How Netflix Reverse Engineered Hollywood

A fascinating thing I learned from Yellin is that the underlying tagging data isn't just used to create genres, but also to increase the level of personalization in all the movies a user is shown. So, if Netflix knows you love Action Adventure movies with high romantic ratings (on their 1-5 scale), it might show you that kind of movie, without ever saying, "Romantic Action Adventure Movies." 

"We're gonna tag how much romance is in a movie. We're not gonna tell you how much romance is in it, but we're gonna recommend it," Yellin said. "You're gonna get an action row and it may have more or less romance in it based on what we know about you."

As Yellin talked, it occurred to me that Netflix has built a system that really only has one analog in the tech world: Facebook's NewsFeed. But instead of serving you up the pieces of web content that the algorithm thinks you'll like, Netflix is serving you up filmed entertainment.

Which makes its hybrid human and machine intelligence approach that much more impressive. They could have purely used computation. For example, looking at people with similar viewing habits and recommending movies based on what they watched. (And Netflix does use this kind of data, too.) But they went beyond that approach to look at the content itself.

"It's a real combination: machine-learned, algorithms, algorithmic syntax," Yellin said, "and also a bunch of geeks who love this stuff going deep."

As a thought experiment: Imagine if Facebook broke down individual websites according to a 36-page tagging document that let the company truly understand what it was people liked about Atlantic or Popular Science or 4chan or ViralNova

It might be impossible with web content. But if Netflix's system didn't already exist, most people would probably say that it couldn't exist either. 


The Perry Mason Mystery

Raymond Burr in Please Murder Me.

As our interview concluded, I pulled my computer back out and showed Yellin this one last chart. Take a good look at it. Something should stand out.

Sitting atop the list of mostly expected Hollywood stars is Raymond Burr, who starred in the 1950s television series Perry Mason. Then, at number seven, we find Barbara Hale, who starred opposite Burr in the show. 

How can Hale and Burr outrank Meryl Streep and Doris Day, not to mention Samuel L. Jackson, Nicholas Cage, Fred Astaire, Sean Connery, and all these other actors in the top few dozen? 

Raymond Burr
Bruce Willis
George Carlin
Jackie Chan
Andy Lau
Robert De Niro
Barbara Hale
Clint Eastwood
Gene Autry
Yun-Fat Chow
Anthony Hopkins
Bob Hope
Cary Grant
Elvis Presley
Fred Astaire
John Wayne

Michael Caine
Roy Rogers
Sean Connery
Burt Reynolds
Charles Bronson
Dolph Lundgren
Harrison Ford
John Cusack
Ken Shamrock
Lance Henriksen
Meryl Streep
Nicolas Cage
Rutger Hauer
Samuel L. Jackson
Steven Seagal
Sylvester Stallone
Tommy Lee Jones
Val Kilmer
Anderson Silva
Buster Keaton
Eric Roberts
Fred Williamson
Jean-Claude Van Damme
Michael Madsen
Mickey Rourke
Quinton Jackson
Robert Mitchum
Smiley Burnette
Tom Berenger
Wesley Snipes


It's not that the list is nonsensical. That would be easy. We'd simply say: Netflix's actor-based genre-creation doesn't make much sense. But that's not the case at all. The rest of the actors at the top of the list make a lot of sense, even if it does not precisely reflect the top box-office earners. 

Take a look at this list of the top 15 directors, too. Since you probably don't recognize his name, Christian I. Nyby II directed several Perry Mason made-for-TV movies in the 1980s. (His father, Christian I. Nyby, directed episodes of the original series, too!)

Christian I. Nyby II
Manny Rodriguez
Takashi Miike
Woody Allen
Ernst Lubitsch
Jim Wynorski
John Woo
Joseph Kane
Norman Taurog
Peter Jackson
Akira Kurosawa
Ingmar Bergman
R.G. Springsteen
Ridley Scott
Roger Corman 

No, the strange thing is that these lists seem pretty spot-on, except for this weird Perry Mason thing

Granted, the existence of all these Raymond Burr and Barbara Hale altgenres doesn't mean that Netflix users are having these movies pop up all the time. They are much more likely to get Action Movies Starring Bruce Willis. 

But, then, why have all these genres?

Mysteries starring Raymond Burr
Movies starring Raymond Burr
Dramas starring Raymond Burr
Thrillers starring Raymond Burr
Suspenseful Movies starring Raymond Burr
Suspenseful Dramas starring Raymond Burr
Cerebral Thrillers starring Raymond Burr
Cerebral Dramas starring Raymond Burr
Cerebral Suspenseful Dramas starring Raymond Burr
Cerebral Mysteries starring Raymond Burr
Cerebral Suspenseful Movies starring Raymond Burr
Cerebral Movies starring Raymond Burr
Murder Mysteries starring Raymond Burr
Understated Movies starring Raymond Burr
Understated Suspenseful Dramas starring Raymond Burr
Understated Suspenseful Movies starring Raymond Burr
Understated Mysteries starring Raymond Burr
Understated Thrillers starring Raymond Burr
Understated Dramas starring Raymond Burr

What was the deal? I asked Yellin. 

Actually, I had a theory, which I told him. "In the DVD days, Perry Mason fans ordered a ton of Perry Mason, one after the other after the other," I said. "It created sufficient demand that you guys thought there should be categories."

That is not an accurate theory, Yellin told me. That's just not how it worked.

On the other hand, no one — not even Yellin — is quite sure why there are so many altgenres that feature Raymond Burr and Barbara Hale. It's inexplicable with human logic. It's just something that happened.

I tried on a bunch of different names for the Perry Mason thing: ghost, gremlin, not-quite-a-bug. What do you call the something-in-the-code-and-data which led to the existence of these microgenres?

The vexing, remarkable conclusion is that when companies combine human intelligence and machine intelligence, some things happen that we cannot understand. 

"Let me get philosophical for a minute. In a human world, life is made interesting by serendipity," Yellin told me. "The more complexity you add to a machine world, you're adding serendipity that you couldn't imagine. Perry Mason is going to happen. These ghosts in the machine are always going to be a by-product of the complexity. And sometimes we call it a bug and sometimes we call it a feature."

Perry Mason episodes were famous for the reveal, the pivotal moment in a trial when Mason would reveal the crucial piece of evidence that makes it all makes sense and wins the day. 

Now, reality gets coded into data for the machines, and then decoded back into descriptions for humans. Along the way, humans ability to understand what's happening gets thinned out. When we go looking for answers and causes, we rarely find that aha! evidence or have the Perry Mason moment. Because it all doesn't actually make sense. 

Netflix may have solved the mystery of what to watch next, but that generated its own smaller mysteries. 

And sometimes we call that a bug and sometimes we call it a feature.

Presented by

Alexis C. Madrigal

Alexis Madrigal is the deputy editor of He's the author of Powering the Dream: The History and Promise of Green Technology. More

The New York Observer has called Madrigal "for all intents and purposes, the perfect modern reporter." He co-founded Longshot magazine, a high-speed media experiment that garnered attention from The New York Times, The Wall Street Journal, and the BBC. While at, he built Wired Science into one of the most popular blogs in the world. The site was nominated for best magazine blog by the MPA and best science website in the 2009 Webby Awards. He also co-founded Haiti ReWired, a groundbreaking community dedicated to the discussion of technology, infrastructure, and the future of Haiti.

He's spoken at Stanford, CalTech, Berkeley, SXSW, E3, and the National Renewable Energy Laboratory, and his writing was anthologized in Best Technology Writing 2010 (Yale University Press).

Madrigal is a visiting scholar at the University of California at Berkeley's Office for the History of Science and Technology. Born in Mexico City, he grew up in the exurbs north of Portland, Oregon, and now lives in Oakland.

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