Code Shift: Using AI to Analyze Zoning Reform in American Cities


Report by Arianna Salazar-Miranda & Emily Talen: “Cities are at the forefront of addressing global sustainability challenges, particularly those exacerbated by climate change. Traditional zoning codes, which often segregate land uses, have been linked to increased vehicular dependence, urban sprawl and social disconnection, undermining broader social and environmental sustainability objectives. This study investigates the adoption and impact of form-based codes (FBCs), which aim to promote sustainable, compact and mixed-use urban forms as a solution to these issues. Using natural language processing techniques, we analyzed zoning documents from over 2,000 United States census-designated places to identify linguistic patterns indicative of FBC principles. Our fndings reveal widespread adoption of FBCs across the country, with notable variations within regions. FBCs are associated with higher foor to area ratios, narrower and more consistent street setbacks and smaller plots. We also fnd that places with FBCs have improved walkability, shorter commutes and a higher share of multifamily housing. Our fndings highlight the utility of natural language processing for evaluating zoning codes and underscore the potential benefts of form-based zoning reforms for enhancing urban sustainability…(More)”.

Artificial Intelligence and the Future of Work


Report by National Academies of Sciences, Engineering, and Medicine: “Advances in artificial intelligence (AI) promise to improve productivity significantly, but there are many questions about how AI could affect jobs and workers.

Recent technical innovations have driven the rapid development of generative AI systems, which produce text, images, or other content based on user requests – advances which have the potential to complement or replace human labor in specific tasks, and to reshape demand for certain types of expertise in the labor market.

Artificial Intelligence and the Future of Work evaluates recent advances in AI technology and their implications for economic productivity, the workforce, and education in the United States. The report notes that AI is a tool with the potential to enhance human labor and create new forms of valuable work – but this is not an inevitable outcome. Tracking progress in AI and its impacts on the workforce will be critical to helping inform and equip workers and policymakers to flexibly respond to AI developments…(More)”.

‘We are flying blind’: RFK Jr.’s cuts halt data collection on abortion, cancer, HIV and more


Article by Alice Miranda Ollstein: “The federal teams that count public health problems are disappearing — putting efforts to solve those problems in jeopardy.

Health Secretary Robert F. Kennedy Jr.’s purge of tens of thousands of federal workers has halted efforts to collect data on everything from cancer rates in firefighters to mother-to-baby transmission of HIV and syphilis to outbreaks of drug-resistant gonorrhea to cases of carbon monoxide poisoning.

The cuts threaten to obscure the severity of pressing health threats and whether they’re getting better or worse, leaving officials clueless on how to respond. They could also make it difficult, if not impossible, to assess the impact of the administration’s spending and policies. Both outside experts and impacted employees argue the layoffs will cost the government more money in the long run by eliminating information on whether programs are effective or wasteful, and by allowing preventable problems to fester.

“Surveillance capabilities are crucial for identifying emerging health issues, directing resources efficiently, and evaluating the effectiveness of existing policies,” said Jerome Adams, who served as surgeon general in the first Trump’s administration. “Without robust data and surveillance systems, we cannot accurately assess whether we are truly making America healthier.”..(More)”.

Statistical methods in public policy research


Chapter by Andrew Heiss: “This essay provides an overview of statistical methods in public policy, focused primarily on the United States. I trace the historical development of quantitative approaches in policy research, from early ad hoc applications through the 19th and early 20th centuries, to the full institutionalization of statistical analysis in federal, state, local, and nonprofit agencies by the late 20th century.

I then outline three core methodological approaches to policy-centered statistical research across social science disciplines: description, explanation, and prediction, framing each in terms of the focus of the analysis. In descriptive work, researchers explore what exists and examine any variable of interest to understand their different distributions and relationships. In explanatory work, researchers ask why does it exist and how can it be influenced. The focus of the analysis is on explanatory variables (X) to either (1) accurately estimate their relationship with an outcome variable (Y), or (2) causally attribute the effect of specific explanatory variables on outcomes. In predictive work, researchers as what will happen next and focus on the outcome variable (Y) and on generating accurate forecasts, classifications, and predictions from new data. For each approach, I examine key techniques, their applications in policy contexts, and important methodological considerations.

I then consider critical perspectives on quantitative policy analysis framed around issues related to a three-part “data imperative” where governments are driven to count, gather, and learn from data. Each of these imperatives entail substantial issues related to privacy, accountability, democratic participation, and epistemic inequalities—issues at odds with public sector values of transparency and openness. I conclude by identifying some emerging trends in public sector-focused data science, inclusive ethical guidelines, open research practices, and future directions for the field…(More)”.

Trump Wants to Merge Government Data. Here Are 314 Things It Might Know About You.


Article by Emily Badger and Sheera Frenkel: “The federal government knows your mother’s maiden name and your bank account number. The student debt you hold. Your disability status. The company that employs you and the wages you earn there. And that’s just a start. It may also know your …and at least 263 more categories of data.These intimate details about the personal lives of people who live in the United States are held in disconnected data systems across the federal government — some at the Treasury, some at the Social Security Administration and some at the Department of Education, among other agencies.

The Trump administration is now trying to connect the dots of that disparate information. Last month, President Trump signed an executive order calling for the “consolidation” of these segregated records, raising the prospect of creating a kind of data trove about Americans that the government has never had before, and that members of the president’s own party have historically opposed.

The effort is being driven by Elon Musk, the world’s richest man, and his lieutenants with the Department of Government Efficiency, who have sought access to dozens of databases as they have swept through agencies across the federal government. Along the way, they have elbowed past the objections of career staff, data security protocols, national security experts and legal privacy protections…(More)”.

Developing countries are struggling to achieve their technology aims. Shared digital infrastructure is the answer


Article by Nii Simmonds: “The digital era offers remarkable prospects for both economic advancement and social development. Yet for emerging economies lacking energy, this potential often seems out of reach. The harsh truths of inconsistent electricity supply and scarce resources looms large over their digital ambitions. Nevertheless, a ray of hope shines through a strategy I call shared digital infrastructure (SDI). This cooperative model has the ability to turn these obstacles into opportunities for growth. By collaborating through regional country partnerships and bodies such as the Association of Southeast Asian Nations (ASEAN), the African Union (AU) and the Caribbean Community (CARICOM), these countries can harness the revolutionary power of digital technology, despite the challenges.

The digital economy is a critical driver of global GDP, with innovations in artificial intelligence, e-commerce and financial technology transforming industries at an unprecedented pace. At the heart of this transformation are data centres, which serve as the backbone of digital services, cloud computing and AI-driven applications. Yet many developing nations struggle to establish and maintain such facilities due to high energy costs, inadequate grid reliability and limited investment capital…(More)”.

Massive, Unarchivable Datasets of Cancer, Covid, and Alzheimer’s Research Could Be Lost Forever


Article by Sam Cole: “Almost two dozen repositories of research and public health data supported by the National Institutes of Health are marked for “review” under the Trump administration’s direction, and researchers and archivists say the data is at risk of being lost forever if the repositories go down. 

“The problem with archiving this data is that we can’t,” Lisa Chinn, Head of Research Data Services at the University of Chicago, told 404 Media. Unlike other government datasets or web pages, downloading or otherwise archiving NIH data often requires a Data Use Agreement between a researcher institution and the agency, and those agreements are carefully administered through a disclosure risk review process. 

A message appeared at the top of multiple NIH websites last week that says: “This repository is under review for potential modification in compliance with Administration directives.”

Repositories with the message include archives of cancer imagery, Alzheimer’s disease research, sleep studies, HIV databases, and COVID-19 vaccination and mortality data…

“So far, it seems like what is happening is less that these data sets are actively being deleted or clawed back and more that they are laying off the workers whose job is to maintain them, update them and maintain the infrastructure that supports them,” a librarian affiliated with the Data Rescue Project told 404 Media. “In time, this will have the same effect, but it’s really hard to predict. People don’t usually appreciate, much less our current administration, how much labor goes into maintaining a large research dataset.”…(More)”.

Europe’s GDPR privacy law is headed for red tape bonfire within ‘weeks’


Article by Ellen O’Regan: “Europe’s most famous technology law, the GDPR, is next on the hit list as the European Union pushes ahead with its regulatory killing spree to slash laws it reckons are weighing down its businesses.

The European Commission plans to present a proposal to cut back the General Data Protection Regulation, or GDPR for short, in the next couple of weeks. Slashing regulation is a key focus for Commission President Ursula von der Leyen, as part of an attempt to make businesses in Europe more competitive with rivals in the United States, China and elsewhere. 

The EU’s executive arm has already unveiled packages to simplify rules around sustainability reporting and accessing EU investment. The aim is for companies to waste less time and money on complying with complex legal and regulatory requirements imposed by EU laws…Seven years later, Brussels is taking out the scissors to give its (in)famous privacy law a trim.

There are “a lot of good things about GDPR, [and] privacy is completely necessary. But we don’t need to regulate in a stupid way. We need to make it easy for businesses and for companies to comply,” Danish Digital Minister Caroline Stage Olsen told reporters last week. Denmark will chair the work in the EU Council in the second half of 2025 as part of its rotating presidency.

The criticism of the GDPR echoes the views of former Italian Prime Minister Mario Draghi, who released a landmark economic report last September warning that Europe’s complex laws were preventing its economy from catching up with the United States and China. “The EU’s regulatory stance towards tech companies hampers innovation,” Draghi wrote, singling out the Artificial Intelligence Act and the GDPR…(More)”.

AI, Innovation and the Public Good: A New Policy Playbook


Paper by Burcu Kilic: “When Chinese start-up DeepSeek released R1 in January 2025, the groundbreaking open-source artificial intelligence (AI) model rocked the tech industry as a more cost-effective alternative to models running on more advanced chips. The launch coincided with industrial policy gaining popularity as a strategic tool for governments aiming to build AI capacity and competitiveness. Once dismissed under neoliberal economic frameworks, industrial policy is making a strong comeback with more governments worldwide embracing it to build digital public infrastructure and foster local AI ecosystems. This paper examines how the national innovation system framework can guide AI industrial policy to foster innovation and reduce reliance on dominant tech companies…(More)”.

DOGE comes for the data wonks


The Economist: “For nearly three decades the federal government has painstakingly surveyed tens of thousands of Americans each year about their health. Door-knockers collect data on the financial toll of chronic conditions like obesity and asthma, and probe the exact doses of medications sufferers take. The result, known as the Medical Expenditure Panel Survey (MEPS), is the single most comprehensive, nationally representative portrait of American health care, a balkanised and unwieldy $5trn industry that accounts for some 17% of GDP.

MEPS is part of a largely hidden infrastructure of government statistics collection now in the crosshairs of the Department of Government Efficiency (DOGE). In mid-March officials at a unit of the Department of Health and Human Services (HHS) that runs the survey told employees that DOGE had slated them for an 80-90% reduction in staff and that this would “not be a negotiation”. Since then scores of researchers have taken voluntary buyouts. Those left behind worry about the integrity of MEPS. “Very unclear whether or how we can put on MEPS” with roughly half of the staff leaving, one said. On March 27th, the health secretary, Robert F. Kennedy junior, announced an overall reduction of 10,000 personnel at the department, in addition to those who took buyouts.

There are scores of underpublicised government surveys like MEPS that document trends in everything from house prices to the amount of lead in people’s blood. Many provide standard-setting datasets and insights into the world’s largest economy that the private sector has no incentive to replicate.

Even so, America’s system of statistics research is overly analogue and needs modernising. “Using surveys as the main source of information is just not working” because it is too slow and suffers from declining rates of participation, says Julia Lane, an economist at New York University. In a world where the economy shifts by the day, the lags in traditional surveys—whose results can take weeks or even years to refine and publish—are unsatisfactory. One practical reform DOGE might encourage is better integration of administrative data such as tax records and social-security filings which often capture the entire population and are collected as a matter of course.

As in so many other areas, however, DOGE’s sledgehammer is more likely to cause harm than to achieve improvements. And for all its clunkiness, America’s current system manages a spectacular feat. From Inuits in remote corners of Alaska to Spanish-speakers in the Bronx, it measures the country and its inhabitants remarkably well, given that the population is highly diverse and spread out over 4m square miles. Each month surveys from the federal government reach about 1.5m people, a number roughly equivalent to the population of Hawaii or West Virginia…(More)”.