N.Y.’s Vaccine Websites Weren’t Working. He Built a New One for $50.


Sharon Otterman at New York Times: “Huge Ma, a 31-year-old software engineer for Airbnb, was stunned when he tried to make a coronavirus vaccine appointment for his mother in early January and saw that there were dozens of websites to check, each with its own sign-up protocol. The city and state appointment systems were completely distinct.

“There has to be a better way,” he said he remembered thinking.

So, he developed one. In less than two weeks, he launched TurboVax, a free website that compiles availability from the three main city and state New York vaccine systems and sends the information in real time to Twitter. It cost Mr. Ma less than $50 to build, yet it offers an easier way to spot appointments than the city and state’s official systems do.

“It’s sort of become a challenge to myself, to prove what one person with time and a little motivation can do,” he said last week. “This wasn’t a priority for governments, which was unfortunate. But everyone has a role to play in the pandemic, and I’m just doing the very little that I can to make it a little bit easier.”

Supply shortages and problems with access to vaccination appointments have been some of the barriers to the equitable distribution of the vaccine in New York City and across the United States, officials have acknowledged….(More)”.

Citizen Scientists Are Filling Research Gaps Created by the Pandemic


Article by  Theresa Crimmins, Erin Posthumus, and Kathleen Prudic: “The rapid spread of COVID-19 in 2020 disrupted field research and environmental monitoring efforts worldwide. Travel restrictions and social distancing forced scientists to cancel studies or pause their work for months. These limits measurably reduced the accuracy of weather forecasts and created data gaps on issues ranging from bird migration to civil rights in U.S. public schools.

Our work relies on this kind of information to track seasonal events in nature and understand how climate change is affecting them. We also recruit and train citizens for community science – projects that involve amateur or volunteer scientists in scientific research, also known as citizen science. This often involves collecting observations of phenomena such as plants and animalsdaily rainfall totalswater quality or asteroids.

Participation in many community science programs has skyrocketed during COVID-19 lockdowns, with some programs reporting record numbers of contributors. We believe these efforts can help to offset data losses from the shutdown of formal monitoring activities….(More)”.

How a Google Street View image of your house predicts your risk of a car accident


MIT Technology Review: “Google Street View has become a surprisingly useful way to learn about the world without stepping into it. People use it to plan journeys, to explore holiday destinations, and to virtually stalk friends and enemies alike.

But researchers have found more insidious uses. In 2017 a team of researchers used the images to study the distribution of car types in the US and then used that data to determine the demographic makeup of the country. It turns out that the car you drive is a surprisingly reliable proxy for your income level, your education, your occupation, and even the way you vote in elections.

Street view of houses in Poland

Now a different group has gone even further. Łukasz Kidziński at Stanford University in California and Kinga Kita-Wojciechowska at the University of Warsaw in Poland have used Street View images of people’s houses to determine how likely they are to be involved in a car accident. That’s valuable information that an insurance company could use to set premiums.

The result raises important questions about the way personal information can leak from seemingly innocent data sets and whether organizations should be able to use it for commercial purposes.

Insurance data

The researchers’ method is straightforward. They began with a data set of 20,000 records of people who had taken out car insurance in Poland between 2013 and 2015. These were randomly selected from the database of an undisclosed insurance company.

Each record included the address of the policyholder and the number of damage claims he or she made during the 2013–’15 period. The insurer also shared its own prediction of future claims, calculated using its state-of-the-art risk model that takes into account the policyholder’s zip code and the driver’s age, sex, claim history, and so on.

The question that Kidziński and Kita-Wojciechowska investigated is whether they could make a more accurate prediction using a Google Street View image of the policyholder’s house….(More)”.

From Tech Critique to Ways of Living


Alan Jacobs at The New Atlantis: “Neil Postman was right. So what? In the 1950s and 1960s, a series of thinkers, beginning with Jacques Ellul and Marshall McLuhan, began to describe the anatomy of our technological society. Then, starting in the 1970s, a generation emerged who articulated a detailed critique of that society. The critique produced by these figures I refer to in the singular because it shares core features, if not a common vocabulary. What Ivan Illich, Ursula Franklin, Albert Borgmann, and a few others have said about technology is powerful, incisive, and remarkably coherent. I am going to call the argument they share the Standard Critique of Technology, or SCT. The one problem with the SCT is that it has had no success in reversing, or even slowing, the momentum of our society’s move toward what one of their number, Neil Postman, called technopoly.

The basic argument of the SCT goes like this. We live in a technopoly, a society in which powerful technologies come to dominate the people they are supposed to serve, and reshape us in their image. These technologies, therefore, might be called prescriptive (to use Franklin’s term) or manipulatory (to use Illich’s). For example, social networks promise to forge connections — but they also encourage mob rule. Facial-recognition software helps to identify suspects — and to keep tabs on whole populations. Collectively, these technologies constitute the device paradigm (Borgmann), which in turn produces a culture of compliance (Franklin).

The proper response to this situation is not to shun technology itself, for human beings are intrinsically and necessarily users of tools. Rather, it is to find and use technologies that, instead of manipulating us, serve sound human ends and the focal practices (Borgmann) that embody those ends. A table becomes a center for family life; a musical instrument skillfully played enlivens those around it. Those healthier technologies might be referred to as holistic (Franklin) or convivial (Illich), because they fit within the human lifeworld and enhance our relations with one another. Our task, then, is to discern these tendencies or affordances of our technologies and, on both social and personal levels, choose the holistic, convivial ones.

The Standard Critique of Technology as thus described is cogent and correct. I have referred to it many times and applied it to many different situations. For instance, I have used the logic of the SCT to make a case for rejecting the “walled gardens” of the massive social media companies, and for replacing them with a cultivation of the “digital commons” of the open web.

But the number of people who are even open to following this logic is vanishingly small. For all its cogency, the SCT is utterly powerless to slow our technosocial momentum, much less to alter its direction. Since Postman and the rest made that critique, the social order has rushed ever faster toward a complete and uncritical embrace of the prescriptive, manipulatory technologies deceitfully presented to us as Liberation and Empowerment. So what next?…(More)”.

The Coup We Are Not Talking About


Shoshana Zuboff in the New York Times: “Two decades ago, the American government left democracy’s front door open to California’s fledgling internet companies, a cozy fire lit in welcome. In the years that followed, a surveillance society flourished in those rooms, a social vision born in the distinct but reciprocal needs of public intelligence agencies and private internet companies, both spellbound by a dream of total information awareness. Twenty years later, the fire has jumped the screen, and on Jan. 6, it threatened to burn down democracy’s house.

I have spent exactly 42 years studying the rise of the digital as an economic force driving our transformation into an information civilization. Over the last two decades, I’ve observed the consequences of this surprising political-economic fraternity as those young companies morphed into surveillance empires powered by global architectures of behavioral monitoring, analysis, targeting and prediction that I have called surveillance capitalism. On the strength of their surveillance capabilities and for the sake of their surveillance profits, the new empires engineered a fundamentally anti-democratic epistemic coupmarked by unprecedented concentrations of knowledge about us and the unaccountable power that accrues to such knowledge.

In an information civilization, societies are defined by questions of knowledge — how it is distributed, the authority that governs its distribution and the power that protects that authority. Who knows? Who decides who knows? Who decides who decides who knows? Surveillance capitalists now hold the answers to each question, though we never elected them to govern. This is the essence of the epistemic coup. They claim the authority to decide who knows by asserting ownership rights over our personal information and defend that authority with the power to control critical information systems and infrastructures….(More)”.

Ten computer codes that transformed science


Jeffrey M. Perkel at Nature: “From Fortran to arXiv.org, these advances in programming and platforms sent biology, climate science and physics into warp speed….In 2019, the Event Horizon Telescope team gave the world the first glimpse of what a black hole actually looks like. But the image of a glowing, ring-shaped object that the group unveiled wasn’t a conventional photograph. It was computed — a mathematical transformation of data captured by radio telescopes in the United States, Mexico, Chile, Spain and the South Pole1. The team released the programming code it used to accomplish that feat alongside the articles that documented its findings, so the scientific community could see — and build on — what it had done.

It’s an increasingly common pattern. From astronomy to zoology, behind every great scientific finding of the modern age, there is a computer. Michael Levitt, a computational biologist at Stanford University in California who won a share of the 2013 Nobel Prize in Chemistry for his work on computational strategies for modelling chemical structure, notes that today’s laptops have about 10,000 times the memory and clock speed that his lab-built computer had in 1967, when he began his prizewinning work. “We really do have quite phenomenal amounts of computing at our hands today,” he says. “Trouble is, it still requires thinking.”

Enter the scientist-coder. A powerful computer is useless without software capable of tackling research questions — and researchers who know how to write it and use it. “Research is now fundamentally connected to software,” says Neil Chue Hong, director of the Software Sustainability Institute, headquartered in Edinburgh, UK, an organization dedicated to improving the development and use of software in science. “It permeates every aspect of the conduct of research.”

Scientific discoveries rightly get top billing in the media. But Nature this week looks behind the scenes, at the key pieces of code that have transformed research over the past few decades.

Although no list like this can be definitive, we polled dozens of researchers over the past year to develop a diverse line-up of ten software tools that have had a big impact on the world of science. You can weigh in on our choices at the end of the story….(More)”.

How Elvis Got Americans to Accept the Polio Vaccine


Hal Hershfield and Ilana Brody at Scientific American: “Campaigns to change behavior thrive on three factors: social influence, social norms and vivid examples…In late 1956, Elvis Presley was on the precipice of global stardom. “Heartbreak Hotel” had reached number one on the charts earlier that year and Love Me Tender, his debut film,would be released in November. In the midst of this trajectory, he was booked as a guest on the most popular TV show at the time, The Ed Sullivan Show. But he wasn’t only there to perform his hits. Before the show started, and in front of the press and Ed Sullivan himself, Presley flashed his swoon-worthy smile, rolled up his sleeves and let a New York state official stick a needle loaded up with the polio vaccine in his arm.

At that point, the polio virus had been ravaging the American landscape for years, and approximately 60,000 children were infected annually. By 1955, hope famously arrived in the form of Jonas Salk’s vaccine. But despite the literally crippling effects of the virus and the promising results of the vaccination, many Americans simply weren’t getting vaccinated. In fact, when Presley appeared on the Sullivan show, immunization levels among American teens were at an abysmal 0.6 percent.

You might think that threats to children’s health and life expectancy would be enough to motivate people to get vaccinated. Yet, convincing people to get a vaccine is a challenging endeavor. Intuitively, it seems like it would be wise to have doctors and other health officials communicate the need to receive the vaccine. Or, failing that, we might just need to give people more information about the effectiveness of the vaccine itself…(More)”.

Scholarly publishing needs regulation


Essay by Jean-Claude Burgelman: “The world of scientific communication has changed significantly over the past 12 months. Understandably, the amazing mobilisation of research and scholarly publishing in an effort to mitigate the effects of Covid-19 and find a vaccine has overshadowed everything else. But two other less-noticed events could also have profound implications for the industry and the researchers who rely on it.

On 10 January 2020, Taylor and Francis announced its acquisition of one of the most innovative small open-access publishers, F1000 Research. A year later, on 5 January 2021, another of the big commercial scholarly publishers, Wiley, paid nearly $300 million for Hindawi, a significant open-access publisher in London.

These acquisitions come alongside rapid change in publishers’ functions and business models. Scientific publishing is no longer only about publishing articles. It’s a knowledge industry—and it’s increasingly clear it needs to be regulated like one.

The two giant incumbents, Springer Nature and Elsevier, are already a long way down the road to open access, and have built up impressive in-house capacity. But Wiley, and Taylor and Francis, had not. That’s why they decided to buy young open-access publishers. Buying up a smaller, innovative competitor is a well-established way for an incumbent in any industry to expand its reach, gain the ability to do new things and reinvent its business model—it’s why Facebook bought WhatsApp and Instagram, for example.

New regulatory approach

To understand why this dynamic demands a new regulatory approach in scientific publishing, we need to set such acquisitions alongside a broader perspective of the business’s transformation into a knowledge industry. 

Monopolies, cartels and oligopolies in any industry are a cause for concern. By reducing competition, they stifle innovation and push up prices. But for science, the implications of such a course are particularly worrying. 

Science is a common good. Its products—and especially its spillovers, the insights and applications that cannot be monopolised—are vital to our knowledge societies. This means that having four companies control the worldwide production of car tyres, as they do, has very different implications to an oligopoly in the distribution of scientific outputs. The latter situation would give the incumbents a tight grip on the supply of knowledge.

Scientific publishing is not yet a monopoly, but Europe at least is witnessing the emergence of an oligopoly, in the shape of Elsevier, Springer Nature, Wiley, and Taylor and Francis. The past year’s acquisitions have left only two significant independent players in open-access publishing—Frontiers and MDPI, both based in Switzerland….(More)”.

Privacy and digital ethics after the pandemic


Carissa Véliz at Nature: “The coronavirus pandemic has permanently changed our relationship with technology, accelerating the drive towards digitization. While this change has brought advantages, such as increased opportunities to work from home and innovations in e-commerce, it has also been accompanied with steep drawbacks, which include an increase in inequality and undesirable power dynamics.

Power asymmetries in the digital age have been a worry since big tech became big. Technophiles have often argued that if users are unhappy about online services, they can always opt-out. But opting-out has not felt like a meaningful alternative for years for at least two reasons.

First, the cost of not using certain services can amount to a competitive disadvantage — from not seeing a job advert to not having access to useful tools being used by colleagues. When a platform becomes too dominant, asking people not to use it is like asking them to refrain from being full participants in society. Second, platforms such as Facebook and Google are unavoidable — no one who has an online life can realistically steer clear of them. Google ads and their trackers creep throughout much of the Internet1, and Facebook has shadow profiles on netizens even when they have never had an account on the platform2.

Citizens have responded to the countless data abuses in the past few years with what has been described as a ‘techlash’3. Tech companies whose business model is based on surveillance ceased to be perceived as good guys in hoodies who offered services to make our lives better. They were instead data predators jeopardizing, not only users’ privacy and security, but also democracy itself. During lockdown, communication apps became necessary for any and all social interaction beyond our homes. People have had to use online tools to work, get an education, receive medical attention, and enjoy much-needed entertainment. Gratefulness for having technology that allows us to stay in contact during such circumstances has thus watered down the general techlash. Big tech’s stocks have been consistently on the rise during the pandemic, in line with its accumulating power.

As a result of the pandemic, however, any lingering illusion of voluntariness in the use of technology has disappeared. It is not only citizens who rely on big tech to perform their jobs: businesses, universities, health services, and governments need the platforms to carry out their everyday functions. All over the world, governmental and diplomatic meetings are being carried out on platforms such as Zoom and Teams. Since governments do not have full control over the platforms they use, confidentiality is uncertain.

Enhanced power asymmetries have also worsened the vulnerability of ordinary citizens in areas that range from the interaction with government to ordering food online, and almost everything in between. The pandemic has, for example, led to an increase in the surveillance of employees as they work from home4. Students are likewise being subjected to more scrutiny: by their schools and teachers, and above all, by the companies on which they depend5. Surveillance for public health purposes has likewise increased. Privacy losses disempower citizens and often lead to further abuses of power. In the UK, for example, companies collecting data for pubs and restaurants for contact-tracing purposes have sold on that information6.

Such abuses are not isolated events. For the past two decades, we have allowed an unethical business model that depends on the systematic violation of the right to privacy to run amok. As long as we treat personal data as a commodity, there will be a high risk of it being misused — by being stolen in a hack or by being sold to the highest bidder (which often includes nefarious agents)….(More)”.

These crowdsourced maps will show exactly where surveillance cameras are watching


Mark Sullivan at FastCompany: “Amnesty International is producing a map of all the places in New York City where surveillance cameras are scanning residents’ faces.

The project will enlist volunteers to use their smartphones to identify, photograph, and locate government-owned surveillance cameras capable of shooting video that could be matched against people’s faces in a database through AI-powered facial recognition.

The map that will eventually result is meant to give New Yorkers the power of information against an invasive technology the usage of which and purpose is often not fully disclosed to the public. It’s also meant to put pressure on the New York City Council to write and pass a law restricting or banning it. Other U.S. cities, such as Boston, Portland, and San Francisco, have already passed such laws.

Facial recognition technology can be developed by scraping millions of images from social media profiles and driver’s licenses without people’s consent, Amnesty says. Software from companies like Clearview AI can then use computer vision algorithms to match those images against facial images captured by closed-circuit television (CCTV) or other video surveillance cameras and stored in a database.

Starting in May, volunteers will be able to use a software tool to identify all the facial recognition cameras within their view—like at an intersection where numerous cameras can often be found. The tool, which runs on a phone’s browser, lets users place a square around any cameras they see. The software integrates Google Street View and Google Earth to help volunteers label and attach geolocation data to the cameras they spot.

The map is part of a larger campaign called “Ban the Scan” that’s meant to educate people around the world on the civil rights dangers of facial recognition. Research has shown that facial recognition systems aren’t as accurate when it comes to analyzing dark-skinned faces, putting Black people at risk of being misidentified. Even when accurate, the technology exacerbates systemic racism because it is disproportionately used to identify people of color, who are already subject to discrimination by law enforcement officials. The campaign is sponsored by Amnesty in partnership with a number of other tech advocacy, privacy, and civil liberties groups.

In the initial phase of the project, which was announced last Thursday, Amnesty and its partners launched a website that New Yorkers can use to generate public comments on the New York Police Department’s (NYPD’s) use of facial recognition….(More)”.