The Time Tax

Curated on Posted on by Stefaan Verhulst

Article by Annie Lowrey: “…In my decade-plus of social-policy reporting, I have mostly understood these stories as facts of life. Government programs exist. People have to navigate those programs. That is how it goes. But at some point, I started thinking about these kinds of administrative burdens as the “time tax”—a levy of paperwork, aggravation, and mental effort imposed on citizens in exchange for benefits that putatively exist to help them. This time tax is a public-policy cancer, mediating every American’s relationship with the government and wasting countless precious hours of people’s time.

The issue is not that modern life comes with paperwork hassles. The issue is that American benefit programs are, as a whole, difficult and sometimes impossible for everyday citizens to use. Our public policy is crafted from red tape, entangling millions of people who are struggling to find a job, failing to feed their kids, sliding into poverty, or managing a disabling health condition.

… the government needs to simplify. For safety-net programs, this means eliminating asset tests, work requirements, interviews, and other hassles. It means federalizing programs like unemployment insurance and Medicaid. It means cross-coordinating, so that applicants are automatically approved for everything for which they qualify.

Finally, it needs to take responsibility for the time tax. Congress needs to pump money into the civil service and into user-friendly, citizen-centered programmatic design. And the federal government needs to reward states and the executive agencies for increasing uptake and participation rates, while punishing them for long wait times and other bureaucratic snafus.

Such changes would eliminate poverty and encourage trust in government. They would make American lives easier and simpler. Yes, Washington should give Americans more money and more security. But most of all, it should give them back their time….(More)”.

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Medical crowdfunding has become essential in India, but it’s leaving many behind

Curated on Posted on by Stefaan Verhulst

Article by Akanksha Singh: “In May, as India grappled with a second wave of the coronavirus pandemic, Mahan and Nishan Sekhon found themselves stretched thin. Their mother had contracted black fungus, a potentially lethal disease. The treatment, at a cost of $1,300 per day, had exhausted their insurance plan and burned through their savings. As a last resort, they turned to Ketto, a crowdfunding platform. 

They shared the campaign within their social networks in mid-June, and within a month the brothers had secured $59,000 of their $76,000 goal. “I even got a call from an [Indian man] in Belgium,” Mahan Sekhon told Rest of World. “His Spanish restaurant manager told him [about the fundraiser].”

This is how Ketto is supposed to work. In a country where out-of-pocket expenses account for nearly 63% of total health expenditures, crowdfunding fills a void in medical needs for thousands of Indians. During the Covid-19 crisis, in which more than 4 million people are estimated to have died and 10 million people have lost their jobs, Ketto saw a fourfold increase in registered fundraisers, hosting nearly 12,500 Covid-19 relief campaigns and raising $40 million, according to the company.

However, for many people in India, crowdfunding medical care is either impractical or impossible. To access the platforms, users need official documentation and formal bank accounts, which are far from universal. In 2018, the World Bank’s Identification for Development initiative estimated that 162 million Indians lack registration, including people from the trans community, homeless people, sex workers, indigenous peoples, and those from oppressed caste and class backgrounds. Even when they can get on the platforms, they are regularly targeted with hate speech and discrimination.

It means they are, effectively, cut off from services they need, or are forced to rely on the empathy of intermediaries. “People from marginalized communities in India often do not possess identity documents,” lawyer and activist Lara Jesani told Rest of World. “There are sections of people who systematically face the problem of documentation,” she said.

Ketto, an Indian online crowdfunding platform, says it has hosted over 200,000 medical fundraisers.https://www.ketto.org/

Ketto was founded in 2012 as an online marketplace that allows people to raise funds for everything from starting a business to helping nonprofits. The company began to focus on healthcare three years ago, Varun Sheth, the company’s co-founder, told Rest of World. “We realized that [medical fundraising] was where the platform was most effectively used,” he said. The company promotes campaigns through targeted advertising on Facebook and YouTube, helping them to reach a wide audience, including Indian citizens overseas. “We constantly got feedback that people outside India, especially, want to support more causes in India,” Sheth said.

Since its launch, Ketto said it has hosted over 200,000 medical fundraisers and raised over $148 million. The platform recently raised its largest ever medical appeal, $460,000 for Mithra, an infant with spinal muscular atrophy….(More)”.

Hundreds of AI tools have been built to catch covid. None of them helped.

Curated on Posted on by Stefaan Verhulst

Article by Will Douglas Heaven: “When covid-19 struck Europe in March 2020, hospitals were plunged into a health crisis that was still badly understood. “Doctors really didn’t have a clue how to manage these patients,” says Laure Wynants, an epidemiologist at Maastricht University in the Netherlands, who studies predictive tools.

But there was data coming out of China, which had a four-month head start in the race to beat the pandemic. If machine-learning algorithms could be trained on that data to help doctors understand what they were seeing and make decisions, it just might save lives. “I thought, ‘If there’s any time that AI could prove its usefulness, it’s now,’” says Wynants. “I had my hopes up.”

It never happened—but not for lack of effort. Research teams around the world stepped up to help. The AI community, in particular, rushed to develop software that many believed would allow hospitals to diagnose or triage patients faster, bringing much-needed support to the front lines—in theory.

In the end, many hundreds of predictive tools were developed. None of them made a real difference, and some were potentially harmful.

That’s the damning conclusion of multiple studies published in the last few months. In June, the Turing Institute, the UK’s national center for data science and AI, put out a report summing up discussions at a series of workshops it held in late 2020. The clear consensus was that AI tools had made little, if any, impact in the fight against covid.

Not fit for clinical use

This echoes the results of two major studies that assessed hundreds of predictive tools developed last year. Wynants is lead author of one of them, a review in the British Medical Journal that is still being updated as new tools are released and existing ones tested. She and her colleagues have looked at 232 algorithms for diagnosing patients or predicting how sick those with the disease might get. They found that none of them were fit for clinical use. Just two have been singled out as being promising enough for future testing.

“It’s shocking,” says Wynants. “I went into it with some worries, but this exceeded my fears.”

Wynants’s study is backed up by another large review carried out by Derek Driggs, a machine-learning researcher at the University of Cambridge, and his colleagues, and published in Nature Machine Intelligence. This team zoomed in on deep-learning models for diagnosing covid and predicting patient risk from medical images, such as chest x-rays and chest computer tomography (CT) scans. They looked at 415 published tools and, like Wynants and her colleagues, concluded that none were fit for clinical use…..(More)”.

Census Data Change to Protect Privacy Rattles Researchers, Minority Groups

Curated on Posted on by Stefaan Verhulst

Paul Overberg at the Wall Street Journal: A plan to protect the confidentiality of Americans’ responses to the 2020 census by injecting small, calculated distortions into the results is raising concerns that it will erode their usability for research and distribution of state and federal funds.

The Census Bureau is due to release the first major results of the decennial count in mid-August. They will offer the first detailed look at the population and racial makeup of thousands of counties and cities, as well as tribal areas, neighborhoods, school districts and smaller areas that will be used to redraw congressional, legislative and local districts to balance their populations.

The bureau will adjust most of those statistics to prevent someone from recombining them in a way that would disclose information about an individual respondent. Testing by the bureau shows that improvements in data science, computing power and commercial databases make that feasible.

Last week the bureau’s acting director said the plan was a necessary update of older methods to protect confidentiality. Ron Jarmin said the agency searched for alternatives before settling on differential privacy, a systematic approach to add statistical noise to data, something it has done in some fashion for years.

“I’m pretty confident that it’s going to meet users’ expectations,” Mr. Jarmin said at a panel during an online conference of government data users. “We have to deal with the technology as it is and as it evolves.”…(More)”.

Chinese web users are writing a new playbook for disaster response

Curated on Posted on by Stefaan Verhulst

Shen Lu at Protocol: Severe floods caused by torrential rains in Central China’s Henan province have killed dozens and displaced tens of thousands of residents since last weekend. In parallel with local and central governments’ disaster relief and rescue efforts, Chinese web users have organized online, using technology in novel ways to mitigate risks and rescue those who were trapped in subway cars and neighborhoods submerged in floodwaters.

Chinese web users are no strangers to digital crowdsourcing efforts. During the COVID-19 outbreak, volunteers archived censored media reports and personal stories of suffering from disease or injustice that were scattered on social media, saving them on sharable files on GitHub and broadcasting them via Telegram. Despite pervasive censorship, in times of crisis, Chinese web users have managed to keep information and communications channels open among themselves, and with the rest of the world.

Now, people in one of the most oppressive information environments in the world might be helping write the future playbook for disaster response…

In hard-hit Zhengzhou, the capital city of Henan province, tens of thousands of residents crowdsourced relief assistance over the past 48 hours through a simple shared spreadsheet powered by the Tencent equivalent of Google Sheets (Google products are banned in China). It was created by a college student to allow those awaiting rescue to log their contact and location information.

In the 36 hours that followed, droves of volunteers have logged on, vastly expanding the breadth of information that lives on the document. It now includes contact information for official and unofficial rescue teams, relief resources, shelter locations, phone-charging stations and online medical consultations. At certain points, over 200 people have edited the sheet simultaneously.

Tencent reported that by Wednesday evening Beijing time, volunteers had entered nearly 1,000 data points. The document has received over 2.5 million visits, becoming the most visited Tencent Doc ever and one of the most efficient and powerful rescue and aid platforms started and contributed by civilians.

Similar crowdsourced documents for flooding victims live elsewhere on the internet. On Shimo Docs, a cloud-based productivity suite developed by the Beijing-based startup Shimo, volunteers have aggregated relief and rescue resources’ contacts by cities and counties. These shared documents have made the rounds on social media platforms like Weibo and WeChat in the past few days….(More)”.

Data Literacy in Government: How Are Agencies Enhancing Data Skills?

Curated on Posted on by Stefaan Verhulst

Randy Barrett at FedTech: “The federal government is vast, and the challenge of understanding its oceans of data grows daily. Rather than hiring thousands of new experts, agencies are moving to train existing employees on how to handle the new frontier.

Data literacy is now a common buzzword, spurred by the publication of the Federal Data Strategy 2020 Action Plan last year and the growing empowerment of chief data officers in the government. The document outlines a multiyear, holistic approach to government information that includes building a culture that values data, encouraging strong management and protection and promoting its efficient and appropriate use.

“While the Federal government leads globally in many instances in developing and providing data about the United States and the world, it lacks a robust, integrated approach to using data to deliver on mission, serve the public and steward resources,” the plan notes.

A key pillar of the plan is to “identify opportunities to increase staff data skills,” and it directs all federal agencies to undertake a gap analysis of skills to see where the weaknesses and needs lie….

The Department of Health and Human Services launched its Data Science CoLab in 2017 to boost basic and intermediate data skills. The collaborative program is the first try at a far reaching and cohort-based data-skills training for the agency. In addition to data analytics skills, HHS is currently training hundreds of employees on how to write Python and R.

“Demand for a seat in the Data Science CoLab has grown approximately 800 percent in the past three years, a testament to its success,” says Bishen Singh, a senior adviser in the Office of the Assistant Secretary for Health. “Beyond skill growth, it has led to incredible time and cost savings, as well as internal career growth for past participants across the department.”

The National Science Foundation was less successful with its Data Science and Data Certification Pilot, which had a class of 10 participants from various federal agencies. The workers were trained in advanced analytics techniques, with a focus on applying data tools to uncover meaning and solve Big Data challenges. However, the vendor curriculum used general data sets rather than agency-specific ones.

“As a result, participants found it more difficult to apply their learnings directly to real-world scenarios,” notes the CDO Council’s “Data Skill Training Program: Case Studies” report. The learning modules were mostly virtual and self-paced. Communication was poor with the vendor, and employees began to lag in completing their coursework. The pilot was discontinued.

Most of the training pilot programs were launched as the pandemic closed down government offices. The shift to virtual learning made progress difficult for some students. Another key lesson: Allow workers to use their new skills quickly, while they’re fresh….(More)”.

To solve big issues like climate change, we need to reframe our problems

Curated on Posted on by Stefaan Verhulst


Essay by Thomas Wedell-Wedellsborg and Jonathan Wichmann: “Imagine you own an office building and your tenants are complaining that the elevator is way too slow. What do you do?

Faced with this problem, most people instinctively jump into solution mode. How can we make the elevator faster? Can we upgrade the motor? Tweak the algorithm? Do we need to buy a new elevator?

The speed of the elevator might be the wrong problem to focus on, however. Talk to an experienced landlord and they might offer you a more elegant solution: put up mirrors next to the elevator so people don’t notice the wait. Gazing lovingly at your own reflection tends to have that effect.

The mirror doesn’t make the elevator faster. It solves a different problem – that the wait is annoying.

Solve the right problem

The slow elevator story highlights an important truth, in that the way we frame a problem often determines which solutions we come up with. By shifting the way we see a problem, we can sometimes find better solutions.

Problem framing is of paramount importance when it comes to tackling the many hard challenges our societies face. And yet, we’re not terribly good at it. In a survey of 106 corporate leaders, 87% said their people waste significant resources solving the wrong problems. When we go to the doctor, we know very well that identifying the right problem is key. Too often, we fail to apply the same thinking to social and global problems.

Three common patterns

So, how do we get better at it? One starting point is to recognise that there are often patterns in the way we frame problems. Get better at recognising those patterns, and you can dramatically improve your ability to solve the right problems. Here are three typical patterns:

1. We prefer framings that allow us to avoid change

People tend to frame problems so they don’t have to change their own behaviour. When the lack of women leading companies first became a prominent concern decades ago, it was often framed as a pipeline problem. Many corporate leaders simply assumed that, once there were enough women in junior positions, the C-suite would follow.

That framing allowed companies to carry on as usual for about a generation until time eventually proved the pipeline theory wrong, or at best radically incomplete. The gender balance among senior executives would surely be better by now if companies had not spent a few decades ignoring other explanations for the skewed ratio….(More)”.

What Should Happen to Our Data When We Die?

Curated on Posted on by Stefaan Verhulst

Adrienne Matei at the New York Times: “The new Anthony Bourdain documentary, “Roadrunner,” is one of many projects dedicated to the larger-than-life chef, writer and television personality. But the film has drawn outsize attention, in part because of its subtle reliance on artificial intelligence technology.

Using several hours of Mr. Bourdain’s voice recordings, a software company created 45 seconds of new audio for the documentary. The A.I. voice sounds just like Mr. Bourdain speaking from the great beyond; at one point in the movie, it reads an email he sent before his death by suicide in 2018.

“If you watch the film, other than that line you mentioned, you probably don’t know what the other lines are that were spoken by the A.I., and you’re not going to know,” Morgan Neville, the director, said in an interview with The New Yorker. “We can have a documentary-ethics panel about it later.”

The time for that panel may be now. The dead are being digitally resurrected with growing frequency: as 2-D projections, 3-D holograms, C.G.I. renderings and A.I. chat bots….(More)”.

Helsinki invites cyclists to collect data on street conditions and earn money

Curated on Posted on by Stefaan Verhulst

Article at the Mayor.eu: “From Saturday 10 July, cyclists in Helsinki will be able to earn money doing what they love whilst simultaneously helping the municipality repair damaged streets. This was announced on 28 June when the City of Helsinki shared that all residents are invited to take part in a game to map out 300 kilometres of cycling paths in the capital.

In a press release, the City of Helsinki reports that anyone can participate as long as they have a bicycle and a smartphone. To take part, one must simply download the free application Crowdchupa and attach their phone to their bicycle. The device will then record footage of the streets and Artificial Intelligence will be used to identify damage that must be repaired.

To make this even more interesting, the Crowdchupa application will allow participants to earn money. The application features a map which depicts various objects (such as coins and berries) on the streets. Cyclists must drive over these virtual objects to collect them and earn money….(More)”.

Human behaviour: what scientists have learned about it from the pandemic

Curated on Posted on by Stefaan Verhulst

Stephen Reicher at The Conversation: “During the pandemic, a lot of assumptions were made about how people behave. Many of those assumptions were wrong, and they led to disastrous policies.

Several governments worried that their pandemic restrictions would quickly lead to “behavioural fatigue” so that people would stop adhering to restrictions. In the UK, the prime minister’s former chief adviser Dominic Cummings recently admitted that this was the reason for not locking down the country sooner.

Meanwhile, former health secretary Matt Hancock revealed that the government’s failure to provide financial and other forms of support for people to self-isolate was down to their fear that the system “might be gamed”. He warned that people who tested positive may then falsely claim that they had been in contact with all their friends, so they could all get a payment.

These examples show just how deeply some governments distrust their citizens. As if the virus was not enough, the public was portrayed as an additional part of the problem. But is this an accurate view of human behaviour?

The distrust is based on two forms of reductionism – describing something complex in terms of its fundamental constituents. The first is limiting psychology to the characteristics – and more specifically the limitations – of individual minds. In this view the human psyche is inherently flawed, beset by biases that distort information. It is seen as incapable of dealing with complexity, probability and uncertainty – and tending to panic in a crisis.

This view is attractive to those in power. By emphasising the inability of people to govern themselves, it justifies the need for a government to look after them. Many governments subscribe to this view, having established so-called nudge units – behavioural science teams tasked with subtly manipulating people to make the “right” decisions, without them realising why, from eating less sugar to filing their taxes on time. But it is becoming increasingly clear that this approach is limited. As the pandemic has shown, it is particularly flawed when it comes to behaviour in a crisis.

In recent years, research has shown that the notion of people panicking in a crisis is something of a myth. People generally respond to crises in a measured and orderly way – they look after each other.

The key factor behind this behaviour is the emergence of a sense of shared identity. This extension of the self to include others helps us care for those around us and expect support from them. Resilience cannot be reduced to the qualities of individual people. It tends to be something that emerges in groups.

Another type of reductionism that governments adopt is “psychologism” – when you reduce the explanation of people’s behaviour to just psychology…(More)”.