction via simulation: what is the relevant data that one should be feeding into the models? The answer to which has to do with (always fallible) judgments about what in the present do we believe will be most important in the future.
On a less positive note, however, the book is framed around a normative conceit which is dubious to say the least and arguably a form of special pleading. Lepore argues that what the Simulmatics crew was trying to do would ultimately be realized in horrifying form in what her even more polemical Harvard colleague Shoshona Zuboff calls “The Age of Surveillance Capitalism.” And alas, WHAT IF suffers from the same fatal intellectual problem as Zuboff’s screed: the formal and utterly unjustified assertion of anthropocentric exceptionalism. Lepore concedes that modeling is great for improving everything from weather forecasting to aircraft safety to public health, but insists (on no basis), that, “The study of the human condition is not the same as the study of the spread of viruses and the density of clouds and the movement of the stars. Human nature does not follow laws like the law of gravity, and to believe that does is to take the oath to a new religion.” To which one must reply: this is only true insofar as what Lepore is doing is even more accurately portrayed as a defense of an OLD religion.
This claim also confuses two things: it is one thing to say that building machines that are completely able to predict our behavior creates terrible possibilities of political control (possibilities she rightly points out that her historical characters looked forward to with great hope, as promising a way for elites to guide the unreliable masses); it is altogether another and much more dubious thing to assert that such predictions are impossible because humans in fact are radically different from every other sort of thing in the world — which is precisely the old religion that Lepore (and Zuboff) quite explicitly defends. As it doesn’t for Zuboff, never does it seem to occur to Lepore that the alleged threat of the former — that is, a society of total control through machines — is only possible if the latter is in fact false, or conversely that if human behavior is in fact NOT modellable and simulatable, then the fears of totalitarian control through these models is not something we need to worry about, since human unruliness will always exceed the machine. In other words, you can’t have it both ways, but the assertion of human exceptionalism traps you in trying to.
In the end, however, these normative contradictions don’t detract much from the rollicking good tale that Lepore tells about a series of at once technically visionary and socially blinkered men who indeed both spyed and limned the simulation-directed future that we all live in today.
November 30, 2020
Gosh, where to start? This book should have been written just for me. I suspect there aren't many readers of the book who can pick off their shelf an original copy of de Sola Pool's Candidates, Issues and Strategies which sits next the Paul Ableson's Voting. Candidates, Issues and Strategies was a seminal book for me, along with A J Allen's The English Voter. The two combined set me off on the road to a politics degree and a market reserch career, though not in polling.
I'm afraid Lepore's writing style is not for me. The pages drip with a non-numerate liberal east-coast condescension, which persists even as the book moves beyond the 1960 election and into the Vietnam period. There's a huge amount of banal and superflous description, and ascription of motives, often repetitive ('wanted, wanted, wanted'). For someone who seems to have constructed the book from a thorough scrabbling around in boxes of Pool's and others papers, she resorts to 'might have', 'probably said' and other such phrases far too often, imputing, in a very lazy way, base motives wherever possible. The author's dislike of practically everyone in the story comes across on every page. It was a real, exasperating, struggle to read this, even though I had no idea about the later life and activities of de Sola Pool. A great disappointment.
I'm afraid Lepore's writing style is not for me. The pages drip with a non-numerate liberal east-coast condescension, which persists even as the book moves beyond the 1960 election and into the Vietnam period. There's a huge amount of banal and superflous description, and ascription of motives, often repetitive ('wanted, wanted, wanted'). For someone who seems to have constructed the book from a thorough scrabbling around in boxes of Pool's and others papers, she resorts to 'might have', 'probably said' and other such phrases far too often, imputing, in a very lazy way, base motives wherever possible. The author's dislike of practically everyone in the story comes across on every page. It was a real, exasperating, struggle to read this, even though I had no idea about the later life and activities of de Sola Pool. A great disappointment.
January 24, 2022
While reading this book, I often found myself astonished, less by the story itself, but moreso by the craft of Jill Lepore in recognizing and compiling this story.
This is a masterful work of history, in that it uncovers a story that continues to have real implications for our present moment, yet has, up to this point, been criminally overlooked (due in no small part to tech's general apathy for the past). Also, she was able to rely on interviews with those who are still around, who has had the time to experience and reflect on the legacy of their work. Meaning it is a work of history that has also contributed new knowledge to that history.
This sense of discovery was palpable throughout the book and Lepore's writing. And I am glad that this significant piece of history has been brought to light. Our society has been fundamentally reshaped by the influence of Big Data, and it's important that we understand how those in the past dealt with similar dilemmas, which course they took, and did not take, and what was lost along the way.
This is a masterful work of history, in that it uncovers a story that continues to have real implications for our present moment, yet has, up to this point, been criminally overlooked (due in no small part to tech's general apathy for the past). Also, she was able to rely on interviews with those who are still around, who has had the time to experience and reflect on the legacy of their work. Meaning it is a work of history that has also contributed new knowledge to that history.
This sense of discovery was palpable throughout the book and Lepore's writing. And I am glad that this significant piece of history has been brought to light. Our society has been fundamentally reshaped by the influence of Big Data, and it's important that we understand how those in the past dealt with similar dilemmas, which course they took, and did not take, and what was lost along the way.
August 28, 2022
Lepore shows the reader all aspects—including the families, the opining, the chronicling, the ethical dilemmas, the data collection, the war gaming— that formed the early days of Big Data practices and new media. The book demonstrates how computers and predictive analytics have lurked behind every twist and turn of the last 70 years, well before social media ever entered our minds. If/then is also a story of culture and politics, of governance, of democracy, of polarization, of Vietnam, and of how America lost its mind in the 60s. Sometimes the writing drags on a bit, but still 100% recommend.
May 16, 2021
"Simulmatics failed, but not before its scientists built a very early version of the machine in which humanity would in the early twenty-first century find itself trapped, a machine that applies the science of psychological warfare to the affairs of ordinary life, a machine that manipulates opinion, exploits attention, commodifies information, divides voters, fractures communities, alienates individuals and undermines democracy."
This book is long and at some points overwritten but it's an incredible research effort by Lepore and an even more incredible story.
This book is long and at some points overwritten but it's an incredible research effort by Lepore and an even more incredible story.
October 8, 2020
Proof that American tech solutionism has always quickly arrived at behaviour change as one of its objectives.
At the end, Lepore has you believe that Facebook-Amazon-Netflix-Google is the outcome of a way of looking at the world that preceded these companies by decades. The book carries a sense of loss with regards to how tech solutionism, despite being sustained by government dollar, escaped the government's oversight (and became its own government, if you like). Lepore traces this to one of the many beginnings, inviting us to find answers in where it all went wrong.
At the end, Lepore has you believe that Facebook-Amazon-Netflix-Google is the outcome of a way of looking at the world that preceded these companies by decades. The book carries a sense of loss with regards to how tech solutionism, despite being sustained by government dollar, escaped the government's oversight (and became its own government, if you like). Lepore traces this to one of the many beginnings, inviting us to find answers in where it all went wrong.
If, then, long ago, Simulmatics had not undertaken this work, it would have been done by someone else. But if, then, someone else had done it, it might have been done differently.
October 20, 2020
Jill Lepore is one of the most interesting historians working today. If Then chronicles a period in our history that has become a forgotten footnote in most ways, but which underpins almost everything that has led to the world we now live in. Just when we start to think some ideas are "new" someone turns over a page, a rock, a leaf and reveals that, no, this idea began much longer ago than we remembered.
Highly recommended.
Highly recommended.
July 22, 2022
A brilliant book about one companies oversized promises, and actualities really predicted so much of what we now face. Its the 1/2 point between the data realities of 'IBM and the Holocaust' and now. Insightful, well researched, and incredibly well written.
November 17, 2020
Not the most riveting of Jill Lepore's books (for that, try her books about Jane Franklin or the history of Wonder Woman), but "If Then" is definitely an interesting piece of the history of how humans eventually just became part of a predictable series of algorithms. What Simulmatics was doing circa 1960 is sort of the prototype of what all tech does now with the personal data that we users willingly hand over in our infatuation with gizmos and convenience. I wish the book had been more clear on what this is all really about: the arrogance of tech that is built into this sort of data mining. Anyhow, the book is thorough, and kind of a slog. Big surprise at the end: the last 100 pages are notes. (Hooray! I was ready to be done. Wonder if this might have worked better as a long two-parter in the New Yorker, where Lepore is a staff writer?)
December 22, 2020
Somewhere in the promotional copy for If Then: How the Simulmatics Corporation Invented the Future, I came across the name Eugene Burdick. I first discovered that name not long after the events covered in the first third of this book. In junior high school, I discovered the book Fail-Safe which was co-written by Burdick and that led me to his co-written The Ugly American. I had to find out what this author of political thrillers had to do with the information technology industry (before it was called that). Strangely, I never encountered his The Ninth Wave or The 480 which would have been very relevant to this subject, but I did read Simulacron-3 in high school (a science-fiction novel that inspired some of the principals in building their model-p. 13). I also learned that Stanley Kubrick filed suit against Burdick and his co-writer for Fail-Safe, claiming a similarity to a British novel about nuclear confrontation that wasn’t really there, so he could delay the film version of Fail-Safe till after Dr. Strangelove: How I Stopped Worrying and Learned to Love the Bomb was released (p. 178). The material on Burdick was interesting but it wasn’t the main course for this history.
If Then: How the Simulmatics Corporation Invented the Future is a story of the bleeding edge in the use of computing, the ragged edge of using statistics in sociology, and the portentous edge in diffusion study. The story is initially tied to politics. It starts among supporters of Illinois Governor Adlai Stevenson II (“Madly for Adlai” versus “I Like Ike”), despite the governor’s own skepticism about the process: “’Better we lose the election than mislead the people,’” he said, ‘and better we lose than misgovern the people.’” (p. 25) [I loved the little touches on p. 25 where Nixon as vice-presidential candidate calls the governor “Adlai the Appeaser” as though a Communist sympathizer and Stevenson calls Nixon, “McCarthyism in a white collar.”]
Despite creating the “People Machine,” Simulmatics modeling of political impact using past data mixed with poll data and analyzed via punch card input on a rented IBM 704, the model for quantitative analysis of political behavior never helped Stevenson. The method, largely built off the graduate and post-graduate work of three Stanford researchers, still makes an impact today. “At Stanford, Lasswell, Lerner, and Pool were trying to invent a kind of ideological radar that could detect the bleep, bleep, bleep of political unrest. (One way to think about this kind of content-analysis work is as a very early version of Google Trends, which also started at Stanford, in the graduate work of Larry Page and Sergey Brin.) (p. 62). And its impact was readily seen after its use in the 1960 election.
Social networks in the 1950s? Yes, part of the groundwork for the original model was researching the number of people necessary to have a group with an acquaintance in common (what became popularly known in the 1990s as " Six Degrees of Kevin Bacon”). “Pool and Kochen aimed to discover ‘through how many introductions would one have to go to get from person A to person B.’ Their justification was national defense: understanding social networks, Pool wrote in a funding proposal, would be useful for “decision-making, communication, morale, psychological warfare, and intelligence.” (pp. 84-85) Initially, one of the main attractions was: “…a simulated population, a miniature United States, consisting of three thousand perfectly representative but entirely imaginary people, living in one thousand separate households.” (p. 143) There is a lengthy quotation from British parody magazine Punch that highlights the complexity of what they were trying to do by taking it to the heights of the ridiculous: “…proposed that Simulmatics’ Media-Mix add a few more categories, including “dog-lover, flat-earther, doughnut dunker, milk-in-firster,…” (p. 144).
Now, while I remember the Cuban Missile Crisis of 1962, my junior high school experience in California didn’t initiate me to the realities of the 114- day newspaper strike in New York City that started in December of that year. While I wasn’t surprised to read about the economic effect of having no newspapers and, hence, no newspaper advertisements, I didn’t have any clue that the strike settlement included a clause against automation: “Automation is allowed to proceed to a certain extent but only in so far as it does not render any compositors redundant.” (p. 173).
The book chronicles Simulmatics’ fiscal instability, as well as using the computer simulation (administered by the same agency that would later help launch the Internet—ARPA) to analyze Soviet and Chinese influencers and decision-makers in psychological warfare (p. 174). The ARPA connection shouldn’t be surprising since the project’s inner core, working different shifts to optimize the time-sharing, invented email (p. 176). The psychological warfare project using the M.I.T. computer’s time-share mode weren’t technically a Simulmatics contract, but it used much of the same model, portions of the database, and researchers/programmers who were on and off actual Simulmatics projects (p. 175). Interestingly, this type of computer analysis was what had intrigued (previously mentioned) novelist and political science professor, Eugene Burdick, to become interested in what became Simulmatics in the first place (and write The Ninth Wave and The 480.
As someone who has chronicled around two decades of computer simulations for entertainment (and some educational) purposes, I’ve become increasingly aware of how assumptions in building the model can skew the results. Even in entertainment, GIGO (Garbage In-Garbage Out) is a basic consideration. But, it isn’t just problems with data collection and selection, it’s what the algorithms can do with the data that can make one take a wrong turn. In If Then: How the Simulmatics Corporation Invented the Future, we see where focusing on one’s model without allowing it to be modified by personal listening and observation. For example, in the Vietnam Conflict, the Department of Defense started a Strategic Hamlet Program. “Simulmatics also urged the development of ’a Hamlet Data Bank,’ a project that the Department of Defense adopted not long afterward, as the Hamlet Evaluation System, a data bank of everything known about every hamlet, updated constantly, updated instantly, a dynamic model.” (p. 229) As Lepore explains: “The Strategic Hamlet Program served as only the latest in a series of decades-old ’pacification’ schemes under which military forces urged and eventually forced South Vietnamese people off their land and into fortified hamlets, to be defended by the joint forces of the United States and the Army of the Republic of Vietnam, or ARVN (Ar-vin).” (p. 230) Of course, these hamlets could be considered concentration camps by another name. The data model perceived these as protected areas. The populace perceived them as armed custody. The computer results couldn’t tell the difference. The model figured hamlets were good; the people figured they were a bargain with the American devils at best. That’s only one example of how the simulation got matters wrong. The defense department ran a simulation in 1967, asking the question, “When will we win in Vietnam?” The answer read, “You won in 1965.” (p. 233)
At approximately the same time, behavioral scientists (including Simulmatics) were trying to predict race riots. A program out of St. Louis tracked “…income, crime, and population figures from 184 cities with a population of fifty thousand or more—to come up with a predictive scheme. He purported to divide cities into those that had already had riots and those that were in “pre-riot tension conditions.” (p. 267) When the predicted riots didn’t occur, the director of the project wrote: “Failure to predict actual riots in the cases above shows considerable localization; intensive analysis may well determine that the composite variables are not yet sufficiently detailed to account for older non-white migration patterns.” (p. 267)
The books walks us through protests against the Vietnam War and the Nixon years, taking Simulmatics Corporation into bankruptcy. Yet, Jill Lepore does a great job of demonstrating how these efforts, many of them seeming to be failures, brought us to the era of the internet and the use of “big data” in analytics similar to what these pioneers tried to accomplish. Indeed, Lepore informs us that Simulmatics used the term “massive data” where today’s computer scientists speak of “big data.” (p. 282)
One story to which I was completely unaware was the original idea of forming a National Data Center, killed before it occurred over, appropriately enough, ethical and privacy concerns (p. 285). But the humorous (to me) part of the story was when student protestors at MIT confused ARPANET, the predecessor to the internet, with that once-proposed National Data Center (p. 299). Why is that humorous? It is humorous to me because the very people who were protesting in 1969 became strong advocates of the internet in the 1990s.
If Then: How the Simulmatics Corporation Invented the Future is a marvelous blend of late 20th century history combined with a corporation that made great impact without gaining the reward. And, even though I only covered a narrow part of the computer industry (entertainment), the book dealt with a few people that I had met or known personally. For me, it was fascinating. Since I also gave a copy of this as a gift, I hope it is fascinating to others, as well.
If Then: How the Simulmatics Corporation Invented the Future is a story of the bleeding edge in the use of computing, the ragged edge of using statistics in sociology, and the portentous edge in diffusion study. The story is initially tied to politics. It starts among supporters of Illinois Governor Adlai Stevenson II (“Madly for Adlai” versus “I Like Ike”), despite the governor’s own skepticism about the process: “’Better we lose the election than mislead the people,’” he said, ‘and better we lose than misgovern the people.’” (p. 25) [I loved the little touches on p. 25 where Nixon as vice-presidential candidate calls the governor “Adlai the Appeaser” as though a Communist sympathizer and Stevenson calls Nixon, “McCarthyism in a white collar.”]
Despite creating the “People Machine,” Simulmatics modeling of political impact using past data mixed with poll data and analyzed via punch card input on a rented IBM 704, the model for quantitative analysis of political behavior never helped Stevenson. The method, largely built off the graduate and post-graduate work of three Stanford researchers, still makes an impact today. “At Stanford, Lasswell, Lerner, and Pool were trying to invent a kind of ideological radar that could detect the bleep, bleep, bleep of political unrest. (One way to think about this kind of content-analysis work is as a very early version of Google Trends, which also started at Stanford, in the graduate work of Larry Page and Sergey Brin.) (p. 62). And its impact was readily seen after its use in the 1960 election.
Social networks in the 1950s? Yes, part of the groundwork for the original model was researching the number of people necessary to have a group with an acquaintance in common (what became popularly known in the 1990s as " Six Degrees of Kevin Bacon”). “Pool and Kochen aimed to discover ‘through how many introductions would one have to go to get from person A to person B.’ Their justification was national defense: understanding social networks, Pool wrote in a funding proposal, would be useful for “decision-making, communication, morale, psychological warfare, and intelligence.” (pp. 84-85) Initially, one of the main attractions was: “…a simulated population, a miniature United States, consisting of three thousand perfectly representative but entirely imaginary people, living in one thousand separate households.” (p. 143) There is a lengthy quotation from British parody magazine Punch that highlights the complexity of what they were trying to do by taking it to the heights of the ridiculous: “…proposed that Simulmatics’ Media-Mix add a few more categories, including “dog-lover, flat-earther, doughnut dunker, milk-in-firster,…” (p. 144).
Now, while I remember the Cuban Missile Crisis of 1962, my junior high school experience in California didn’t initiate me to the realities of the 114- day newspaper strike in New York City that started in December of that year. While I wasn’t surprised to read about the economic effect of having no newspapers and, hence, no newspaper advertisements, I didn’t have any clue that the strike settlement included a clause against automation: “Automation is allowed to proceed to a certain extent but only in so far as it does not render any compositors redundant.” (p. 173).
The book chronicles Simulmatics’ fiscal instability, as well as using the computer simulation (administered by the same agency that would later help launch the Internet—ARPA) to analyze Soviet and Chinese influencers and decision-makers in psychological warfare (p. 174). The ARPA connection shouldn’t be surprising since the project’s inner core, working different shifts to optimize the time-sharing, invented email (p. 176). The psychological warfare project using the M.I.T. computer’s time-share mode weren’t technically a Simulmatics contract, but it used much of the same model, portions of the database, and researchers/programmers who were on and off actual Simulmatics projects (p. 175). Interestingly, this type of computer analysis was what had intrigued (previously mentioned) novelist and political science professor, Eugene Burdick, to become interested in what became Simulmatics in the first place (and write The Ninth Wave and The 480.
As someone who has chronicled around two decades of computer simulations for entertainment (and some educational) purposes, I’ve become increasingly aware of how assumptions in building the model can skew the results. Even in entertainment, GIGO (Garbage In-Garbage Out) is a basic consideration. But, it isn’t just problems with data collection and selection, it’s what the algorithms can do with the data that can make one take a wrong turn. In If Then: How the Simulmatics Corporation Invented the Future, we see where focusing on one’s model without allowing it to be modified by personal listening and observation. For example, in the Vietnam Conflict, the Department of Defense started a Strategic Hamlet Program. “Simulmatics also urged the development of ’a Hamlet Data Bank,’ a project that the Department of Defense adopted not long afterward, as the Hamlet Evaluation System, a data bank of everything known about every hamlet, updated constantly, updated instantly, a dynamic model.” (p. 229) As Lepore explains: “The Strategic Hamlet Program served as only the latest in a series of decades-old ’pacification’ schemes under which military forces urged and eventually forced South Vietnamese people off their land and into fortified hamlets, to be defended by the joint forces of the United States and the Army of the Republic of Vietnam, or ARVN (Ar-vin).” (p. 230) Of course, these hamlets could be considered concentration camps by another name. The data model perceived these as protected areas. The populace perceived them as armed custody. The computer results couldn’t tell the difference. The model figured hamlets were good; the people figured they were a bargain with the American devils at best. That’s only one example of how the simulation got matters wrong. The defense department ran a simulation in 1967, asking the question, “When will we win in Vietnam?” The answer read, “You won in 1965.” (p. 233)
At approximately the same time, behavioral scientists (including Simulmatics) were trying to predict race riots. A program out of St. Louis tracked “…income, crime, and population figures from 184 cities with a population of fifty thousand or more—to come up with a predictive scheme. He purported to divide cities into those that had already had riots and those that were in “pre-riot tension conditions.” (p. 267) When the predicted riots didn’t occur, the director of the project wrote: “Failure to predict actual riots in the cases above shows considerable localization; intensive analysis may well determine that the composite variables are not yet sufficiently detailed to account for older non-white migration patterns.” (p. 267)
The books walks us through protests against the Vietnam War and the Nixon years, taking Simulmatics Corporation into bankruptcy. Yet, Jill Lepore does a great job of demonstrating how these efforts, many of them seeming to be failures, brought us to the era of the internet and the use of “big data” in analytics similar to what these pioneers tried to accomplish. Indeed, Lepore informs us that Simulmatics used the term “massive data” where today’s computer scientists speak of “big data.” (p. 282)
One story to which I was completely unaware was the original idea of forming a National Data Center, killed before it occurred over, appropriately enough, ethical and privacy concerns (p. 285). But the humorous (to me) part of the story was when student protestors at MIT confused ARPANET, the predecessor to the internet, with that once-proposed National Data Center (p. 299). Why is that humorous? It is humorous to me because the very people who were protesting in 1969 became strong advocates of the internet in the 1990s.
If Then: How the Simulmatics Corporation Invented the Future is a marvelous blend of late 20th century history combined with a corporation that made great impact without gaining the reward. And, even though I only covered a narrow part of the computer industry (entertainment), the book dealt with a few people that I had met or known personally. For me, it was fascinating. Since I also gave a copy of this as a gift, I hope it is fascinating to others, as well.
February 14, 2022
I am reviewing the audio book and the reading is very poorly executed by the author. It is not unusual for author’s to over estimate their skills and take on the role reading for the audio book. It is an interesting story with well considered information on the politics of the 1850s and 1960s taking center stage. The first psychographic profiling of the electorate combined with Madison Avenue and the dawn of computing makes for great subject matter. The parallels to our social media monster of today are very compelling, but for the authors delivery was a major distraction. Content really deserves a 4, but don’t do the audio book without listening f to Jill in an interview. You will then be able to make your own decision.
June 16, 2022
Read this for work ;)
December 29, 2020
I love modern history and computer science, so this book is right up my alley. In addition, it's extremely well written and engaging. At first, I was curious about why the author devoted so much time to Adlai Stevenson, but it all made sense by the middle of the book. And I was stunned to learn about the various attempts to use technology for social engineering in the sixties. Technologists, take heed: history matters.
October 5, 2020
Fascinating, not just for the story it purports to tell. Also about Vietnam, women’s history and the 1950’s in general. I couldn’t put it down. Great reporting, reaching from government documents to unknown wives’ letters to their mothers.
October 13, 2020
This is a history of the origins of what we now call “predictive analytics.” It is a rather disjointed history. The first hundred or so pages discuss, in a jumbled fashion, the dramatis personae of the story: a core of men drawn from business and academia who found common cause in promoting the presidential candidacies of Adlai Stevenson. They vowed to use the infant tools of computers and data collection to boost the election chances of the next Democrat to run for president (and, not insignificantly, to use those tools to make money) by identifying the voter groups necessary to achieve an election victory and the messages needed to attract them. They called their enterprise “Simulmatics” and they sought consulting business from corporations and government contracts. Theirs was a rather fly-by-night operation (they owned no computer hardware and their intellectual property seems scant), and the company had a string of failures performing shoddy work that included selling the New York Times a system that crashed in the course of making real-time projection of election winners, modeling the likely spots for civil disturbances in the late 60’s, and devising strategies for winning the hearts and minds of the people of Vietnam over the course of the war. Unsurprisingly, the company crashed and burned in the early 70’s, and its principals scattered.
The story is moderately interesting, but overall merits just a footnote, not a 300 page exposition. Much research and scholarship went into the creation of this work, but really there is nothing other than imagination to tie these “pioneers” to the computer-dominated culture of today.
The story is moderately interesting, but overall merits just a footnote, not a 300 page exposition. Much research and scholarship went into the creation of this work, but really there is nothing other than imagination to tie these “pioneers” to the computer-dominated culture of today.
June 28, 2021
If Then is a fascinating and flawed account of how Simulmatics, a pioneering market research team, prefigured much of contemporary concerns around big data and surveillance capitalism, while failing in almost every venture it embarked on. Lepore bounces between her primary protagonists and the great events that they failed to substantially influence or capitalize on to paint a picture of the 60s as a decade when a utopian dream of technocratic moderation became a nightmare of simulated insanity.
Ed Greenfeld, the founder of Simulmatics, was a Madison Avenue ad man and backslapping hustlers, who frustrated at the perennial failure of his favored candidate Adlai Stevenson in 1952 and 1956, teamed up with social scientists in the nascent fields of behavioral science to create an election in a box, a computerized data model that would give a cannier Democrat an oraclucular advantage. The first few reports went to the Kennedy campaign in the summer of 1960 suggested that he should embrace civil rights and Catholicism; that the votes of racists and anti-Catholics had already been lost, and he could shore up support among African-Americans and non-bigots. Kennedy famously won by a narrow margin. An article in Harper's Magazine by Thomas Morgan sold Simulmatics as a magic people machine that gave the Kennedy campaign strategic insights (Morgan would shortly join the company), but Simulmatics proved best at selling itself, and failed to land subsequent opportunities.
Madison Avenue was rightfully skeptical of the shoddy data bases and under theorized models of consumer behavior. An attempt to use computers to model the 1964 election in near real time for the New York Times collapsed under a tidal waves of bugs and lack of technical experience with actual IBM mainframes. The most successful project was an expansion to Saigon, to try and simulate how communist insurgencies could be defeated, but Simulmatics was never more than a tertiary player in McNamara's data-driven war. After failing to deliver on an expensive contract, their efforts were cancelled by ARPA.
Meanwhile, the personnelle of Simulmatics imploded in their own way. Ed Greenfeld sunk into alcoholism. Mathematician Bill McPhee was committed to an insane asylum for a time, and then mostly failed to deal with his bipolar disorder. Political scientist/novelist Eugene Burdick (The Ugly American, among other didactic 60s political thrillers) used his insider access to skewer the company in his 1964 novel The 480, a reference to the 480 identified categories of people in the Simulmatics database. Burdick died shortly thereafter of a heart attack. Ithial de Sola Pool, a Trotskyite turned ardent cold warrior, pushed Simulmatics ever closer to the defense establishment, while fighting the rising peace movement in American universities. Everybody's marriage fell apart.
A last gasp at predicting urban race riots collapsed in 1968, and Simulmatics suffered an undignified bankruptcy in 1970. Ithiel de Sola Pool had the longest successful career, serving as a neoconservative prophet of the nascent internet until his death in 1984. Much like cybernetics, another trendy 1950s computerized synthesis, Simulmatics abilities never matched its ambitions. Yet, as Lepore shows, the concerns raised then are the same as our current concerns around Facebook, face news, information warfare, and all that postmodern jazz. Nothing is new under the sun, except in 2021 computers are fast enough and data models rich enough that it actually works.
Lepore ably blends the "Mad Men but real" flawed personalities with the great events of this time, but I wish she'd been a little more detailed as an intellectual and technical historian. I'm a lover of obsolete ideas and obsolete machines, and I'd have liked a little more detail on how it worked. Still, a fascinating book on a mostly forgotten group of visionaries.
Ed Greenfeld, the founder of Simulmatics, was a Madison Avenue ad man and backslapping hustlers, who frustrated at the perennial failure of his favored candidate Adlai Stevenson in 1952 and 1956, teamed up with social scientists in the nascent fields of behavioral science to create an election in a box, a computerized data model that would give a cannier Democrat an oraclucular advantage. The first few reports went to the Kennedy campaign in the summer of 1960 suggested that he should embrace civil rights and Catholicism; that the votes of racists and anti-Catholics had already been lost, and he could shore up support among African-Americans and non-bigots. Kennedy famously won by a narrow margin. An article in Harper's Magazine by Thomas Morgan sold Simulmatics as a magic people machine that gave the Kennedy campaign strategic insights (Morgan would shortly join the company), but Simulmatics proved best at selling itself, and failed to land subsequent opportunities.
Madison Avenue was rightfully skeptical of the shoddy data bases and under theorized models of consumer behavior. An attempt to use computers to model the 1964 election in near real time for the New York Times collapsed under a tidal waves of bugs and lack of technical experience with actual IBM mainframes. The most successful project was an expansion to Saigon, to try and simulate how communist insurgencies could be defeated, but Simulmatics was never more than a tertiary player in McNamara's data-driven war. After failing to deliver on an expensive contract, their efforts were cancelled by ARPA.
Meanwhile, the personnelle of Simulmatics imploded in their own way. Ed Greenfeld sunk into alcoholism. Mathematician Bill McPhee was committed to an insane asylum for a time, and then mostly failed to deal with his bipolar disorder. Political scientist/novelist Eugene Burdick (The Ugly American, among other didactic 60s political thrillers) used his insider access to skewer the company in his 1964 novel The 480, a reference to the 480 identified categories of people in the Simulmatics database. Burdick died shortly thereafter of a heart attack. Ithial de Sola Pool, a Trotskyite turned ardent cold warrior, pushed Simulmatics ever closer to the defense establishment, while fighting the rising peace movement in American universities. Everybody's marriage fell apart.
A last gasp at predicting urban race riots collapsed in 1968, and Simulmatics suffered an undignified bankruptcy in 1970. Ithiel de Sola Pool had the longest successful career, serving as a neoconservative prophet of the nascent internet until his death in 1984. Much like cybernetics, another trendy 1950s computerized synthesis, Simulmatics abilities never matched its ambitions. Yet, as Lepore shows, the concerns raised then are the same as our current concerns around Facebook, face news, information warfare, and all that postmodern jazz. Nothing is new under the sun, except in 2021 computers are fast enough and data models rich enough that it actually works.
Lepore ably blends the "Mad Men but real" flawed personalities with the great events of this time, but I wish she'd been a little more detailed as an intellectual and technical historian. I'm a lover of obsolete ideas and obsolete machines, and I'd have liked a little more detail on how it worked. Still, a fascinating book on a mostly forgotten group of visionaries.
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