We thought badly of the Internet

We thought badly of the Internet

For years, the primary metaphor of the internet has been the town square, an infinite space of free expression where everyone can have their say. But as large-scale digital platforms have grown to dominate most of modern life, metaphors focused solely on language have failed to explain our current civic dysfunction.

Perhaps the best way to understand the Internet is to compare it to a much older infrastructure problem: urban sewage systems. The posted content is similar to water; websites and other interfaces are analogous to pumps; and unintentional feedback loops correspond to the risk of infection. A public health framework for understanding the internet would focus not on online information itself, but on how it is generated, disseminated and consumed via digital platforms.

The genesis of this model lies in the two-century history of early advocates of clean water in Victorian England. At that time, the deadly diseases ravaging cities: cholera, typhoid, tuberculosis, and scarlet fever were not new. What was new was the modern living conditions. Infections that could have taken weeks to spread through a village suddenly devastated entire populations within days, and no one understood what was causing the massive outbreaks.

The Victorian working classes knew who to blame when the disease broke out: the doctors. The mob assaulted members of the medical establishment, leaving government officials unsure how to weigh doctors’ safety against the public interest. Why the anger? The traditional quarantine disease response had become ineffective in industrialized cities, prompting the public to distrust those who profited from the treatments.

The first serious approach to the problem was taken by a coalition of physicians, liberal advocates and social reformers beginning in the 1830s. Known as miasmists, they pushed the idea that noxious air was the culprit for epidemics. If a neighborhood couldn’t pass the smell test, they argued, it quickly became clear that it was already too late to be saved.

Miasmists, including prominent ones like Florence Nightingale, have an ambivalent heritage. They were among the first to point out that the disease had not only biological but also social and economic causes, a crucial insight. But at the same time, they were dead wrong about the role of air in spreading the common diseases of the time, reflecting an elitist worldview and over-prescribed morality.

This tension was revealed during two key events. One was the Great Stink of 1858, in which a combination of heat and poor waste disposal turned the River Thames into a cesspool. The stench was so strong that even the curtains of the houses of Parliament had to be caked with lime. No one was safe from stale air, and miasmist guesses meant that no one was safe from disease. But, in reality, no major epidemics followed the Great Stink.

The second was the pioneering work of a brilliant physician, John Snow, who had suspected for years that water (not air) was the real cause of urban epidemics. In a painstaking natural experiment, Snow demonstrated that the Broad Street pump was the source of the 1854 cholera epidemic in the Soho area of ‚Äč‚ÄčLondon. His data revealed that residents living throughout the city got sick if he happened to get their water from the pump, though a nearby brewery that drew its water from a different source had no recorded cases. There was no other reasonable explanation: some as yet undiscovered mechanism, located at the pump, was responsible for the infection. While Snow was careful to frame his findings so as not to outright reject the miasma theory, the implications were obvious.

After much debate, over the next 20 years London implemented the world’s first modern sewage system. And from 1850 to 1900, urban disease was reframed from a problem of individual circumstance and neglect to one of economic dependency and social interconnectedness. Once it became clear that not only medical professionals but also effective water pipes and safety valves were needed, public policy shifted from one-time treatments to longitudinal assessment of population health, fueled by new assessment mechanisms. The public health stakes had changed: if cholera outbreaks continued, they only did so because cities refused to provide clean water to vulnerable populations.

Today we live in an online version of the Great Stink and desperately need John Snow’s methods. Evidence is rapidly accumulating that social media causes serious harm on a large scale, especially in terms of declining mental health and societal trust. But because these effects aren’t directly measurable (except what’s been revealed by whistleblowers and difficult natural experiments), like Snow, we’re left to speculate about the causes as we try to get better data.

What would it take to build something like healthcare infrastructure for social media or generative AI? As we discuss in detail in a recently published project, it would mean building evaluation tools to link design features such as the feedback loops embedded in content recommender systems with population outcomes such as mental health effects.

To extend the metaphor, current technological interventions tend to focus on moderation strategies focused on specific users and individual content. This is similar to the role of nurses in public health, crucial and under-resourced providers of well-being. But just as no one should think good nursing is the best way to deal with bathwater, content moderation isn’t enough to address dysfunctional platform architectures.

Modern platforms already operate like experimental laboratories, repeatedly running randomized controlled trials to improve outcomes based on business goals. What we need are tools to evaluate the models and platform interfaces that determine how populations are exposed to content over time to assess whether restrictions need to be implemented to protect at-risk groups. For potential issues such as mental health impacts or systemic decreases in trust, platform effects would be evaluated alongside internal metrics for growth and revenue. And just as epidemiologists have learned to focus on infants and children as particularly vulnerable subpopulations, today’s researchers need to pay close attention to crucial risk vectors, such as adolescents’ chronic use of social media.

Sanitation has not only made epidemics easier to control and mitigate; it made diseases themselves easier to understand, eventually leading to the germ theory. Since Louis Pasteur’s first experiments, the new science of bacteriology has confirmed the existence of microorganisms, as John Snow only suspected. Once the specific bacterium responsible for cholera was identified under the microscope, a new cornerstone of public health was established.

We are now in a similar moment: We have strong ideas about causal mechanisms that might mediate harms caused by products (such as interpersonal comparisons among adolescents leading to mental health problems). But just as 1850s London didn’t need germ theory to begin assessing the effects of water and establishing sanitation systems, the first step in mitigating harm in large-scale models is to establish baseline effects regardless of the explanation. The public health lesson is that such baselines will be needed to build consensus on which platforms and large language models they need to measure and optimize.

We can continue to treat technology platforms as a town square where the loudest and ugliest voice wins. But instead of metaphors that blame people or encourage us to disconnect when things get harmful, we can embrace the public health standard. The solution won’t come from more content moderators or ever smarter chatbots, but from new infrastructural commitments: pipes, valves and pumps that would actually keep users safe.

#thought #badly #Internet

Previous articleThe internet is losing its mind because Barbie Land has no water and I’m right there with them
Next articlePeak Design Everyday Case for Pixel 7a review: a case designed for accessories

LEAVE A REPLY

Please enter your comment!
Please enter your name here