With a subscriber base of more than 225 million people globally, Netflix is the largest streaming company that people pay for or share (steal?) passwords for. By offering viewers a vast selection of content and the ability to watch entire seasons at once, Netflix has eliminated the wait for weekly releases, and binge-watching has become a common way of consuming content. So far so good. The explosive growth of Netflix is good for the shareholders, and the people trying to understand human behaviour.
Cracking the code
Netflix's remarkable success is due to its unique ability to leverage user data to create a personalised viewing experience. By analysing user behaviour and preferences, Netflix tailors content and advertisements to specific demographics, predicts popular shows, and recommends new content that users are likely to enjoy. One technique that Netflix uses to implement loss aversion is the auto-play feature, which creates a sense of fait accompli in viewers by automatically starting the next episode of a series or suggesting a new show to watch. Reducing decision fatigue by increasing the scope of passive consumption by making exiting an additional unit of work. The revolution at the margins, the good Professor Jevons, would be excited and possibly appalled in equal measures at the changing nature of utility in the attention economy.
In addition, Netflix incorporates social proof principles by displaying personalized recommendations and popular programming in the "trending now" section, as well as operant conditioning by providing viewers with access to new episodes as a reward for finishing the previous ones. To give users a sense of control over their viewing experience, Netflix allows them to watch shows anytime, anywhere, and on any device, as well as skip intros and credits. These innovative characteristics help to alleviate viewer concerns about missing out and promote regular viewing habits.
The Covid-19 pandemic has further fueled the popularity of binge-watching. Netflix saw an unexpected influx of revenue, new subscribers, and time spent viewing in the spring of 2020. One survey of participants from four Southeast Asian countries found that 73.7% reported an increase in time spent binge-watching during the pandemic. A survey of U.S. adults found that 52% reported spending more time streaming in the summer of 2020 than they would in a normal summer due to Covid-19 restrictions.
The hidden costs
While binge-watching can be highly entertaining and satisfy an individual's specific needs, it is important not to overlook the negative effects of excessive binge-watching. Research suggests that excessive binge-watching may result in personality traits that lead to isolation and loneliness, similar to video game/internet addiction and problematic social media use. There are significant predictors of excessive binge-watching, including neuroticism, introversion, low self-esteem, isolation, and low conscientiousness. Furthermore, excessive binge-watching is associated with maladaptive coping strategies and a need for instant gratification. While we all love the instant gratification of scrolling through social media or binge-watching a show, Studies show that excessive screen time can negatively impact sleep quality, physical health, and mental well-being, and even strain personal relationships.
The problem of instant gratification extends beyond just streaming services like Netflix. In fact, the internet has fundamentally altered our search habits for both products and entertainment, with long-term negative consequences on our behaviour. As technology continues to advance, our devices have become more intertwined with our daily lives, shaping our behaviours and habits. There is enough evidence that shows how the constant need for immediate satisfaction can lead to addictive behaviours.
However, there is another layer to this story, which pertains to the collective impact of platforms like Netflix, where technology not only stimulates addiction but also moulds experiences through algorithms. Yet with all of the diversity available on Netflix servers contributing to tech enabled global warming, the ersatz nature of attention economy comes to fore, year after year, the large chunk of Netflixens watch a very small sample of the shows on offer with the same level of enthusiasm, there are clear consumption patterns that emerge but they have to be looked at through a storytelling lens rather than just marketing.
Engineering experiences
In 2006, Netflix launched The Netflix Prize to improve its recommendation algorithm for suggesting movies and TV shows to users. The competition offered a cash prize of $1 million to any individual or team that could improve the algorithm's accuracy by at least 10%, and it lasted for three years, attracting thousands of participants from around the world. The Netflix Prize is widely regarded as a landmark event in the field of data science and machine learning, as it helped to accelerate the development of recommendation systems.
However, with the increasing sophistication of algorithms and their pervasive use in our lives, questions about the extent to which they can influence our decision-making have emerged. Tristan Harris, a “design ethicist,” argues that people's lack of willpower is not the primary problem, but rather the fact that there are countless individuals on the other side of the screen whose job it is to break down the self-regulation people have. This raises questions about the extent to which algorithms can influence and shape our decision-making, especially in areas such as culture, where our tastes and preferences are deeply personal.
The integration of technology and algorithms into our cultural experiences is transforming the way we perceive and create culture. The Netflix Prize is a prime example of this, highlighting how people and algorithms are increasingly intertwined in shaping cultural production. As a result, our perception of culture is shifting, with competing demands for what it should represent. Looking ahead, it's probable that we will see even greater interdependence between people and algorithms in shaping the cultural landscape.
Ultimately, what is at stake in these issues is the very nature of culture and how it is produced, consumed, and valued. These questions require further exploration as the relationship between culture and technology continues to evolve.
