Brazil
An AI model now reads Brazil's messy $75 billion medicine-procurement records
Brazil's public health system buys $75 billion of medicine a year through 263 different local systems with unstandardised records. A large language model now matches each purchase to a federal product code, cutting a 90-minute manual task to five seconds and lifting the match rate from 5% to 80%.
Assorted links for 30 September 2026
Five links: a Nigerian fintech AI-evaluation framework finds standard safety tests miss local fraud risks in both directions, India pitches its digital-infrastructure experience to the Global South at the UN, the Trump administration launches an AI front door for US federal services, Code for America and Anthropic pilot Claude for SNAP caseworkers, and Rondonia's state government adapts a wildfire-physics model for an AI early-warning system in the Amazon.
Assorted links for 29 September 2026
Four links: Kenya and Anthropic sign a data-sovereignty AI framework at UNGA, Goa puts its state government portal behind a WhatsApp chatbot, a 118-student study finds generative AI's learning effect depends on how it is used, and a Brazilian legal commentary traces today's AI-governance gap to a 2017 audit of un-shared government data.
Assorted links for 14 September 2026
Five links: at least 39 submissions to Australian parliamentary inquiries carrying apparently hallucinated references, a retrieval system whose recall falls from 84 to 16 per cent when a benefits question is asked in plain English, federal AI obligations reaching $7.2 billion, 300,000 hours saved by bots at the Defense Logistics Agency, and Brazil's open platform for reusable public-sector AI.
Brazil and Portugal account for about 69% of Portuguese dataset records
Twenty researchers built the first country-level atlas of who is represented in the datasets behind language models. Brazil and Portugal hold about 69% of the Portuguese records, France, Switzerland and Canada about 63% of the French, and 121 of 197 countries have ten or fewer records attributed to them at all.
Half these jurisdictions have no AI law of their own
Five researchers pulled 382 provisions out of 101 legal instruments across twenty jurisdictions that build no frontier AI model. Only 22 per cent sit in binding law, half the jurisdictions hold no domestic instrument of their own, and two provisions in the whole sample reach the party that built the model.
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.
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.
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.
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.
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.
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.
Agents for the few, queues for the many – or agents for all?
Closing the public services divide by regulating for AI's opportunities.