A Blog by Jonathan Low

 

Feb 1, 2015

Netflix's Secret Special Algorithm Is a Human

Music, politics, sports, business. And now, movies. Data has changed the way we watch, listen, hear and yes, think. Because its use has decided what options we are given.

Not that choice has been entirely eliminated, but given that convenience is the driving force for much of what zooms by us on the net or any other electronically-driven access point, we are increasingly reliant on others to help us cut through the clutter. And those others, more often than not, are computers and algorithms, rather than people.

At least that is the popular narrative. But it turns out that we homo sapiens, as idiosyncratic and unreliable and kludgy as we may be, continue to serve a rather significant purpose. Which is to make sense of the data these various digital sources provide, by aggregating, collating, curating and interpreting not just the raw knowledge but the context, history and implications of that information so that it becomes something closer to wisdom.

This may well be a task that computers and their algorithms will learn to perform as well as or better than humans. But the guess here is that as in so many other contemporary endeavors the optimal solution will emerge from a collaborative process encompassing the efforts of many contributors, including machines, algorithms - and humans. JL

Tim Wu reports in the New Yorker:

What we are seeing is the rise of a different kind of talent. It is a form of curation whose aim is guessing not simply what will attract viewers but what will attract fans. Data may help, but what may matter more is a sense of what appeals to the hearts of obsessive people.
On the opening night of this year’s Sundance Film Festival, two films, as usual, had their premières, gaining maximum exposure to reporters and critics. The first was “What Happened, Miss Simone?,” a documentary about the singer and civil-rights icon Nina Simone. It was funded by Netflix, based at least in part on data the company collects about its users: information about what we watch, when we watch, how highly we rate what we’ve seen, and even when we hit rewind. The second film that premièred was a comedy named “The Bronze,” featuring the television star Melissa Rauch (“The Big Bang Theory”) as a vulgar gymnast; the film’s high point is a vivid gymnastic sex scene involving what might fairly be called a new take on the pommel dismount. “The Bronze” was privately funded by a few wealthy individuals and was the personal selection of Sundance’s director, John Cooper—or, at least, that’s what he said at its screening.
While not a formal competition in any sense, the night seemed to be a clear victory for algorithms over instincts. “Miss Simone” gained a standing ovation at its screening and has earned critical respect. “The Bronze,” while garnering some laughs, currently sits at ten per cent on Rotten Tomatoes, where critics have called it “a grueling experience to sit through” and “a mean-spirited and largely witless satire.”
Studios and television networks have long made decisions about what to produce based on the intuitions of a limited number of executives. Television studios have Nielsen ratings, and movie studios have box-office sales, to help guide them. But those are relatively simple metrics, and notoriously unreliable; as the screenwriter William Goldman famously said, “nobody, nobody—not now, not ever—knows the least goddamn thing about what is or isn’t going to work at the box office.” As with the arrival of sabermetrics in baseball or the rise of pollsters in politics, the potential for the quants to change the industry—to really figure out what people want to watch—is clear.
Netflix and its chief content officer, Ted Sarandos, have been the most outspoken proponents of data-driven programming, which they say was behind the company’s biggest successes, such as “House of Cards” and “Orange is the New Black.” Soon after the début of “House of Cards,” David Carr, writing in the Times, pronounced that “Big bets are now being informed by Big Data.” In 2013, Kevin Spacey, the star of the show, said that Netflix had come to him and said, “We believe in you. We’ve run our data and it tells us that our audience would watch this series. We don’t need you to do a pilot. How many do you wanna do?”
Over the years, however, I’ve started to wonder whether Netflix’s big decisions are truly as data driven as they are purported to be. The company does have more audience data than nearly anyone else (with the possible exception of YouTube), so it has a reason to emphasize its comparative advantage. But, when I was reporting a story, a couple of years ago, about Netflix’s embrace of fandom over mass culture, I began to sense that their biggest bets always seemed ultimately driven by faith in a particular cult creator, like David Fincher (“House of Cards”), Jenji Leslie Kohan (“Orange is the New Black”), Ricky Gervais (“Derek”), John Fusco (“Marco Polo”), or Mitchell Hurwitz (“Arrested Development”). And, while Netflix does not release its viewership numbers, some of the company’s programming, like “Marco Polo,” hasn’t seemed to generate the same audience excitement as, say, “House of Cards.” In short, I do think that there is a sophisticated algorithm at work here—but I think his name is Ted Sarandos.
I presented Sarandos with this theory at a Sundance panel called “How I Learned to Stop Worrying and Trust the Algorithm,” moderated by Jason Hirschhorn, formerly of MySpace. Sarandos, very agreeably, wobbled a bit. “It is important to know which data to ignore,” he conceded, before saying, at the end, “In practice, its probably a seventy-thirty mix.” But which is the seventy and which is the thirty? “Seventy is the data, and thirty is judgment,” he told me later. Then he paused, and said, “But the thirty needs to be on top, if that makes sense.”
Of course, there is a big difference between using data in combination with intuition and relying entirely on an algorithm—the decision-making equivalent of Siri finding gas stations near you. I don’t think anyone—Netflix, Mitt Romney—makes big decisions that way. As Chris Kelly, the C.E.O. of Fandor, an indie-film Internet channel told me, “It just isn’t true that you can rely on data completely.” Even Google, the champion of algorithms, employs substantial human adjustments to make its search engines perform just right. (It cares so much about this that Google claims First Amendment protection for its tweaks.) I do not doubt that companies rely more on data every day, but the best human curators still maintain their supremacy.
Perhaps what we are seeing here is better explained by the rise of a different kind of talent. It is a form of curation (at which Sarandos excels) whose aim is guessing not simply what will attract viewers but what will attract fans—people who will get excited enough to spread the word. Data may help, but what may matter more is a sense of what appeals to the hearts of obsessive people, and who can deliver that. And what that suggests is that competition will remain possible for companies that aren’t Amazon or Netflix, without massive piles of data on hand. It might be enough to know just which cults to bet on.

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