Algorithms of Life

Following the Italian Data Protection Authority (DPA), opening of an investigation following the death of a 10-year-old girl in Palermo who took part in a “blackout challenge” on TikTok, our Education Officer Louise O’Hagan takes a quick look at the world of algorithms.

Algorithms: a defined sequence of operations.

Do we really understand how the internet works? We hear our lives are being shaped by algorithms, but what are they and how do they work? Algorithms are widely used across internet platforms and smart device apps. ­­­They regulate what is important in our technological society, for example they decide what we see or read and what entertains us. The decision on what to show us is based on our own internet activities such as likes, dislikes, queries, views, interests, relationships, news, entertainment choices and more. These internet activities create electronic data which is collected about us to make these decisions for our future.

Let’s look at some of the current algorithms that shape our everyday lives…

SEARCH ENGINES

We type a search phrase into the search box and within seconds the algorithm will have trawled through the approximately 400 million websites on the internet and show us a list of suggested web pages to visit based on the search phrase. The algorithm ranks the webpages as they see most fitting for the search term. The Google PageRank algorithm system is patented and is one of their most important features.

NETFLIX & YOUTUBE

These platforms suggest to us what to watch next called recommendation algorithms – these are other examples of algorithms that trawl electronic data on the internet to determine what to show. These types of algorithms can learn on their own. They have a set of instructions such as pattern recognition in a data set, they then can trawl through masses of data to find what they need to complete the task. This is called machine learning, simply the machine learns on its own. ‘Machine learning’ is defined as a computer’s ability to learn without being explicitly instructed. Simply explained, machine learning uses programmed algorithms that analyse data to predict output. Each time new data is fed to these algorithms, they learn and improve their processes to optimise performance. These machine learning algorithms, who learn what the viewers want without assistance from humans. It bases decisions from going through users’ online activities and user generated data. The home pages on both of these sites provide a list of suggestions and recommendations of what to watch. This will all depend on the users’ previous watch history, which will have been collected as electronic data and used to feed the algorithm.

FACEBOOK

This algorithm choses what posts the user sees by deciding what is most relevant to the user. This is based on their past behavior, such as how long they spend on certain posts or pages they like. Facebook’s first algorithm was not until 2009, on their newsfeed. The idea of Facebook’s algorithms is to keep people on the website as long as possible. Facebook bases their algorithms on with whom, what and when users interact, indicated by the user’s previous activity.

These examples show  how algorithms can speed up tasks, which is beneficial in many aspects – we all love a good recommendation – but can also be harmful. We don’t have the opportunity to explore other ideas and content different to ones they have chosen or viewed before because they are targeted with similar content, and can end up in an information bubble. To conclude, our lives are being shaped by algorithmic ranking and recommendations and the first step to regaining control of our choices is to be aware of this.

For more information on the potentially devastating  impact of algorithms, check out the New York Times’ fantastic Rabbit Hole podcast series.