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By Emily Howerton, Penn State; Cecile Viboud, National Institutes of Health, and Justin Lessler, University of North Carolina at Chapel Hill 

How can anyone decide on the best course of action in a world full of unknowns?

There are few better examples of this challenge than the COVID-19 pandemic, when officials fervently compared potential outcomes as they weighed options like whether to implement lockdowns or require masks in schools. The main tools they used to compare these futures were epidemic models.

But often, models included numerous unstated assumptions and considered only one scenario – for instance, that lockdowns would continue. Chosen scenarios were rarely consistent across models. All this variability made it difficult to compare models, because it’s unclear whether the differences between them were due to different starting assumptions or scientific disagreement.

In response, we came together with colleagues to found the U.S. COVID-19 Scenario Modeling Hub in December 2020. We provide real-time, long-term projections in the U.S. for use by federal agencies such as the Centers for Disease Control and Prevention, local health authorities and the public. We work directly with public health officials to identify which possible futures, or scenarios, would be most helpful to consider as they set policy, and we convene multiple independent modeling teams to make projections of public health outcomes for each scenario. Crucially, having multiple teams address the same question allows us to better envision what could possibly happen in the future.

Since its inception, the Scenario Modeling Hub has generated 17 rounds of projections of COVID-19 cases, hospitalizations and deaths in the U.S. across varying stages of the pandemic. In a recent study published in the journal Nature Communications, we looked back at all these projections and evaluated how well they matched the reality that unfolded. This work provided insights about when and what kinds of model projections are most trustworthy – and most importantly supported our strategy of combining multiple models into one ensemble.

Multiple models are better than just one

A founding principle of our Scenario Modeling Hub is that multiple models are more reliable than one.

From tomorrow’s temperature on your weather app to predictions of interest rates in the next few months, you likely use the combined results of multiple models all the time. Especially in times like the COVID-19 pandemic when uncertainty abounds, combining projections from multiple models into an ensemble provides a fuller picture of what could happen in the future. Ensembles have become ubiquitous in many fields, primarily because they work.

Our analysis of this approach with COVID-19 models resoundingly showed the strong performance of the Scenario Modeling Hub ensemble. Not only did the ensemble give us more accurate predictions of what could happen in the future overall, it was substantially more consistent than any individual model throughout the different stages of the pandemic. When one model failed, another performed well, and by taking into account results from all of these varying models, the ensemble emerged as more accurate and more reliable.

Researchers have previously shown performance benefits of ensembles for short-term forecasts of influenza, dengue and SARS-CoV-2. But our recent study is one of the first times researchers have tested this effect for long-term projections of alternative scenarios.

A ‘hub’ makes multimodel projections possible

While scientists know combining multiple models into an ensemble improves predictions, it can be tricky to put an ensemble together. For example, in order for an ensemble to be meaningful, model outputs and key assumptions need to be standardized. If one model assumes a new COVID-19 variant will gain steam and another model does not, they will come up with vastly different results. Likewise, a model that projects cases and one that projects hospitalizations would not provide comparable results.

Many of these challenges are overcome by convening as a “hub.” Our modeling teams meet weekly to make sure we’re all on the same page about the scenarios we model. This way, any differences in what individual models project are the result of things researchers truly do not know. Retaining this scientific disagreement is essential; the success of the Scenario Modeling Hub ensemble arises because each modeling team takes a different approach.

At our hub we work together to design our scenarios strategically and in close collaboration with public health officials. By projecting outcomes under specific scenarios, we can estimate the impact of particular interventions, like vaccination.

For example, a scenario with higher vaccine uptake can be compared with a scenario with current vaccination rates to understand how many lives could potentially be saved. Our projections have informed recommendations of COVID-19 vaccines for children and bivalent boosters for all age groups, both in 2022 and 2023.

In other cases, we design scenarios to explore the effects of important unknowns, such as the impact of a new variant – known or hypothetical. These types of scenarios can help individuals and institutions know what they might be up against in the future and plan accordingly.

Although the hub process requires substantial time and resources, our results showed that the effort has clear payoffs: The information we generate together is more reliable than the information we could generate alone.

The sum is greater than the parts when researchers build an ensemble from multiple coordinated but independent models.
Matteo Chinazzi, CC BY-ND

Past reliability, confidence for future

Because Scenario Modeling Hub projections can inform real public health decisions, it is essential that we provide the best possible information. Holding ourselves accountable in retrospective evaluations not only allows us to identify places where the models and the scenarios can be improved, but also helps us build trust with the people who rely on our projections.

Our hub has expanded to produce scenario projections for influenza, and we are introducing projections of respiratory syncytial virus, or RSV. And encouragingly, other groups abroad, particularly in the EU, are replicating our setup.

Scientists around the world can take the hub-based approach that we’ve shown improves reliability during the COVID-19 pandemic and use it to support a comprehensive public health response to important pathogen threats.

About the Authors:

Emily Howerton, Postdoctoral Scholar in Biology, Penn State; Cecile Viboud, Senior Research Scientist, National Institutes of Health, and Justin Lessler, Professor of Epidemiology, University of North Carolina at Chapel Hill

This article is republished from The Conversation under a Creative Commons license. Read the original article.

By Christopher Pollard, Deakin University 

Yanis Varoufakis grew up during the Greek dictatorship of 1967-1974. He later became an economics professor and was briefly Greek finance minister in 2015.

His late father, a chemical engineer in a steel plant, instilled in his son a critical appreciation of how technology drives social change. He also instilled him with a belief that capitalism and genuine freedom were antithetical – a leftist politics that made his father a political prisoner for several years during the “junta”, as they called it.

In 1993, when he first got the internet, Varoufakis’s father posed a “killer question” to his son: “now computers speak to each other, will this network make capitalism impossible to overthrow? Or might it finally reveal its Achilles heel?”

Varoufakis has been mulling it over ever since.

Though, sadly, it is now too late to explain to his father in person, Varoufakis’s new book Technofeudalism: What Killed Capitalism answers the question in the form of an extended reflection addressed to his father.

“Achilles heel” was on the right track. In his striking response, Varoufakis argues that we no longer live in a capitalist society; capitalism has morphed into a “technologically advanced form of feudalism”.

Review: Technofeudalism: What Killed Capitalism – Yanis Varoufakis (Bodley Head)

Rent over profit

Traditional capitalists are people who can use capital – defined as “anything that can be used to produce saleable goods” (such as factories, machinery, raw materials, money) – to coerce workers and generate income in the form of profits. Such capitalists are clearly still flourishing, but Varoufakis argues they are not driving the economy in the way they used to.

“In the early 19th century,” he writes,

many feudal relations remained intact, but capitalist relations had begun to dominate. Today, capitalist relations remain intact, but techno-feudalist relations have begun to overtake them.

Traditional capitalists, he proposes, have become “vassal capitalists”. They are subordinate and dependent on a new breed of “lords” – the Big Tech companies – who generate enormous wealth via new digital platforms. A new form of algorithmic capital has evolved – what Varoufakis calls “cloud capital” – and it has displaced “capitalism’s two pillars: markets and profits”.

Markets have been “replaced by digital trading platforms which look like, but are not, markets”. The moment you enter amazon.com “you exit capitalism” and enter something that resembles a “feudal fief”: a digital world belonging to one man and his algorithm, which determines what products you will see and what products you won’t see.

If you are a seller, the platform will determine how you can sell and which customers you can approach. The terms in which you interact, share information and trade are dictated by an “algo” that “works for [Jeff Bezos’] bottom line”.

The capitalists who rely on this mode of selling are granted access to the digital estate by its virtual landowners, the Big Tech companies. And if “vassal capitalists” don’t abide by the laws of the estate, they are kicked out – removed from Apple’s App Store or Google’s search index – with disastrous consequences for their business.

Access to the “digital fief” comes at the cost of exorbitant rents. Varoufakis notes that many third-party developers on the Apple store, for example, pay 30% “on all their revenues”, while Amazon charges its sellers “35% of revenues”. This, he argues, is like a medieval feudal lord sending round the sheriff to collect a large chunk of his serfs’ produce because he owns the estate and everything within it.

This is not extracting profit through the production or provision of goods and services, as these platforms are not a “service” in the sense in which the term is used in economics. They are extracting rents in the form of the huge cuts they take from the capitalists on their platforms.

There is “no disinterested invisible hand of the market” here. The Big Tech platforms are exempted from free-market competition. Their owners – “cloudalists” – increase their wealth and power at a dizzying pace with each click, exploiting a new form of rent-seeking made possible by the new algorithmically structured digital platforms. Parasitic on capitalist production, they are now dominating it.

Cloud serfs

But something even more transformative has happened, Varoufakis argues.

Even though most of us are regularly interacting with capitalists and earning wages via our labour, now, for the first time in history, all of us contribute to “the wealth and power of the new ruling class” through our “unpaid labour”.

Every time we use our cloud-linked devices – smartphones, laptops, Alexa, Google Assistant, Siri – we replenish the capital of the Big Tech cloudalists. This in turn increases their capacity to generate more wealth. How? We train their algorithms, which train us, to train them, and so on, in a feedback loop whose goal is to shape our desires and behaviour. They are “selling things to us while selling our attention to others”.

This interaction, Varoufakis insists, is not taking place as any kind of market exchange, such as wages being paid by a capitalist to a group of workers. In this interaction, we are all high-tech “cloud serfs”.

The new advertising men of the postwar world, portrayed in the series Mad Men (Yanis is clearly a fan), thought television was amazing because of its power to deliver audiences to advertisers. They could innovate “attention-grabbing” ways of “manufacturing” consumer desires – and it was delivered free-to-air!

But, Varoufakis emphasises, the ad men of the previous century could never have imagined the development of something like Amazon’s Alexa: a digital network learning “at lightning speed”, via the input of millions of people, how to train us. It is shaping our desires and behaviours in a process of perpetual reinforcement. Our experience and reality are increasingly algorithmically curated. And due to the incredible ease and utility, the information is all freely given.

So the “cloud capital” we are generating for them all the time increases their capacity to generate yet more wealth, and thus increases their power – something we have only begun to realise. Approximately 80% of the income of traditional capitalist conglomerates go to salaries and wages, according to Varoufakis, while Big Tech’s workers, in contrast, collect “less than 1% of their firms’ revenues”.

Quantitative easing

So how did this dystopian turn happen without us really noticing the change? Varoufakis’s story is detailed, but he emphasises two main drivers.

First, the “internet commons” of Web 1.0 transformed into Web 2.0, privatised by American and Chinese Big Tech.

Second, the colossal sums of central bank money that were supposed to refloat our economies in the aftermath of the 2008 Global Financial Crisis (GFC) – a process known as “quantitative easing” – were lent out to big business. Coupled with “austerity” economics for the many, this “murder[ed] investment” and led to what Varoufakis calls “gilded stagnation”.

Much of the central bank money, particularly following another round of quantitative easing during the COVID pandemic, made its way to the Big Tech companies. Their share prices soared to astronomical levels.

The “world of money” was decoupled from the “real economy” where most of us live and work. In an environment where profit became “optional”, loss-making Big Tech companies run by “intrepid and talented entrepreneurs” chose to build up their cloud capital.

So along with markets being steadily replaced by digital platforms, central bank money displaced private profits as the fuel that “fire[s] the global economy’s engine”. Intended by G7 central bankers and their presidents and prime ministers to “save capitalism”, it has unintentionally helped finance the emergence of a new form of capital (cloud capital) and a “new ruling class”.

GFC: the turning point

So why was the GFC such a pivotal point? Varoufakis has a lot to say. Here’s a brief sketch. (Bear with me!)

Crucial changes had taken place in our economies since the rise of large corporations in industry and banking, which grew ever bigger over the course of the 20th century, eventually becoming global in scale.

The Bretton Woods international financial system – designed to prevent the “greed-fuelled recklessness” that led to the 1929 crash, the Great Depression and a world war – was abolished in 1971. From the 1970s, economies were progressively deregulated and free-market policies were increasingly enthusiastically practised, leading to a new “financialised” version of capitalism.

This was facilitated by the suppression of workers’ wages and bargaining power. The weakened state was progressively captured by lobbyists for the interests of big business. And the hegemony of the US dollar in the global system led to a “tsunami” of dollars pouring back into US markets from Europe, Japan, and later China, “[enriching] America’s ruling class, despite its [large trade] deficit”.

By the new millennium, this had led to an orgy of speculation and, by 2007, the financiers, using “computer-generated complexity” to obscure the “gargantuan risks”, had “placed bets worth ten times more than humanity’s total income”.

The new version of capitalism was failing. But it had grown to such scale and in such a complex, integrated “globalised” way that the banks and insurance companies were “too big to fail”. Their collapse in 2008 would have taken down the US banking system, and the rest of the world with it. Their hubris was thus “rewarded with massive state bailouts”.

What could have happened, as in Sweden in the 1990s, was to “kick out” the bankers, nationalise the banks, appoint new directors and, years later, sell them to new owners – thus saving the banks, but not the bankers.

What happened instead was that bankers, handed large bailouts, did not direct the money to where it was most needed. Neither punished nor chastened, they sent it straight to Wall Street. And there it stayed. Combined with the profits sent to Wall Street from the rest of the world, it eventually caused an “everything rally” that went on for over a decade.

This ultimately helped fuel the development of the cloud capital that has overtaken capitalism. And every time we use our devices, we contribute to its value. The more we transact via platforms, the further we move away from an economic system primarily driven by markets and profits, and the more power concentrates “in the hands of even fewer individuals” – a “tiny band of multi-billionaires residing mostly in California or Shanghai”.

A tech-driven economic revolution

Varoufakis suggests his theory helps us better understand extreme wealth inequalities, the “atrophied democracies” and “poisoned politics” of the West, geopolitics (he interprets the United States and China as two rival “super cloud fiefs”), the stalling of the green energy revolution, and more.

For Varoufakis, we are not just living through a tech revolution, but a tech-driven economic revolution. He challenges us to come to terms with just what has happened to our economies – and our societies – in the era of Big Tech and Big Finance.

The first decades of the 21st century have brought challenges that we are still struggling to come to grips with. One thing is for sure – we have no hope of improving things without properly understanding our predicament.

This book is a welcome contribution towards that task. A technofeudalist age, Varoufakis argues, is not inevitable. Despite the difficulties we face, we have the agency to reject “techno dystopia” and structure our institutions in ways that more meaningfully embody freedom and democracy.

Towards the end of Technofeudalism, Varoufakis canvasses some proposals, drawn from his earlier book Another Now (2020), for how to address these issues. These include ending the cloudalists faux “free service” model and replacing it with a universal micro-payment model, instituting a Bill of Digital Rights, and using digital technology to “democratise companies” (with decisions being taken collectively by “employee-shareholders”).

Varoufakis also proposes to “democratise money”. This plan would involve central banks issuing digital wallets, a universal basic income, reconfiguring “the central bank’s ledger” in the direction of a “common payment and savings system”, and abolishing the current capacity of private banks to “create money”.

The proposals are pretty radical, but I think Varoukais would say they are as radical as the times require them to be.

About the Author:

Christopher Pollard, Tutor in Sociology and Philosophy, Deakin University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

By Jason W. Osborne, Miami University 

Three out of four college students have gambled in the past year, whether legally or illegally, according to the National Council on Problem Gambling.

An estimated 2% to 3% of U.S. adults have a gambling problem. The portion of college students with a problem, however, is potentially twice that number – up to 6%.

As an educational psychologist who follows gambling in America, I foresee the potential for gambling on campus to become an even bigger problem. Sports betting continues to expand, including on college campuses, since a 2018 Supreme Court ruling allowing states to make it legal.

As a faculty fellow at an institute that promotes responsible gaming, I know that colleges can take steps to curtail problem gambling among students. It is all the more urgent given that adolescents in general, including college students, are often uniquely susceptible to gambling problems, both because of their exposure to video games – which often have hallmarks of gambling behavior – and the stress and anxiety of college life, which can lead to using gambling as a coping strategy.

The spread of legal sports betting

As of November 2023, sports betting is legal in some form in 38 states and Washington, D.C. Further, 26 states allow sports betting online. Bills have been introduced – and some recently passed – in more states. These states include Vermont, Missouri and North Carolina. Thanks to technology, sports betting is now accessible beyond casinos. Anyone can access it online and on their smartphone.

More than US$268 billion has been gambled legally on sports betting between June 2018 and November 2023. Revenue in all U.S. gaming sectors has increased significantly, with sports betting growing the fastest, at an estimated 75% annually. It has generated about $3.9 billion in tax revenue to date.

Sports betting is also becoming more accessible on college campuses. A New York Times investigation found that sports betting companies and universities have essentially “Caesarized” college life. That is to say, they’ve made campuses resemble elements of the world famous casinos by introducing online gambling to students.

These profits have driven increased advertising. Some estimate that total advertising through all media channels could approach $3 billion annually. This includes social media platforms like TikTok, where young adults are more likely to see ads for gambling. A study in the United Kingdom found that 72% of 18- to 24-year-olds have seen gambling ads through social media.

While advertisers reportedly focus on young adults of legal age, research suggests that children under 18 are also being exposed to advertising related to gambling. The intensity of advertising activity on social media has raised concerns and brought scrutiny. Earlier this year, for example, prosecutors in the Massachusetts attorney general’s office expressed concern that sports betting and other gambling might spread quickly through college campuses as a result of advertising.

Why college students are at greater risk of gambling addiction

Gambling addiction affects people from all backgrounds and across all ages, but it is an even bigger threat to college students. Adolescents of college age are uniquely likely to engage in impulsive or risky behaviors because of a variety of developmental factors, leaving them more susceptible to take bigger risks and experience adverse consequences.

It’s no secret that drinking alcohol is prevalent on college campuses, and this can increase the likelihood of other risk-taking behaviors such as gambling. Like other addictive behaviors, gambling can stimulate the reward centers of the brain, which makes it more difficult to stop even if someone is building up losses.

What colleges and universities can do to help

If you’re worried a student in your life might have a gambling problem, the Mayo Clinic describes signs to look for. These include restlessness or irritability when attempting to stop or reduce gambling, gambling more when feeling distressed, and lying to hide gambling or financial losses from it. Gamblers Anonymous provides a 20-question, self-diagnostic questionnaire to help people identify problems or compulsive gambling.

For more resources, organizations like the Gateway Foundation offer information and support to help someone with a gambling problem. Immediate help is available at the national problem gambling helpline, 1-800-GAMBLER. The National Council on Problem Gaming has lists of resources within each state that can provide more local support and assistance.

At the Miami University Institute for Responsible Gaming, Lottery and Sport, my colleagues and I are working to ensure that the recent dramatic expansion of legalized gaming is matched by effective guidance for policymakers and leaders within higher education. Many institutions, like the University of Oregon, have begun to acknowledge that widespread legalized sports betting and gambling can affect their students. A comprehensive and coordinated approach is required to protect them from harm.

There are resources available to help institutions, such as the “get set before you bet” initiative adopted by the University of Colorado, Boulder and others. This gives students practical tips to follow if they are going to gamble, such as setting time and money limits before they start.

Colleges and universities could do even more. According to the International Center for Responsible Gaming, institutions can address gambling risks to students by:

• Ensuring there are clear policies on gambling and making sure they align with alcohol policies. United Educators provides examples of how institutions can create effective policies and support student wellness, like Arizona State’s policy. Theirs prohibits legal and illegal gambling at any event related to ASU and reinforces that alcohol possession, consumption or inebriation is illegal for all students under 21.
• Promoting awareness of addiction as a mental health disorder and making resources for getting help available to students.
• Ensuring those who work in campus counseling and health services are familiar with gambling addiction and prepared to support students struggling with addiction or problem behavior. Providers should also be aware that multiple addictions can be present, enhancing the challenges to management and recovery.
• Surveying student attitudes toward gambling to track changes in attitudes, behaviors and norms.

With various sports championships, including in baseball, football and college basketball, taking place throughout the academic year, there’s no shortage of occasions for universities to check in with students about sports betting on campus. Gambling addiction is treatable, but preventing it from the start is the best solution.

About the Author:

Jason W. Osborne, Professor of Statistics, Miami University

This article is republished from The Conversation under a Creative Commons license. Read the original article.