Fixing the US statistical infrastructure

Curated on Posted on by Stefaan Verhulst

Article by Nancy Potok and Erica L. Groshen: “Official government statistics are critical infrastructure for the information age. Reliable, relevant, statistical information helps businesses to invest and flourish; governments at the local, state, and national levels to make critical decisions on policy and public services; and individuals and families to invest in their futures. Yet surrounded by all manner of digitized data, one can still feel inadequately informed. A major driver of this disconnect in the US context is delayed modernization of the federal statistical system. The disconnect will likely worsen in coming months as the administration shrinks statistical agencies’ staffing, terminates programs (notably for health and education statistics), and eliminates unpaid external advisory groups. Amid this upheaval, might the administration’s appetite for disruption be harnessed to modernize federal statistics?

Federal statistics, one of the United States’ premier public goods, differ from privately provided data because they are privacy protected, aggregated to address relevant questions for decision-makers, constructed transparently, and widely available without a subscription. The private sector cannot be expected to adequately supply such statistical infrastructure. Yes, some companies collect and aggregate some economic data, such as credit card purchases and payroll information. But without strong underpinnings of a modern, federal information infrastructure, there would be large gaps in nationally consistent, transparent, trustworthy data. Furthermore, most private providers rely on public statistics for their internal analytics, to improve their products. They are among the many data users asking for more from statistical agencies…(More)”.

Sentinel Cities for Public Health

Curated on Posted on by Stefaan Verhulst

Article by Jesse Rothman, Paromita Hore & Andrew McCartor: “In 2017, a New York City health inspector visited the home of a 5-year-old child with an elevated blood lead level. With no sign of lead paint—the usual suspect in such cases—the inspector discovered dangerous levels of lead in a bright yellow container of “Georgian Saffron,” a spice obtained in the family’s home country. It was not the first case associated with the use of lead-containing Georgian spices—the NYC Health Department shared their findings with authorities in Georgia, which catalyzed a survey of children’s blood lead levels in Georgia, and led to increased regulatory enforcement and education. Significant declines in spice lead levels in the country have had ripple effects in NYC also: not only a drop in spice samples from Georgia containing detectable lead but also a significant reduction in blood lead levels among NYC children of Georgian ancestry.

This wasn’t a lucky break—it was the result of a systematic approach to transform local detection into global impact. Findings from local NYC surveillance are, of course, not limited to Georgian spices. Surveillance activities have identified a variety of lead-containing consumer products from around the world, from cosmetics and medicines to ceramics and other goods. Routinely surveying local stores for lead-containing products has resulted in the removal of over 30,000 hazardous consumer products from NYC store shelves since 2010.

How can we replicate and scale up NYC’s model to address the global crisis of lead poisoning?…(More)”.

AI alone cannot solve the productivity puzzle

Curated on Posted on by Stefaan Verhulst

Article by Carl Benedikt Frey: “Each time fears of AI-driven job losses flare up, optimists reassure us that artificial intelligence is a productivity tool that will help both workers and the economy. Microsoft chief Satya Nadella thinks autonomous AI agents will allow users to name their goal while the software plans, executes and learns across every system. A dream tool — if efficiency alone was enough to solve the productivity problem.

History says it is not. Over the past half-century we have filled offices and pockets with ever-faster computers, yet labour-productivity growth in advanced economies has slowed from roughly 2 per cent a year in the 1990s to about 0.8 per cent in the past decade. Even China’s once-soaring output per worker has stalled.

The shotgun marriage of the computer and the internet promised more than enhanced office efficiency — it envisioned a golden age of discovery. By placing the world’s knowledge in front of everyone and linking global talent, breakthroughs should have multiplied. Yet research productivity has sagged. The average scientist now produces fewer breakthrough ideas per dollar than their 1960s counterpart.

What went wrong? As economist Gary Becker once noted, parents face a quality-versus-quantity trade-off: the more children they have, the less they can invest in each child. The same might be said for innovation.

Large-scale studies of inventive output confirm the result: researchers juggling more projects are less likely to deliver breakthrough innovations. Over recent decades, scientific papers and patents have become increasingly incremental. History’s greats understood why. Isaac Newton kept a single problem “constantly before me . . . till the first dawnings open slowly, by little and little, into a full and clear light”. Steve Jobs concurred: “Innovation is saying no to a thousand things.”

Human ingenuity thrives where precedent is thin. Had the 19th century focused solely on better looms and ploughs, we would enjoy cheap cloth and abundant grain — but there would be no antibiotics, jet engines or rockets. Economic miracles stem from discovery, not repeating tasks at greater speed.

Large language models gravitate towards the statistical consensus. A model trained before Galileo would have parroted a geocentric universe; fed 19th-century texts it would have proved human flight impossible before the Wright brothers succeeded. A recent Nature review found that while LLMs lightened routine scientific chores, the decisive leaps of insight still belonged to humans. Even Demis Hassabis, whose team at Google DeepMind produced AlphaFold — a model that can predict the shape of a protein and is arguably AI’s most celebrated scientific feat so far — admits that achieving genuine artificial general intelligence systems that can match or surpass humans across the full spectrum of cognitive tasks may require “several more innovations”…(More)”.

5 Ways AI is Boosting Citizen Engagement in Africa’s Democracies

Curated on Posted on by Stefaan Verhulst

Article by Peter Agbesi Adivor: “Artificial Intelligence (AI) is increasingly influencing democratic participation across Africa. From campaigning to voter education, AI is transforming electoral processes across the continent. While concerns about misinformation and government overreach persist, AI also offers promising avenues to enhance citizen engagement. This article explores five key ways AI is fostering more inclusive and participatory democracies in Africa.

1. AI-Powered Voter Education and Campaign

AI-driven platforms are revolutionizing voter education by providing accessible, real-time information. These platforms ensure citizens receive standardized electoral information delivered to them on their digital devices regardless of their geographical location, significantly reducing the cost for political actors as well as state and non-state actors who focus on voter education. They also ensure that those who can navigate these tools easily access the needed information, allowing authorities to focus limited resources on citizens on the other side of the digital divide.

 In Nigeria, ChatVE developed CitiBot, an AI-powered chatbot deployed during the 2024 Edo State elections to educate citizens on their civic rights and responsibilities via WhatsApp and Telegram. The bot offered information on voting procedures, eligibility, and the importance of participation.

Similarly, in South Africa, the Rivonia Circle introduced Thoko the Bot, an AI chatbot designed to answer voters’ questions about the electoral process, including where and how to vote, and the significance of participating in elections.

These AI tools enhance voter understanding and engagement by providing personalized, easily accessible information, thereby encouraging greater participation in democratic processes…(More)”.

5 Ways AI Supports City Adaptation to Extreme Heat

Curated on Posted on by Stefaan Verhulst

Article by Urban AI: “Cities stand at the frontline of climate change, confronting some of its most immediate and intense consequences. Among these, extreme heat has emerged as one of the most pressing and rapidly escalating threats. As we enter June 2025, Europe is already experiencing its first major and long-lasting heatwave of the summer season with temperatures surpassing 40°C in parts of Spain, France, and Portugal — and projections indicate that this extreme event could persist well into mid-June.

This climate event is not an isolated incident. By 2050, the number of cities exposed to dangerous levels of heat is expected to triple, with peak temperatures of 48°C (118°F) potentially becoming the new normal in some regions. Such intensifying conditions place unprecedented stress on urban infrastructure, public health systems, and the overall livability of cities — especially for vulnerable communities.

In this context, Artificial Intelligence (AI) is emerging as a vital tool in the urban climate adaptation toolbox. Urban AI — defined as the application of AI technologies to urban systems and decision-making — can help cities anticipate, manage, and mitigate the effects of extreme heat in more targeted and effective ways.

Cooling the Metro with AI-Driven Ventilation, in Barcelona

With over 130 stations and a century-old metro network, the city of Barcelona faces increasing pressure to ensure passenger comfort and safety — especially underground, where heat and air quality are harder to manage. In response, Transports Metropolitans de Barcelona (TMB), in partnership with SENER Engineering, developed and implemented the RESPIRA® system, an AI-powered ventilation control platform. First introduced in 2020 on Line 1, RESPIRA® demonstrated its effectiveness by lowering ambient temperatures, improving air circulation during the COVID-19 pandemic, and achieving a notable 25.1% reduction in energy consumption along with a 10.7% increase in passenger satisfaction…(More)”

Beyond the Checkbox: Upgrading the Right to Opt Out

Curated on Posted on by Stefaan Verhulst

Article by Sebastian Zimmeck: “…rights, as currently encoded in privacy laws, put too much onus on individuals when many privacy problems are systematic.5 Indeed, privacy is a systems property. If we want to make progress toward a more privacy-friendly Web as well as mobile and smart TV platforms, we need to take a systems perspective. For example, instead of requiring people to opt out from individual websites, there should be opt-out settings in browsers and operating systems. If a law requires individual opt-outs, those can be generalized by applying one opt-out toward all future sites visited or apps used, if a user so desires.8

Another problem is that the ad ecosystem is structured such that if people opt out, in many cases, their data is still being shared just as if they would not have opted out. The only difference is that in the latter case the data is accompanied by a privacy flag propagating the opt-out to the data recipient.7 However, if people opt out, their data should not be shared in the first place! The current system relying on the propagation of opt-out signals and deletion of incoming data by the recipient is complicated, error-prone, violates the principle of data minimization, and is an obstacle for effective privacy enforcement. Changing the ad ecosystem is particularly important as it is not only used on the web but also on many other platforms. Companies and the online ad industry as a whole need to do better!..(More)”

Can AI Agents Be Trusted?

Curated on Posted on by Stefaan Verhulst

Article by Blair Levin and Larry Downes: “Agentic AI has quickly become one of the most active areas of artificial intelligence development. AI agents are a level of programming on top of large language models (LLMs) that allow them to work towards specific goals. This extra layer of software can collect data, make decisions, take action, and adapt its behavior based on results. Agents can interact with other systems, apply reasoning, and work according to priorities and rules set by you as the principal.

Companies such as Salesforce have already deployed agents that can independently handle customer queries in a wide range of industries and applications, for example, and recognize when human intervention is required.

But perhaps the most exciting future for agentic AI will come in the form of personal agents, which can take self-directed action on your behalf. These agents will act as your personal assistant, handling calendar management, performing directed research and analysis, finding, negotiating for, and purchasing goods and services, curating content and taking over basic communications, learning and optimizing themselves along the way.

The idea of personal AI agents goes back decades, but the technology finally appears ready for prime-time. Already, leading companies are offering prototype personal AI agents to their customers, suppliers, and other stakeholders, raising challenging business and technical questions. Most pointedly: Can AI agents be trusted to act in our best interests? Will they work exclusively for us, or will their loyalty be split between users, developers, advertisers, and service providers? And how will be know?

The answers to these questions will determine whether and how quickly users embrace personal AI agents, and if their widespread deployment will enhance or damage business relationships and brand value…(More)”.

What World Does Bitcoin Want To Build For Itself?

Curated on Posted on by Stefaan Verhulst

Article by Patrick Redford: “We often talk about baseball games as a metric for where we are, and we’re literally in the first inning,” one of the Winklevoss twins gloats. “And this game’s going to overtime.”

It’s the first day of Bitcoin 2025, industry day here at the largest cryptocurrency conference in the world. This Winklevoss is sharing the stage with the other one, plus Donald Trump’s newly appointed crypto and AI czar David Sacks. They are in the midst of a victory lap, laughing with the free ease of men who know they have it made. The mangled baseball metaphor neither lands nor elicits laughs, but that’s fine. He’s earned, or at any rate acquired, the right to be wrong.

This year’s Bitcoin Conference takes place amid a boom, the same month the price of a single coin stabilized above $100,000 for the first time. More than 35,000 people have descended on Las Vegas in the final week of May for the conference: bitcoin miners, bitcoin dealers, several retired athletes, three U.S. senators, two Trump children, one U.S. vice president, people who describe themselves as “content creators,” people who describe themselves as “founders,” venture capitalists, ex-IDF bodyguards, tax-dodging experts, crypto heretics, evangelists, paladins, Bryan Johnson, Eric Adams, and me, trying to figure out what they were all doing there together. I’m in Vegas talking to as many people as I can in order to conduct an assay of the orange pill. What is the argument for bitcoin, exactly? Who is making it, and why?

Here is the part of the story where I am supposed to tell you it’s all a fraud. I am supposed to point out that nobody has come up with a use case for blockchain technology in 17 years beyond various forms of money laundering; that half of these people have been prosecuted for one financial crime or another; that the game is rigged in favor of the casino and those who got there before you; that this is an onerous use of energy; that all the mystification around bitcoin is a fog intended to draw in suckers where they can be bled. All that stuff is true, but the trick is that being true isn’t quite the same thing as mattering.

The bitcoin people are winning…(More)”

The path for AI in poor nations does not need to be paved with billions

Curated on Posted on by Stefaan Verhulst

Editorial in Nature: “Coinciding with US President Donald Trump’s tour of Gulf states last week, Saudi Arabia announced that it is embarking on a large-scale artificial intelligence (AI) initiative. The proposed venture will have state backing and considerable involvement from US technology firms. It is the latest move in a global expansion of AI ambitions beyond the existing heartlands of the United States, China and Europe. However, as Nature India, Nature Africa and Nature Middle East report in a series of articles on AI in low- and middle-income countries (LMICs) published on 21 May (see go.nature.com/45jy3qq), the path to home-grown AI doesn’t need to be paved with billions, or even hundreds of millions, of dollars, or depend exclusively on partners in Western nations or China…, as a News Feature that appears in the series makes plain (see go.nature.com/3yrd3u2), many initiatives in LMICs aren’t focusing on scaling up, but on ‘scaling right’. They are “building models that work for local users, in their languages, and within their social and economic realities”.

More such local initiatives are needed. Some of the most popular AI applications, such as OpenAI’s ChatGPT and Google Gemini, are trained mainly on data in European languages. That would mean that the model is less effective for users who speak Hindi, Arabic, Swahili, Xhosa and countless other languages. Countries are boosting home-grown apps by funding start-up companies, establishing AI education programmes, building AI research and regulatory capacity and through public engagement.

Those LMICs that have started investing in AI began by establishing an AI strategy, including policies for AI research. However, as things stand, most of the 55 member states of the African Union and of the 22 members of the League of Arab States have not produced an AI strategy. That must change…(More)”.

Europe’s dream to wean off US tech gets reality check

Curated on Posted on by Stefaan Verhulst

Article by Pieter Haeck and Mathieu Pollet: “..As the U.S. continues to up the ante in questioning transatlantic ties, calls are growing in Europe to reduce the continent’s reliance on U.S. technology in critical areas such as cloud services, artificial intelligence and microchips, and to opt for European alternatives instead.

But the European Commission is preparing on Thursday to acknowledge publicly what many have said in private: Europe is nowhere near being able to wean itself off U.S. Big Tech.

In a new International Digital Strategy the EU will instead promote collaboration with the U.S., according to a draft seen by POLITICO, as well as with other tech players including China, Japan, India and South Korea. “Decoupling is unrealistic and cooperation will remain significant across the technological value chain,” the draft reads. 

It’s a reality check after a year that has seen calls for a technologically sovereign Europe gain significant traction. In December the Commission appointed Finland’s Henna Virkkunen as the first-ever commissioner in charge of tech sovereignty. After few months in office, European Parliament lawmakers embarked on an effort to draft a blueprint for tech sovereignty. 

Even more consequential has been the rapid rise of the so-called Eurostack movement, which advocates building out a European tech infrastructure and has brought together effective voices including competition economist Cristina Caffarra and Kai Zenner, an assistant to key European lawmaker Axel Voss.

There’s wide agreement on the problem: U.S. cloud giants capture over two-thirds of the European market, the U.S. outpaces the EU in nurturing companies for artificial intelligence, and Europe’s stake in the global microchips market has crumbled to around 10 percent. Thursday’s strategy will acknowledge the U.S.’s “superior ability to innovate” and “Europe’s failure to capitalise on the digital revolution.”

What’s missing are viable solutions to the complex problem of unwinding deep-rooted dependencies….(More)”