A Slow Scroll Into Addiction

Addiction is a disease of the mind and not of a moral consequence. It is no longer limited to drug abuse or gambling; it exists in the overuse of social media, the internet and dependency on technology. Online experiences can become addictive due to a combination of factors, including ease of access, rewards and reinforcement, social connection, escapism and lack of regulation.

Social media addiction is no different from traditional forms of addiction. People suffering from social media addiction may spend excessive amounts of time on their platform of choice, constantly checking their accounts and experiencing anxiety or restlessness when they are not able to log on, leading them to overlook their other responsibilities, such as work, school or relationships.

Multiple studies have shown evidence of the adverse effect of excessive social media use. Findings from the Problematic Social Media Use and Mental Health in Adolescents (Boers et al., 2020) study, revealed a significant relationship between excessive social media use and depression, anxiety and loneliness among adolescents. Another study (Kircaburun & Griffiths, 2018), explored the relationship between social media addiction, self-esteem and life satisfaction, indicating that higher levels of social media addiction are associated with lower self-esteem and life satisfaction.

Some people are more susceptible to addiction than others and it can have many different causes, including psychological, social, genetic, environmental and physical factors. Although the categories of addiction are many, they are not always mutually exclusive and can overlap. Social media addiction and smartphone addiction can be closely related as social media platforms are often accessed through smartphones. Similarly, online shopping addiction and online gambling addiction can both involve excessive use of the internet for the purpose of seeking pleasure or escape.

Some technologies are designed to be addictive through the use of features such as notifications, rewards and streaks, creating a sense of accomplishment and motivation to keep users engaged. This said, it is important to recognise that not all technology is addictive. It is normal and even necessary to use technology for work, communication and entertainment. The difference between healthy technology use and addiction is the degree to which it interferes with daily life and responsibilities as well as the manifestation of withdrawal symptoms when unable to access the technology. It is also important to recognise that the causes of technology addiction are complex and multifaceted. While boredom, anxiety, depression and social isolation are common factors, genetics, personality traits and environmental factors play a role. A nuanced understanding of the different categories of addiction involves recognising the potential for overlap and the importance of healthy technology use, as well as understanding the factors that contribute to technology addiction.

In 2018, the World Health Organization (WHO) added gaming disorder to its International Classification of Diseases (ICD-11), officially recognising it as a mental health condition characterised by a pattern of gaming behaviour. This development was further canvassed by the American Psychiatric Association (APA) which developed the criteria for diagnosing technology addiction, also known as internet gaming disorder (IGD).

An addictive algorithm refers to an algorithmic decision-making process that can lead to addictive behaviour. The science behind addictive algorithms is based on understanding how the brain responds to rewards. Elements essential to this understanding draw on the principles of behavioural psychology; forming programmed habits through conditioning, leading to persuasive designs that influence thoughts and actions and which create neurological effects that can steer changes in mood, behaviour or sensation. For example, a dark pattern is a user interface (UI) design that intentionally misleads or manipulates users into making decisions that are not in their best interests. They are often used in online advertising and social media platforms to trick users into clicking on ads, signing up for subscriptions or sharing personal information. The range of some of the techniques used in designing includes scarcity (FOMO), urgency, social proof, authority (power of experts) and liking (power of association).

When we do something that is rewarding, our brains release dopamine, a neurotransmitter associated with pleasure and motivation. Dopamine release reinforces a behaviour, making us more likely to do it again. Addictive algorithms are designed to exploit this reward pathway in our brains. They do this by providing us with small, frequent rewards, such as likes, comments and shares. These rewards are often unpredictable – which keeps us engaged and coming back for more. In addition to exploiting our reward pathway, addictive algorithms take advantage of our natural tendency to seek out novelty. They do this by constantly serving us new content, which prevents us from getting bored. This constant stream of new content can be overwhelming; it also makes it difficult to step away from the app.

The combination of these factors makes addictive algorithms very powerful. They can easily hook us into a cycle of compulsive use, even when we know that our use is excessive. They are designed to keep us engaged for as long as possible in order to generate revenue from advertisements. One of the key mechanisms underlying the addictive nature of social media algorithms are the ‘variable’ or unpredictable rewards, which are known to activate the brain’s dopamine system. When we receive a reward that is unpredictable or unexpected, our dopamine levels spike, creating a sense of excitement and anticipation, which is the reason why they are so effective in keeping us engaged. They not only create this sense of unpredictability and excitement that keeps us coming back for more, but they also form habits that lead to an increase in motivation and in the time spent on social media platforms along with a decrease in overall satisfaction. However, the brain responds differently to predictable rewards. Predictable rewards tend to keep our dopamine levels stable, while unpredictable rewards create a high dopamine rush in anticipation of rewards that we cannot exactly predict. This is because our brains are wired to search endlessly for the next reward and are never satisfied. In fact, variability is the brain’s cognitive nemesis, and our minds make the deduction of cause and effect a priority over functions such as self-control and moderation. Humans crave predictability and struggle to find patterns, even when none exist.

Another mechanism is the flow-inducing interface. Social media platforms are designed to be easy to use, with a simple ‘flow-inducing’ interface that encourages us to keep scrolling content and be engaged for as long as possible, thereby encouraging addictive use. Social media platforms allow users to scroll endlessly, without any clear stopping point. User-specific data is used to deliver personalised content that is more likely to keep us engaged, as it is more relevant to our interests. Social media platforms collect data on user behaviour and preferences and use this information to deliver content tailored to each individual user. These mechanisms capitalise on classical conditioning and reward-based learning processes to facilitate the formation of habit loops that encourage addictive use.

Simplicity, seamlessness, visual appeal and gamification are some of the characteristics of a flow-inducing interface. These interfaces can activate a range of brain chemicals that are associated with optimal performance and positive emotions and involve dopamine, norepinephrine, serotonin and endorphins.

By understanding the mechanisms underlying these algorithms, strategies to mitigate their negative effects can be developed. For example, the International Society for Technology in Education (ISTE) has developed guidelines for responsible technology use in schools. The guidelines are designed to help schools protect students from the risks of technology addiction. Regulating addictive algorithms can be challenging, as there is no clear definition of what an addictive algorithm is.

While it is important to approach the subject of online experiences and mental health with compassion, it is also essential to understand that social media platforms are designed to keep us online; it is how these companies make money. While online experiences can be a great way to stay connected, excessive use can fuel feelings of addiction, anxiety, depression, isolation and FOMO. It is also important to recognise that spending too much time online can potentially make us feel more isolated and lonely and that the future of the online space is going to be more personalised, more immersive and easier to access.

Puruesh Chaudhary is an award-winning futures researcher and strategic narrative professional. She was featured amongst the World’s top female futurists and works for AGAHI. puruesh@gmail.com