The trap of social media algorithms

A decade ago it was fashionable to talk about the social media platform Facebook as if it were a country. Commentators measured its active user base against the giant and growing populations of China and India to convey some sense of its scale, reach and power. Back then Facebook had around 850 million users, now it is nearer 3 billion people. Both China and India, by comparison, are home to around 1.4bn people each today.

With such vast and sudden “population” explosions on social media, we worried about what these platforms were doing with all the data they were harvesting. Despite those serious concerns, social media was also viewed as a positive agent of change. The role that Facebook, Twitter and others played in the 2011 Arab uprisings in gathering young people together was regularly cited as an example of the powerful catalyst these platforms could be.

In those days, Facebook’s log-in page featured the “it’s free and always will be” strapline. The phrase was key to explaining the platform’s popularity. The quid pro quo, such as it was, lay somewhere between being able to use a dazzling application without cost and surrendering some personal data to big tech. Active users across all social media platforms in 2022 number closer to 5bn people, now equivalent to the entire population of Asia, and the intervening years have turned the so-called digital town square into a challenging space. The quid pro quo seems more inequitable than ever.

Part of that is because the combination of social media and smartphones has made us into discreet, addictive and private beings. It is possible to spend hours on these platforms with an algorithm serving you an inexhaustible feed of machine-generated content.

Online giant Amazon’s recommendation algorithm famously started outperforming human editor’s picks a long time ago because it used a filtering system that was based on links between products rather than customers. It learnt that if you were searching for a copy of, say, F Scott Fitzgerald’s The Great Gatsby, there was a good chance you’d also be interested in works by Ernest Hemingway. It didn’t have to understand why customers might be interested in both authors, it just had to know that there was a correlation between products by those authors. Similarly, social media doesn’t have to interrogate why I may be searching for and interested in content about a particular subject, they just have to feed that need regardless of whether it is good for me or not.

Some people used to think social media would allow all of us to be exposed to a diverse range of opinions, but it has become far too easy to be caught in an echo chamber, consuming, liking and commenting on the posts that reinforce our own biases and disappearing down dangerous trap doors with no easy way out. The separation between our digital personalities and our real one seems to widen every year. While user bases continue to grow across social media platforms – and TikTok now captures vast tracts of the attention economy – the inner workings of the technology need rethinking and rebuilding.

A year ago, Frances Haugen, a former Facebook product manager turned whistleblower, told a US Congressional hearing that the platform’s algorithms promote posts with high levels of engagement, often pushing harmful content towards users. Facebook vigorously denied the accusation.

The National