Hospitals Hide Pricing Data From Search Results


Tom McGintyAnna Wilde Mathews and Melanie Evans at the Wall Street Journal: “Hospitals that have published their previously confidential prices to comply with a new federal rule have also blocked that information from web searches with special coding embedded on their websites, according to a Wall Street Journal examination.

The information must be disclosed under a federal rule aimed at making the $1 trillion sector more consumer friendly. But hundreds of hospitals embedded code in their websites that prevented Alphabet Inc.’s Google and other search engines from displaying pages with the price lists, according to the Journal examination of more than 3,100 sites.

The code keeps pages from appearing in searches, such as those related to a hospital’s name and prices, computer-science experts said. The prices are often accessible other ways, such as through links that can require clicking through multiple layers of pages.

“It’s technically there, but good luck finding it,” said Chirag Shah, an associate professor at the University of Washington who studies human interactions with computers. “It’s one thing not to optimize your site for searchability, it’s another thing to tag it so it can’t be searched. It’s a clear indication of intentionality.”…(More)”.

Negligence, Not Politics, Drives Most Misinformation Sharing


John Timmer at Wired: “…a small international team of researchers… decided to take a look at how a group of US residents decided on which news to share. Their results suggest that some of the standard factors that people point to when explaining the tsunami of misinformation—inability to evaluate information and partisan biases—aren’t having as much influence as most of us think. Instead, a lot of the blame gets directed at people just not paying careful attention.

The researchers ran a number of fairly similar experiments to get at the details of misinformation sharing. This involved panels of US-based participants recruited either through Mechanical Turk or via a survey population that provided a more representative sample of the US. Each panel had several hundred to over 1,000 individuals, and the results were consistent across different experiments, so there was a degree of reproducibility to the data.

To do the experiments, the researchers gathered a set of headlines and lead sentences from news stories that had been shared on social media. The set was evenly mixed between headlines that were clearly true and clearly false, and each of these categories was split again between those headlines that favored Democrats and those that favored Republicans.

One thing that was clear is that people are generally capable of judging the accuracy of the headlines. There was a 56 percentage point gap between how often an accurate headline was rated as true and how often a false headline was. People aren’t perfect—they still got things wrong fairly often—but they’re clearly quite a bit better at this than they’re given credit for.

The second thing is that ideology doesn’t really seem to be a major factor in driving judgements on whether a headline was accurate. People were more likely to rate headlines that agreed with their politics, but the difference here was only 10 percentage points. That’s significant (both societally and statistically), but it’s certainly not a large enough gap to explain the flood of misinformation.

But when the same people were asked about whether they’d share these same stories, politics played a big role, and the truth receded. The difference in intention to share between true and false headlines was only 6 percentage points. Meanwhile the gap between whether a headline agreed with a person’s politics or not saw a 20 percentage point gap. Putting it in concrete terms, the authors look at the false headline “Over 500 ‘Migrant Caravaners’ Arrested With Suicide Vests.” Only 16 percent of conservatives in the survey population rated it as true. But over half of them were amenable to sharing it on social media….(More)”.

Mastercard, SoftBank and others call on G7 to create tech group


Siddharth Venkataramakrishnan at the Financial Times: “A group of leading companies including Mastercard, SoftBank and IBM have called on the G7 to create a new body to help co-ordinate how member states tackle issues ranging from artificial intelligence to cyber security.

The Data and Technology Forum, which would be modelled on the Financial Stability Board that was created after the 2008 financial crisis, would provide recommendations on how tech governance can be co-ordinated internationally, rather than proposing firm regulations.

“We believe a similar forum [to the FSB] is urgently needed to prevent fragmentation and strengthen international co-operation and consensus on digital governance issues,” said Michael Froman, vice-chair and president of strategic growth for Mastercard. “There is a window of opportunity — right now — to strengthen collaboration.”

The proposal comes as countries’ approaches to tech policy are becoming increasingly divergent, creating problems of international co-operation, while concerns grow globally over issues such as privacy and data security.

The 25 companies involved come from a broad range of sectors, including payment providers Visa and Nexi, carmakers Toyota and Mercedes and global healthcare company GlaxoSmithKline.

Like the Basel-based FSB, which was set up to identify and address systemic risks in the financial system, the new body would provide a forum for tackling major challenges in the tech sector such as cross-border data transfers and the regulation of artificial intelligence.

Froman said the forum was “essential” to promote trust in new technologies while avoiding diverging industry standards. The body would work with existing organisations such as the World Trade Organization, and professional standard-setting bodies.

Struggles over which government gets to set the rules of the internet of the future have intensified in recent years, with the US, EU and China all seeking to gain first-mover advantage.

The new body’s first three areas of focus would be co-operation on cyber security, the alignment of AI frameworks and the global interoperability of data….(More)”.

How ‘Good’ Social Movements Can Triumph over ‘Bad’ Ones


Essay by Gilda Zwerman and Michael Schwartz: “…How, then, can we judge which movement was the “good” one and which the “bad?”

The answer can be found in the sociological study of social movements. Over decades of focused research, the field has demonstrated that evaluating the moral compass of individual participants does little to advance our understanding of the morality or the actions of a large movement. Only by assessing the goals, tactics and outcomes of movements as collective phenomena can we begin to discern the distinction between “good” and “bad” movements.

Modern social movement theory developed from foundational studies by several generations of scholars, notably W.E.B. DuBoisIda B. WellsC.L.R. JamesE.P. ThompsonEric HobsbawmCharles Tilly and Howard Zinn. Their works analyzing “large” historical processes provided later social scientists with three working propositions.

First, the morality of a movement is measured by the type of change it seeks. “Good” movements are emancipatory: they seek to pressure institutional authorities into reducing systemic inequality, extending democratic rights to previously excluded groups, and alleviating material, social, and political injustices. “Bad” movements tend to be reactionary. They arise in response to good movements and they seek to preserve or intensify the exclusionary structures, laws and policies that the emancipatory movements are challenging.

Second, large-scale institutional changes that broaden freedom or advance the cause of social justice are rarely initiated by institutional authorities or political elites. Rather, most social progress is the result of pressure exerted from the bottom up, by ordinary people who press for reform by engaging in collective and creative disorders outside the bounds of mainstream institutions.

And third, good intentions—aspiring to achieve emancipatory goals—by no means guarantee that a movement will succeed.

The highly popular and emancipatory protests of the 1960s, as well as the influence of groundbreaking works in social history mentioned above, inspired a renaissance in the study of social movements in subsequent decades. Focusing primarily on “good” movements, a new generation of social scientists sought to identify the environmental circumstances, organizational features and strategic choices that increased the likelihood that “good intentions” would translate into tangible change. This research has generated a rich trove of findings:…(More)”.

Coming wave of video games could build empathy on racism, environment and aftermath of war


Mike Snider at USA Today: “Some of the newest video games in development aren’t really games at all, but experiences that seek to build empathy for others.

Among the five such projects getting funding grants and support from 3D software engine maker Unity is “Our America,” in which the player takes the role of a Black man who is driving with his son when their car is pulled over by a police officer.

The father worries about getting his car registration from the glove compartment because the officer “might think it’s a gun or something,” the character says in the trailer.

On the project’s website, the developers describe “Our America” as “an autobiographical VR Experience” in which “the audience must make quick decisions, answer questions – but any wrong move is the difference between life and death.”…

The other Unity for Humanity winners include:

  • Ahi Kā Rangers: An ecological mobile game with development led by Māori creators. 
  • Dot’s Home: A game that explores historical housing injustices faced by Black and brown home buyers. 
  • Future Aleppo: A VR experience for children to rebuild homes and cities destroyed by war. 
  • Samudra: A children’s environmental puzzle game that takes the player across a polluted sea to learn about pollution and plastic waste.

While “Our America” may serve best as a VR experience, other projects such as “Dot’s Home” may be available on mobile devices to expand its accessibility….(More)”.

Who Is Making Sure the A.I. Machines Aren’t Racist?


Cade Metz at the New York Times: “Hundreds of people gathered for the first lecture at what had become the world’s most important conference on artificial intelligence — row after row of faces. Some were East Asian, a few were Indian, and a few were women. But the vast majority were white men. More than 5,500 people attended the meeting, five years ago in Barcelona, Spain.

Timnit Gebru, then a graduate student at Stanford University, remembers counting only six Black people other than herself, all of whom she knew, all of whom were men.

The homogeneous crowd crystallized for her a glaring issue. The big thinkers of tech say A.I. is the future. It will underpin everything from search engines and email to the software that drives our cars, directs the policing of our streets and helps create our vaccines.

But it is being built in a way that replicates the biases of the almost entirely male, predominantly white work force making it.

In the nearly 10 years I’ve written about artificial intelligence, two things have remained a constant: The technology relentlessly improves in fits and sudden, great leaps forward. And bias is a thread that subtly weaves through that work in a way that tech companies are reluctant to acknowledge.

On her first night home in Menlo Park, Calif., after the Barcelona conference, sitting cross-​legged on the couch with her laptop, Dr. Gebru described the A.I. work force conundrum in a Facebook post.

“I’m not worried about machines taking over the world. I’m worried about groupthink, insularity and arrogance in the A.I. community — especially with the current hype and demand for people in the field,” she wrote. “The people creating the technology are a big part of the system. If many are actively excluded from its creation, this technology will benefit a few while harming a great many.”

The A.I. community buzzed about the mini-manifesto. Soon after, Dr. Gebru helped create a new organization, Black in A.I. After finishing her Ph.D., she was hired by Google….(More)”.

The Mathematics of How Connections Become Global


Kelsey Houston-Edwards at Scientific American: “When you hit “send” on a text message, it is easy to imagine that the note will travel directly from your phone to your friend’s. In fact, it typically goes on a long journey through a cellular network or the Internet, both of which rely on centralized infrastructure that can be damaged by natural disasters or shut down by repressive governments. For fear of state surveillance or interference, tech-savvy protesters in Hong Kong avoided the Internet by using software such as FireChat and Bridgefy to send messages directly between nearby phones.

These apps let a missive hop silently from one phone to the next, eventually connecting the sender to the receiver—the only users capable of viewing the message. The collections of linked phones, known as mesh networks or mobile ad hoc networks, enable a flexible and decentralized mode of communication. But for any two phones to communicate, they need to be linked via a chain of other phones. How many people scattered throughout Hong Kong need to be connected via the same mesh network before we can be confident that crosstown communication is possible?

Mesh network in action: when cell-phone ranges overlap, a linked chain of connections is established.
Credit: Jen Christiansen (graphic); Wee People font, ProPublica and Alberto Cairo (figure drawings)

A branch of mathematics called percolation theory offers a surprising answer: just a few people can make all the difference. As users join a new network, isolated pockets of connected phones slowly emerge. But full east-to-west or north-to-south communication appears all of a sudden as the density of users passes a critical and sharp threshold. Scientists describe such a rapid change in a network’s connectivity as a phase transition—the same concept used to explain abrupt changes in the state of a material such as the melting of ice or the boiling of water.

A phase transition in a mesh network: the density of users suddenly passes a critical threshold.
Credit: Jen Christiansen (graphic); Wee People font, ProPublica and Alberto Cairo (figure drawings)

Percolation theory examines the consequences of randomly creating or removing links in such networks, which mathematicians conceive of as a collection of nodes (represented by points) linked by “edges” (lines). Each node represents an object such as a phone or a person, and the edges represent a specific relation between two of them. The fundamental insight of percolation theory, which dates back to the 1950s, is that as the number of links in a network gradually increases, a global cluster of connected nodes will suddenly emerge….(More)”.

What the drive for open science data can learn from the evolving history of open government data


Stefaan Verhulst, Andrew Young, and Andrew Zahuranec at The Conversation: “Nineteen years ago, a group of international researchers met in Budapest to discuss a persistent problem. While experts published an enormous amount of scientific and scholarly material, few of these works were accessible. New research remained locked behind paywalls run by academic journals. The result was researchers struggled to learn from one another. They could not build on one another’s findings to achieve new insights. In response to these problems, the group developed the Budapest Open Access Initiative, a declaration calling for free and unrestricted access to scholarly journal literature in all academic fields.

In the years since, open access has become a priority for a growing number of universitiesgovernments, and journals. But while access to scientific literature has increased, access to the scientific data underlying this research remains extremely limited. Researchers can increasingly see what their colleagues are doing but, in an era defined by the replication crisis, they cannot access the data to reproduce the findings or analyze it to produce new findings. In some cases there are good reasons to keep access to the data limited – such as confidentiality or sensitivity concerns – yet in many other cases data hoarding still reigns.

To make scientific research data open to citizens and scientists alike, open science data advocates can learn from open data efforts in other domains. By looking at the evolving history of the open government data movement, scientists can see both limitations to current approaches and identify ways to move forward from them….(More) (French version)”.

Lessons from all democracies


David Stasavage at Aeon: “Today, many people see democracy as under threat in a way that only a decade ago seemed unimaginable. Following the fall of the Berlin Wall in 1989, it seemed like democracy was the way of the future. But nowadays, the state of democracy looks very different; we hear about ‘backsliding’ and ‘decay’ and other descriptions of a sort of creeping authoritarianism. Some long-established democracies, such as the United States, are witnessing a violation of governmental norms once thought secure, and this has culminated in the recent insurrection at the US Capitol. If democracy is a torch that shines for a time before then burning out – think of Classical Athens and Renaissance city republics – it all feels as if we might be heading toward a new period of darkness. What can we do to reverse this apparent trend and support democracy?

First, we must dispense with the idea that democracy is like a torch that gets passed from one leading society to another. The core feature of democracy – that those who rule can do so only with the consent of the people – wasn’t invented in one place at one time: it evolved independently in a great many human societies.

Over several millennia and across multiple continents, early democracy was an institution in which rulers governed jointly with councils and assemblies of the people. From the Huron (who called themselves the Wendats) and the Iroquois (who called themselves the Haudenosaunee) in the Northeastern Woodlands of North America, to the republics of Ancient India, to examples of city governance in ancient Mesopotamia, these councils and assemblies were common. Classical Greece provided particularly important instances of this democratic practice, and it’s true that the Greeks gave us a language for thinking about democracy, including the word demokratia itself. But they didn’t invent the practice. If we want to better understand the strengths and weaknesses of our modern democracies, then early democratic societies from around the world provide important lessons.

The core feature of early democracy was that the people had power, even if multiparty elections (today, often thought to be a definitive feature of democracy) didn’t happen. The people, or at least some significant fraction of them, exercised this power in many different ways. In some cases, a ruler was chosen by a council or assembly, and was limited to being first among equals. In other instances, a ruler inherited their position, but faced constraints to seek consent from the people before taking actions both large and small. The alternative to early democracy was autocracy, a system where one person ruled on their own via bureaucratic subordinates whom they had recruited and remunerated. The word ‘autocracy’ is a bit of a misnomer here in that no one in this position ever truly ruled on their own, but it does signify a different way of organising political power.

Early democratic governance is clearly apparent in some ancient societies in Mesopotamia as well as in India. It flourished in a number of places in the Americas before European conquest, such as among the Huron and the Iroquois in the Northeastern Woodlands and in the ‘Republic of Tlaxcala’ that abutted the Triple Alliance, more commonly known as the Aztec Empire. It was also common in precolonial Africa. In all of these societies there were several defining features that tended to reinforce early democracy: small scale, a need for rulers to depend on the people for knowledge, and finally the ability of members of society to exit to other locales if they were unhappy with a ruler. These three features were not always present in the same measure, but collectively they helped to underpin early democracy….(More)”

Biden Creates Road Map for Equitable State and Local Data


Daniel Castro at GovTech: “On his first day in office, President Biden issued a flurry of administrative actions to reverse a number of President Trump’s policies and address the ongoing coronavirus pandemic. One of these included an executive order to advance racial equity and provide support for underserved communities. Notably, the order recognizes that achieving this goal will be difficult, if not impossible, without better data. This is a lesson that many state and local governments should take to heart by revisiting their collection policies to ensure data is equitable.

The executive order establishes that it is the policy of the Biden administration to “pursue a comprehensive approach to advancing equity for all, including people of color and others who have been historically underserved, marginalized, and adversely affected by persistent poverty and inequality.” To that end, the order dedicates a section to establishing an interagency working group on equitable data tasked with identifying inadequacies in federal data collection policies and programs, and recommending strategies for addressing any deficiencies.   

An inability to disaggregate data prevents policymakers from identifying disparate impacts of government programs on different populations in a variety of areas including health care, education, criminal justice, workforce and housing. Indeed, the U.S. Commission on Civil Rights has found that “data collection and reporting are essential to effective civil rights enforcement, and that a lack of effective civil rights data collection is problematic.”

This problem has repeatedly been on display throughout the COVID-19 pandemic. For example, at the outset of the pandemic last year, nearly half of states did not report data on race or ethnicity on those who were tested, hospitalized or died of COVID-19. And while the government has tried to take a data-driven response to the COVID-19 pandemic, a lack of data about different groups means that their needs are often hidden from policymakers….(More)”.