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This story originally appeared in Jacobin on March 16, 2022. It is shared here with permission.

In April 2020, Google and Apple announced a partnership to “beat” COVID-19 by releasing contact-tracing applications on Android and Apple devices around the world. Subsequent announcements about the number of lives saved or infections prevented using these apps have been conspicuously absent, as the Bluetooth technology underlying these apps does not work. Bluetooth is not precise enough to detect close contacts who test positive for COVID, as even the inventors of Bluetooth admit.

Nevertheless, governments the world over have followed suit, authorizing the private sector to collect sensitive biometric data in partnership with health authorities. These public-private partnerships waste scarce time and money. They are examples of “technology theater,” tech initiatives that only work to distract media and the public from systemic solutions to the pandemic.

Basic public health initiatives—such as hiring contact tracers, providing facilities and financial compensation for quarantining, knocking on doors to decrease vaccine hesitancy, and providing free masks, tests, and vaccines—have proven to be the best ways to save lives during the pandemic. Unfortunately, many governments have chosen instead to partner with Big Tech to implement needlessly complex initiatives that do little more than boost large companies’ profits and increase surveillance.

Few pundits have noted the role that technology companies—some of the wealthiest organizations on the planet—and their data-driven business models have played in extending the pandemic. In the critical early months of the COVID crisis, governments worked with technology companies to collect massive data sets underpinning technological solutions that were ultimately ineffective, wasting precious time that could have been used to deploy low-tech solutions to slow the spread of COVID.

Some countries have used high-tech tools to great effect, but only when married to an essentially human-centered approach. Contact-tracing apps and other high-tech solutions have only been effective insofar as they have enabled the implementation of low-tech solutions.

Tech companies have also diverted investment away from approaches oriented toward public health and toward data-intensive tools. They have lobbied for, and in many cases won, government contracts to develop technologies that have failed to deliver results. Besides flushing money down the drain, governments incurred a severe opportunity cost by prioritizing unproven, high-tech approaches to the pandemic over tried-and-true low-tech solutions.

Failing the First Test

Take COVID testing as an example. In 2020, Verily, a company backed by Google’s parent company, Alphabet, won a $70 million no-bid contract from California to administer tests and track symptoms in vulnerable communities. Despite promising to “develop the next wave of healthcare innovation,” Verily’s rollout was a catastrophe. The company not only erected self-serving barriers to testing—patients were required to have a Gmail account and provide sensitive personal data to use Verily’s portal—but its tests also took over ten days to return results, rendering them useless in stopping the spread of COVID.

Verily is a tech company, not a medical provider, and so it saw the pandemic as a business opportunity to sell health data to the highest bidder. It lacked the know-how for scaling up testing sites, but provided elected officials like California governor Gavin Newsom and President Donald Trump a glitzy pitch for their COVID-prevention efforts.

The cities of San Francisco and Oakland ended their partnerships with Verily in late 2020. Beyond failing to ramp up testing, Verily price-gouged throughout California, initially charging $330 per test, and often refused to test people experiencing homelessness. San Francisco, one of the wealthiest cities in the world, still does not provide free testing on demand throughout the city.

[C]ountries that have rolled out testing effectively have one thing in common: they invested in low-tech, human-centered ways to provide tests directly to their populations.

“Verily did literally everything wrong,” Dr Anthony Iton, cochair of Oakland’s COVID-19 Racial Disparities Task Force, told Jacobin. “Verily [and other tech companies] were the worst possible partners to reach vulnerable communities [most impacted by COVID] . . . populations who are formerly incarcerated, have immigration issues, or who even just have unpaid parking tickets are not looking to divulge all their information to a private contractor that doesn’t promise to maintain confidentiality.” Dr Iton noted that California’s $70 million would have been better spent buying tests and paying trusted grassroots organizations to administer them.

On the other hand, countries that have rolled out testing effectively have one thing in common: they invested in low-tech, human-centered ways to provide tests directly to their populations. South Korea, for instance, hired thousands of people to operate testing sites in hospitals and drive-throughs, doubling testing capacity. The World Health Organization recommends sending outreach workers to help distribute tests in at-risk communities, which the ministries of health in Ecuador and Argentina did successfully by deploying “COVID brigades” in working-class neighborhoods.

Verily is no outlier. Across the pond, the UK’s homicidal “herd immunity” approach involved making the largest transfer of confidential NHS data in history to Palantir, Peter Thiel’s dystopian machine-learning company known for helping the Trump administration accelerate deportations. In exchange for any “personal data that may be useful” to the company, Palantir promised to predict where medical equipment, such as tests, was most needed. Though Palantir did little to stop Britain from having one of the world’s highest per capita death tolls from COVID, it still won an extension to its contract with the UK.

Ghana and Mexico City also paid the private sector to develop apps to detect COVID symptoms and allocate testing resources, but the apps were ineffective due to low uptake. The cost of testing, not technological mishaps, presents the main barrier to their availability worldwide. “Gold-standard” PCR tests are still too expensive for most countries to afford, and rich countries have hoarded them, as evidenced by American and Europeans export restrictions. In 2020, one PCR test in India cost $70, 40 percent of the average Indian’s annual income.

A Trojan Horse

The most widespread use of technology against the pandemic is contact-tracing applications. At least seventy countries have rolled out a contact-tracing app, with some apps like Bangladesh’s Corona Tracer being developed entirely by the private sector. In other cases, governments preferred to develop their own invasive contact-tracing apps in consultation with firms in order to provide legal justification for making downloads mandatory.

The contact-tracing app with the most downloads is the Indian government’s Aarogya Setu (meaning “bridge to health”). It became the fastest-growing app in history in April 2020, and now has over 200 million users, aided by the government’s de facto mandate. According to Srinivas Kodali, a public-interest technologist with the Free Software Movement of India in New Delhi, worked with a “cabal” of private sector actors to create the app, including executives at tech companies like MakeMyTrip. “The app became the only thing the government could think of,” Kodali told Jacobin. The government and the media agreed that “there was no other solution except technology, this is the only thing we in India should be doing.”

Like other apps, Aarogya Setu simply does not work for contact tracing. Bluetooth-based apps are highly inaccurate, as they depend on radio waves, which are deflected and absorbed by solid objects, leading to many false positives and false negatives. GPS-enabled contact-tracing apps also lack the granularity necessary to accurately record potentially infectious contacts, as they cannot determine if two people are within fifteen feet of one another, which is already less precise than the six-foot range in which COVID is communicable. A digital contact-tracing system requires 60 percent participation in order to track infections throughout the population; with only half of Indians having internet access, India’s contact-tracing effort was doomed from the start.

[C]ontact-tracing apps have helped discover only two positive cases in all of Brazil, four in Italy, and ten in Germany, countries with 350 million people between them.

Some contact-tracing apps were exorbitant to develop, costing well over $5 million to build and deploy, although they were nothing more than “a really expensive WebMD.” By one count, contact-tracing apps have helped discover only two positive cases in all of Brazil, four in Italy, and ten in Germany, countries with 350 million people between them.

In contrast to the harms caused by contact-tracing apps, low-tech approaches have helped slow the pandemic. The Indian state of Kerala, for instance, deployed tens of thousands of contact tracers early on in the pandemic. As a result, at the height of India’s crisis, Kerala’s COVID death rate was half the national average. In Mumbai’s shantytowns, using Aarogya Setu was a “futile exercise”—health workers who went door-to-door to trace contacts were much more effective. Contact tracing requires contact tracers; it cannot be automated with dysfunctional technology.

The plaintiff in a successful lawsuit against the Indian government argued that, as shown by its technical infeasibility, the true purpose of Aarogya Setu was to experiment with sharing health data with the public sector, not to perform contact tracing. High-tech solutions like contact-tracing apps serve only to legitimate government surveillance of whole populations and to increase profits by enhancing the public and private sectors’ access to ever-larger data sets of valuable personal information.

According to Nuria Oliver, chief data scientist at the Vodafone Institute, governments made a poor trade-off by deploying apps rather than low-tech solutions, meaning that they “didn’t have the resources or the bandwidth to do a side project to try” low-tech solutions. “There was a lot of interest in contact-tracing apps because (a) it made countries feel as though they had done something, and (b) it was a trojan horse into other potential uses of this technology,” Oliver told Jacobin.

In India, Aarogya Setu has excluded millions of working-class Indians without mobile phones from essential services like public transit. Kodali of the Free Software Movement of India adds that “police were demanding Aarogya Setu wherever you go” and “location data was shared with the police in Jammu and Kashmir,” facilitating violent crackdowns in the region.

Before Omicron, India had the worst outbreak in the world by far, recording 10 million cases in a one-month span from April to May 2021. Independent estimates have found that as many as 3 million people died from April to July. Aarogya Setu did not help whatsoever. Subhashis Banerjee, a computer scientist at Indian Institute of Technology Delhi, argues that “the app was nothing but random rubbish”—a poorly designed experiment for sharing health data that was unable to scale up to meet the challenge.

The Talking Cure

Efforts to increase vaccination rates have been hobbled by fruitless technological solutions that distracted from more effective approaches. The most effective methods are often the lowest tech, like knocking on doors to decrease vaccine hesitancy.

In September, YouTube buckled under regulatory pressure and banned vaccine misinformation, deleting accounts from prominent anti-vaxxers. But this policy change was too little, too late. Vaccine disinformation had already gone global. By mid-2021, 32 percent of the world’s population was unwilling to be vaccinated, preventing the world from reaching herd immunity.

Here again, low-tech public health solutions provide a path forward. The best way to increase vaccination rates is through deep canvassing, a community organizing tactic that involves going door-to-door to have one-on-one conversations centered around people’s life experiences. Prioritizing this strategy requires a recognition that some portion of vaccine-hesitant people are persuadable, and that it is worth listening to their concerns in order to save lives.

Public outrage at unvaccinated people has escalated, however, and people willing to listen are in short supply. Greece and Austria have imposed fines on the unvaccinated, while Singapore refuses to pay their medical bills. Philippine president Rodrigo Duterte has threatened to jail unvaccinated people and said he is indifferent if they die. A new genre of obituary has emerged in which commentators dance on the graves of unvaccinated people who have died, glorying in their own supposed moral superiority. But persuading people to get vaccinated requires talking to them.

Contact tracing requires contact tracers; it cannot be automated with dysfunctional technology.

As Josh Kalla, a political scientist at Yale, told Jacobin, “Vaccines have become a political issue, and my research shows that deep canvassing can often be an effective form of political persuasion.” Kalla’s research on deep canvassing finds that it is among the most durable forms of persuasion that have been studied. Prior to the pandemic, Kalla also examined the effects of deep canvassing on vaccine hesitancy and found promising preliminary results.

Even President Joe Biden has recognized the benefits of this approach, saying in July 2021 that canvassing would be a new pillar of the White House’s vaccination strategy. Despite endorsing the strategy, the administration waited six months to provide any funding for states to hire canvassers and, in response to right-wing backlash, has admitted that it does not plan to deploy federal canvassers. White House coronavirus coordinator Jeff Zients admitted defeat in December: “For the unvaccinated, you’re looking at a winter of severe illness and death for yourselves, your families, and the hospitals you may soon overwhelm.”

Technology’s Real Role

High-tech tools cannot be a substitute for public health basics, but they can supplement them, possibly to great effect.

In February 2020, the Chinese province of Zhejiang rapidly rolled out mandatory “health codes”—digital passports within existing apps that gauge infection risk using large and highly integrated data sets provided by firms like Tencent and Alibaba. Though the health codes were used to repress human rights, they may have helped China enact more targeted lockdowns by identifying regions with surging COVID cases. However, they were effective only after the government deployed “legions of people to man checkpoints armed with clipboards and thermometer guns, or to go door-to-door making note of sniffles.”

In Valencia, Spain, the government was able to use data collection to tailor its public health response. Nuria Oliver, who also serves as the Valencian government’s commissioner for artificial intelligence (AI) and COVID, found that using fully anonymized data from a large survey of citizens allowed her team to build predictive models that accurately gauged hospital occupancy and ICU bed capacity.

Oliver has proposed that low-tech solutions should be more widely deployed in future pandemics. For example, she has written about the advantages of “anonymous citizen-driven contact tracing,” in which every person who receives a positive test is given vouchers to distribute to their close contacts, who can exchange those vouchers for free tests. “There are other ways to facilitate contact tracing that are scalable, less technological, and probably cheaper and more likely to succeed,” she told Jacobin. Unfortunately, privacy-preserving innovations like these are far from widespread and are unlikely to be scalable by the time the next pandemic hits.

Far from helping to stop the pandemic, AI systems have been used by governments to increase punitive surveillance.

But techno-optimism abounds. The misguided consensus among mainstream tech experts is that although AI did not solve COVID, it could save humanity from the next pandemic. What is more likely, however, is that governments and firms will capitalize on the next shock just as they seized upon the COVID crisis: as an opportunity to consolidate their power.

Far from helping to stop the pandemic, AI systems have been used by governments to increase punitive surveillance. Sri Lanka used drones to surveil COVID curfew violators. Russia used facial recognition to track individuals’ location data. Hong Kong forced travelers to wear faulty, Bluetooth-enabled wristbands at all times to prove they were staying in quarantine.

As Edward Snowden said in the wake of his revelations about the National Security Agency, “No system of mass surveillance has existed in any society that we know of to this point that has not been abused.”

A Simpler Solution

Low-tech measures to mitigate the pandemic have been proven to work from Seoul to Kerala. Providing well-paying jobs to canvass, trace contacts, and distribute free vaccines, masks, and tests is a simpler, more effective solution than app-based pandemic responses.

Technology was never going to stop the pandemic. The technical challenges were significant, but, more importantly, high-tech solutions were built to increase profits, not save lives. The outcome of these contrived failures is more data to feed the surveillance economy in both the public and the private sector.

It would cost $70 billion to vaccinate the world. Amazon makes that much every quarter. Elon Musk made that much in 2021 alone. We have the resources and the tools to stop the pandemic. All we have to do is use them.

Kevin Klyman

Kevin Klyman researches US-China relations and has written data protection policies adopted by the World Health Organization.