Selection effects in media become increasingly strong as populations and media increase, meaning that rare datapoints driven by unusual processes such as the mentally ill or hoaxers are increasingly unreliable as evidence of anything at all and must be ignored. At scale, anything that can happen will happen a small but nonzero times.

Online & mainstream media and social networking have become increasingly misleading as to the state of the world by focusing on ‘stories’ and ‘events’ rather than trends and averages. This is because as the global population increases and the scope of media increases, media’s urge for narrative focuses on the most extreme outlier datapoints—but such datapoints are, at a global scale, deeply misleading as they are driven by unusual processes such as the mentally ill or hoaxers.

At a global scale, anything that can happen will happen a small but nonzero times: this has been epitomized as “Littlewood’s Law: in the course of any normal person’s life, miracles happen at a rate of roughly one per month.” This must now be extended to a global scale for a hyper-networked global media covering anomalies from 8 billion people—all coincidences, hoaxes, mental illnesses, psychological oddities, extremes of continuums, mistakes, misunderstandings, terrorism, unexplained phenomena etc. Hence, there will be enough ‘miracles’ that all media coverage of events can potentially be composed of nothing but extreme outliers, even though it would seem like an ‘extraordinary’ claim to say that all media-reported events may be flukes.

This creates an epistemic environment deeply hostile to understanding reality, one which is dedicated to finding arbitrary amounts of and amplifying the least representative datapoints.

Given this, it is important to maintain extreme skepticism of any individual anecdotes or stories which are selectively reported but still claimed (often implicitly) to be representative of a general trend or fact about the world. Standard techniques like critical thinking, emphasizing trends & averages, and demanding original sources can help fight the biasing effect of news.