Cash rules everything around us, and so do simulations. Many governing decisions are based on information gathered, modeled, and simulated: future sales expand supply chains, accidents create traffic lights, death forces us into quarantine, and the effects on the economy might force us out. Yes, COVID-19 revealed our death is simulated in dollars too. These necroeconomics have been with us since the Great Plague. But can they survive the climate crisis? Can we? Laying bare the history of our monetary mortality, we offer a shot at rethinking the governing simulations that decide over our lives.

French philosopher Michel Foucault defined biopower as the power over bodies, or the social and political techniques to control people’s lives. Cameroonian philosopher Achille Mbembe continued this line of thinking to arrive at necropolitics, the politics of death, or as he phrases it: “contemporary forms of subjugation of life, to the power of death.” COVID-19 has put these powers in sharp relief. Most world-changing events of the twenty-first century have been internalized with the question “where were you?” For example, “where were you when the planes hit?” But the pandemic knows no single universal moment to refer to. It’s become as much a question of when, as of where. “When did you take the pandemic seriously?” Most likely, your answer stands in direct relation to your proximity to death. Whether a critical mass or a specific loss, fatality defined COVID-19’s reality.

For many governments, it wasn’t the absolute count of death, but rather its simulations that made them take action. The United States was one of the last countries holding out on a lockdown until the Imperial College report projected the possibility of two million to four million fatalities in the US alone (if no measures were taken). And these weren’t the only simulations being run. A week into the lockdown, it was wondered aloud whether this was all worth the cost. It was a unique public reveal of the deadly economics—or necroeconomics—that we’re usually insulated from, whether through specialist language games or simply because they’re too grim to face. But ignoring the financialization of our demise doesn’t make it go away. If we are to ever reconsider the systems meant to keep us alive, we’d better get familiar. What better place to start than to see the current crisis through the eyes of one of the most widely used models of death: the one that puts a price on life. It’s called the “Value of a Statistical Life” or VSL, and this is how much it might value the lives lost to COVID-19 thus far:

VALUE OF A STATISTICAL LIFE AND DEATH

What better currency to express the death value in than the US dollar? It’s not just the preeminent global currency, but also the only one to trade against the anaerobic decomposition of buried dead organisms, better known as oil (every oil-exporting nation must receive dollars for their exports, not their own currency). Admittedly, the COVID-19 Death Value is a crude estimate, and perhaps even an offensive one, which all aligns with the VSL model that underpins it.

Whether aware of it or not, VSL has been pricing life and death for decades. In 2017, the White House used VSL to put a price on the opioid epidemic ($504 billion). The World Bank often cites it, as in their reports on poverty. The EPA used it in their six-year retroactive study on the 1970 Clean Air Act, concluding that the cost was worth the lives it saved ($523 billion for $5.6 to $49.4 trillion in lives). And it caused Ford to lobby against federal fuel tank regulations whilst in the midst of its Pinto fiasco (the infamously popular car from the 70s that had a fatally flawed gas tank), simply because the 180 lives the regulations could save were priced at $200,000 per statistical life by the National Highway and Traffic Safety Administration, which didn’t outweigh the $137 million the regulations would cost.

VSL often works contextually, based off of “revealed preference.” For example, the eventual adaptation of the fuel tank regulations, despite Ford’s lobbying, reveals that those in charge value life at at least $760,000 ($137 million for 180 lives). “At least” is indicative here. This one instance merely sets a lower bound.

In order to establish the average VSL of a population, multiple revealed preferences are compared, including stated preference by surveying people on what they’re willing to pay (WTP) in exchange for reducing their risk of premature death.

Take for example an air pollution policy that on the individual level costs $3 in taxes in exchange for a reduction in risk for premature death by 0.0002 percent. Scaling this up reveals a cost of $3 million (one million people times $3) to save two lives (0.0002 percent of one million people), and thus a VSL of $1.5 million. Another way to calculate this is to simply divide the Willingness to Pay (WTP) by the reduction in risk.

RAND’S RHETORICAL TRICK

Here lies the critical intellectual move that made way for VSL. By aggregating up the price of risk, the value speaks to statistical lives rather than any particular lives or life itself. It’s a rhetorical trick, but one that made it politically viable for the model to emerge. The same trick was employed by the governor of New York on March 24 (when the global fatalities of COVID-19 were still at 17,241), as he declared: “We’re not going to put a dollar figure on human life.” Politically and technically he’s correct. Thomas Shelling said as much himself when he laid the groundwork and put forth the terminology of VSL in his 1968 book The Life You Save May Be Your Own. Schelling said the question of the worth of human life itself was too “awesome” for economists to address. But statistical lives—now that was another story.

Schelling had picked up where his student Jackson Carlson had left off, a few years prior. Both were working at RAND Corporation, an American-based policy think-tank, where they inherited the legacy of RAND’s massive failure in 1950. At this time, RAND had been contracted by the US Air Force to devise an airstrike on the Soviet Union, which had just detonated its first nuclear bomb. A total of 400,000 configurations were simulated in order to figure out how to maximize damage within the budget of fissile materials. The eventual report recommended filling the Soviet sky with inexpensive planes, consisting mainly of decoys, to overwhelm and distract their defenses. Left out of this picture were the lives of those piloting the planes. Safe to say that the US Air Force was not pleased.

To avoid further loss of face, RAND labeled the issue a criterion problem, one that could not be solved due to imperfectly observed or measured objectives. But a decade later, Carlson found a new approach. He looked at the $80 million investment the US Air Force had made into the B-58 bomber’s capsule ejection system, which was assumed to save one to three lives annually. Taking into account additional costs, Carlson calculated that this choice revealed that the Air Force valued the lives of their pilots to the sum of at least $1.17 million to $9 million. Once again, this merely reveals a lower bound, but it was a breakthrough approach that Schelling would extend to the individual in order to create the Value of a Statistical Life.

THE SEVEN MILLION POUND PLAGUE

The history of necroeconomics is much longer than that of VSL. It goes as far back as blood money, or weregild, the money a killer had to pay the family of their victim in the times before criminal justice systems. But perhaps the first time that death was truly put in economic terms was in the aftermath of the Great Plague of the late seventeenth century. At the time, English economist William Petty calculated that the 68,989 lives lost (today the estimates are closer to 100,000) equaled an economic cost of about £7 million. Petty came to this conclusion by way of England’s total income and expenditure (the first use of GDP, although that term wouldn’t be coined until later), from which he then derived the price of the average Englishman and laborer (£69 and £138 respectively). This evaluation of gross income and labor would later be called human capital, and for a while it was the only model that could put a price on life, and death.

Of course human capital is extremely limited in scope, focusing solely on the material value a person produces. Today’s VSL model provides a better picture, taking in a multitude of revealed preferences in combination with surveying people’s stated preferences. But many countries lack such surveys and data, leading to VSL’s often Western-centric, dollar-focused point of view. For the COVID-19 Death Value, we looked to a widely cited Cambridge paper called “Income Elasticities and Global Values of a Statistical Life,” in which population-averages for 189 countries are calculated in relation to the benchmark VSL from the United States.

The COVID-19 Death Value, within the context of the VSL model, is a generous estimate. Population averages leave out details such as age, something that’s easier to account for when focusing on a single country, as some articles did when looking at the cost-benefit analysis of the lockdown. But much like the VSL model itself, taking age into account doesn’t go without controversy. 

TRAGEDIES OF TRIAGE

As death rates spiked and world leaders invoked wartime rhetoric, the nurses and doctors on the frontlines faced the true wartime tragedy: triage, the decision of who to extend care to based on urgency and need, usually reserved for times of limited capacity such as war or catastrophe medicine. China had already been triaging hospital admissions, having to turn away those patients who still seemed able to cope without medical support. But in Italy, medical workers faced the heart-wrenching choice of distributing limited ventilators between already incapacitated patients. Rather than prioritizing those worse off, the ventilator would be extended to whomever was most likely to survive, which usually came down to age. The young before the old. Official guidelines even mentioned that “it may become necessary to establish an age limit for access to intensive care.”

According to the head of medical ethics at NYU School of Medicine, prioritizing age “would not fly in the US.” And he was right. A precedent can even be found in relation to VSL. Back in 2003, the EPA lowered the VSL of elderly citizens to account for the fewer years they had left. It became a public outcry. Known as the “Senior Death Discount,” the US Congress had to get involved and the EPA eventually retreated. This time, with COVID-19, the US federal civil rights office made sure it wouldn’t come to an outcry, as they told hospitals not to discriminate on the basis of age, disabilities, race, or religion.

Some have argued that occupation should be taken into account instead, mainly in reference to medical workers and the classic case of the Army doctor coming first in order to help others. But semantic and moral pitfalls abound, as this can quickly slip into prioritizing “valuable” workers overall. This is what the 9/11 Victim Compensation Fund did. Their payouts were initially based on the loss of expected earnings (the value of the worker), resulting in the families of stockbrokers getting paid out more than those of the firefighters that went in to save them. This strange form of modern blood money, or neo-weregild if you will, caused a legal feud that dragged out for years.

With age, disability, and occupation off the table, the American hospitals facing the realities of limited beds and ventilators were to rely on the overall health status of the patient. As the priority of those with pre-existing conditions gets lowered, the systemic inequalities taking place further upstream are exacerbated. Pre-existing conditions disproportionately affect those unable to afford healthcare, and so it’s people of lower income and communities of color that find themselves on the receiving end of this supposedly indiscriminate triage. To no fault of the doctors forced to make this choice.

THE GREAT EMPHASIZER

Death has never been a stranger to disproportionality, something once again made painfully clear by COVID-19. While at first the virus seemed to be able to inspire a new internalization of our biological universality, the increased death count revealed the problems that were always already there, necroeconomics included. The pandemic is not the great equalizer, if anything it’s the great emphasizer.

As we try to stay afloat in the swamp of a pandemic with many maps still missing, we look at the models that do exist and consider where to look for a future. While COVID-19 has hit hardest in those countries that happen to carry a VSL of more than $1 million a life, we should think about what this means in the face of ongoing climate change.

As with all death, the continuous onslaught of environmental disasters will have disproportionate effects as well. The parts of the planet to be hit hardest are the ones that the current necroeconomics deems less valuable. What happens when the value of their deaths are not seen as outweighing the cost of mitigation? With the ecological crisis crashing down on us, perhaps it’s time to include more ecological models into the picture. As philosopher Slavoj Žižek mentions in his latest book on COVID-19:

“So it is not enough to put together some kind of global healthcare for humans, nature in its entirety has to be included. Viruses also attack plants, which are the main sources of our food. We have to constantly bear in mind the global picture of the world we live in, with all the paradoxes this implies. For example, it is good to know that the coronavirus lockdown in China saved more lives than the number of those killed by the virus (if one trusts official statistics).”

Indeed. What could death models learn from the models of, say, food webs? Ones that appreciate the planet’s interconnectivity and help understand the value of those lives that might seem insignificant or even imperceivable at first. What about social network theory that provides a better understanding of the ripple effects of death into the social structures that the life was previously part of? There is even room for the continuation of necroeconomics. But not unless it steps out of the shadows, invites wider conversation, and incorporates a value of death in the context of the larger planetarity, rather than just the economy.​

Yevheniia Berchul is an architect and urban designer based in Kyiv.

Yu Gong is an information designer from China.

Andrey Shevlyakov is a researcher at the Moscow Institute of Control Sciences.

Bryan Wolff is a creative director and writer from the Netherlands, usually based in New York.

Source: https://strelkamag.com/en/article/governing-simulations-intro-to-necroeconomics