Stefaan Verhulst
Abdi Latif Dahir at Quartz: “Tanzania’s government wants to have exclusive control over who collects and shares data about the country.
In a bill tabled in parliament this week, the government aims to criminalize the collection, analysis, and dissemination of any data without first obtaining authorization from the country’s chief statistician. The key amendments to the Statistics Act also prohibit researchers from publicly releasing any data “which is intended to invalidate, distort, or discredit official statistics.” Any person who does anything to the contrary could merit a fine of not less than 10 million shillings ($4,400), a jail term of three years, or both.
Officials have said the amendments are being passed as a measure to promote peace and security and to stop the publication of fake information. Critics, however, argue the laws will curtail both the collection of crucial data and the ability to fact-check and hold official sources accountable. Opposition members in parliament also said the law could target institutions and scholars releasing data that isn’t in favor of the government….
the move to ban independent data collection could be damaging given how much quality information could help in national development. African nations increasingly lack evidence-based research that could inform how they formulate national policies. And many times in Tanzania, independent actors fulfill this gap, providing data on flood-prone areas to avoid disasters, or documenting citizens’ needs—something that isn’t captured in official government statistics….(More)”.
Social Science Research Council: “For decades, the social sciences have generated knowledge vital to guiding public policy, informing business, and understanding and improving the human condition. But today, the social sciences face serious threats. From dwindling federal funding to public mistrust in institutions to widespread skepticism about data, the infrastructure supporting the social sciences is shifting in ways that threaten to undercut research and knowledge production.
How can we secure social knowledge for future generations?
This question has guided the Social Science Research Council’s Task Force. Following eighteen months of consultation with key players as well as internal deliberation, we have identified both long-term developments and present threats that have created challenges for the social sciences, but also created unique opportunities. And we have generated recommendations to address these issues.
Our core finding focuses on the urgent need for new partnerships and collaborations among several key players: the federal government, academic institutions, donor organizations, and the private sector. Several decades ago, these institutions had clear zones of responsibility in producing social knowledge, with the federal government constituting the largest portion of funding for basic research. Today, private companies represent an increasingly large share not just of research and funding, but also the production of data that informs the social sciences, from smart phone usage to social media patterns.
In addition, today’s social scientists face unprecedented demands for accountability, speedy publication, and generation of novel results. These pressures have emerged from the fragmented institutional foundation that undergirds research. That foundation needs a redesign in order for the social sciences to continue helping our communities address problems ranging from income inequality to education reform.
To build a better future, we identify five areas of action: Funding, Data, Ethics, Research Quality, and Research Training. In each area, our recommendations range from enlarging corporate-academic pilot programs to improving social science training in digital literacy.
A consistent theme is that none of the measures, if taken unilaterally, can generate optimal outcomes. Instead, we have issued a call to forge a new research compact to harness the potential of the social sciences for improving human lives. That compact depends on partnerships, and we urge the key players in the construction of social science knowledge—including universities, government, foundations, and corporations—to act swiftly. With the right realignments, the security of social knowledge lies within our reach….(More)”
The Constitution itself was understood by its framers as a machine, a precisely constructed instrument whose measures — its separation of powers, its checks and balances — were mechanical devices, as intricate as the gears of a clock, designed to thwart tyrants, mobs and demagogues, and to prevent the forming of factions. Once those factions began to appear, it became clear that other machines would be needed to establish stable parties. “The engine is the press,” Thomas Jefferson, an inveterate inventor, wrote in 1799.
Even that savage war didn’t diminish Americans’ faith that technology could solve the problem of political division. In the 1920s, Herbert Hoover, as secretary of commerce, rightly anticipated that radio, the nation’s next great mechanical experiment, would make it possible for political candidates and officeholders to speak to voters without the bother and expense of traveling to meet them. NBC began radio broadcasting in 1926, CBS in 1928. By the end of the decade, nearly every household would have a wireless. Hoover promised that radio would make Americans “literally one people.”
All of this history was forgotten or ignored by the people who wrote the rules of the internet and who peer out upon the world from their offices in Silicon Valley and boast of their disdain for the past. But the building of a new machinery of communications began even before the opening of the internet. In the 1980s, conservatives campaigned to end the Fairness Doctrine in favor of a public-interest-based rule for broadcasters, a market-based rule: If people liked it, broadcasters could broadcast it….(More)”
Christoph Koettl at the New York Times: “Was a video of a chemical attack really filmed in Syria? What time of day did an airstrike happen? Which military unit was involved in a shooting in Afghanistan? Is this dramatic image of glowing clouds really showing wildfires in California?
These are some of the questions the video team at The New York Times has to answer when reviewing raw eyewitness videos, often posted to social media. It can be a highly challenging process, as misinformation shared through digital social networks is a serious problem for a modern-day newsroom. Visual information in the digital age is easy to manipulate, and even easier to spread.
What is thus required for conducting visual investigations based on social media content is a mix of traditional journalistic diligence and cutting-edge internet skills, as can be seen in our recent investigation into the chemical attack in Douma, Syria.
Press Release: “Stanford University School of Medicine and Unanimous AI presented a new study today showing that a small group of doctors, connected by intelligence algorithms that enable them to work together as a “hive mind,” could achieve higher diagnostic accuracy than the individual doctors or machine learning algorithms alone. The technology used is called Swarm AI and it empowers networked human groups to combine their individual insights in real-time, using AI algorithms to converge on optimal solutions.
As presented at the 2018 SIIM Conference on Machine Intelligence in Medical Imaging, the study tasked a group of experienced radiologists with diagnosing the presence of pneumonia in chest X-rays. This is one of the most widely performed imaging procedures in the US, with more than 1 million adults hospitalized with pneumonia each year. But, despite this prevalence, accurately diagnosing X-rays is highly challenging with significant variability across radiologists. This makes it both an optimal task for applying new AI technologies, and an important problem to solve for the medical community.
When generating diagnoses using Swarm AI technology, the average error rate was reduced by 33% compared to traditional diagnoses by individual practitioners. This is an exciting result, showing the potential of AI technologies to amplify the accuracy of human practitioners while maintaining their direct participation in the diagnostic process.
Swarm AI technology was also compared to the state-of-the-art in automated diagnosis using software algorithms that do not employ human practitioners. Currently, the best system in the world for the automated diagnosing of pneumonia from chest X-rays is the CheXNet system from Stanford University, which made headlines in 2017 by significantly outperforming individual practitioners using deep-learning derived algorithms.
The Swarm AI system, which combines real-time human insights with AI technology, was 22% more accurate in binary classification than the software-only CheXNet system. In other words, by connecting a group of radiologists into a medical “hive mind”, the hybrid human-machine system was able to outperform individual human doctors as well as the state-of-the-art in deep-learning derived algorithms….(More)”.
Skot Thayer and Alex Hern at the Guardian: “Rohingya refugees are turning to blockchain-type technology to help address one of their most existential threats: lack of officially-recognised identity.
Denied citizenship in their home country of Myanmar for decades, the Muslim minority was the target of a brutal campaign of violence by the military which culminated a year ago this week. A “clearance operation” led by Buddhist militia sent more than 700,000 Rohingya pouring over the border into Bangladesh, without passports or official ID.
The Myanmar government has since agreed to take the Rohingya back, but are refusing to grant them citizenship. Many Rohingya do not want to return and face life without a home or an identity. This growing crisis prompted Muhammad Noor and his team at the Rohingya Project to try to find a digital solution.
“Why does a centralised entity like a bank or government own my identity,” says Noor, a Rohingya community leader based in Kuala Lumpur. “Who are they to say if I am who I am?”
Using blockchain-based technology, Noor, is trialling the use of digital identity cards that aim to help Rohingya in Malaysia, Bangladesh and Saudi Arabia access services such as banking and education. The hope is that successful trials might lead to a system that can help the community across southeast Asia.
Under the scheme, a blockchain database is used to record individual digital IDs, which can then be issued to people once they have taken a test to verify that they are genuine Rohingya….
Blockchain-based initiatives, such as the Rohingya Project, could eventually allow people to build the network of relationships necessary to participate in the modern global economy and prevent second and third generation “invisible” people from slipping into poverty. It could also allow refugees to send money across borders, bypassing high transaction fees.
In Jordan’s Azraq refugee camp, the United Nations World Food Programme (WFP) is using blockchain and biometrics to help Syrian refugees to purchase groceries using a voucher system. This use of the technology allows the WFP to bypass bank fees.
But Al Rjula says privacy is still an issue. “The technology is maturing, yet implementation by startups and emerging tech companies is still lacking,” he says.
The involvement of a trendy technology such as blockchains can often be enough to secure the funding, attention and support that start-ups – whether for-profit or charitable – need to thrive. But companies such as Tykn still have to tackle plenty of the same issues as their old-fashioned database-using counterparts, from convincing governments and NGOs to use their services in the first place to working out how to make enough overhead to pay staff, while also dealing with the fickle issues of building on a cutting-edge platform.
Blockchain-based humanitarian initiatives will also need to reckon with the problem of accountability in their efforts to aid refugees and those trapped in the limbo of statelessness.
Dilek Genc, a PhD candidate at the University of Edinburgh who studies blockchain-type applications in humanitarian aid and development, saysif the aid community continues to push innovation using Silicon Valley’s creed of “fail fast and often,” and experiment on vulnerable peoples they will be fundamentally at odds with humanitarian principles and fail to address the political roots of issues facing refugees…(More)”.
Book by Mark A. Abramson, Daniel J. Chenok and John M. Kamensky: “In recognition of its 20th anniversary, The IBM Center for the Business of Government offers a retrospective of the most significant changes in government management during that period and looks forward over the next 20 years to offer alternative scenarios as to what government management might look like by the year 2040.
Part I will discuss significant management improvements in the federal government over the past 20 years, based in part on a crowdsourced survey of knowledgeable government officials and public administration experts in the field. It will draw on themes and topics examined in the 350 IBM Center reports published over the past two decades. Part II will outline alternative scenarios of how government might change over the coming 20 years. The scenarios will be developed based on a series of envisioning sessions which are bringing together practitioners and academics to examine the future. The scenarios will be supplemented with short essays on various topics. Part II will also include essays by winners of the Center’s Challenge Grant competition. Challenge Grant winners will be awarded grants to identify futuristic visions of government in 2040….(More)”.
Joshua Blumenstock at Nature: “Today, 95% of the global population has mobile-phone coverage, and the number of people who own a phone is rising fast (see ‘Dialling up’)1. Phones generate troves of personal data on billions of people, including those who live on a few dollars a day. So aid organizations, researchers and private companies are looking at ways in which this ‘data revolution’ could transform international development.
Some businesses are starting to make their data and tools available to those trying to solve humanitarian problems. The Earth-imaging company Planet in San Francisco, California, for example, makes its high-resolution satellite pictures freely available after natural disasters so that researchers and aid organizations can coordinate relief efforts. Meanwhile, organizations such as the World Bank and the United Nations are recruiting teams of data scientists to apply their skills in statistics and machine learning to challenges in international development.
But in the rush to find technological solutions to complex global problems there’s a danger of researchers and others being distracted by the technology and losing track of the key hardships and constraints that are unique to each local context. Designing data-enabled applications that work in the real world will require a slower approach that pays much more attention to the people behind the numbers…(More)”.
Press Release: “As the United Nations celebrates the International Day of Democracy on September 15 with its theme of “Democracy Under Strain,” The Governance Lab (The GovLab) at the NYU Tandon School of Engineering will unveil its CrowdLaw Manifesto to strengthen public participation in lawmaking by encouraging citizens to help build, shape, and influence the laws and policies that affect their daily lives.
Among its 12 calls to action to individuals, legislatures, researchers and technology designers, the manifesto encourages the public to demand and institutions to create new mechanisms to harness collective intelligence to improve the quality of lawmaking as well as more research on what works to build a global movement for participatory democracy.
The CrowdLaw Manifesto emerged from a collaborative effort of 20 international experts and CrowdLaw community members. At a convening held earlier this year by The GovLab at The Rockefeller Foundation Bellagio Center in Italy, government leaders, academics, NGOs, and technologists formulated the CrowdLaw Manifesto to detail the initiative’s foundational principles and to encourage greater implementation of CrowdLaw practices to improve governance through 21st century technology and tools….
“The successes of the CrowdLaw concept – and its remarkably rapid adoption across the world by citizens seeking to affect change – exemplify the powerful force that academia can exert when working in concert with government and citizens,” said NYU Tandon Dean Jelena Kovačević. “On behalf of the NYU Tandon School of Engineering, I proudly sign the CrowdLaw Manifesto and congratulate The GovLab and its collaborators for creating these digital tools and momentum for good government.”…(More)”.
Gillian Hadfield at TechCrunch: “Knowledge, to paraphrase British journalist Miles Kington, is knowing a tomato is a fruit; wisdom is knowing there’s a norm against putting it in a fruit salad.
Any kind of artificial intelligence clearly needs to possess great knowledge. But if we are going to deploy AI agents widely in society at large — on our highways, in our nursing homes and schools, in our businesses and governments — we will need machines to be wise as well as smart.
Researchers who focus on a problem known as AI safety or AI alignment define artificial intelligence as machines that can meet or beat human performance at a specific cognitive task. Today’s self-driving cars and facial recognition algorithms fall into this narrow type of AI.
But some researchers are working to develop artificial general intelligence (AGI) — machines that can outperform humans at any cognitive task. We don’t know yet when or even if AGI will be achieved, but it’s clear that the research path is leading to ever more powerful and autonomous AI systems performing more and more tasks in our economies and societies.
Building machines that can perform any cognitive task means figuring out how to build AI that can not only learn about things like the biology of tomatoes but also about our highly variable and changing systems of norms about things like what we do with tomatoes.
Humans live lives populated by a multitude of norms, from how we eat, dress and speak to how we share information, treat one another and pursue our goals.
For AI to be truly powerful will require machines to comprehend that norms can vary tremendously from group to group, making them seem unnecessary, yet it can be critical to follow them in a given community.
Tomatoes in fruit salads may seem odd to the Brits for whom Kington was writing, but they are perfectly fine if you are cooking for Koreans or a member of the culinary avant-garde. And while it may seem minor, serving them the wrong way to a particular guest can cause confusion, disgust, even anger. That’s not a recipe for healthy future relationships….(More)”.