ON AIR
metal + hardcore
pop punk + alt-rock
indie spins
 

News

What if you built a machine to predict hit movies?

One sunny afternoon not long ago, Dick Copaken sat in a booth at
Daniel, one of those hushed, exclusive restaurants on Manhattan’s Upper
East Side where the waiters glide spectrally fro table to table.
He was wearing a starched button-down shirt and a blue blazer. Every
strand of his thinning hair was in place, and he spoke calmly and
slowly, his large pink Charlie Brow head bobbing along evenly as
he did. Copaken spent many years as a partner at the white-shoe
Washington, D.C., firm Covington & Burling, and he has a lawyer’s
gravitas. One of his bes friends calls him, admiringly,
“relentless.” He likes to tell stories. Yet he is not, strictly, a
storyteller, because storytellers are people who know when to leave
things out, and Copaken neve leaves anything out: each detail is
adduced, considered, and laid on the table–and then adjusted and
readjusted so that the corners of the new fact are flush with the
corners of the fact tha preceded it. This is especially true when
Copaken is talking about things that he really cares about, such as
questions of international law or his grandchildren or, most of all,
the movies

Dick Copaken loves the movies. His friend Richard Light, a statistician
at Harvard, remembers summer vacations on Cape Cod with the Copakens,
when Copaken would take his children and the Light children to the
movies every day. “Fourteen nights out of fourteen,” Light said. “Dick
would say at seven o’clock, ‘Hey, who’s up for the movies?’ And, all by
himself, he would take the six kids to the movies. The kids had the
time of their lives. And Dick would come back and give, with a
completely straight face, a rigorous analysis of how each movie was put
together, and the direction and the special effects and the animation.”
This is a man who has seen two or three movies a week for the past
fifty years, who has filed hundreds of plots and characters and scenes
away in his mind, and at Daniel he was talking about a movie that
touched him as much as any he’d ever seen.

“Nobody’s heard of it,” he said, and he clearly regarded this fact as a
minor tragedy. “It’s called ‘Dear Frankie.’ I watched it on a Virgin
Atlantic flight because it was the only movie they had that I hadn’t
already seen. I had very low expectations. But I was blown away.” He
began, in his lawyer-like manner, to lay out the plot. It takes place
in Scotland. A woman has fled an abusive relationship with her infant
son and is living in a port town. The boy, now nine, is deaf, and
misses the father he has never known. His mother has told him that his
father is a sailor on a ship that rarely comes to shore, and has
suggested that he write his father letters. These she intercepts, and
replies to, writing as if she were the father. One day, the boy finds
out that what he thinks is his father’s ship is coming to shore. The
mother has to find a man to stand in for the father. She does. The two
fall in love. Unexpectedly, the real father reëmerges. He’s dying, and
demands to see his son. The mother panics. Then the little boy reveals
his secret: he knew about his mother’s ruse all along.

“I was in tears over this movie,” Copaken said. “You know, sometimes
when you see a movie in the air you’re in such an out-of-body mood that
things get exaggerated. So when I got home I sat down and saw it
another time. I was bawling again, even though I knew what was coming.”
Copaken shook his head, and then looked away. His cheeks were flushed.
His voice was suddenly thick. There he was, a buttoned-down corporate
lawyer, in a hushed restaurant where there is practically a sign on the
wall forbidding displays of human emotion–and he was crying, a third
time. “That absolutely hits me,” he said, his face still turned away.
“He knew all along what the mother was doing.” He stopped to collect
himself. “I can’t even retell the damn story without getting emotional.”

He tried to explain why he was crying. There was the little boy, first
of all. He was just about the same age as Copaken’s grandson Jacob. So
maybe that was part of it. Perhaps, as well, he was reacting to the
idea of an absent parent. His own parents, Albert and Silvia, ran a
modest community-law practice in Kansas City, and would shut down their
office whenever Copaken or his brother had any kind of school activity
or performance. In the Copaken world, it was an iron law that parents
had to be present. He told a story about representing the Marshall
Islands in negotiations with the U.S. government during the Cold War. A
missile-testing range on the island was considered to be strategically
critical. The case was enormously complex–involving something like
fifty federal agencies and five countries–and, just as the negotiations
were scheduled to begin, Copaken learned of a conflict: his eldest
daughter was performing the lead role in a sixth-grade production of
“The Wiz.” “I made an instant decision,” Copaken said. He told the
President of the Marshall Islands that his daughter had to come first.
Half an hour passed. “I get a frantic call from the State Department,
very high levels: ‘Dick, I got a call from the President of the
Marshall Islands. What’s going on?’ I told him. He said, ‘Dick, are you
putting in jeopardy the national security of the United States for a
sixth-grade production?’ ” In the end, the negotiations were suspended
while Copaken flew home from Hawaii. “The point is,” Copaken said,
“that absence at crucial moments has been a worry to me, and maybe this
movie just grabbed at that issue.”

He stopped, seemingly dissatisfied. Was that really why he’d cried?
Hollywood is awash in stories of bad fathers and abandoned children,
and Copaken doesn’t cry in fancy restaurants every time he thinks of
one of them. When he tried to remember the last time he cried at the
movies, he was stumped. So he must have been responding to something
else, too–some detail, some unconscious emotional trigger in the
combination of the mother and the boy and the Scottish seaside town and
the ship and the hired surrogate and the dying father. To say that he
cried at “Dear Frankie” because of that lonely fatherless boy was as
inadequate as saying that people cried at the death of Princess Diana
because she was a beautiful princess. Surely it mattered as well that
she was killed in the company of her lover, a man distrusted by the
Royal Family. Wasn’t this “Romeo and Juliet”? And surely it mattered
that she died in a tunnel, and that the tunnel was in Paris, and that
she was chased by motorbikes, and that she was blond and her lover was
dark–because each one of those additional narrative details has
complicated emotional associations, and it is the subtle combination of
all these associations that makes us laugh or choke up when we remember
a certain movie, every single time, even when we’re sitting in a fancy
restaurant.

Of course, the optimal combination of all those elements is a mystery.
That’s why it’s so hard to make a really memorable movie, and why we
reward so richly the few people who can. But suppose you really, really
loved the movies, and suppose you were a relentless type, and suppose
you used all of the skills you’d learned during the course of your
career at the highest rungs of the law to put together an international
team of story experts. Do you think you could figure it out?

The most famous dictum about Hollywood belongs to the screenwriter
William Goldman. “Nobody knows anything,” Goldman wrote in “Adventures
in the Screen Trade” a couple o decades ago. “Not one person in
the entire motion picture field knows for a certainty what’s going to
work. Every time out it’s a guess.” One of the highest-grossing movies
in history, “Raiders of the Lost Ark,” was offered to every studio in
Hollywood, Goldman writes, and every one of them turned it down except
Paramount: “Why did Paramount say yes? Because nobody knows anything.
And why did all the other studios say no? Because nobody knows
anything. And why did Universal, the mightiest studio of all, pass on
Star Wars? . . . Because nobody, nobody–not now, not ever–knows the
least goddamn thing about what is or isn’t going to work at the box
office.”

What Goldman was saying was a version of something that has long been
argued about art: that there is no way of getting beyond one’s own
impressions to arrive at some larger, objective truth. There are no
rules to art, only the infinite variety of subjective experience.
“Beauty is no quality in things themselves,” the eighteenth-century
Scottish philosopher David Hume wrote. “It exists merely in the mind
which contemplates them; and each mind perceives a different beauty.”
Hume might as well have said that nobody knows anything.

But Hume had a Scottish counterpart, Lord Kames, and Lord Kames was
equally convinced that traits like beauty, sublimity, and grandeur were
indeed reducible to a rational system of rules and precepts. He devised
principles of congruity, propriety, and perspicuity: an elevated
subject, for instance, must be expressed in elevated language; sound
and signification should be in concordance; a woman was most attractive
when in distress; depicted misfortunes must never occur by chance. He
genuinely thought that the superiority of Virgil’s hexameters to
Horace’s could be demonstrated with Euclidean precision, and for every
Hume, it seems, there has always been a Kames–someone arguing that if
nobody knows anything it is only because nobody’s looking hard enough.

In a small New York loft, just below Union Square, for example, there
is a tech startup called Platinum Blue that consults for companies in
the music business. Record executives have tended to be Humean: though
they can tell you how they feel when they listen to a song, they don’t
believe anyone can know with confidence whether a song is going to be a
hit, and, historically, fewer than twenty per cent of the songs picked
as hits by music executives have fulfilled those expectations. Platinum
Blue thinks it can do better. It has a proprietary computer program
that uses “spectral deconvolution software” to measure the mathematical
relationships among all of a song’s structural components: melody,
harmony, beat, tempo, rhythm, octave, pitch, chord progression,
cadence, sonic brilliance, frequency, and so on. On the basis of that
analysis, the firm believes it can predict whether a song is likely to
become a hit with eighty-per-cent accuracy. Platinum Blue is staunchly
Kamesian, and, if you have a field dominated by those who say there are
no rules, it is almost inevitable that someone will come along and say
that there are. The head of Platinum Blue is a man named Mike McCready,
and the service he is providing for the music business is an exact
model of what Dick Copaken would like to do for the movie business.

McCready is in his thirties, baldish and laconic, with rectangular
hipster glasses. His offices are in a large, open room, with a row of
windows looking east, across the rooftops of downtown Manhattan. In the
middle of the room is a conference table, and one morning recently
McCready sat down and opened his laptop to demonstrate the Platinum
Blue technology. On his screen was a cluster of thousands of white
dots, resembling a cloud. This was a “map” of the songs his group had
run through its software: each dot represented a single song, and each
song was positioned in the cloud according to its particular
mathematical signature. “You could have one piano sonata by Beethoven
at this end and another one here,” McCready said, pointing at the
opposite end, “as long as they have completely different chord
progressions and completely different melodic structures.”

McCready then hit a button on his computer, which had the effect of
eliminating all the songs that had not made the Billboard Top 30 in the
past five years. The screen went from an undifferentiated cloud to
sixty discrete clusters. This is what the universe of hit songs from
the past five years looks like structurally; hits come out of a small,
predictable, and highly conserved set of mathematical patterns. “We
take a new CD far in advance of its release date,” McCready said. “We
analyze all twelve tracks. Then we overlay them on top of the already
existing hit clusters, and what we can tell a record company is which
of those songs conform to the mathematical pattern of past hits. Now,
that doesn’t mean that they will be hits. But what we are saying is
that, almost certainly, songs that fall outside these clusters will not
be hits–regardless of how much they sound and feel like hit songs, and
regardless of how positive your call-out research or focus-group
research is.” Four years ago, when McCready was working with a similar
version of the program at a firm in Barcelona, he ran thirty
just-released albums, chosen at random, through his system. One stood
out. The computer said that nine of the fourteen songs on the album had
clear hit potential–which was unheard of. Nobody in his group knew much
about the artist or had even listened to the record before, but the
numbers said the album was going to be big, and McCready and his crew
were of the belief that numbers do not lie. “Right around that time, a
local newspaper came by and asked us what we were doing,” McCready
said. “We explained the hit-prediction thing, and that we were really
turned on to a record by this artist called Norah Jones.” The record
was “Come Away with Me.” It went on to sell twenty million copies and
win eight Grammy awards.

The strength of McCready’s analysis is its precision. This past spring,
for instance, he analyzed “Crazy,” by Gnarls Barkley. The computer
calculated, first of all, the song’s Hit Grade–tha is, how close
it was to the center of any of those sixty hit clusters. Its Hit Grade
was 755, on a scale where anything above 700 is exceptional. The
computer also found that “Crazy” belonge to the same hit cluster
as Dido’s “Thank You,” James Blunt’s “You’re Beautiful,” and Ashanti’s
“Baby,” as well as older hits like “Let Me Be There,” by Olivia
Newton-John, and “On Sweet Day,” by Mariah Carey, so that
listeners who liked any of those songs would probably like “Crazy,”
too. Finally, the computer gave “Crazy” a Periodicity Grade–which
refers to th fact that, at any given time, only twelve to fifteen
hit clusters are “active,” because from month to month the particular
mathematical patterns that excite music listeners will shift around.
“Crazy ’s periodicity score was 658–which suggested a very good
fit with current tastes. The data said, in other words, that “Crazy”
was almost certainly going to be huge–and, sure enough, it was

If “Crazy” hadn’t scored so high, though, the Platinum Blue people
would have given the song’s producers broad suggestions for fixing it.
McCready said, “We can tell a producer, ‘These are the elements that
seem to be pushing your song into the hit cluster. These are the
variables that are pulling your song away from the hit cluster. The
problem seems to be in your bass line.’ And the producer will make a
bunch of mixes, where they do something different with the bass
lines–increase the decibel level, or muddy it up. Then they come back
to us. And we say, ‘Whatever you were doing with mix No. 3, do a little
bit more of that and you’ll be back inside the hit cluster.’ ”

McCready stressed that his system didn’t take the art out of
hit-making. Someone still had to figure out what to do with mix No. 3,
and it was entirely possible that whatever needed to be done to put the
song in the hit cluster wouldn’t work, because it would make the song
sound wrong–and in order to be a hit a song had to sound right. Still,
for the first time you wouldn’t be guessing about what needed to be
done. You would know. And what you needed to know in order to fix the
song was much simpler than anyone would have thought. McCready didn’t
care about who the artist was, or the cleverness of the lyrics. He
didn’t even have a way of feeding lyrics into his computer. He cared
only about a song’s underlying mathematical structure. “If you go back
to the popular melodies written by Beethoven and Mozart three hundred
years ago,” he went on, “they conform to the same mathematical patterns
that we are looking at today. What sounded like a beautiful melody to
them sounds like a beautiful melody to us. What has changed is simply
that we have come up with new styles and new instruments. Our brains
are wired in a way–we assume–that keeps us coming back, again and
again, to the same answers, the same pleasure centers.” He had sales
data and Top 30 lists and deconvolution software, and it seemed to him
that if you put them together you had an objective way of measuring
something like beauty. “We think we’ve figured out how the brain works
regarding musical taste,” McCready said.

It requires a very particular kind of person, of course, to see the
world as a code waiting to be broken. Hume once called Kames “the most
arrogant man in the world,” and to take this side of the argument you
have to be. Kames was also a brilliant lawyer, and no doubt that
matters as well, because to be a good lawyer is to be invested with a
reverence for rules. (Hume defied his family’s efforts to make him a
lawyer.) And to think like Kames you probably have to be an outsider.
Kames was born Henry Home, to a farming family, and grew up in the
sparsely populated cropping-and-fishing county of Berwickshire; he
became Lord Kames late in life, after he was elevated to the bench.
(Hume was born and reared in Edinburgh.) His early published work was
about law and its history, but he soon wandered into morality,
religion, anthropology, soil chemistry, plant nutrition, and the
physical sciences, and once asked his friend Benjamin Franklin to
explain the movement of smoke in chimneys. Those who believe in the
power of broad patterns and rules, rather than the authority of
individuals or institutions, are not intimidated by the boundaries and
hierarchies of knowledge. They don’t defer to the superior expertise of
insiders; they set up shop in a small loft somewhere downtown and take
on the whole music industry at once. The difference between Hume and
Kames is, finally, a difference in kind, not degree. You’re either a
Kamesian or you’re not. And if you were to create an archetypal
Kamesian–to combine lawyerliness, outsiderness, and supreme
self-confidence in one dapper, Charlie Brown-headed combination? You’d
end up with Dick Copaken.

“I remember when I was a sophomore in high school and I went into the
bathroom once to wash my hands,” Copaken said. “I noticed the bubbles
on the sink, and it fascinated me the way these bubbles would form and
move around and float and reform, and I sat there totally transfixed.
My father called me, and I didn’t hear him. Finally, he comes in. ‘Son.
What the . . . are you all right?’ I said, ‘Bubbles, Dad, look what
they do.’ He said, ‘Son, if you’re going to waste your time, waste it
on something that may have some future consequence.’ Well, I kind of
rose to the challenge. That summer, I bicycled a couple of miles to a
library in Kansas City and I spent every day reading every book and
article I could find on bubbles.”

Bubbles looked completely random, but young Copaken wasn’t convinced.
He built a bubble-making device involving an aerator from a fish tank,
and at school he pleaded with the math department to teach him the
quadratic equations he needed to show why the bubbles formed the way
they did. Then he devised an experiment, and ended up with a bronze
medal at the International Science Fair. His interest in bubbles was
genuine, but the truth is that almost anything could have caught
Copaken’s eye: pop songs, movies, the movement of chimney smoke. What
drew him was not so much solving this particular problem as the general
principle that problems were solvable–that he, little Dick Copaken from
Kansas City, could climb on his bicycle and ride to the library and
figure out something that his father thought wasn’t worth figuring out.

Copaken has written a memoir of his experience defending the tiny
Puerto Rican islands of Culebra and Vieques against the U.S. Navy,
which had been using their beaches for target practice. It is a
riveting story. Copaken takes on the vast Navy bureaucracy, armed only
with arcane provisions of environmental law. He investigates the
nesting grounds of the endangered hawksbill turtle, and the mating
habits of a tiny yet extremely loud tree frog known as the coqui, and
at one point he transports four frozen whale heads from the Bahamas to
Harvard Medical School. Copaken wins. The Navy loses.

The memoir reads like a David-and-Goliath story. It isn’t. David
changed the rules on Goliath. He brought a slingshot to a sword fight.
People like Copaken, though, don’t change the rules; they believe in
rules. Copaken would have agreed to sword-on-sword combat. But then he
would have asked the referee for a stay, deposed Goliath and his team
at great length, and papered him with brief after brief until he
conceded that his weapon did not qualify as a sword under §48(B)(6)(e)
of the Samaria Convention of 321 B.C. (The Philistines would have
settled.) And whereas David knew that he couldn’t win a conventional
fight with Goliath, the conviction that sustained Copaken’s long battle
with the Navy was, to the contrary, that so long as the battle remained
conventional–so long as it followed the familiar pathways of the law
and of due process–he really could win. Dick Copaken didn’t think he
was an underdog at all. If you believe in rules, Goliath is just
another Philistine, and the Navy is just another plaintiff. As for the
ineffable mystery of the Hollywood blockbuster? Well, Mr. Goldman, you
may not know anything. But I do.

Dick Copaken has a friend named Nick Meaney. They met on a case years
ago. Meaney has thick dark hair. He is younger and much taller than
Copaken, and seems to regard his friend wit affectionate
amusement. Meaney’s background is in risk management, and for years
he’d been wanting to bring the principles of that world to the movie
business. In 2003, Meaney an Copaken were driving through the
English countryside to Durham when Meaney told Copaken about a friend
of his from college. The friend and his business partner were students
of popula narrative: the sort who write essays for obscure
journals serving the small band of people who think deeply about, say,
the evolution of the pilot episode in transnational TV crime dramas.
And for some time, they had been developing a system for
evaluating the commercial potential of stories. The two men, Meaney
told Copaken, had broken down the elements of screenpla narrative
into multiple categories, and then drawn on their encyclopedic
knowledge of television and film to assign scripts a score in each of
those categories–creating a giant screenplay repor card. The
system was extraordinarily elaborate. It was under constant refinement.
It was also top secret. Henceforth, Copaken and Meaney would refer to
the two men publicly only as “Mr Pink” and “Mr. Brown,” an homage
to “Reservoir Dogs.

“The guy had a big wall, and he started putting up little Post-its
covering everything you can think of,” Copaken said. It was unclear
whether he was talking about Mr. Pink or Mr. Brown or possibly some
Obi-Wan Kenobi figure from whom Mr. Pink and Mr. Brown first learned
their trade. “You know, the star wears a blue shirt. The star doesn’t
zip up his pants. Whatever. So he put all these factors up and began
moving them around as the scripts were either successful or
unsuccessful, and he began grouping them and eventually this evolved to
a kind of ad-hoc analytical system. He had no theory as to what would
work, he just wanted to know what did work.”

Copaken and Meaney also shared a fascination with a powerful kind of
computerized learning system called an artificial neural network.
Neural networks are used for data mining–to look for patterns in very
large amounts of data. In recent years, they have become a critical
tool in many industries, and what Copaken and Meaney realized, when
they thought about Mr. Pink and Mr. Brown, was that it might now be
possible to bring neural networks to Hollywood. They could treat
screenplays as mathematical propositions, using Mr. Pink and Mr.
Brown’s categories and scores as the motion-picture equivalents of
melody, harmony, beat, tempo, rhythm, octave, pitch, chord progression,
cadence, sonic brilliance, and frequency.

Copaken and Meaney brought in a former colleague of Meaney’s named Sean
Verity, and the three of them signed up Mr. Pink and Mr. Brown. They
called their company Epagogix–a reference to Aristotle’s discussion of
epagogic, or inductive, learning–and they started with a “training set”
of screenplays that Mr. Pink and Mr. Brown had graded. Copaken and
Meaney won’t disclose how many scripts were in the training set. But
let’s say it was two hundred. Those scores–along with the U.S.
box-office receipts for each of the films made from those
screenplays–were fed into a neural network built by a computer
scientist of Meaney’s acquaintance. “I can’t tell you his name,” Meaney
said, “but he’s English to his bootstraps.” Mr. Bootstraps then went to
work, trying to use Mr. Pink and Mr. Brown’s scoring data to predict
the box-office receipts of every movie in the training set. He started
with the first film and had the neural network make a guess: maybe it
said that the hero’s moral crisis in act one, which rated a 7 on the
10-point moral-crisis scale, was worth $7 million, and having a
gorgeous red-headed eighteen-year-old female lead whose
characterization came in at 6.5 was worth $3 million and a 9-point
bonding moment between the male lead and a four-year-old boy in act
three was worth $2 million, and so on, putting a dollar figure on every
grade on Mr. Pink and Mr. Brown’s report card until the system came up
with a prediction. Then it compared its guess with how that movie
actually did. Was it close? Of course not. The neural network then went
back and tried again. If it had guessed $20 million and the movie
actually made $110 million, it would reweight the movie’s Pink/Brown
scores and run the numbers a second time. And then it would take the
formula that worked best on Movie One and apply it to Movie Two, and
tweak that until it had a formula that worked on Movies One and Two,
and take that formula to Movie Three, and then to four and five, and on
through all two hundred movies, whereupon it would go back through all
the movies again, through hundreds of thousands of iterations, until it
had worked out a formula that did the best possible job of predicting
the financial success of every one of the movies in its database.

That formula, the theory goes, can then be applied to new scripts. If
you were developing a $75-million buddy picture for Bruce Willis and
Colin Farrell, Epagogix says, it can tell you, based on past
experience, what that script’s particular combination of narrative
elements can be expected to make at the box office. If the formula says
it’s a $50-million script, you pull the plug. “We shoot turkeys,”
Meaney said. He had seen Mr. Bootstraps and the neural network in
action: “It can sometimes go on for hours. If you look at the computer,
you see lots of flashing numbers in a gigantic grid. It’s like ‘The
Matrix.’ There are a lot of computations. The guy is there, the whole
time, looking at it. It eventually stops flashing, and it tells us what
it thinks the American box-office will be. A number comes out.”

The way the neural network thinks is not that different from the way a
Hollywood executive thinks: if you pitch a movie to a studio, the
executive uses an ad-hoc algorithm–perfected through years of trial and
error–to put a value on all the components in the story. Neural
networks, though, can handle problems that have a great many variables,
and they never play favorites–which means (at least in theory) that as
long as you can give the neural network the same range of information
that a human decision-maker has, it ought to come out ahead. That’s
what the University of Arizona computer scientist Hsinchun Chen
demonstrated ten years ago, when he built a neural network to predict
winners at the dog track. Chen used the ten variables that greyhound
experts told him they used in making their bets–like fastest time and
winning percentage and results for the past seven races–and trained his
system with the results of two hundred races. Then he went to the
greyhound track in Tucson and challenged three dog-racing handicappers
to a contest. Everyone picked winners in a hundred races, at a modest
two dollars a bet. The experts lost $71.40, $61.20, and $70.20,
respectively. Chen won $124.80. It wasn’t close, and one of the main
reasons was the special interest the neural network showed in something
called “race grade”: greyhounds are moved up and down through a number
of divisions, according to their ability, and dogs have a big edge when
they’ve just been bumped down a level and a big handicap when they’ve
just been bumped up. “The experts know race grade exists, but they
don’t weight it sufficiently,” Chen said. “They are all looking at win
percentage, place percentage, or thinking about the dogs’ times.”

Copaken and Meaney figured that Hollywood’s experts also had biases and
skipped over things that really mattered. If a neural network won at
the track, why not Hollywood? “One of the most powerful aspects of what
we do is the ruthless objectivity of our system,” Copaken said. “It
doesn’t care about maintaining relationships with stars or agents or
getting invited to someone’s party. It doesn’t care about climbing the
corporate ladder. It has one master and one master only: how do you get
to bigger box-office? Nobody else in Hollywood is like that.”

In the summer of 2003, Copaken approached Josh Berger, a senior
executive at Warner Bros. in Europe. Meaney was opposed to the idea: in
his mind, it was too early. “I just screamed at Dick,” he said. But
Copaken was adamant. He had Mr. Bootstraps, Mr. Pink, and Mr. Brown run
sixteen television pilots through the neural network, and try to
predict the size of each show’s eventual audience. “I told Josh, ‘Stick
this in a drawer, and I’ll come back at the end of the season and we
can check to see how we did,’ ” Copaken said. In January of 2004,
Copaken tabulated the results. In six cases, Epagogix guessed the
number of American homes that would tune in to a show to within .06 per
cent. In thirteen of the sixteen cases, its predictions were within two
per cent. Berger was floored. “It was incredible,” he recalls. “It was
like someone saying to you, ‘We’re going to show you how to count cards
in Vegas.’ It had that sort of quality.”

Copaken then approached another Hollywood studio. He was given nine
unreleased movies to analyze. Mr. Pink, Mr. Brown, and Mr. Bootstraps
worked only from the script–without reference to the stars or the
director or the marketing budget or the producer. On three of the
films–two of which were low-budget–the Epagogix estimates were way off.
On the remaining six–including two of the studio’s biggest-budget
productions–they correctly identified whether the film would make or
lose money. On one film, the studio thought it had a picture that would
make a good deal more than $100 million. Epagogix said $49 million. The
movie made less than $40 million. On another, a big-budget picture, the
team’s estimate came within $1.2 million of the final gross. On a
number of films, they were surprisingly close. “They were basically
within a few million,” a senior executive at the studio said. “It was
shocking. It was kind of weird.” Had the studio used Epagogix on those
nine scripts before filming started, it could have saved tens of
millions of dollars. “I was impressed by a couple of things,” another
executive at the same studio said. “I was impressed by the things they
thought mattered to a movie. They weren’t the things that we typically
give credit to. They cared about the venue, and whether it was a love
story, and very specific things about the plot that they were convinced
determined the outcome more than anything else. It felt very objective.
And they could care less about whether the lead was Tom Cruise or Tom
Jones.”

The Epagogix team knocked on other doors that weren’t quite so
welcoming. This was the problem with being a Kamesian. Your belief in a
rule-bound universe was what gave you, an outsider, a claim to real
expertise. But you were still an outsider. You were still Dick Copaken,
the blue-blazered corporate lawyer who majored in bubbles as a little
boy in Kansas City, and a couple of guys from the risk-management
business, and three men called Pink, Brown, and Bootstraps–and none of
you had ever made a movie in your life. And what were you saying? That
stars didn’t matter, that the director didn’t matter, and that all that
mattered was story–and, by the way, that you understood story the way
the people on the inside, people who had spent a lifetime in the
motion-picture business, didn’t. “They called, and they said they had a
way of predicting box-office success or failure, which is everyone’s
fantasy,” one former studio chief recalled. “I said to them, ‘I hope
you’re right.’ ” The executive seemed to think of the Epagogix team as
a small band of Martians who had somehow slipped their U.F.O. past
security. “In reality, there are so many circumstances that can affect
a movie’s success,” the executive went on. “Maybe the actor or actress
has an external problem. Or this great actor, for whatever reason, just
fails. You have to fire a director. Or September 11th or some other
thing happens. There are many people who have come forward saying they
have a way of predicting box-office success, but so far nobody has been
able to do it. I think we know something. We just don’t know enough. I
still believe in something called that magical thing–talent, the
unexpected. The movie god has to shine on you.” You were either a
Kamesian or you weren’t, and this person wasn’t: “My first reaction to
those guys? Bullshit.”

A few months ago, Dick Copaken agreed to lift the cloud of unknowing
surrounding Epagogix, at least in part. He laid down three conditions:
the meeting was to be in London, Mr. Pink an Mr. Brown would
continue to be known only as Mr. Pink and Mr. Brown, and no mention was
to be made of the team’s current projects. After much discussion, an
agreement was reached Epagogix would analyze the 2005 movie “The
Interpreter,” which was directed by Sydney Pollack and starred Sean
Penn and Nicole Kidman. “The Interpreter” had a complicated
history having gone through countless revisions, and there was a
feeling that it could have done much better at the box office. If ever
there was an ideal case study for the alleged wizardry o
Epagogix, this was it

The first draft of the movie was written by Charles Randolph, a
philosophy professor turned screenwriter. It opened in the fictional
African country of Matobo. Two men in a Land Rover pull up to a soccer
stadium. A group of children lead them to a room inside the building.
On the ground is a row of corpses.

Cut to the United Nations, where we meet Silvia Broome, a young woman
who works as an interpreter. She goes to the U.N. Security Service and
relates a terrifying story. The previous night, while working late in
the interpreter’s booth, she overheard two people plotting the
assassination of Matobo’s murderous dictator, Edmund Zuwanie, who is
coming to New York to address the General Assembly. She says that the
plotters saw her, and that her life may be in danger. The officer
assigned to her case, Tobin Keller, is skeptical, particularly when he
learns that she, too, is from Matobo, and that her parents were killed
in the country’s civil war. But after Broome suffers a series of
threatening incidents Keller starts to believe her. His job is to
protect Zuwanie, but he now feels moved to act as Broome’s bodyguard as
well. A quiet, slightly ambiguous romantic attraction begins to develop
between them. Zuwanie’s visit draws closer. Broome’s job is to be his
interpreter. On the day of the speech, Broome ends up in the greenroom
with Zuwanie. Keller suddenly realizes the truth: that she has made up
the whole story as a way of bringing Zuwanie to justice. He rushes to
the greenroom. Broome, it seems, has poisoned Zuwanie and is
withholding the antidote unless he goes onstage and confesses to the
murder of his countrymen. He does. Broome escapes. A doctor takes a
look at the poison. It’s harmless. The doctor turns to the dictator,
who has just been tricked into writing his own prison sentence: “You
were never in danger, Mr. Zuwanie.”

Randolph says that the film he was thinking of while he was writing
“The Interpreter” was Francis Ford Coppola’s classic “The
Conversation.” He wanted to make a spare, stark movie about an isolated
figure. “She’s a terrorist,” Randolph said of Silvia Broome. “She comes
to this country to do a very specific task, and when that task is done
she’s gone again. I wanted to write about this idea of a noble
terrorist, who tried to achieve her ends with a character
assassination, not a real assassination.” Randolph realized that most
moviegoers–and most Hollywood executives–prefer characters who have
psychological motivations. But he wasn’t trying to make “Die Hard.”
“Look, I’m the son of a preacher,” he said. “I believe that ideology
motivates people.”

In 2004, Sydney Pollack signed on to direct the project. He loved the
idea of an interpreter at the United Nations and the conceit of an
overheard conversation. But he wanted to make a commercial movie, and
parts of the script didn’t feel right to him. He didn’t like the twist
at the end, for instance. “I felt like I had been tricked, because in
fact there was no threat,” Pollack said. “As much as I liked the
original script, I felt like an audience would somehow, at the end,
feel cheated.” Pollack also felt that audiences would want much more
from Silvia Broome’s relationship with Tobin Keller. “I’ve never been
able to do a movie without a love story in it,” he said. “For me, the
heart of it is always the man and the woman and who they are and what
they are going through.” Pollack brought Randolph back for rewrites. He
then hired Scott Frank and Steven Zaillian, two of the most highly
sought-after screenwriters in Hollywood–and after several months the
story was turned inside out. Now Broome didn’t tell the story of
overhearing that conversation. It actually happened. She wasn’t a
terrorist anymore. She was a victim. She wasn’t an isolated figure. She
was given a social life. She wasn’t manipulating Keller. Their
relationship was more prominent. A series of new characters–political
allies and opponents of Zuwanie’s–were added, as was a scene in
Brooklyn where a bus explodes, almost killing Broome. “I remember when
I came on ‘Minority Report,’ and started over,” said Frank, who wrote
many of the new scenes for “The Interpreter.” “There weren’t many
characters. When I finished, there were two mysteries and a hundred
characters. I have diarrhea of the plot. This movie cried out for that.
There are never enough suspects and red herrings.”

The lingering problem, though, was the ending. If Broome wasn’t after
Zuwanie, who was? “We struggled,” Pollack said. “It was a long process,
to the point where we almost gave up.” In the end, Zuwanie was made the
engineer of the plot: he fakes the attempt on his life in order to
justify his attacks on his enemies back home. Zuwanie hires a man to
shoot him, and then another of Zuwanie’s men shoots the assassin before
he can do the job–and in the chaos Broome ends up with a gun in her
hand, training it on Zuwanie. “The end was the hardest part,” Frank
said. “All these balls were in the air. But I couldn’t find a
satisfying way to resolve it. We had to put a gun in the hand of a
pacifist. I couldn’t quite sew it up in the right way. Sydney kept
saying, ‘You’re so close.’ But I kept saying, ‘Yeah, but I don’t
believe what I’m writing.’ I wonder if I did a disservice to ‘The
Interpreter.’ I don’t know that I made it better. I may have just made
it different.”

This, then, was the question for Epagogix: If Pollack’s goal was to
make “The Interpreter” a more commercial movie, how well did he
succeed? And could he have done better?

The debriefing took place in central London, behind the glass walls of
the private dining room of a Mayfair restaurant. The waiters came in
waves, murmuring their announcements of th latest arrival from
the kitchen. The table was round. Copaken, dapper as always in his navy
blazer, sat next to Sean Verity, followed by Meaney, Mr. Brown, and Mr.
Pink. Mr. Brown wa very tall, and seemed to have a northern
English accent. Mr. Pink was slender and graying, and had an air of
authority about him. His academic training was in biochemistry. He said
h thought that, in the highly emotional business of Hollywood,
having a scientific background was quite useful. There was no sign of
Mr. Bootstraps

Mr. Pink began by explaining the origins of their system. “There were
certain historical events that allowed us to go back and test how
appealing one film was against another,” he said. “The very simple one
is that in the English market, in the sixties on Sunday night,
religious programming aired on the major networks. Nobody watched it.
And, as soon as that finished, movies came on. There were no lead-ins,
and only two competing channels. Plus, across the country you had a
situation where the commercial sector was playing a whole variety of
movies against the standard, the BBC. It might be a John Wayne movie in
Yorkshire, and a musical in Somerset, and the BBC would be the same
movie everywhere. So you had a control. It was very pure and very
simple. That was a unique opportunity to try and make some guesstimates
as to why movies were doing what they were doing.”

Brown nodded. “We built a body of evidence until we had something systematic,” he said.

Pink estimated that they had analyzed thousands of movies. “The thing
is that not everything comes to you as a script. For a long period, we
worked for a broadcaster who used to send us a couple of paragraphs. We
made our predictions based on that much. Having the script is actually
too much information sometimes. You’re trying to replicate what the
audience is doing. They’re trying to make a choice between three
movies, and all they have at that point is whatever they’ve seen in TV
Guide or on any trailer they’ve seen. We have to take a piece here and
a piece here. Take a couple of reference points. When I look at a
story, there are certain things I’m looking for–certain themes, and
characters you immediately focus on.” He thought for a moment. “That’s
not to deny that it matters whether the lead character wears a hat,” he
added, in a way that suggested he and Mr. Brown had actually thought
long and hard about leads and hats.

“There’s always a pattern,” he went on. “There are certain stories that
come back, time and time again, and that always work. You know,
whenever we go into a market–and we work in fifty markets–the initial
thing people say is ‘What do you know about our market?’ The assumption
is that, say, Japan is different from us–that there has to be something
else going on there. But, basically, they’re just like us. It’s the
consistency of these reappearing things that I find amazing.”

“Biblical stories are a classic case,” Mr. Brown put in. “There is
something about what they’re telling and the message that’s coming out
that seems to be so universal. With Mel Gibson’s ‘The Passion,’ people
always say, ‘Who could have predicted that?’ And the answer is, we
could have.”

They had looked at “The Interpreter” scripts a few weeks earlier. The
process typically takes them a day. They read, they graded, and then
they compared notes, because Mr. Pink was the sort who went for
“Yojimbo” and Mr. Brown’s favorite movie was “Alien” (the first one),
so they didn’t always agree. Mr. Brown couldn’t remember a single
script he’d read where he thought there wasn’t room for improvement,
and Mr. Pink, when asked the same question, could come up with just
one: “Lethal Weapon.” “A friend of mine gave me the shooting script
before it came out, and I remember reading it and thinking, It’s all
there. It was all on the page.” Once Mr. Pink and Mr. Brown had scored
“The Interpreter,” they gave their analyses to Mr. Bootstraps, who did
fifteen runs through the neural network: the original Randolph script,
the shooting script, and certain variants of the plot that Epagogix
devised. Mr. Bootstraps then passed his results to Copaken, who wrote
them up. The Epagogix reports are always written by Copaken, and they
are models of lawyerly thoroughness. This one ran to thirty-eight
pages. He had finished the final draft the night before, very late. He
looked fresh as a daisy.

Mr. Pink started with the original script. “My pure reaction? I found
it very difficult to read. I got confused. I had to reread bits. We do
this a lot. If a project takes more than an hour to read, then there’s
something going on that I’m not terribly keen on.”

“It didn’t feel to me like a mass-appeal movie,” Mr. Brown added. “It seemed more niche.”

When Mr. Bootstraps ran Randolph’s original draft through the neural
network, the computer called it a $33-million movie–an “intelligent”
thriller, in the same commercial range as “The Constant Gardener” or
“Out of Sight.” According to the formula, the final shooting script was
a $69-million picture (an estimate that came within $4 million of the
actual box-office). Mr. Brown wasn’t surprised. The shooting script, he
said, “felt more like an American movie, where the first one seemed
European in style.”

Everyone agreed, though, that Pollack could have done much better.
There was, first of all, the matter of the United Nations. “They had a
unique opportunity to get inside the building,” Mr. Pink said. “But I
came away thinking that it could have been set in any boxy office tower
in Manhattan. An opportunity was missed. That’s when we get
irritated–when there are opportunities that could very easily be turned
into something that would actually have had an impact.”

“Locale is an extra character,” Mr. Brown said. “But in this case it’s a very bland character that didn’t really help.”

In the Epagogix secret formula, it seemed, locale matters a great deal.
“You know, there’s a big difference between city and countryside,” Mr.
Pink said. “It can have a huge effect on a movie’s ability to draw in
viewers. And writers just do not take advantage of it. We have a
certain set of values that we attach to certain places.”

Mr. Pink and Mr. Brown ticked off the movies and television shows that
they thought understood the importance of locale: “Crimson Tide,”
“Lawrence of Arabia,” “Lost,” “Survivor,” “Castaway,” “Deliverance.”
Mr. Pink said, “The desert island is something that we have always
recognized as a pungent backdrop, but it’s not used that often. In the
same way, prisons can be a powerful environment, because they are so
well defined.” The U.N. could have been like that, but it wasn’t. Then
there was the problem of starting, as both scripts did, in Africa–and
not just Africa but a fictional country in Africa. The whole team found
that crazy. “Audiences are pretty parochial, by and large,” Mr. Pink
said. “If you start off by telling them, ‘We’re going to begin this
movie in Africa,’ you’re going to lose them. They’ve bought their
tickets. But when they come out they’re going to say, ‘It was all
right. But it was Africa.’ ” The whole thing seemed to leave Mr. Pink
quite distressed. He looked at Mr. Brown beseechingly.

Mr. Brown changed the subject. “It’s amazing how often quite little
things, quite small aspects, can spoil everything,” he said. “I
remember seeing the trailer for ‘V for Vendetta’ and deciding against
it right there, for one very simple reason: there was a ridiculous mask
on the main character. If you can’t see the face of the character, you
can’t tell what that person is thinking. You can’t tell who they are.
With ‘Spider-Man’ and ‘Superman,’ though, you do see the face, so you
respond to them.”

The team once gave a studio a script analysis in which almost
everything they suggested was, in Hollywood terms, small. They wanted
the lead to jump off the page a little more. They wanted the lead to
have a young sidekick–a relatively minor character–to connect with a
younger demographic, and they wanted the city where the film was set to
be much more of a presence. The neural network put the potential value
of better characterization at an extra $2.46 million in U.S. box-office
revenue; the value of locale adjustment at $4.92 million; the value of
a sidekick at $12.3 million–and the value of all three together (given
the resulting synergies) at $24.6 million. That’s another $25 million
for a few weeks of rewrites and maybe a day or two of extra filming.
Mr. Bootstraps, incidentally, ran the numbers and concluded that the
script would make $47 million if the suggested changes were not made.
The changes were not made. The movie made $50 million.

Mr. Pink and Mr. Brown went on to discuss the second “Interpreter”
screenplay, the shooting script. They thought the ending was
implausible. Charles Randolph had originally suggested that the Tobin
Keller character be black, not white, in order to create the frisson of
bringing together a white African and a black American. Mr. Pink and
Mr. Brown independently came to the same conclusion. Apparently, the
neural network ran the numbers on movies that paired black and white
leads–“Lethal Weapon,” “The Crying Game,” “Independence Day,” “Men in
Black,” “Die Another Day,” “The Pelican Brief”–and found that the
black-white combination could increase box-office revenue. The computer
did the same kind of analysis on Scott Frank’s “diarrhea of the plot,”
and found that there were too many villains. And if Silvia Broome was
going to be in danger, Mr. Bootstraps made clear, she really had to be
in danger.

“Our feeling–and Dick, you may have to jump in here–is that the notion
of a woman in peril is a very powerful narrative element,” Mr. Pink
said. He glanced apprehensively at Copaken, evidently concerned that
what he was about to say might fall in the sensitive category of the
proprietary. “How powerful?” He chose his words carefully. “Well above
average. And the problem is that we lack a sense of how much danger she
is in, so an opportunity is missed. There were times when you were
thinking, Is this something she has created herself? Is someone
actually after her? You are confused. There is an element of doubt, and
that ambiguity makes it possible to doubt the danger of the situation.”
Of course, all that ambiguity was there because in the Randolph script
she was making it all up, and we were supposed to doubt the danger of
the situation. But Mr. Pink and Mr. Brown believed that, once you
decided you weren’t going to make a European-style niche movie, you had
to abandon ambiguity altogether.

“You’ve got to make the peril real,” Mr. Pink said.

The Epagogix revise of “The Interpreter” starts with an upbeat Silvia
Broome walking into the United Nations, flirting with the security
guard. The two men plotting the assassination later see her and chase
her through the labyrinthine cor-ridors of what could only be the U.N.
building. The ambiguous threats to Broome’s life are now explicit. At
one point in the Epagogix version, a villain pushes Broome’s Vespa off
one of Manhattan’s iconic East River bridges. She hangs on to her
motorbike for dear life, as it swings precariously over the edge of the
parapet. Tobin Keller, in a police helicopter, swoops into view: “As
she clings to Tobin’s muscular body while the two of them are hoisted
up into the hovering helicopter, we sense that she is feeling more than
relief.” In the Epagogix ending, Broome stabs one of Zuwanie’s security
men with a knife. Zuwanie storms off the stage, holds a press
conference, and is shot dead by a friend of Broome’s brother. Broome
cradles the dying man in her arms. He “dies peacefully,” with “a smile
on his blood-spattered face.” Then she gets appointed Matobo’s U.N.
ambassador. She turns to Keller. “‘This time,’ she notes with a wry
smile . . . ‘you will have to protect me.’ ” Bootstraps’s verdict was
that this version would result in a U.S. box-office of $111 million.

“It’s funny,” Mr. Pink said. “This past weekend, ‘The Bodyguard’ was on
TV. Remember that piece of”–he winced–“entertainment? Which is about a
bodyguard and a woman. The final scene is that they are right back
together. It is very clearly and deliberately sown. That is the
commercial way, if you want more bodies in the seats.”

“You have to either consummate it or allow for the possibility of that,” Copaken agreed.

They were thinking now of what would happen if they abandoned all
fealty to the original, and simply pushed the movie’s premise as far as
they could possibly go.

Mr. Pink went on, “If Dick had said, ‘You can take this project
wherever you want,’ we probably would have ended up with something a
lot closer to ‘The Bodyguard’–where you have a much more romantic film,
a much more powerful focus to the two characters–without all the
political stuff going on in the background. You go for the emotions on
a very basic level. What would be the upper limit on that? You know,
the upper limit of anything these days is probably still ‘Titanic.’ I’m
not saying we could do six hundred million dollars. But it could be two
hundred million.”

It was clear that the whole conversation was beginning to make Mr. Pink
uncomfortable. He didn’t like “The Bodyguard.” Even the title made him
wince. He was the sort who liked “Yojimbo,” after all. The question
went around the room: What would you do with “The Interpreter”? Sean
Verity wanted to juice up the action-adventure elements and push it to
the $150- t $160-million range. Meaney wanted to do without
expensive stars: he didn’t think they were worth the money. Copaken
wanted more violence, and he also favored making Keller black. Bu
he didn’t want to go all the way to “The Bodyguard,” either. This was a
man who loved “Dear Frankie” as much as any film he’d seen in recent
memory, and “Dear Frankie” had a domesti box-office gross of $1.3
million. If you followed the rules of Epagogix, there wouldn’t be any
movies like “Dear Frankie.” The neural network had one master, the
market, and answered on question: how do you get to bigger
box-office? But once a movie had made you vulnerable–once you couldn’t
even retell the damn story without getting emotional–you couldn’t be
conten with just one master anymore

That was the thing about the formula: it didn’t make the task of
filmmaking easier. It made it harder. So long as nobody knows anything,
you’ve got license to do whatever you want. You can start a movie in
Africa. You can have male and female leads not go off together–all in
the name of making something new. Once you came to think that you knew
something, though, you had to decide just how much money you were
willing to risk for your vision. Did the Epagogix team know what the
answer to that question was? Of course not. That question required
imagination, and they weren’t in the imagination business. They were
technicians with tools: computer programs and analytical systems and
proprietary software that calculated mathematical relationships among a
laundry list of structural variables. At Platinum Blue, Mike McCready
could tell you that the bass line was pushing your song out of the
center of hit cluster 31. But he couldn’t tell you exactly how to fix
the bass line, and he couldn’t guarantee that the redone version would
still sound like a hit, and you didn’t see him releasing his own album
of computer-validated pop music. A Kamesian had only to read Lord Kames
to appreciate the distinction. The most arrogant man in the world was a
terrible writer: clunky, dense, prolix. He knew the rules of art. But
that didn’t make him an artist.

Mr. Brown spoke last. “I don’t think it needs to be a big-budget
picture,” he said. “I think we do what we can with the original script
to make it a strong story, with an ending that is memorable, and then
do a slow release. A low-budget picture. One that builds through word
of mouth–something like that.” He was confident that he had the means
to turn a $69-million script into a $111-million movie, and then again
into a $150- to $200-million blockbuster. But it had been a long
afternoon, and part of him had a stubborn attachment to “The
Interpreter” in something like its original form. Mr. Bootstraps might
have disagreed. But Mr. Bootstraps was nowhere to be seen.

 
COOKIE NOTICE
We utilize cookie technology to collect data regarding the number of visits a person has made to our site. This data is stored in aggregate form and is in no way singled out in an individual file. This information allows us to know what pages/sites are of interest to our users and what pages/sites may be of less interest. See more