An information bubble is a confined view that forms in the online environment based on your own online behavior. The filtering of information can create a digital echo chamber, where you’re surrounded by content that reinforces your existing beliefs, leading to a distorted perception of a broader consensus.
These information bubbles are a product of algorithms designed to enhance the user experience by tailoring content based on the information they gather about us. These algorithms go beyond social media platforms, extending their influence on our purchasing decisions, information searches, and even restaurant recommendations through services like TripAdvisor.
With the overwhelming influx of information on the internet, it becomes necessary for users to have some form of pre-selection or prioritization to find relevant information (Kantele 2016). However, the downside is that algorithms, like humans, are susceptible to biases that can result in unfair decision-making (Angwin et al. 2016).
Furthermore, algorithms differ significantly from human decision-making processes (Van Giffen et al., 2022). While humans often consider soft goals and compromises when making decisions, algorithms are focused solely on predetermined objectives (Luca et al. 2016).
Algorithms are simply fulfilling their function
Algorithms strive to serve users to the best of their ability within the confines of their programming. They operate on Boolean logic (Boole 2010). The more we engage with or show interest in certain content, the more of it we’ll see. Our social lives revolve around the boundaries of AND, OR, and NOT.
In my experience, algorithms work most effectively on the video platform TikTok, while the social networking service Facebook receives the lowest rating from me due to its tendency to limit the content I see to around 20 individuals, despite having thousands of contacts.
These echo chambers created by algorithms hinder the free exchange of ideas, impede innovation, and undermine Habermasian communicative rationality, which emphasizes the importance of building consensus through constructive arguments (Habermas 1984). However, it’s important to recognize that algorithms are simply carrying out the tasks we assign to them.
Although the issue has mathematical and technological aspects, I believe it should primarily be approached from a humanistic perspective because people have become heavily reliant on online services that employ algorithms.
Breaking free from the bubble
Even the most mindful individuals can unknowingly find themselves trapped in an information bubble. These bubbles can be professional or ideological in nature. In an interdependent society, no bubble fosters progress. Embracing diversity and interdisciplinary approaches is essential in today’s world.
Distinguishing one phenomenon from another is increasingly challenging, necessitating the examination of interdependencies between different phenomena using multidisciplinary methods and perspectives (Laine 2015). Achieving this requires engaging with people outside of your bubble.
Bursting your bubble doesn’t require much effort. Start exploring topics within your networks that you wouldn’t typically follow. On Facebook, manually search for friends who may have remained outside the algorithms’ reach and engage with their updates. On Twitter, actively participate in discussions initiated by leading astrophysicists or experts in their fields.
While algorithms will eventually adapt, the power of choice ultimately resides with us. By consciously seeking out diverse perspectives and breaking free from our information bubbles, we can broaden our understanding of the world and promote a more inclusive and well-rounded discourse.
Angwin, J., Larson, J., Mattu, S. & Kirchner, L. 2016. Machine bias: There’s software used across the country to predict future criminals. And it’s biased against blacks. ProPublicassa 23.5.2016. New York.
Boole, G. 2010. The Mathematical Analysis of Logic: Being an Essay Towards a Calculus of Deductive Reasoning (1847). Kessinger Publishing. Whitefish.
Habermas, J. 1984. Theory of communicative action volume one. Beacon press. Boston.
Kantele, T. 2016. Näin sinua ohjataan Facebookissa ja internetissä. Yle News 19.12.2016. Helsinki.
Van Giffen, B., Herhausen, D. & Fahse, T. 2022. Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods. Journal of Business Research, 144, p. 93-106. Elsevier. Amsterdam.
Laine, P. 2015. Sitran trendit: Keskinäisriippuvuus lisääntyy. Sitra 28.4.2015. Helsinki.