More of Less: A Case Against Netflix’s Tailored Posters
In today’s data-driven economy, digital businesses can leverage users’ feedback and usage patterns to tailor their products and react to shifts in the market. Generally speaking, tailoring guarantees a more customized experience which improves customers satisfaction of the service. However, sometimes it’s used as smokescreen, masking a company’s botched attempts to create meaningful inclusion or diversity in their products.
A good example of a reactive business is Netflix, the largest paid streaming service in the world with over 203 million subscribers as of 2020. Netflix offers a tailored experience for its users through endless curated lists of content based on their watch history, but Netflix also engages in another less overt practice meant to personalize your home screen: tailored movie posters. This is a feature that I have been aware of for a while and one that Ruha Benjamin highlights in her book, Race After Technology, “Netflix movie recommendations … can entice Black viewers, by using tailored movie posters of Black supporting cast members, to get you to click on an option that you might otherwise pass on.”
Despite how wary I am now, I’m sorry to say that this kind of targeting has worked on me in the past. I’ve dedicated too many hours to movies and shows on Netflix hoping to see characters that turn out to be underdeveloped supporting cast, one-offs, or otherwise unessential to the plot. It’s disappointing because there’s still a shortage of black stories being shown on screen despite films like Black Panther and series like Insecure proving how viable the market for them is. By seeking out what appeared to be black stories I thought I was voting with my attention and my clicks for more diverse content, but actually, I was just chasing representation that didn’t exist. I was settling for less without even knowing it.
It’s sinister. Race-baiting is one thing but when Netflix is also seeing POC walk from their writer’s rooms due to mistreatment and their more ‘diversely’ casted series miss the mark on representation it’s clear that Netflix’s tailored algorithms are simply a way to put an inclusive face on a company that is deeply uninterested in real inclusion.
Benjamin says, “The dominant shift toward multiculturalism has been marked by a move away from one-size-fits-all mass marketing toward ethnically tailored niches that capitalize on calls for diversity.” But what do we do when ethnically tailored advertising masks one-size-fits-all content? How do we avoid settling for less when our data enables an algorithm that maintains the status quo? Catherine D’Ignazio and Lauren Klein in Data Feminism suggest, “If you are concerned with justice in data communication, or data science more generally … practice recognizing, naming, and talking about these structural forces of oppression.” In short, we can’t allow our data to speak for itself when it comes to inclusivity and representation. We must continue to advocate for the changes we want to see in our entertainment and beyond by supporting the right projects and speaking out against companies like Netflix when they seek to exploit their users or their employees.
