The Data That Turned the
World Upside Down
Psychologist
Michal Kosinski developed a method to analyze people in minute detail based on
their Facebook activity. Did a similar tool help propel Donald Trump to
victory? Two reporters from Zurich-based Das Magazin (where an earlier version
of this story appeared in December in German) went data-gathering.
On November 9 at around
8.30 AM., Michal Kosinski woke up in the Hotel Sunnehus in Zurich. The
34-year-old researcher had come to give a lecture at the Swiss Federal
Institute of Technology (ETH) about the dangers of Big Data and the digital
revolution. Kosinski gives regular lectures on this topic all over the world.
He is a leading expert in psychometrics, a data-driven sub-branch of
psychology. When he turned on the TV that morning, he saw that the bombshell
had exploded: contrary to forecasts by all leading statisticians, Donald J.
Trump had been elected president of the United States.
For a long time, Kosinski
watched the Trump victory celebrations and the results coming in from each
state. He had a hunch that the outcome of the election might have something to
do with his research. Finally, he took a deep breath and turned off the TV.
On the same day, a then
little-known British company based in London sent out a press release: “We are
thrilled that our revolutionary approach to data-driven communication has
played such an integral part in President-elect Trump’s extraordinary win,” Alexander
James Ashburner Nix was quoted as saying. Nix is British, 41 years old, and CEO
of Cambridge Analytica. He is always immaculately turned out in tailor-made
suits and designer glasses, with his wavy blonde hair combed back from his
forehead. His company wasn't just integral to Trump’s online campaign, but to
the UK's Brexit campaign as well.
Of these three
players—reflective Kosinski, carefully groomed Nix and grinning Trump—one of
them enabled the digital revolution, one of them executed it and one of them
benefited from it.
How dangerous is big
data?
Anyone who has not spent
the last five years living on another planet will be familiar with the term Big
Data. Big Data means, in essence, that everything we do, both on and offline,
leaves digital traces. Every purchase we make with our cards, every search we
type into Google, every movement we make when our mobile phone is in our
pocket, every “like” is stored. Especially every “like.” For a long time, it
was not entirely clear what use this data could have—except, perhaps, that we
might find ads for high blood pressure remedies just after we’ve Googled
“reduce blood pressure.”
On November 9, it became
clear that maybe much more is possible. The company behind Trump’s online
campaign—the same company that had worked for Leave.EU in the very early stages
of its "Brexit" campaign—was a Big Data company: Cambridge Analytica.
To understand the outcome
of the election—and how political communication might work in the future—we
need to begin with a strange incident at Cambridge University in 2014, at
Kosinski’s Psychometrics Center.
Psychometrics, sometimes
also called psychographics, focuses on measuring psychological traits, such as
personality. In the 1980s, two teams of psychologists developed a model that
sought to assess human beings based on five personality traits, known as the
“Big Five.” These are: openness (how open you are to new experiences?),
conscientiousness (how much of a perfectionist are you?), extroversion (how
sociable are you?), agreeableness (how considerate and cooperative you are?)
and neuroticism (are you easily upset?). Based on these dimensions—they are
also known as OCEAN, an acronym for openness, conscientiousness, extroversion,
agreeableness, neuroticism—we can make a relatively accurate assessment of the
kind of person in front of us. This includes their needs and fears, and how
they are likely to behave. The ”Big Five” has become the standard technique of
psychometrics. But for a long time, the problem with this approach was data
collection, because it involved filling out a complicated, highly personal
questionnaire. Then came the Internet. And Facebook. And Kosinski.
Michal Kosinski was a
student in Warsaw when his life took a new direction in 2008. He was accepted
by Cambridge University to do his PhD at the Psychometrics Centre, one of the
oldest institutions of this kind worldwide. Kosinski joined fellow student
David Stillwell (now a lecturer at Judge Business School at the University of
Cambridge) about a year after Stillwell had launched a little Facebook
application in the days when the platform had not yet become the behemoth it is
today. Their MyPersonality app enabled users to fill out different psychometric
questionnaires, including a handful of psychological questions from the Big
Five personality questionnaire (“I panic easily,“ “I contradict others”). Based
on the evaluation, users received a “personality profile”—individual Big Five
values—and could opt-in to share their Facebook profile data with the researchers.
Followers of Lady Gaga
were most probably extroverts, while those who “liked” philosophy tended to be
introverts.
Kosinski had expected a
few dozen college friends to fill in the questionnaire, but before long,
hundreds, thousands, then millions of people had revealed their innermost
convictions. Suddenly, the two doctoral candidates owned the largest dataset
combining psychometric scores with Facebook profiles ever to be collected.
The approach that
Kosinski and his colleagues developed over the next few years was actually
quite simple. First, they provided test subjects with a questionnaire in the
form of an online quiz. From their responses, the psychologists calculated the
personal Big Five values of respondents. Kosinski’s team then compared the results
with all sorts of other online data from the subjects: what they “liked,"
shared or posted on Facebook, or what gender, age, place of residence they
specified, for example. This enabled the researchers to connect the dots and
make correlations.
Remarkably reliable
deductions could be drawn from simple online actions. For example, men who
“liked” the cosmetics brand MAC were slightly more likely to be gay; one of the
best indicators for heterosexuality was “liking” Wu-Tang Clan. Followers of
Lady Gaga were most probably extroverts, while those who “liked” philosophy
tended to be introverts. While each piece of such information is too weak to
produce a reliable prediction, when tens, hundreds, or thousands of individual
data points are combined, the resulting predictions become really accurate.
Kosinski and his team
tirelessly refined their models. In 2012, Kosinski proved that on the basis of
an average of 68 Facebook “likes” by a user, it was possible to predict their
skin color (with 95 percent accuracy), their sexual orientation (88 percent
accuracy), and their affiliation to the Democratic or Republican party (85
percent). But it didn’t stop there. Intelligence, religious affiliation, as
well as alcohol, cigarette and drug use, could all be determined. From the data
it was even possible to deduce whether deduce whether someone's parents were
divorced.
The strength of their
modeling was illustrated by how well it could predict a subject’s answers.
Kosinski continued to work on the models incessantly: before long, he was able
to evaluate a person better than the average work colleague, merely on the
basis of ten Facebook “likes.” Seventy “likes” were enough to outdo what a
person’s friends knew, 150 what their parents knew, and 300 “likes” what their
partner knew. More “likes” could even surpass what a person thought they knew
about themselves. On the day that Kosinski published these findings, he
received two phone calls. The threat of a lawsuit and a job offer. Both from
Facebook.
MICHAL KOSINSKI. COURTESY
OF KOSINSKI
Only weeks later Facebook
“likes“ became private by default. Before that, the default setting was that
anyone on the internet could see your "likes." But this was no
obstacle to data collectors: while Kosinski always asked for the consent of
Facebook users, many apps and online quizzes today require access to private
data as a precondition for taking personality tests. (Anybody who wants to
evaluate themselves based on their Facebook “likes” can do so on Kosinski’s website,
and then compare their results to those of a classic Ocean questionnaire, like
that of the Cambridge Psychometrics Center.)
Our smartphone, Kosinski
concluded, is a vast psychological questionnaire that we are constantly filling
out, both consciously and unconsciously.
But it was not just about
“likes” or even Facebook: Kosinski and his team could now ascribe Big Five
values based purely on how many profile pictures a person has on Facebook, or
how many contacts they have (a good indicator of extraversion). But we also
reveal something about ourselves even when we’re not online. For example, the
motion sensor on our phone reveals how quickly we move and how far we travel
(this correlates with emotional instability). Our smartphone, Kosinski concluded,
is a vast psychological questionnaire that we are constantly filling out, both
consciously and unconsciously.
Above all, however—and
this is key—it also works in reverse: not only can psychological profiles be
created from your data, but your data can also be used the other way round to
search for specific profiles: all anxious fathers, all angry introverts, for
example—or maybe even all undecided Democrats? Essentially, what Kosinski had
invented was sort of a people search engine. He started to recognize the
potential—but also the inherent danger—of his work.
To him, the internet had
always seemed like a gift from heaven. What he really wanted was to give
something back, to share. Data can be copied, so why shouldn’t everyone benefit
from it? It was the spirit of a whole generation, the beginning of a new era
that transcended the limitations of the physical world. But what would happen,
wondered Kosinski, if someone abused his people search engine to manipulate
people? He began to add warnings to most of his scientific work. His approach,
he warned, “could pose a threat to an individual’s well-being, freedom, or even
life.” But no one seemed to grasp what he meant.
Around this time, in
early 2014, Kosinski was approached by a young assistant professor in the
psychology department called Aleksandr Kogan. He said he was inquiring on
behalf of a company that was interested in Kosinski’s method, and wanted to
access the MyPersonality database. Kogan wasn’t at liberty to reveal for what
purpose; he was bound to secrecy.
At first, Kosinski and
his team considered this offer, as it would mean a great deal of money for the
institute, but then he hesitated. Finally, Kosinski remembers, Kogan revealed
the name of the company: SCL, or Strategic Communication Laboratories. Kosinski
Googled the company: “[We are] the premier election management agency,” says
the company’s website. SCL provides marketing based on psychological modeling.
One of its core focuses: Influencing elections. Influencing elections?
Perturbed, Kosinski clicked through the pages. What kind of company was this?
And what were these people planning?
What Kosinski did not
know at the time: SCL is the parent of a group of companies. Who exactly owns
SCL and its diverse branches is unclear, thanks to a convoluted corporate
structure, the type seen in the UK Companies House, the Panama Papers, and the
Delaware company registry. Some of the SCL offshoots have been involved in
elections from Ukraine to Nigeria, helped the Nepalese monarch against the rebels,
whereas others have developed methods to influence Eastern European and Afghan
citizens for NATO. And, in 2013, SCL spun off a new company to participate in
US elections: Cambridge Analytica.
Kosinski knew nothing
about all this, but he had a bad feeling. “The whole thing started to stink,”
he recalls. On further investigation, he discovered that Aleksandr Kogan had
secretly registered a company doing business with SCL. According to a December
2015 report in The Guardian and to internal company documents given to Das
Magazin, it emerges that SCL learned about Kosinski’s method from Kogan.
Kosinski came to suspect
that Kogan's company might have reproduced the Facebook "Likes"-based
Big Five measurement tool in order to sell it to this election-influencing
firm. He immediately broke off contact with Kogan and informed the director of
the institute, sparking a complicated conflict within the university. The
institute was worried about its reputation. Aleksandr Kogan then moved to
Singapore, married, and changed his name to Dr. Spectre. Michal Kosinski
finished his PhD, got a job offer from Stanford and moved to the US.
Mr. Brexit
All was quiet for about a
year. Then, in November 2015, the more radical of the two Brexit campaigns,
“Leave.EU,” supported by Nigel Farage, announced that it had commissioned a Big
Data company to support its online campaign: Cambridge Analytica. The company’s
core strength: innovative political marketing—microtargeting—by measuring
people's personality from their digital footprints, based on the OCEAN model.
After the Brexit result,
friends and acquaintances wrote to him: Just look at what you’ve done.
Now Kosinski received
emails asking what he had to do with it—the words Cambridge, personality, and
analytics immediately made many people think of Kosinski. It was the first time
he had heard of the company, which borrowed its name, it said, from its first
employees, researchers from the university. Horrified, he looked at the
website. Was his methodology being used on a grand scale for political
purposes?
After the Brexit result,
friends and acquaintances wrote to him: Just look at what you’ve done. Everywhere
he went, Kosinski had to explain that he had nothing to do with this company.
(It remains unclear how deeply Cambridge Analytica was involved in the Brexit
campaign. Cambridge Analytica would not discuss such questions.)
For a few months, things
are relatively quiet. Then, on September 19, 2016, just over a month before the
US elections, the guitar riffs of Creedence Clearwater Revival’s “Bad Moon
Rising” fill the dark-blue hall of New York's Grand Hyatt hotel. The Concordia
Summit is a kind of World Economic Forum in miniature. Decision-makers from all
over the world have been invited, among them Swiss President Johann
Schneider-Ammann. “Please welcome to the stage Alexander Nix, chief executive
officer of Cambridge Analytica,” a smooth female voice announces. A slim man in
a dark suit walks onto the stage. A hush falls. Many in attendance know that
this is Trump’s new digital strategy man. (A video of the presentation was
posted on YouTube.)
A few weeks earlier,
Trump had tweeted, somewhat cryptically, "Soon you’ll be calling me Mr.
Brexit." Political observers had indeed noticed some striking similarities
between Trump’s agenda and that of the right-wing Brexit movement. But few had
noticed the connection with Trump’s recent hiring of a marketing company named
Cambridge Analytica.
ALEXANDER NIX. IMAGE:
CAMBRIDGE ANALYTICA
“Pretty much every
message that Trump put out was data-driven," says Cambridge Analytica CEO
Alexander Nix
Up to this point, Trump’s
digital campaign had consisted of more or less one person: Brad Parscale, a
marketing entrepreneur and failed start-up founder who created a rudimentary
website for Trump for $1,500. The 70-year-old Trump is not digitally
savvy—there isn’t even a computer on his office desk. Trump doesn’t do emails,
his personal assistant once revealed. She herself talked him into having a
smartphone, from which he now tweets incessantly.
Hillary Clinton, on the
other hand, relied heavily on the legacy of the first “social-media president,”
Barack Obama. She had the address lists of the Democratic Party, worked with
cutting-edge big data analysts from BlueLabs and received support from Google
and DreamWorks. When it was announced in June 2016 that Trump had hired
Cambridge Analytica, the establishment in Washington just turned up their
noses. Foreign dudes in tailor-made suits who don’t understand the country and
its people? Seriously?
“It is my privilege to
speak to you today about the power of Big Data and psychographics in the
electoral process.” The logo of Cambridge Analytica— a brain composed of
network nodes, like a map, appears behind Alexander Nix. “Only 18 months ago,
Senator Cruz was one of the less popular candidates,” explains the blonde man
in a cut-glass British accent, which puts Americans on edge the same way that a
standard German accent can unsettle Swiss people. “Less than 40 percent of the
population had heard of him,” another slide says. Cambridge Analytica had
become involved in the US election campaign almost two years earlier, initially
as a consultant for Republicans Ben Carson and Ted Cruz. Cruz—and later
Trump—was funded primarily by the secretive US software billionaire Robert
Mercer who, along with his daughter Rebekah, is reported to be the largest
investor in Cambridge Analytica.
“So how did he do this?”
Up to now, explains Nix, election campaigns have been organized based on
demographic concepts. “A really ridiculous idea. The idea that all women should
receive the same message because of their gender—or all African Americans
because of their race.” What Nix meant is that while other campaigners so far
have relied on demographics, Cambridge Analytica was using psychometrics.
Though this might be
true, Cambridge Analytica’s role within Cruz’s campaign isn’t undisputed. In
December 2015 the Cruz team credited their rising success to psychological use
of data and analytics. In Advertising Age, a political client said the embedded
Cambridge staff was "like an extra wheel," but found their core
product, Cambridge's voter data modeling, still ”excellent.” The campaign would
pay the company at least $5.8 million to help identify voters in the Iowa
caucuses, which Cruz won, before dropping out of the race in May.
Nix clicks to the next
slide: five different faces, each face corresponding to a personality profile.
It is the Big Five or OCEAN Model. “At Cambridge,” he said, “we were able to
form a model to predict the personality of every single adult in the United
States of America.” The hall is captivated. According to Nix, the success of
Cambridge Analytica’s marketing is based on a combination of three elements:
behavioral science using the OCEAN Model, Big Data analysis, and ad targeting.
Ad targeting is personalized advertising, aligned as accurately as possible to
the personality of an individual consumer.
Nix candidly explains how
his company does this. First, Cambridge Analytica buys personal data from a
range of different sources, like land registries, automotive data, shopping
data, bonus cards, club memberships, what magazines you read, what churches you
attend. Nix displays the logos of globally active data brokers like Acxiom and
Experian—in the US, almost all personal data is for sale. For example, if you
want to know where Jewish women live, you can simply buy this information, phone
numbers included. Now Cambridge Analytica aggregates this data with the
electoral rolls of the Republican party and online data and calculates a Big
Five personality profile. Digital footprints suddenly become real people with
fears, needs, interests, and residential addresses.
The methodology looks
quite similar to the one that Michal Kosinski once developed. Cambridge
Analytica also uses, Nix told us, “surveys on social media” and Facebook data.
And the company does exactly what Kosinski warned of: “We have profiled the
personality of every adult in the United States of America—220 million people,”
Nix boasts.
He opens the screenshot.
“This is a data dashboard that we prepared for the Cruz campaign.” A digital
control center appears. On the left are diagrams; on the right, a map of Iowa,
where Cruz won a surprisingly large number of votes in the primary. And on the
map, there are hundreds of thousands of small red and blue dots. Nix narrows
down the criteria: “Republicans”—the blue dots disappear; “not yet
convinced”—more dots disappear; “male”, and so on. Finally, only one name
remains, including age, address, interests, personality and political
inclination. How does Cambridge Analytica now target this person with an
appropriate political message?
ALEXANDER NIX AT THE 2016
CONCORDIA SUMMIT IN NEW YORK. IMAGE: CONCORDIA SUMMIT
Nix shows how
psychographically categorized voters can be differently addressed, based on the
example of gun rights, the 2nd Amendment: “For a highly neurotic and
conscientious audience the threat of a burglary—and the insurance policy of a
gun.“ An image on the left shows the hand of an intruder smashing a window. The
right side shows a man and a child standing in a field at sunset, both holding
guns, clearly shooting ducks: “Conversely, for a closed and agreeable audience.
People who care about tradition, and habits, and family.”
How to keep Clinton
voters away from the ballot box
Trump’s striking
inconsistencies, his much-criticized fickleness, and the resulting array of
contradictory messages, suddenly turned out to be his great asset: a different
message for every voter. The notion that Trump acted like a perfectly
opportunistic algorithm following audience reactions is something the
mathematician Cathy O’Neil observed in August 2016.
These “dark
posts”—sponsored Facebook posts that can only be seen by users with specific
profiles—included videos aimed at African-Americans in which Hillary Clinton
refers to black men as predators, for example.
“Pretty much every
message that Trump put out was data-driven,” Alexander Nix remembers. On the
day of the third presidential debate between Trump and Clinton, Trump’s team
tested 175,000 different ad variations for his arguments, in order to find the
right versions above all via Facebook. The messages differed for the most part
only in microscopic details, in order to target the recipients in the optimal
psychological way: different headings, colors, captions, with a photo or video.
This fine-tuning reaches all the way down to the smallest groups, Nix explained
in an interview with us. “We can address villages or apartment blocks in a
targeted way. Even individuals.”
In the Miami district of
Little Haiti, for instance, Trump’s campaign provided inhabitants with news
about the failure of the Clinton Foundation following the earthquake in Haiti,
in order to keep them from voting for Hillary Clinton. This was one of the
goals: to keep potential Clinton voters (which include wavering left-wingers,
African-Americans, and young women) away from the ballot box, to “suppress”
their vote, as one senior campaign official told Bloomberg in the weeks before the
election. These “dark posts”—sponsored news-feed-style ads in Facebook
timelines that can only be seen by users with specific profiles—included videos
aimed at African-Americans in which Hillary Clinton refers to black men as
predators, for example.
Nix finishes his lecture
at the Concordia Summit by stating that traditional blanket advertising is
dead. “My children will certainly never, ever understand this concept of mass
communication.” And before leaving the stage, he announced that since Cruz had left
the race, the company was helping one of the remaining presidential candidates.
Just how precisely the
American population was being targeted by Trump’s digital troops at that moment
was not visible, because they attacked less on mainstream TV and more with
personalized messages on social media or digital TV. And while the Clinton team
thought it was in the lead, based on demographic projections, Bloomberg
journalist Sasha Issenberg was surprised to note on a visit to San
Antonio—where Trump’s digital campaign was based—that a “second headquarters”
was being created. The embedded Cambridge Analytica team, apparently only a
dozen people, received $100,000 from Trump in July, $250,000 in August, and $5
million in September. According to Nix, the company earned over $15 million
overall. (The company is incorporated in the US, where laws regarding the
release of personal data are more lax than in European Union countries. Whereas
European privacy laws require a person to “opt in” to a release of data, those
in the US permit data to be released unless a user “opts out.")
GROUNDGAME, AN APP FOR
ELECTION CANVASSING THAT INTEGRATES VOTER DATA WITH "GEOSPATIAL
VISUALIZATION TECHNOLOGY," WAS USED BY CAMPAIGNERS FOR TRUMP AND BREXIT.
IMAGE: L2
The measures were radical:
From July 2016, Trump’s canvassers were provided with an app with which they
could identify the political views and personality types of the inhabitants of
a house. It was the same app provider used by Brexit campaigners. Trump’s
people only rang at the doors of houses that the app rated as receptive to his
messages. The canvassers came prepared with guidelines for conversations
tailored to the personality type of the resident. In turn, the canvassers fed
the reactions into the app, and the new data flowed back to the dashboards of
the Trump campaign.
Again, this is nothing
new. The Democrats did similar things, but there is no evidence that they
relied on psychometric profiling. Cambridge Analytica, however, divided the US
population into 32 personality types, and focused on just 17 states. And just
as Kosinski had established that men who like MAC cosmetics are slightly more
likely to be gay, the company discovered that a preference for cars made in the
US was a great indication of a potential Trump voter. Among other things, these
findings now showed Trump which messages worked best and where. The decision to
focus on Michigan and Wisconsin in the final weeks of the campaign was made on
the basis of data analysis. The candidate became the instrument for
implementing a big data model.
What's Next?
But to what extent did
psychometric methods influence the outcome of the election? When asked,
Cambridge Analytica was unwilling to provide any proof of the effectiveness of
its campaign. And it is quite possible that the question is impossible to
answer.
And yet there are clues:
There is the fact of the surprising rise of Ted Cruz during the primaries. Also
there was an increased number of voters in rural areas. There was the decline
in the number of African-American early votes. The fact that Trump spent so
little money may also be explained by the effectiveness of personality-based
advertising. As does the fact that he invested far more in digital than TV
campaigning compared to Hillary Clinton. Facebook proved to be the ultimate
weapon and the best election campaigner, as Nix explained, and as comments by
several core Trump campaigners demonstrate.
CAMBRIDGE ANALYTICA
COUNTS AMONG ITS CLIENTS THE U.S. STATE DEPARTMENT, AND HAS BEEN REPORTED TO
HAVE COMMUNICATED WITH BRITISH PRIME MINISTER THERESA MAY, PICTURED HERE WITH
SECRETARY OF STATE JOHN KERRY ON JULY 19, 2016. IMAGE: U.S. DEPT. OF STATE
Many voices have claimed
that the statisticians lost the election because their predictions were so off
the mark. But what if statisticians in fact helped win the election—but only
those who were using the new method? It is an irony of history that Trump, who
often grumbled about scientific research, used a highly scientific approach in
his campaign.
Another big winner is
Cambridge Analytica. Its board member Steve Bannon, former executive chair of
the right-wing online newspaper Breitbart News, has been appointed as Donald
Trump’s senior counselor and chief strategist. Whilst Cambridge Analytica is
not willing to comment on alleged ongoing talks with UK Prime Minister Theresa
May, Alexander Nix claims that he is building up his client base worldwide, and
that he has received inquiries from Switzerland, Germany, and Australia. His
company is currently touring European conferences showcasing their success in
the United States. This year three core countries of the EU are facing
elections with resurgent populist parties: France, Holland and Germany. The
electoral successes come at an opportune time, as the company is readying for a
push into commercial advertising.
Kosinski has observed all
of this from his office at Stanford. Following the US election, the university
is in turmoil. Kosinski is responding to developments with the sharpest weapon
available to a researcher: a scientific analysis. Together with his research
colleague Sandra Matz, he has conducted a series of tests, which will soon be
published. The initial results are alarming: The study shows the effectiveness
of personality targeting by showing that marketers can attract up to 63 percent
more clicks and up to 1,400 more conversions in real-life advertising campaigns
on Facebook when matching products and marketing messages to consumers’
personality characteristics. They further demonstrate the scalability of
personality targeting by showing that the majority of Facebook Pages promoting
products or brands are affected by personality and that large numbers of
consumers can be accurately targeted based on a single Facebook Page.
In a statement after the
German publication of this article, a Cambridge Analytica spokesperson said,
"Cambridge Analytica does not use data from Facebook. It has had no
dealings with Dr. Michal Kosinski. It does not subcontract research. It does
not use the same methodology. Psychographics was hardly used at all. Cambridge
Analytica did not engage in efforts to discourage any Americans from casting
their vote in the presidential election. Its efforts were solely directed
towards increasing the number of voters in the election."
The world has been turned
upside down. Great Britain is leaving the EU, Donald Trump is president of the
United States of America. And in Stanford, Kosinski, who wanted to warn against
the danger of using psychological targeting in a political setting, is once
again receiving accusatory emails. “No,” says Kosinski, quietly and shaking his
head. “This is not my fault. I did not build the bomb. I only showed that it
exists.”
Regards!
Librarian
Rizvi Institute of
Management
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