It’s been hard not to notice that in the years since it first began to change watching habits around the world, Netflix has become to many cynical cinephiles a shadow of the promising space it once was.
Just a few years ago there was enthusiastic excitement to be had from the streaming giant’s promotion of original films by cinematic boundary pushers like Alfonso Cuaron (Roma), Charlie Kaufman (I’m Thinking of Ending Things), Martin Scorsese (The Irishman) and David Fincher (Mank). But these days your Netflix home page is more likely to be filled by a mix of popularity-seeking romcoms, expensively produced sci-fi mis-hits, Harlan Coben adaptations and reality TV knock-offs.
The trend is not exclusive to Netflix as other streaming services trying to reach the same global reach have followed suit. In The Guardian last week Phil Hoad argued that the rise of the troubling new genre of “mockbuster, algorithm movies” on streaming platforms was the worrying start of reliance on computer-generated data to judge audience preferences and tastes, and use the results to produce content that catered to the data.
With 301-million subscribers worldwide, Netflix is the biggest player in the streaming arena and the way that it chooses to make films has consequences for the future of movies and TV. The company produces more than 100 “originals” a year — which Hoad says makes it “more prolific than the Hollywood studios in their golden age peak”. It’s also able to deliver those films to viewers in almost 200 countries. Also, because streaming doesn’t require the expenses of theatrical release, viewership figures for these products can greatly increase over time, with a little help from Netflix’s algorithm, which pushes content to viewers based on viewing history.
Though viewers will not have been able to ignore the proliferation of algorithm films, there’s some relief to be had that while these films are created to satisfy the algorithm beast, they aren’t created directly by it yet. Rather, Netflix has fine-tuned its algorithm over the past 15 years to enable it to deliver billions of “data events” it can use for development, creation, promotion and tracking. This data is also used to advise creators when pitching projects to Netflix, so the algorithm and its data are involved from the very beginning of production.
While this kind of intervention may make many filmmakers balk at the thought of losing their creative freedom to the demands of Netflix’s machine, the truth is, as Hoad says, that the film business has always relied on overarching one-size-fits-all methods to try to figure out what will be popular with audiences.
From typecasting actors to a zealous belief in screenwriting bibles like Robert McKee’s Story and Syd Field’s Screenplay — the list of new guaranteed success guides in the movie business is almost as long as the list of films that have fallen flat with audiences.
As an anonymous former Netflix executive told Hoad: “You can have all the metrics you want, but that does not mean you are making better decisions or creating more loved content.”
Despite all the helicopter-parent, pre-production guidelines that the algorithm helps to create and all the adages that Netflix execs throw at potential producers and directors, “surprise hits” still manage to surprise — and not just audiences, but executives too.
For every Russo Brothers’ mega-budget flop like Electric State or The Gray Man there’s the unforeseen success of shows like The Queen’s Gambit and Squid Game, which no amount of data could help to predict.
The earlier period, when Netflix’s feature film division seemed set to offer a platform to auteur directors for the realisation of passion projects that traditional studios were too nervous to back, started dying in 2016, when the streamer realised that its audience was growing so fast that it may not have enough content to feed the hunger of its subscribers.
Netflix’s solution was to issue huge amounts of debt to bankroll the fast-and-furious production of enough content to keep its subscriber base and profits growing. After record subscriber numbers, with help from the Covid-19 lockdowns, the party seemed to come to a crashing halt in 2022, when subscriber numbers plummeted and investors became jittery, resulting in Netflix’s stock price losing 57% in a single day.
Since then, the streamer has cut down on its production funding, introduced advertising-supported packages and enforced tight controls to end the practice of password sharing — all of which have seen a steadying of the corporate ship, even if they haven’t resulted in the kind of risk-taking creative approach that characterised the earlier golden age.
The idea that once held sway, as Hoad notes, that “streaming companies — facilitated by infinite server space and bottomless catalogues — would find new audiences for more obscure film titles” has also proven to be a fallacy. Research has shown that Netflix is “even more reliant on a handful of big titles than the theatrical box office: the top 7% of Netflix titles in the US accounted for 50% of views (compared to 41% of box-office takings for the top 7% of cinema titles)”.
The algorithm may not yet be making the next generation of blockbusters, but it is — “by continually surfacing the mass-market or safe choice” — having “a flattening, coarsening effect on our overall tastes”. By the time — closer than we imagine — that AI is used to auto-generate expensive and time-consuming aspects of film production, from scriptwriting to editing patterns and special effects, the results may only serve to flatten movies and TV more than they already have been.
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