A US-run system alerts the world to famines. It’s gone dark after Trump slashed foreign aid


Article by Lauren Kent: “A vital, US-run monitoring system focused on spotting food crises before they turn into famines has gone dark after the Trump administration slashed foreign aid.

The Famine Early Warning Systems Network (FEWS NET) monitors drought, crop production, food prices and other indicators in order to forecast food insecurity in more than 30 countries…Now, its work to prevent hunger in Sudan, South Sudan, Somalia, Yemen, Ethiopia, Afghanistan and many other nations has been stopped amid the Trump administration’s effort to dismantle the US Agency for International Development (USAID).

“These are the most acutely food insecure countries around the globe,” said Tanya Boudreau, the former manager of the project.

Amid the aid freeze, FEWS NET has no funding to pay staff in Washington or those working on the ground. The website is down. And its treasure trove of data that underpinned global analysis on food security – used by researchers around the world – has been pulled offline.

FEWS NET is considered the gold-standard in the sector, and it publishes more frequent updates than other global monitoring efforts. Those frequent reports and projections are key, experts say, because food crises evolve over time, meaning early interventions save lives and save money…The team at the University of Colorado Boulder has built a model to forecast water demand in Kenya, which feeds some data into the FEWS NET project but also relies on FEWS NET data provided by other research teams.

The data is layered and complex. And scientists say pulling the data hosted by the US disrupts other research and famine-prevention work conducted by universities and governments across the globe.

“It compromises our models, and our ability to be able to provide accurate forecasts of ground water use,” Denis Muthike, a Kenyan scientist and assistant research professor at UC Boulder, told CNN, adding: “You cannot talk about food security without water security as well.”

“Imagine that that data is available to regions like Africa and has been utilized for years and years – decades – to help inform divisions that mitigate catastrophic impacts from weather and climate events, and you’re taking that away from the region,” Muthike said. He cautioned that it would take many years to build another monitoring service that could reach the same level…(More)”.

Extending the CARE Principles: managing data for vulnerable communities in wartime and humanitarian crises


Essay by Yana Suchikova & Serhii Nazarovets: “The CARE Principles (Collective Benefit, Authority to Control, Responsibility, Ethics) were developed to ensure ethical stewardship of Indigenous data. However, their adaptability makes them an ideal framework for managing data related to vulnerable populations affected by armed conflicts. This essay explores the application of CARE principles to wartime contexts, with a particular focus on internally displaced persons (IDPs) and civilians living under occupation. These groups face significant risks of data misuse, ranging from privacy violations to targeted repression. By adapting CARE, data governance can prioritize safety, dignity, and empowerment while ensuring that data serves the collective welfare of affected communities. Drawing on examples from Indigenous data governance, open science initiatives, and wartime humanitarian challenges, this essay argues for extending CARE principles beyond their original scope. Such an adaptation highlights CARE’s potential as a universal standard for addressing the ethical complexities of data management in humanitarian crises and conflict-affected environments…(More)”.

Data, waves and wind to be counted in the economy


Article by Robert Cuffe: “Wind and waves are set to be included in calculations of the size of countries’ economies for the first time, as part of changes approved at the United Nations.

Assets like oilfields were already factored in under the rules – last updated in 2008.

This update aims to capture areas that have grown since then, such as the cost of using up natural resources and the value of data.

The changes come into force in 2030, and could mean an increase in estimates of the size of the UK economy making promises to spend a fixed share of the economy on defence or aid more expensive.

The economic value of wind and waves can be estimated from the price of all the energy that can be generated from the turbines in a country.

The update also treats data as an asset in its own right on top of the assets that house it like servers and cables.

Governments use a common rule book for measuring the size of their economies and how they grow over time.

These changes to the rule book are “tweaks, rather than a rewrite”, according to Prof Diane Coyle of the University of Cambridge.

Ben Zaranko of the Institute for Fiscal Studies (IFS) calls it an “accounting” change, rather than a real change. He explains: “We’d be no better off in a material sense, and tax revenues would be no higher.”

But it could make economies look bigger, creating a possible future spending headache for the UK government…(More)”.

Elon Musk Also Has a Problem with Wikipedia


Article by Margaret Talbot: “If you have spent time on Wikipedia—and especially if you’ve delved at all into the online encyclopedia’s inner workings—you will know that it is, in almost every aspect, the inverse of Trumpism. That’s not a statement about its politics. The thousands of volunteer editors who write, edit, and fact-check the site manage to adhere remarkably well, over all, to one of its core values: the neutral point of view. Like many of Wikipedia’s s principles and procedures, the neutral point of view is the subject of a practical but sophisticated epistemological essay posted on Wikipedia. Among other things, the essay explains, N.P.O.V. means not stating opinions as facts, and also, just as important, not stating facts as opinions. (So, for example, the third sentence of the entry titled “Climate change” states, with no equivocation, that “the current rise in global temperatures is driven by human activities, especially fossil fuel burning since the Industrial Revolution.”)…So maybe it should come as no surprise that Elon Musk has lately taken time from his busy schedule of dismantling the federal government, along with many of its sources of reliable information, to attack Wikipedia. On January 21st, after the site updated its page on Musk to include a reference to the much-debated stiff-armed salute he made at a Trump inaugural event, he posted on X that “since legacy media propaganda is considered a ‘valid’ source by Wikipedia, it naturally simply becomes an extension of legacy media propaganda!” He urged people not to donate to the site: “Defund Wikipedia until balance is restored!” It’s worth taking a look at how the incident is described on Musk’s page, quite far down, and judging for yourself. What I see is a paragraph that first describes the physical gesture (“Musk thumped his right hand over his heart, fingers spread wide, and then extended his right arm out, emphatically, at an upward angle, palm down and fingers together”), goes on to say that “some” viewed it as a Nazi or a Roman salute, then quotes Musk disparaging those claims as “politicized,” while noting that he did not explicitly deny them. (There is also now a separate Wikipedia article, “Elon Musk salute controversy,” that goes into detail about the full range of reactions.)

This is not the first time Musk has gone after the site. In December, he posted on X, “Stop donating to Wokepedia.” And that wasn’t even his first bad Wikipedia pun. “I will give them a billion dollars if they change their name to Dickipedia,” he wrote, in an October, 2023, post. It seemed to be an ego thing at first. Musk objected to being described on his page as an “early investor” in Tesla, rather than as a founder, which is how he prefers to be identified, and seemed frustrated that he couldn’t just buy the site. But lately Musk’s beef has merged with a general conviction on the right that Wikipedia—which, like all encyclopedias, is a tertiary source that relies on original reporting and research done by other media and scholars—is biased against conservatives.

The Heritage Foundation, the think tank behind the Project 2025 policy blueprint, has plans to unmask Wikipedia editors who maintain their privacy using pseudonyms (these usernames are displayed in the article history but don’t necessarily make it easy to identify the people behind them) and whose contributions on Israel it deems antisemitic…(More)”.

To Stop Tariffs, Trump Demands Opioid Data That Doesn’t Yet Exist


Article by Josh Katz and Margot Sanger-Katz: “One month ago, President Trump agreed to delay tariffs on Canada and Mexico after the two countries agreed to help stem the flow of fentanyl into the United States. On Tuesday, the Trump administration imposed the tariffs anyway, saying that the countries had failed to do enough — and claiming that tariffs would be lifted only when drug deaths fall.

But the administration has seemingly established an impossible standard. Real-time, national data on fentanyl overdose deaths does not exist, so there is no way to know whether Canada and Mexico were able to “adequately address the situation” since February, as the White House demanded.

“We need to see material reduction in autopsied deaths from opioids,” said Howard Lutnick, the commerce secretary, in an interview on CNBC on Tuesday, indicating that such a decline would be a precondition to lowering tariffs. “But you’ve seen it — it has not been a statistically relevant reduction of deaths in America.”

In a way, Mr. Lutnick is correct that there is no evidence that overdose deaths have fallen in the last month — since there is no such national data yet. His stated goal to measure deaths again in early April will face similar challenges.

But data through September shows that fentanyl deaths had already been falling at a statistically significant rate for months, causing overall drug deaths to drop at a pace unlike any seen in more than 50 years of recorded drug overdose mortality data.

The declines can be seen in provisional data from the Centers for Disease Control and Prevention, which compiles death records from states, which in turn collect data from medical examiners and coroners in cities and towns. Final national data generally takes more than a year to produce. But, as the drug overdose crisis has become a major public health emergency in recent years, the C.D.C. has been publishing monthly data, with some holes, at around a four-month lag…(More)”.

Commerce Secretary’s Comments Raise Fears of Interference in Federal Data


Article by Ben Casselman and Colby Smith: “Comments from a member of President Trump’s cabinet over the weekend have renewed concerns that the new administration could seek to interfere with federal statistics — especially if they start to show that the economy is slipping into a recession.

In an interview on Fox News on Sunday, Howard Lutnick, the commerce secretary, suggested that he planned to change the way the government reports data on gross domestic product in order to remove the impact of government spending.

“You know that governments historically have messed with G.D.P.,” he said. “They count government spending as part of G.D.P. So I’m going to separate those two and make it transparent.”

It wasn’t immediately clear what Mr. Lutnick meant. The basic definition of gross domestic product is widely accepted internationally and has been unchanged for decades. It tallies consumer spending, private-sector investment, net exports, and government investment and spending to arrive at a broad measure of all goods and services produced in a country.The Bureau of Economic Analysis, which is part of Mr. Lutnick’s department, already produces a detailed breakdown of G.D.P. into its component parts. Many economists focus on a measure — known as “final sales to private domestic purchasers” — that excludes government spending and is often seen as a better indicator of underlying demand in the economy. That measure has generally shown stronger growth in recent quarters than overall G.D.P. figures.

In recent weeks, however, there have been mounting signs elsewhere that the economy could be losing momentumConsumer spending fell unexpectedly in January, applications for unemployment insurance have been creeping upward, and measures of housing construction and home sales have turned down. A forecasting model from the Federal Reserve Bank of Atlanta predicts that G.D.P. could contract sharply in the first quarter of the year, although most private forecasters still expect modest growth.

Cuts to federal spending and the federal work force could act as a further drag on economic growth in coming months. Removing federal spending from G.D.P. calculations, therefore, could obscure the impact of the administration’s policies…(More)”.

AI could supercharge human collective intelligence in everything from disaster relief to medical research


Article by Hao Cui and Taha Yasseri: “Imagine a large city recovering from a devastating hurricane. Roads are flooded, the power is down, and local authorities are overwhelmed. Emergency responders are doing their best, but the chaos is massive.

AI-controlled drones survey the damage from above, while intelligent systems process satellite images and data from sensors on the ground and air to identify which neighbourhoods are most vulnerable.

Meanwhile, AI-equipped robots are deployed to deliver food, water and medical supplies into areas that human responders can’t reach. Emergency teams, guided and coordinated by AI and the insights it produces, are able to prioritise their efforts, sending rescue squads where they’re needed most.

This is no longer the realm of science fiction. In a recent paper published in the journal Patterns, we argue that it’s an emerging and inevitable reality.

Collective intelligence is the shared intelligence of a group or groups of people working together. Different groups of people with diverse skills, such as firefighters and drone operators, for instance, work together to generate better ideas and solutions. AI can enhance this human collective intelligence, and transform how we approach large-scale crises. It’s a form of what’s called hybrid collective intelligence.

Instead of simply relying on human intuition or traditional tools, experts can use AI to process vast amounts of data, identify patterns and make predictions. By enhancing human decision-making, AI systems offer faster and more accurate insights – whether in medical research, disaster response, or environmental protection.

AI can do this, by for example, processing large datasets and uncovering insights that would take much longer for humans to identify. AI can also get involved in physical tasks. In manufacturing, AI-powered robots can automate assembly lines, helping improve efficiency and reduce downtime.

Equally crucial is information exchange, where AI enhances the flow of information, helping human teams coordinate more effectively and make data-driven decisions faster. Finally, AI can act as social catalysts to facilitate more effective collaboration within human teams or even help build hybrid teams of humans and machines working alongside one another…(More)”.

China wants tech companies to monetize data, but few are buying in


Article by Lizzi C. Lee: “Chinese firms generate staggering amounts of data daily, from ride-hailing trips to online shopping transactions. A recent policy allowed Chinese companies to record data as assets on their balance sheets, the first such regulation in the world, paving the way for data to be traded in a marketplace and boost company valuations. 

But uptake has been slow. When China Unicom, one of the world’s largest mobile operators, reported its earnings recently, eagle-eyed accountants spotted that the company had listed 204 million yuan ($28 million) in data assets on its balance sheet. The state-owned operator was the first Chinese tech giant to take advantage of the Ministry of Finance’s new corporate data policy, which permits companies to classify data as inventory or intangible assets. 

“No other country is trying to do this on a national level. It could drive global standards of data management and accounting,” Ran Guo, an affiliated researcher at the Asia Society Policy Institute specializing in data governance in China, told Rest of World. 

In 2023 alone, China generated 32.85 zettabytes — more than 27% of the global total, according to a government survey. To put that in perspective, storing this volume on standard 1-terabyte hard drives would require more than 32 billion units….Tech companies that are data-rich are well-positioned tobenefit from logging data as assets to turn the formalized assets into tradable commodities, said Guo. But companies must first invest in secure storage and show that the data is legally obtained in order to meet strict government rules on data security. 

“This can be costly and complex,” he said. “Not all data qualifies as an asset, and companies must meet stringent requirements.” 

Even China Unicom, a state-owned enterprise, is likely complying with the new policy due to political pressure rather than economic incentive, said Guo, who conducted field research in China last year on the government push for data resource development. The telecom operator did not respond to a request for comment. 

Private technology companies in China, meanwhile, tend to be protective of their data. A Chinese government statement in 2022 pushed private enterprises to “open up their data.” But smaller firms could lack the resources to meet the stringent data storage and consumer protection standards, experts and Chinese tech company employees told Rest of World...(More)”.

Open Data Under Attack: How to Find Data and Why It Is More Important Than Ever


Article by Jessica Hilburn: “This land was made for you and me, and so was the data collected with our taxpayer dollars. Open data is data that is accessible, shareable, and able to be used by anyone. While any person, company, or organization can create and publish open data, the federal and state governments are by far the largest providers of open data.

President Barack Obama codified the importance of government-created open data in his May 9, 2013, executive order as a part of the Open Government Initiative. This initiative was meant to “ensure the public trust and establish a system of transparency, public participation, and collaboration” in furtherance of strengthening democracy and increasing efficiency. The initiative also launched Project Open Data (since replaced by the Resources.data.gov platform), which documented best practices and offered tools so government agencies in every sector could open their data and contribute to the collective public good. As has been made readily apparent, the era of public good through open data is now under attack.

Immediately after his inauguration, President Donald Trump signed a slew of executive orders, many of which targeted diversity, equity, and inclusion (DEI) for removal in federal government operations. Unsurprisingly, a large number of federal datasets include information dealing with diverse populations, equitable services, and inclusion of marginalized groups. Other datasets deal with information on topics targeted by those with nefarious agendas—vaccination rates, HIV/AIDS, and global warming, just to name a few. In the wake of these executive orders, datasets and website pages with blacklisted topics, tags, or keywords suddenly disappeared—more than 8,000 of them. In addition, President Trump fired the National Archivist, and top National Archives and Records Administration officials are being ousted, putting the future of our collective history at enormous risk.

While it is common practice to archive websites and information in the transition between administrations, it is unprecedented for the incoming administration to cull data altogether. In response, unaffiliated organizations are ramping up efforts to separately archive data and information for future preservation and access. Web scrapers are being used to grab as much data as possible, but since this method is automated, data requiring a login or bot challenger (like a captcha) is left behind. The future information gap that researchers will be left to grapple with could be catastrophic for progress in crucial areas, including weather, natural disasters, and public health. Though there are efforts to put out the fire, such as the federal order to restore certain resources, the people’s library is burning. The losses will be permanently felt…Data is a weapon, whether we like it or not. Free and open access to information—about democracy, history, our communities, and even ourselves—is the foundation of library service. It is time for anyone who continues to claim that libraries are not political to wake up before it is too late. Are libraries still not political when the Pentagon barred library access for tens of thousands of American children attending Pentagon schools on military bases while they examined and removed supposed “radical indoctrination” books? Are libraries still not political when more than 1,000 unique titles are being targeted for censorship annually, and soft censorship through preemptive restriction to avoid controversy is surely occurring and impossible to track? It is time for librarians and library workers to embrace being political.

In a country where the federal government now denies that certain people even exist, claims that children are being indoctrinated because they are being taught the good and bad of our nation’s history, and rescinds support for the arts, humanities, museums, and libraries, there is no such thing as neutrality. When compassion and inclusion are labeled the enemy and the diversity created by our great American experiment is lambasted as a social ill, claiming that libraries are neutral or apolitical is not only incorrect, it’s complicit. To update the quote, information is the weapon in the war of ideas. Librarians are the stewards of information. We don’t want to be the Americans who protested in 1933 at the first Nazi book burnings and then, despite seeing the early warning signs of catastrophe, retreated into the isolation of their own concerns. The people’s library is on fire. We must react before all that is left of our profession is ash…(More)”.

Combine AI with citizen science to fight poverty


Nature Editorial: “Of the myriad applications of artificial intelligence (AI), its use in humanitarian assistance is underappreciated. In 2020, during the COVID-19 pandemic, Togo’s government used AI tools to identify tens of thousands of households that needed money to buy food, as Nature reports in a News Feature this week. Typically, potential recipients of such payments would be identified when they apply for welfare schemes, or through household surveys of income and expenditure. But such surveys were not possible during the pandemic, and the authorities needed to find alternative means to help those in need. Researchers used machine learning to comb through satellite imagery of low-income areas and combined that knowledge with data from mobile-phone networks to find eligible recipients, who then received a regular payment through their phones. Using AI tools in this way was a game-changer for the country.Can AI help beat poverty? Researchers test ways to aid the poorest people

Now, with the pandemic over, researchers and policymakers are continuing to see how AI methods can be used in poverty alleviation. This needs comprehensive and accurate data on the state of poverty in households. For example, to be able to help individual families, authorities need to know about the quality of their housing, their children’s diets, their education and whether families’ basic health and medical needs are being met. This information is typically obtained from in-person surveys. However, researchers have seen a fall in response rates when collecting these data.

Missing data

Gathering survey-based data can be especially challenging in low- and middle-income countries (LMICs). In-person surveys are costly to do and often miss some of the most vulnerable, such as refugees, people living in informal housing or those who earn a living in the cash economy. Some people are reluctant to participate out of fear that there could be harmful consequences — deportation in the case of undocumented migrants, for instance. But unless their needs are identified, it is difficult to help them.Leveraging the collaborative power of AI and citizen science for sustainable development

Could AI offer a solution? The short answer is, yes, although with caveats. The Togo example shows how AI-informed approaches helped communities by combining knowledge of geographical areas of need with more-individual data from mobile phones. It’s a good example of how AI tools work well with granular, household-level data. Researchers are now homing in on a relatively untapped source for such information: data collected by citizen scientists, also known as community scientists. This idea deserves more attention and more funding.

Thanks to technologies such as smartphones, Wi-Fi and 4G, there has been an explosion of people in cities, towns and villages collecting, storing and analysing their own social and environmental data. In Ghana, for example, volunteer researchers are collecting data on marine litter along the coastline and contributing this knowledge to their country’s official statistics…(More)”.