World Development Report 2021: Data for Better Lives — Leveraging greater value from data to help the poor

Curated on Posted on by Stefaan Verhulst

Report by the World Bank: “Data has become ubiquitous—with global data flows increasing one thousand times over the last 20 years. What is not always appreciated is the extent to which data offer the potential to improve people’s lives, including the poor and those living in lower-income countries.

Consider this example. The Indian state of Odisha is susceptible to devastating cyclones. When disaster struck in 1999, as many as 10,000 people lost their lives. This tragedy prompted the Odisha State Disaster Management Authority to invest heavily in weather forecast data. When another, similarly powerful storm struck in 2013, the capture and broadcast of early warning data allowed nearly one million people to be evacuated to safety, slashing the death toll to just 38.

Data’s direct benefits on lives and livelihoods can come not only from government initiatives, as in Odisha, but also through a plethora of new private business models. Many of us are familiar with on-demand ride-hailing platforms that have revolutionized public transportation in major cities. In Nigeria, the platform business Hello Tractor has adapted the concept of a ride-hailing platform allowing farmers to rent agricultural equipment on demand and increase their agricultural productivity.

Furthermore, Civil Society Organizations across the world are using crowdsourced data collected from citizens as a way of holding governments accountable. For example, the platform ForestWatchers allows people to directly report deforestation of the Amazon. And in Egypt, the HarrassMap tool allows women to report the location of sexual harassment incidents.

Despite all these innovative uses, data still remain grossly under-utilized, leaving much of the economic and social value of data untapped. Collecting and using data for a single purpose without making it available to others for reuse is a waste of resources.  By reusing and combining data from both public and private sources, and applying modern analytical techniques, merged data sets can cover more people, more precisely, and more frequently.  Leveraging these data synergies can bring real benefits….(More)”.

The (Im)possibility of Fairness: Different Value Systems Require Different Mechanisms For Fair Decision Making

Curated on Posted on by Stefaan Verhulst

Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian at Communications of the ACM: “Automated decision-making systems (often machine learning-based) now commonly determine criminal sentences, hiring choices, and loan applications. This widespread deployment is concerning, since these systems have the potential to discriminate against people based on their demographic characteristics. Current sentencing risk assessments are racially biased, and job advertisements discriminate on gender. These concerns have led to an explosive growth in fairness-aware machine learning, a field that aims to enable algorithmic systems that are fair by design.

To design fair systems, we must agree precisely on what it means to be fair. One such definition is individual fairness: individuals who are similar (with respect to some task) should be treated similarly (with respect to that task). Simultaneously, a different definition states that demographic groups should, on the whole, receive similar decisions. This group fairness definition is inspired by civil rights law in the U.S. and U.K. Other definitions state that fair systems should err evenly across demographic groups. Many of these definitions have been incorporated into machine learning pipelines.

In this article, we introduce a framework for understanding these different definitions of fairness and how they relate to each other. Crucially, our framework shows these definitions and their implementations correspond to different axiomatic beliefs about the world. We present two such worldviews and will show they are fundamentally incompatible. First, one can believe the observation processes that generate data for machine learning are structurally biased. This belief provides a justification for seeking non-discrimination. When one believes that demographic groups are, on the whole, fundamentally similar, group fairness mechanisms successfully guarantee the top-level goal of non-discrimination: similar groups receiving similar treatment. Alternatively, one can assume the observed data generally reflects the true underlying reality about differences between people. These worldviews are in conflict; a single algorithm cannot satisfy either definition of fairness under both worldviews. Thus, researchers and practitioners ought to be intentional and explicit about world-views and value assumptions: the systems they design will always encode some belief about the world….(More)”.

Hospitals Hide Pricing Data From Search Results

Curated on Posted on by Stefaan Verhulst

Tom McGinty, Anna 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

Curated on Posted on by Stefaan Verhulst

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

Curated on Posted on by Stefaan Verhulst

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)”.

The World Happiness Report 2021

Curated on Posted on by Stefaan Verhulst

Report by the Sustainable Development Solutions Network: “There has been surprising resilience in how people rate their lives overall. The Gallup World Poll data are confirmed for Europe by the separate Eurobarometer surveys and several national surveys.

  • The change from 2017-2019 to 2020 varied considerably among countries, but not enough to change rankings in any significant fashion materially. The same countries remain at the top.
  • Emotions changed more than did life satisfaction during the first year of COVID-19, worsening more during lockdown and recovering faster, as illustrated by large samples of UK data. For the world as a whole, based on the annual data from the Gallup World Poll, there was no overall change in positive affect, but there was a roughly 10% increase in the number of people who said they were worried or sad the previous day.
  • Trust and the ability to count on others are major supports to life evaluations, especially in the face of crises. To feel that your lost wallet would be returned if found by a police officer, by a neighbour, or a stranger, is estimated to be more important for happiness than income, unemployment, and major health risks (see Figure 2.4 in chapter 2)
  • Trust is even more important in explaining the very large international differences in COVID-19 death rates, which were substantially higher in the Americas and Europe than in East Asia, Australasia, and Africa, as shown here (see Figure 2.5 of chapter 2). These differences were almost half due to differences in the age structure of populations (COVID-19 much more deadly for the old), whether the country is an island, and how exposed each country was, early in the pandemic, to large numbers of infections in nearby countries. Whatever the initial circumstances, the most effective strategy for controlling COVID-19 was to drive community transmission to zero and to keep it there. Countries adopting this strategy had death rates close to zero, and were able to avoid deadly second waves, and ended the year with less loss of income and lower death rates.
  • Factors supporting successful COVID-19 strategies include
    • confidence in public institutions. Trusted public institutions were more likely to choose the right strategy and have their populations support the required actions. For example, Brazil’s death rate was 93 per 100,000, higher than in Singapore, and of this difference, over a third could be explained by the difference in public trust….(More)”

Building Behavioral Science in an organization

Curated on Posted on by Stefaan Verhulst
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Report by Action Design Network in conjunction with UPenn Master of Behavioral and Decision Sciences: “Behavioral science can be applied to a variety of practice areas within an organization via a range of design and measurement tactics. It can influence strategy and design throughout an organization, including product design, marketing and communications, employee and customer engagement, and strategic decision making. Applied behavioral science includes both designing for the moment (the domain of nudges and cognitive biases) as well as creating the broader context for shaping the thoughts, emotions, and behavioral patterns of employees and customers. 

This book draws on the collective wisdom of applied behavioral scientists with deep experience within their respective practice areas to provide practical guidance on building a behavioral science function that has a meaningful impact on your organization….(More)”.

Lawmakers’ use of scientific evidence can be improved

Curated on Posted on by Stefaan Verhulst

Paper by D. Max Crowley et al: “This study is an experimental trial that demonstrates the potential for formal outreach strategies to change congressional use of research. Our results show that collaboration between policy and research communities can change policymakers’ value of science and result in legislation that appears to be more inclusive of research evidence. The findings of this study also demonstrated changes in researchers’ knowledge and motivation to engage with policymakers as well as their actual policy engagement behavior. Together, the observed changes in both policymakers and researchers randomized to receive an intervention for supporting legislative use of research evidence (i.e., the Research-to-Policy Collaboration model) provides support for the underlying theories around the social nature of research translation and evidence use….(More)”.

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

Curated on Posted on by Stefaan Verhulst

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. DuBois, Ida B. Wells, C.L.R. James, E.P. Thompson, Eric Hobsbawm, Charles 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)”.

A New Portal for the Decentralized Web and its Guiding Principles

Curated on Posted on by Stefaan Verhulst

Internet Archive: “For a long time, we’ve felt that the growing, diverse, global community interested in building the decentralized Web needed an entry point. A portal into the events, concepts, voices, and resources critical to moving the Decentralized Web forward.

This is why we created, getdweb.net, to serve as a portal, a welcoming entry point for people to learn and share strategies, analysis, and tools around how to build a decentralized Web.

Screenshot of https://getdweb.net/

It began at DWeb Camp 2019, when designer Iryna Nezhynska of Jolocom led a workshop to imagine what form that portal should take. Over the next 18 months, Iryna steered a dedicated group of DWeb volunteers through a process to create this new website. If you are new to the DWeb, it should help you learn about its core concepts. If you are a seasoned coder, it should point you to opportunities nearby. For our nine local nodes, it should be a clearinghouse and archive for past and future events.

Above all, the new website was designed to clearly state the principles we believe in as a community, the values we are trying to build right into the code.

At our February DWeb Meetup, our designer Iryna took us on a tour of the new website and the design concepts that support it.

Then John Ryan and I (Associate Producer of DWeb Projects) shared the first public version of the Principles of the DWeb and described the behind-the-scenes process that went into developing them. It was developed in consultation with dozens of community members, including technologists, organizers, academics, policy experts, and artists. These DWeb Principles are a starting point, not an end point — open for iteration.

As stewards, we felt that we needed to crystallize the shared vision of this community, to demonstrate how and why we are building a Decentralized Web. Our aim is to identify our guiding principles through discussion and distill them into a living document that we can point to. It is to create a set of practical guiding values as we design and build the Web of the future….(More)”.