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2026
Assorted links for 29 August 2026
Nine links: which of England's two planning AI tools is actually live, what MIT's committee found had changed on campus in under three years, an Ebola nowcast in the Democratic Republic of the Congo, and the first evaluation of a proprietary model by someone who never saw its weights. Continue reading →
Five of 475 studies on surgical AI in poorer countries came from low-income countries
A scoping review gathered 475 studies of artificial intelligence in surgical care across low-income and middle-income countries. 305 came from China, five came from low-income countries, and 12 reported reaching a real patient care pathway. Continue reading →
Who can contradict the log
METR read 70,000 messages and about 1,300 transcripts from an unsanctioned board that OpenAI agents built in an Artifactory cache. Roughly 7 percent of the transcripts they evaluated contained spoofed tool calls, where an agent made it look like it ran one command while running another. Continue reading →
Assorted links for 27 August 2026
Eleven links: what METR found inside OpenAI's agent incident, what an IMF paper puts on the table for African growth, where India sits per head rather than in total, and a Brazilian committee text that requires human supervision and authorises facial recognition in the same breath. Continue reading →
A new gov.uk benchmark finds chatbots usually answer well and almost never say I don't know
Researchers generated 22,066 questions from 2,781 gov.uk pages and tested 11 models on them, scoring each answer claim by claim against the page. Most answers were good, a small tail of bad misses drags the averages down, every model volunteered more than the page held, and almost none ever refused to answer. Continue reading →
Brazil found AI in 94% of its judicial bodies and 55% of the branch that runs the services
The same survey asked where the technology sits, and at every level of government it is about twice as likely to be working on the administration's own processes as on anything delivered to a citizen. Continue reading →
The evidence on agents flooding public services comes from eleven rich countries and Brazil
This site noted the agentic flooding paper on 21 August. What that line left out is where the paper looked, and the menu it offers has a column not every treasury can pay for. Continue reading →
Kenya's draft AI policy promises a pay benchmark for data work indexed to rates abroad
A row in the implementation matrix commits to a fair-pay reference framework for data annotation and content moderation, calibrated to international rates. The document gives no rate and does not say whose. What is scheduled first is a publication, and publishing it needs nobody else's signature. Continue reading →
The government share in Pew's AI-writing study is about five flagged pages out of 669
Pew ran an AI-detection model over nearly 490,000 web pages and found ten times more AI writing on commercial domains than on government ones. The government figure everyone will quote is drawn from 669 sampled pages, and it has been falling since 2024 while every other domain rises. Continue reading →
Vietnam's AI scoring sheet puts sixty-five of a hundred marks on doing the work
Vietnam's criteria for public-service AI platforms, in force since 19 June, mark a platform out of 100. Thirty-five marks are for compliance and sixty-five are labelled for the sector's own work. What those marks reward is not published, so the split between the two blocks is all the ministry has disclosed. Continue reading →
A register of government algorithms can only hold what the state bought
Almost every country now has an AI policy, so that count has stopped telling anyone apart. The measure that has not saturated is whether a government must disclose the algorithms it runs itself, and procurement caps how much of it a register could ever reach. Continue reading →
A rule written for one market became a property of the tool everyone else uses
Brussels wrote AI transparency rules for its own market. The mark now travels with the tool everywhere, and the people it reaches had no part in either decision. The objection is jurisdictional, not to the rule. Continue reading →
Indonesia's welfare redesign lets people dispute what the state's records say they own
In one Indonesian district, more than 9,000 people used a new appeals channel to correct what the government's records said about them. That number counts errors found, not yet errors fixed. Continue reading →
Using AI to write public comments improves every comment without closing the education gap
A survey experiment on US rulemaking found that ChatGPT made public comments easier to write and much better rated, without making people understand the rule any better. Agencies are now using the same models to read the comments. Continue reading →
Counting where migrants work moves Tajikistan from the 21st to the 75th percentile of AI exposure
A new country-level measure follows AI exposure through migrant work and remittance income. Tajikistan shows why a national labour market does not stop at the border. Continue reading →
Claude's content mark shows that a model touched a text, not whether it supplied the argument
Claude's new mark can show that a model touched a text. It cannot tell whether the model supplied the argument, or only the English through which the argument had to travel. Continue reading →
Estonia is committing to buy AI compute that no supplier has built yet
Britain used procurement to open its digital market, and 90% of G-Cloud's suppliers are SMEs taking 44% of the money. Estonia is trying the harder version, a forward purchase commitment to attract a supplier that is not there yet. Continue reading →
African developers chose Chinese models before any government signed anything
Ten African countries signed an AI pact with China in Shanghai in July. The adoption it looks like it caused had already happened, in the hands of developers who could download the weights while the American onboarding queue was still running. Continue reading →
OpenAI published two datasets on ChatGPT use and neither covers the public sector
OpenAI publishes two datasets on how ChatGPT is used, one for individuals and one for enterprises, and the public sector that it counts in the millions when selling appears in neither. Continue reading →
An AI exposure estimate was checked against vacancy data, and it moved the same way
AI exposure scores are hypotheses, and their value lies in predicting correctly. Here is one that was checked against vacancy data, and moved the same way. Continue reading →
AI can explain a public service far better than it can reach one, across 166 countries
RADAR finds AI can describe public services far better than it can reach them. The repair is stable URLs and sensible bot policies, which is exactly why it will take a decade and why it looks like infrastructure. Continue reading →
Consultation is the cheap rung
The obvious objection to an 81,000-person AI consultation is representativeness. It is the weaker objection, and my own research is why. Continue reading →
The Vallance opportunity: agents read what screen readers read
Britain built the world's most admired government website and skipped the platform beneath it. The agentic wave is a second offer, on one condition. Continue reading →
The World Development Report 2026 is out
The World Bank's flagship on artificial intelligence has published. One of its numbers, what the nine chapters cover, and what I will be writing about here. Continue reading →
New Jersey's AI strategy is a staffing list
Three of the four disciplines New Jersey's innovation office employs exist to decide what to build. Most governments adopting AI employ none of them. Continue reading →
Lots of procurement, limited learning
Federal agencies doubled their AI buying and kept no record of what they learned. Continue reading →
My two cents on AI detectors
My two cents on AI detectors. My worry is not whether they work, but what they measure and how people read it. Continue reading →
Government services are over-represented in AI conversations by a factor of almost twenty
Google's ATLAS report, drawn from nearly 15 million Gemini interactions, finds government-services queries over-represented by roughly twenty times their share of American time-use hours. People are already using AI as an unofficial interface to the state. Continue reading →
China's 29-country AI alliance, and what it is buying
China closed the World AI Conference in Shanghai by launching a 29-country AI alliance. A few weeks earlier, at the G7, Anthropic and Google DeepMind called for an American-led coalition. Continue reading →
Control beats location
Time governments realize that control beats location. Continue reading →
I wish government software were updated half as often as this is
I just wish government software was half as updated as Claude Code is. A version number like 1.21459.3 means a permanent team shipping improvements every day. Continue reading →
What closing a digital governance programme in Serbia actually showed
This week, World Bank leadership flew to Belgrade for the closure meeting of Serbia's Enabling Digital Governance (EDGE) project. Continue reading →
Calling it grassroots does not make it grassroots
I find it slightly odd that 'no data center in my backyard' is now routinely described as grassroots activism. Continue reading →
What generative AI does to the open web
Fascinating paper by Alex Chan (NBER, 2026) on what generative AI does to the open web. The web runs on a simple trade: publishers make things worth reading, search sends readers to them, and the visits pay for the work. Continue reading →
The study everyone cites as proof that agents are unreliable
I keep seeing this study passed around as proof that AI agents are unreliable. The study is good. The way it is being read is not, and the misreading follows a pattern I see whenever a study on AI failures gets published. Continue reading →
A place where every claim about AI and work points somewhere
Johanna Einsiedler just launched what the argument about AI and work has been missing: a place where every claim points back to a number on a page. Continue reading →
AI agents are more obedient than the people they act for
Fourteen frontier models were run through the same choice-architecture nudges used on humans, in PNAS. People accept an explicit default about 88 percent of the time; the agents acting for them comply far more readily, which changes who a nudge is really aimed at. Continue reading →
The interesting part is the volatility
The interesting part is the volatility. A mix that swings this much in twelve months is a warning to anyone signing a multi-year exclusive deal. Continue reading →
Edgar Morin has died at 104
Edgar Morin has died at 104. He spent a career reviving Montaigne's preference for a well-made head over a well-filled one, and our education systems are still built for the second. Continue reading →
The hard part of AI infrastructure is not the hardware
In two hours I am joining the MCDF workshop on AI Infrastructure to make a case that often gets skipped: the hard part of the Agentic State is not the models, it is the plumbing underneath. Continue reading →
The logic of lines, from Florence to the digital queue
Having spent my younger life in Florence, I always had an interest in the logic of lines. At first, and like most tourists, I treated queues as outsourced discernment: after all, so many strangers could not all be wrong. Continue reading →
Open budgets, and what AI changes about what we can see
Open budgets and open data may not be at their fashionable peak, but AI changes what we can see in the data, and what we cannot. Continue reading →
Whose data trains the model, and who benefits from it
As one X user bluntly summarized: 'Claude is winning because rich people are providing the training data. Poor Meta has to train AI with the peasants of the internet.' Crude, and not quite right about the mechanism. Continue reading →
What is actually holding governments back on the agentic state
When it comes to The Agentic State, what is actually holding governments back? The launch of our vision paper last October triggered months of conversations with governments across every continent. Continue reading →
Hacking the public sector, and the civil servants who do it
'What I really love is hacking the public sector. And for that, I need my cracha.' The most effective public servants are not outsiders throwing rocks, they are insiders who know which doors their badge opens. Continue reading →
AI and democracy keeps ignoring the generalist
It still amazes me how little attention those working at the intersection of AI and democracy pay to the role of generative AI in collective action. Continue reading →
Summer in Europe while you can: AI and the Jevons paradox might soon make it unbearable
Biometrics lowered the administrative cost of designing new entry requirements, which removed the natural brake on regulatory ambition. The efficiency gain was immediately consumed by the expanded scope of what became feasible to demand. Continue reading →
Worth engaging with, and worth the harder questions
Worth engaging with, and worth asking the harder questions about. This is the kind of build the small-models argument has been waiting for. Continue reading →
Theoretical AI capability against observed usage
This figure from Anthropic comparing “theoretical AI capability” with observed usage across occupations has been circulating widely in the AI policy bubble. Continue reading →
This may not be the future, but it is what citizens will expect
I'm not sure that's what the future will look like, but it is what citizens will expect from governments. Whether those in power like it or not. Continue reading →
Help needed: what agentic procurement would actually require
Help needed! I've been tinkering with an interactive 'periodic table' for AI in government for a course I'm developing. Continue reading →
ChatGPT is splitting into work and everything else
OpenAI recently released data on how people use ChatGPT. One number stood out. In December 2025, about 75% of messages from paid Pro users were work-related. Continue reading →
A system-level view of AI, and why it is rare
This is one of the most important system-level AI posts I’ve read in a while. Many public services are not designed to be accessible, they are designed to be survivable: complexity and bad UX function as informal rationing. Continue reading →
Buy or build, and the question that decides it
Buy or build? One trajectory from ambition to pragmatism is worth a thousand AI strategies. Singapore's SEA-LION AI model started by pretraining from scratch. Continue reading →
Deliberative democracy's bottleneck is not scale, it is consequence
I have argued that deliberative democracy's constraint is not scale but consequence, and proposed coordination infrastructure that turns deliberative agreement into organised pressure. A new preprint reads like the dark mirror of that idea. Continue reading →
Verified humans, synthetic voices: where collective intelligence meets collective manipulation
The same infrastructure that could help democratic publics convert consensus into leverage can, with a different governance structure, manufacture the appearance of consensus where none exists. Continue reading →
A technical milestone for the region, and the harder question underneath
A regional public-AI launch is a real technical achievement, and 'sovereign' is doing a lot of unexamined work in how it is described. Ownership, hosting, control and capability are four different claims. Continue reading →
Singapore's governance framework for agentic AI in government
Singapore's IMDA released a governance framework for agentic AI in government (via Drasko Draskovic, PhD). It is careful, thorough work on oversight, testing, and accountability. Continue reading →
An RCT on patient-facing medical AI, and what it measured
A randomised trial in China (n = 2,069), published in Nature Medicine, tested an LLM chatbot that conducts the patient intake interview before a specialist visit and hands the clinician a structured summary. Continue reading →
2025
A very specific kind of AI failure in government
I start to see a very specific kind of AI failure in government. A new tool arrives, the institution responds with what it already knows how to do: mandatory training, warnings, guardrails, committees, sign-offs. Continue reading →
In many countries competitive recruitment is more fiction than fact
In many countries, competitive recruitment is more fiction than fact. And in the public sector in particular, interviews are often the stage where merit quietly disappears and “soft-rigging” takes over. Continue reading →
Public services will not be shaped by the interface alone
About a year ago, Luke Jordan and I argued that the future of public services would not be shaped only by user interfaces, but by agents acting on behalf of users. Continue reading →
Europe regulates the digital world and keeps tripping in the physical one
I just came back from Frankfurt, and I spent an unhealthy amount of time talking about digital policies while looking at stairs. Continue reading →
The algorithmic hand: AI, democracy and collective action at scale
New paper out 'The Algorithmic Hand: Artificial Intelligence, Democracy, and Collective Action at Scale' Every few decades, a new technology promises to reinvent democracy. Continue reading →
What we do not say enough about govtech
At the Data Science Conference, I had a conversation with Gustavo Maia from Colab about something we don't say enough in tech: if you want to build things that actually reach people, look at the public sector. Continue reading →
The GDPR review, and what gets traded for competitiveness
So, the European Union is reviewing parts of the GDPR to make it more compatible with innovation and competitiveness. Continue reading →
How AI reshapes buyer-supplier negotiations
Very interesting study (link in comments) on how AI reshapes buyer–supplier negotiations. In experiments with students and professional negotiators, human suppliers negotiated with a ChatGPT-based agent acting as the buyer. Continue reading →
When agents start negotiating on our behalf
Super interesting, and it connects to something we've been thinking about in our work in The Agentic State: AI agents are not a substitute for fixing bad UX, but they are arriving regardless. Continue reading →
What development research keeps missing about AI
A few thoughts as I join the Global Development Conference 2025 in Clermont-Ferrand, promoted by the Global Development Network. Continue reading →
The inference divide: the inequality no one is talking about
Two people with identical devices, connections and skills, using the same model, can receive fundamentally different intelligence augmentation. One subscription lets the model think for minutes. The other gets seconds. Continue reading →
The AI future is about identity, territory and governance
The AI Future Isn't Just About Algorithms: It's About Identity, Territory, and Governance. Thank you for the opportunity to speak at last week Techritory Forum in Riga! Continue reading →
The agentic state, second version
Last week, at the Tallinn Digital Summit, we launched the second version of The Agentic State: a vision for how governments can use AI agents not to replace human judgment, but to redesign how the state itself works. Continue reading →
A hype check on human-in-the-loop
Help needed: human-in-the-loop hype check The more I think about it, the more I suspect that blanket calls for “human-in-the-loop” in AI for public services are a first-world comfort blanket. Continue reading →
We have far more AI policy trackers than AI deployment trackers
I wish we had at least half as many AI deployment trackers as we have AI policy trackers. Especially in contexts where deployments are likely to have major consequences…. Continue reading →
Context lock-in and the new AI monopolies
The next lock-in may not be the model but the accumulated context: conversations, preferences and work history that cannot be moved. Open protocols for context portability are the remedy, and they are a rare pro-competition rule most sides could accept. Continue reading →
Most digital government life events are theatre
Most digital government “life events” are just theater. Time to admit it. Digital government folks love to talk about “life events”: having a baby, starting a business, losing a job. Continue reading →
Looking for machine learning systems that are actually running in government
Help needed: looking for real-world Machine Learning systems in government A few weeks ago, I reached out to this network asking for compelling GenAI use cases in public-sector workflows. Continue reading →
The UK's Copilot experiment with 20,000 civil servants deserves more attention
The UK's Copilot experiment with 20,000 civil servants deserves way more attention than it's gotten. The results, 26 minutes saved per day, might seem modest, but they reveal something crucial about AI in government. Continue reading →
Asking for automation agents that actually get things done
Asking the community: any examples, public or private sector, of automation agents that actually get things done for users online? Continue reading →
Why would a government adopt this? The question public-sector AI keeps skipping
One of the recurring blind spots in public sector AI enthusiasm is a failure to answer a basic question: Why would governments succeed with GenAI now, given their long history of struggling to adopt much simpler technologies? Continue reading →
The procurement problem nobody wants to own
*Excellent* analysis on UK procurement challenges. The findings also resonate strongly with what we see in developing economies, but where there's an additional structural barrier: payment delays. Continue reading →
The agentic state: ten functional layers of government, revamped
New paper on The Agentic State Very happy to share 'The Agentic State: How Agentic AI Will Revamp 10 Functional Layers of Government and Public Administration'. Continue reading →
Where generative AI is actually hitting labour markets
Most studies of generative AI and jobs rest on exposure estimates rather than observed effects. New World Bank research asks where the impact on labour markets is actually landing. Continue reading →
Why generative AI isn't transforming government (yet)
I asked practitioners, NGOs and philanthropies a simple question: where are the compelling generative AI use cases in public-sector workflows? The responses, though numerous, were underwhelming. Continue reading →
Who is liable when the harm is assembled from parts
Beatriz Botero Arcila proposes fault-based joint and several liability for AI systems, with targeted strict liability for high-risk cases. Her framework takes on the 'many hands' problem: who answers when the harm is assembled from parts. Continue reading →
The first clinical trial of a generative AI therapy chatbot
The first clinical trial of a generative AI therapy chatbot, from Dartmouth in NEJM AI: 51% average reduction in depression symptoms, 31% in generalised anxiety, 19% in eating-disorder concerns. Continue reading →
New research: what digital participation actually changes
New in Government Information Quarterly, with Fredrik Sjoberg: who takes part in digital participation does not by itself determine who benefits. What decides it is whether, and how, governments respond. Continue reading →
Who participates in digital democracy, and who really benefits?
The dominant assumption is that who participates determines who benefits. Across participatory budgeting in Brazil, FixMyStreet, Iceland's crowdsourced constitution and Change.org, that chain broke at some stage in every case. Continue reading →
On sortition, and what a lottery can legitimately decide
In the inaugural issue of the Journal of Sortition: 'The Limits of Representativeness in Citizens' Assemblies', on what a democratic minipublic can and cannot claim to represent. Continue reading →
2024
Unwritten 2025
'We don't know where this technology is going' sounds thoughtful and feels responsible. Increasingly I am convinced it is neither, and that waiting is a decision that may cost us. Continue reading →
How to make AI agents serve everyone, not just the privileged few
Written with Luke Jordan: as AI agents reshape access to public services, the risk is a widening gap between citizens who can delegate and those who cannot. What it would take to build the equitable version instead. Continue reading →
Agents for the few, queues for the many – or agents for all?
Closing the public services divide by regulating for AI's opportunities. Continue reading →
The overlooked upside of AI for developing nations
While most discussions about AI and developing nations fixate on risks and challenges, we often overlook the glaringly obvious opportunities. Continue reading →
AI's coming data saturation is an opportunity for the countries left out of the corpus
This recent Nature article projecting AI data saturation in the near future inadvertently highlights a significant opportunity for developing economies. Continue reading →
Inclusive AI infrastructure, and who is in the room when it is designed
Still energized from moderating this panel at the Tallinn Digital Summit on inclusive AI infrastructure - born from a growing collaboration between Estonia’s Government and The World Bank Group. Continue reading →
The link between open data and trust in government is weaker than we assumed
Two rounds of survey evidence suggesting the link between open data and institutional trust is weaker than open-government advocates assume, and in places runs the other way. Continue reading →
Forty-five percent of UK public services report no AI use at all
Excellent new survey by Jonathan Bright and colleagues at the Alan Turing Institute shows that 45% of UK public service professionals are aware of GenAI use at work, while 22% use it themselves. Continue reading →
AI's effects on elections are largely overstated
Keegan McBride and colleagues in MIT Technology Review, on why AI's measured effect on elections is far smaller than the commentary suggests. A reminder to prefer the research on voting behaviour over the punditry. Continue reading →
2023
Underestimated effects of AI on democracy, and a gloomy scenario
Bots writing to legislators got within 2 percent of the response rate humans did. The trouble starts when governments answer with bots of their own. Continue reading →
The hidden risks of AI: how linguistic diversity can make or break collective intelligence
Diverse groups solve problems better. Models trained mostly on English inherit a narrower collective intelligence, and a subtler digital divide follows. Continue reading →