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What About Flattening the Infodemic Curve?

Jason T. Widjaja, towards data science

Leveraging ethical AI and human-centric product design to treat the chronic disease of the digital economy.

Intertwined with the rapidly unfolding Coronavirus epidemic is an insidious infodemic which may prove no less deadly. In February 2020, the director-general of the World Health Organization, Tedros Adhanom Ghebreyesus, made first coined the term:

“…we’re not just fighting an epidemic; we’re fighting an infodemic. Fake news spreads faster and more easily than this virus, and is just as dangerous.”

The comparison is neither sensationalism or hyperbole — the spread of social phenomena is so powerful, 2016 research shows that it can literally follow the same models that trace the contagion of epidemics.

Examples of the interplay of the two -demics include a slew of debunked news articles ranging from miracle cures and prevention methods such as consuming green herbs, boiled ginger or vitamin D, to false claims of vaccines curing hundreds of patients.

Unlike the Coronavirus that has emerged in the short span of a few months to wreak havoc in the world, the infodemic is deeply seeded in the fabric of the digital economy.

But like the virus, everyone has a part to play to stop its spread.

Flavours of Fake News

Before we proceed, it is worth deconstructing the concept of ‘fake news’. The UNESCO Handbook for Journalism Education and Training notes the term is both ambiguous and easily politicised, and proposes a more helpful breakdown of fake news across the dimensions of intent and factual truth, resulting in the following helpful definitions

  • Disinformation: Information that is false and deliberately created to harm a person, social group, organisation or country
  • Misinformation: Information that is false but not created with the intention of causing harm
  • Mal-information: Information that is based on reality, used to inflict harm on a person, social group, organisation or country.

Taking the virus situation as context, an example of disinformation would be a herb seller publishing that eating their herbs would prevent contracting COVID-19. In contrast, a witness to someone fainting tweeting that it is a virus-related death before proper fact checking due to being caught up in the moment would be misinformation. And hacking into a politician’s email to destabilise their election campaign would be mal-information.

All are harmful, especially when amplified by today’s technology. But knowing your enemy is the first step to victory.

Tracing the Source

But how did we get here? We investigate this in three parts:

  • Platforms that have lost the curation and balance,
  • User Interfaces that are now designed for addiction, and
  • Both preying on consumers’ inbuilt cognitive weakness to feed a ruthless commercial model that leaves addiction and filter bubbles in its wake.

Examining Our Migration To Digital Platforms

While findings vary by country and our obsession with screens may seem ubiquitous judging from what we see in public spaces, data shows it was only as recent as 2018 that social media replaced print newspapers as the primary news distribution platform in the US. And that has profound implications to the concentration of content we consume.

The nature of classic newspaper broadsheets mean that readers buying a newspaper get exposed to relatively even distribution of content — a mix of local, foreign and world news, opinions and editorials, entertainment and sports sections, and classified ads. If an average newspaper carried 100 stories, a reader might be interested in only 10. But he or she would be exposed to all 100 by virtue of the medium’s design.

But digital platforms changed the dynamics of distribution, the economics of news, and its methods of aggregation, laying the foundation for today’s infodemic:

  • The ability of anyone with an internet connection to publish has changed the face of news. And while trust in independent journalism was declining, newspapers had until recently been acting as (albeit imperfect) gatekeepers of truth by distributing only the views of people deemed credible.
  • However, the economics of digital news is harsh — a digital view brings in only a fraction of revenue compared with a print view, plus attention increasingly goes to non-traditional sources of news, leading to news revenue dropping over 60% over the past decade.
  • Enter the recommendation engine. The market had moved from news to attention, and with the nasty economics of news pushing companies to maximize eyeball time (and thus ad revenue), recommendation engines emerged to provide the means. Powered by algorithmic editors that are optimized for each individual, they had but one task: learn the unique cocktail that keeps us addicted. Then feed it to us unceasingly.

The net result UK telecommunications regulatory body Ofcom’s research into news consumption summarised this in three clear trends for people who access news online:

  • The primary device they are getting their news through is their smartphone.
  • The primary platform they are reaching most of their news through is social media.
  • The primary mindset with which they approach news is now passive.

Read the full story on towardsdatascience

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