AI Is Evolving — And Changing Our Understanding Of Intelligence

Curated on Posted on by Stefaan Verhulst

Essay by Blaise Agüera y Arcas and James Manyika: “Dramatic advances in artificial intelligence today are compelling us to rethink our understanding of what intelligence truly is. Our new insights will enable us to build better AI and understand ourselves better.

In short, we are in paradigm-shifting territory.

Paradigm shifts are often fraught because it’s easier to adopt new ideas when they are compatible with one’s existing worldview but harder when they’re not. A classic example is the collapse of the geocentric paradigm, which dominated cosmological thought for roughly two millennia. In the geocentric model, the Earth stood still while the Sun, Moon, planets and stars revolved around us. The belief that we were at the center of the universe — bolstered by Ptolemy’s theory of epicycles, a major scientific achievement in its day — was both intuitive and compatible with religious traditions. Hence, Copernicus’s heliocentric paradigm wasn’t just a scientific advance but a hotly contested heresy and perhaps even, for some, as Benjamin Bratton notes, an existential trauma. So, today, artificial intelligence.

In this essay, we will describe five interrelated paradigm shifts informing our development of AI:

  1. Natural Computing — Computing existed in nature long before we built the first “artificial computers.” Understanding computing as a natural phenomenon will enable fundamental advances not only in computer science and AI but also in physics and biology.
  2. Neural Computing — Our brains are an exquisite instance of natural computing. Redesigning the computers that power AI so they work more like a brain will greatly increase AI’s energy efficiency — and its capabilities too.
  3. Predictive Intelligence — The success of large language models (LLMs) shows us something fundamental about the nature of intelligence: it involves statistical modeling of the future (including one’s own future actions) given evolving knowledge, observations and feedback from the past. This insight suggests that current distinctions between designing, training and running AI models are transitory; more sophisticated AI will evolve, grow and learn continuously and interactively, as we do.
  4. General Intelligence — Intelligence does not necessarily require biologically based computation. Although AI models will continue to improve, they are already broadly capable, tackling an increasing range of cognitive tasks with a skill level approaching and, in some cases, exceeding individual human capability. In this sense, “Artificial General Intelligence” (AGI) may already be here — we just keep shifting the goalposts.
  5. Collective Intelligence — Brains, AI agents and societies can all become more capable through increased scale. However, size alone is not enough. Intelligence is fundamentally social, powered by cooperation and the division of labor among many agents. In addition to causing us to rethink the nature of human (or “more than human”) intelligence, this insight suggests social aggregations of intelligences and multi-agent approaches to AI development that could reduce computational costs, increase AI heterogeneity and reframe AI safety debates.

But to understand our own “intelligence geocentrism,” we must begin by reassessing our assumptions about the nature of computing, since it is the foundation of both AI and, we will argue, intelligence in any form…(More)”.

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

Curated on Posted on by Stefaan Verhulst

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)”.

So You Want to Be a Dissident?

Curated on Posted on by Stefaan Verhulst

Essay by Julia Angwin and Ami Fields-Meyer: “…Heimans points to an increasingly hostile digital landscape as one barrier to effective grassroots campaigns. At the dawn of the digital era, in the two-thousands, e-mail transformed the field of political organizing, enabling groups like MoveOn.org to mobilize huge campaigns against the Iraq War, and allowing upstart candidates like Howard Dean and Barack Obama to raise money directly from people instead of relying on Party infrastructure. But now everyone’s e-mail inboxes are overflowing. The tech oligarchs who control the social-media platforms are less willing to support progressive activism. Globally, autocrats have more tools to surveil and disrupt digital campaigns. And regular people are burned out on actions that have failed to remedy fundamental problems in society.

It’s not clear what comes next. Heimans hopes that new tactics will be developed, such as, perhaps, a new online platform that would help organizing, or the strengthening of a progressive-media ecosystem that will engage new participants. “Something will emerge that kind of revitalizes the space.”

There’s an oft-told story about Andrei Sakharov, the celebrated twentieth-century Soviet activist. Sakharov made his name working as a physicist on the development of the U.S.S.R.’s hydrogen bomb, at the height of the Cold War, but shot to global prominence after Leonid Brezhnev’s regime punished him for speaking publicly about the dangers of those weapons, and also about Soviet repression.

When an American friend was visiting Sakharov and his wife, the activist Yelena Bonner, in Moscow, the friend referred to Sakharov as a dissident. Bonner corrected him: “My husband is a physicist, not a dissident.”

This is a fundamental tension of building a principled dissident culture—it risks wrapping people up in a kind of negative identity, a cloak of what they are not. The Soviet dissidents understood their work as a struggle to uphold the laws and rights that were enshrined in the Soviet constitution, not as a fight against a regime.

“They were fastidious about everything they did being consistent with Soviet law,” Benjamin Nathans, a history professor at the University of Pennsylvania and the author of a book on Soviet dissidents, said. “I call it radical civil obedience.”

An affirmative vision of what the world should be is the inspiration for many of those who, in these tempestuous early months of Trump 2.0, have taken meaningful risks—acts of American dissent.

Consider Mariann Budde, the Episcopal bishop who used her pulpit before Trump on Inauguration Day to ask the President’s “mercy” for two vulnerable groups for whom he has reserved his most visceral disdain. For her sins, a congressional ally of the President called for the pastor to be “added to the deportation list.”..(More)”.

The Future of Health Is Preventive — If We Get Data Governance Right

Curated on Posted on by Stefaan Verhulst

Article by Stefaan Verhulst: “After a long gestation period of three years, the European Health Data Space (EHDS) is now coming into effect across the European Union, potentially ushering in a new era of health data access, interoperability, and innovation. As this ambitious initiative enters the implementation phase, it brings with it the opportunity to fundamentally reshape how health systems across Europe operate. More generally, the EHDS contains important lessons (and some cautions) for the rest of the world, suggesting how a fragmented, reactive model of healthcare may transition to one that is more integrated, proactive, and prevention-oriented.

For too long, health systems–in the EU and around the world–have been built around treating diseases rather than preventing them. Now, we have an opportunity to change that paradigm. Data, and especially the advent of AI, give us the tools to predict and intervene before illness takes hold. Data offers the potential for a system that prioritizes prevention–one where individuals receive personalized guidance to stay healthy, policymakers access real-time evidence to address risks before they escalate, and epidemics are predicted weeks in advance, enabling proactive, rapid, and highly effective responses.

But to make AI-powered preventive health care a reality, and to make the EHDS a success, we need a new data governance approach, one that would include two key components:

  • The ability to reuse data collected for other purposes (e.g., mobility, retail sales, workplace trends) to improve health outcomes.
  • The ability to integrate different data sources–clinical records and electronic health records (EHRS), but also environmental, social, and economic data — to build a complete picture of health risks.

In what follows, we outline some critical aspects of this new governance framework, including responsible data access and reuse (so-called secondary use), moving beyond traditional consent models to a social license for reuse, data stewardship, and the need to prioritize high-impact applications. We conclude with some specific recommendations for the EHDS, built from the preceding general discussion about the role of AI and data in preventive health…(More)”.

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

Curated on Posted on by Stefaan Verhulst

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)”.

We Must Steward, Not Subjugate Nor Worship AI

Curated on Posted on by Stefaan Verhulst

Essay by Brian J. A. Boyd: “…How could stewardship of artificially living AI be pursued on a broader, even global, level? Here, the concept of “integral ecology” is helpful. Pope Francis uses the phrase to highlight the ways in which everything is connected, both through the web of life and in that social, political, and environmental challenges cannot be solved in isolation. The immediate need for stewardship over AI is to ensure that its demands for power and industrial production are addressed in a way that benefits those most in need, rather than de-prioritizing them further. For example, the energy requirements to develop tomorrow’s AI should spur research into small modular nuclear reactors and updated distribution systems, making energy abundant rather than causing regressive harms by driving up prices on an already overtaxed grid. More broadly, we will need to find the right institutional arrangements and incentive structures to make AI Amistics possible.

We are having a painfully overdue conversation about the nature and purpose of social media, and tech whistleblowers like Tristan Harris have offered grave warnings about how the “race to the bottom of the brain stem” is underway in AI as well. The AI equivalent of the addictive “infinite scroll” design feature of social media will likely be engagement with simulated friends — but we need not resign ourselves to it becoming part of our lives as did social media. And as there are proposals to switch from privately held Big Data to a public Data Commons, so perhaps could there be space for AI that is governed not for maximizing profit but for being sustainable as a common-pool resource, with applications and protocols ordered toward long-run benefit as defined by local communities…(More)”.

Why more AI researchers should collaborate with governments

Curated on Posted on by Stefaan Verhulst

Article by Mohamed Ibrahim: “Artificial intelligence (AI) is beginning to transform many industries, yet its use to improve public services remains limited globally. AI-based tools could streamline access to government benefits through online chatbots or automate systems by which citizens report problems such as potholes.

Currently, scholarly advances in AI are mostly confined to academic papers and conferences, rarely translating into actionable government policies or products. This means that the expertise at universities is not used to solve real-world problems. As a No10 Innovation Fellow with the UK government and a lecturer in spatial data science, I have explored the potential of AI-driven rapid prototyping in public policy.

Take Street.AI, a prototype smartphone app that I developed, which lets citizens report issues including potholes, street violence or illegal litter dumping by simply taking a picture through the app. The AI model classifies the problem automatically and alerts the relevant local authority, passing on the location and details of the issue. A key feature of the app is its on-device processing, which ensures privacy and reduces operational costs. Similar tools were tested as an early-warning system during the riots that swept the United Kingdom in July and August 2024.

AI models can also aid complex decision-making — for instance, that involved in determining where to build houses. The UK government plans to construct 1.5 million homes in the next 5 years, but planning laws require that several parameters be considered — such as proximity to schools, noise levels, the neighbourhoods’ built-up ratio and flood risk. The current strategy is to compile voluminous academic reports on viable locations, but an online dashboard powered by AI that can optimize across parameters would be much more useful to policymakers…(More)”.

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

Curated on Posted on by Stefaan Verhulst

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)”.

Exploring Human Mobility in Urban Nightlife: Insights from Foursquare Data

Curated on Posted on by Stefaan Verhulst

Article by Ehsan Dorostkar: “In today’s digital age, social media platforms like Foursquare provide a wealth of data that can reveal fascinating insights into human behavior, especially in urban environments. Our recent study, published in Cities, delves into how virtual mobility on Foursquare translates into actual human mobility in Tehran’s nightlife scenes. By analyzing user-generated data, we uncovered patterns that can help urban planners create more vibrant and functional nightlife spaces…

Our study aimed to answer two key questions:

  1. How does virtual mobility on Foursquare influence real-world human mobility in urban nightlife?
  2. What spatial patterns emerge from these movements, and how can they inform urban planning?

To explore these questions, we focused on two bustling nightlife spots in Tehran—Region 1 (Darband Square) and Region 6 (Valiasr crossroads)—where Foursquare data indicated high user activity.

Methodology

We combined data from two sources:

  1. Foursquare API: To track user check-ins and identify popular nightlife venues.
  2. Tehran Municipality API: To contextualize the data within the city’s urban framework.

Using triangulation and interpolation techniques, we mapped the “human mobility triangles” in these areas, calculating the density and spread of user activity…(More)”.

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

Curated on Posted on by Stefaan Verhulst

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)”.