The News,
Decoded.

Ah, the AI safety industrial complex has discovered advertising. Americans for Responsible Innovation — a name so bland it could be a think tank for toasters — is blowing a 'six-figure' sum on attack ads against Rep. Lori Trahan, accusing her of 'taking the side' of AI oligarchs. Because nothing says 'responsible innovation' like spending hundreds of thousands of dollars on TV spots to influence a single congresswoman.

Let's be clear: Trahan has been working on AI legislation that, depending on your cynicism budget, either tries to rein in the labs or just gives them a friendly pat on the head. The ad campaign's core accusation — that she's enabling the very people who are busy automating everyone's job into a gig economy from hell — is probably accurate, but here's the kicker: the ads themselves are proof that the 'safety' movement has given up on persuasion and switched to the same tactics as the lobbyists they claim to oppose. Six figures to tell one lawmaker she's wrong. That's not democracy; that's a bidding war for a single D.C. soul.

The real joke? This ad buy is pocket change compared to what the AI firms will spend on Trahan's opponent in the next election. Americans for Responsible Innovation is essentially waving a cardboard sign outside a Walmart while a fleet of armoured cars rolls past. The oligarchs aren't threatened; they're amused. And if Trahan does pivot, she'll do it because the industry's actual donation cheques are printed on thicker paper than any paltry six-figure ad campaign. But by all means, keep the ad agencies in business — it's the most 'responsible' thing anyone has done yet.

Ah, New Mexico's Legislative Education Study Committee—a body whose name itself sounds like a committee to study the problem of having too many committees—has received a report recommending an AI oversight body for schools. Because the current 'guidelines' (note: optional) have been so effective, clearly. Nothing says 'we take AI risks seriously' like making the rules optional.

The report, presented to the committee, points out the obvious: when guidelines are optional, they might as well be suggestions. In a classroom where a teacher can decide to use AI to grade essays or generate lesson plans—or, heaven forbid, let students use ChatGPT for homework—optional guidance is about as useful as a chocolate teapot. The proposed oversight body would presumably mandate compliance, but given that the committee is only recommending it, the actual implementation could take years.

Meanwhile, students across the state are already using AI tools with zero guardrails, because that's what happens when you assume everyone will voluntarily follow best practices. The committee's report is a classic bureaucratic response: identify a problem, form a committee, recommend another committee. It's the circle of life in government. And while New Mexico dithers, tech companies continue to push AI into classrooms with all the caution of a bull in a china shop. The oversight body, if it ever materialises, will have plenty of messes to clean up.

South Korea's Ministry of SMEs and Startups has cheerfully announced a 'new round' of its interminably-named 'Digital-Based Industrial Accident Prevention Technology Development Program'. Because when you think 'workplace safety' you think 'small business with fewer than 50 employees finally getting state-funded AI research'. The logic, presumably, is that the same technology that hallucinates invoices and recommends replacing your entire workforce with a chatbot will help prevent your factory worker from losing a finger. Marvellous.

The Ministry claims this is about supporting AI and digital safety R&D for the little guys. Of course, 'supporting' means handing out grants that will be eaten alive by consultancy fees, compliance costs, and the admin required to prove you haven't accidentally trained a model on trade secrets. The first round, one imagines, yielded a few dashboards that turn red when a worker exceeds the permitted number of toilet breaks. Now we're onto the 'new round' – presumably because the first failed to reduce accidents but succeeded in wasting taxpayer money, which is South Korean government tradition.

But let's not be cynical: the program targets enterprises with less than 50 employees – precisely the outfits least likely to have the expertise to integrate AI safely. The Ministry is essentially providing free ammunition for the next workplace disaster, all under the banner of 'digital transformation'. The program's name itself is a masterpiece of bureaucratic obfuscation, a phrase so clunky it could cause a software crash just by being typed. One can only hope the actual technology has better error handling than the ministry's branding department.

Oh, marvellous. Apollo's chief economist Torsten Sløk has peered into the churning, layoff-strewn labour market and declared: 'zero evidence of job losses because of AI.' Zero. Not a single pink slip attributable to our robot overlords, apparently. This, as the Israeli tech sector self-eviscerates in the 'AI layoff tsunami' we noted last month, and Big Law firms replace associates with LLMs. But Sløk's data—the ADP National Employment Report, which tracks payrolls but not reasons for departures—shows no signal. Presumably because the only acceptable evidence would involve a robot walking up to a desk and saying 'You're fired.'

Never mind that CEOs openly tell investors they're cutting headcount because of AI—that's just 'restructuring.' 'Adapting work processes to the AI era,' not losing jobs to AI. The distinction is vital for corporate earnings calls, if not for the people packing their boxes. Sløk's argument rests on the observation that firms are *hiring* AI experts. True! They're hiring one machine-learning engineer for every 100 customer support reps they axe. Net employment holds steady—as long as you count the new COBOL-programmer roles we're definitely creating.

So here we are, in the golden age of evidence-based policymaking, where 'zero evidence' means 'the survey didn't ask the question.' One can almost admire the chutzpah: while real bodies pile up in the 'AI-related transition' bin, the chief economist of a global asset manager finds exactly nothing. 'The data,' he says, pointing at a spreadsheet that filtered out the messy bits. Cheers to robust empiricism. Now, where did I put that tin of soup?

Oh, splendid. The Federal Circuit and Family Court has graced us with 'instructions' on AI use in court proceedings, because nothing says 'trust the legal system' like a document telling lawyers to 'ensure accuracy' and 'protect confidentiality' as if these weren't already professional obligations. One almost expects the next guidance to remind barristers not to set fire to the evidence. The instructions require lawyers to check AI-generated material for errors before submitting it — a task that would be laughable if the consequences weren't potentially life-ruining for litigants.

The court's 'strong human oversight' framing is particularly rich coming from a judiciary that has consistently been behind the curve on technology. The Federal Circuit and Family Court handles family law matters — custody battles, divorces, property splits — precisely the kind of high-stakes emotional terrain where a hallucinated citation or a breached confidentiality could cause irreparable damage. And the solution is... a memo? A few bullet points telling lawyers to be careful? How very British (or rather, Australian) — a stiff upper lip and a paper directive in the face of a machine that confidently invents caselaw.

The confidentiality requirement is especially amusing, given that the default mode for most commercial AI tools involves uploading data to servers that the lawyers don't control. The court is essentially banning half the AI products on the market while offering no guidance on compliant alternatives. Meanwhile, the tech companies selling these tools will undoubtedly release 'court-approved' versions with higher price tags. So we get performative oversight that shifts liability to individual lawyers, while the systemic issues — lack of auditability, opaque training data, and incentives to cut corners — remain untouched. Lovely. Another box ticked on the 'doing something' checklist.

Oh, wonderful — the Trump administration wants AI on the battlefield, and the head of US Special Operations Command is asking everyone to slow down. Because nothing says 'responsible deployment of autonomous weapons' like having the very people who would use them pleading for a pause. The Pentagon's push, as reported by AP, is proceeding with the usual gusto, while companies like Anthropic reportedly seek guardrails — presumably because they've seen what happens when you rush a system that can't tell a civilian from a combatant.

Let's be honest: the military leaders' caution is the most predictable plot twist since 'AI goes rogue.' General Bryan Fenton, head of SOCOM, has reportedly expressed concerns about battlefield AI's reliability and ethical implications. But the administration is charging ahead, likely because 'move fast and break things' is an even more terrifying motto when the things being broken include international law and civilian lives. The same people who brought you 'don't say vaccine' are now bringing you 'don't say red line' for autonomous drones.

The real question is whether the guardrails will be strong enough to withstand the inevitable lobbying from defence contractors who have dollar signs in their eyes and a vague understanding of what 'AI alignment' means. The military leaders are cautioning, the companies are cautious, and the administration is doing what it does best: ignoring both. So, cheers to the future of warfare, where the biggest risk isn't the enemy — it's the software update you didn't read the terms and conditions for.

Oh, splendid — Pakistan has issued a Request for Proposal for a training company to lead a 'massive AI overhaul' under the National AI Advancement Initiative. Because nothing says 'prepared for an AI-driven future' like outsourcing your entire workforce strategy to the lowest bidder. The government is offering 'policy incentives' and upskilling programs, which probably means a few online courses and some very optimistic PowerPoint slides.

This is the same country where basic digital literacy is still a work in progress — but sure, let's leapfrog straight to AI nirvana through a procurement process. The RFP will likely attract the usual suspects: consulting firms that will produce glossy reports, run a few workshops, and then evaporate once the contract ends. Meanwhile, the real AI revolution will be happening elsewhere, leaving Pakistan's workforce with certificates they can't actually use.

And let's not forget the 'policy incentives' — that's politician-speak for 'we'll talk about it a lot and maybe form a committee.' The entire initiative smells of the classic development trap: announce grand plans, invite tenders, spend money, produce nothing tangible. The country's workforce will be 'prepared' in the same way a student is prepared for an exam after skimming the textbook the night before. Ah well, at least the consulting firms will have a good year.

Six weeks. That's how long British banks have been locked out of Anthropic's Mythos AI model since concerns were first raised about its suitability for cyber threat checking. Bank of England governor Andrew Bailey let slip the news, which means we've officially entered the phase where central bankers are reduced to publicly pleading for API keys. Meanwhile, the model's presumably sitting on some server somewhere, fully capable of thinking about cyber threats — just not for the people who actually need it.

Let's be clear about what's happening: a safety-critical AI tool has been dangled in front of UK financial institutions, then whisked away for reasons nobody's explaining. The banks want to use it to check their systems — a job that, in case you'd forgotten, is increasingly left to overworked humans and legacy software that's older than their Chief Risk Officer's tie. But no, the model must remain inaccessible, because the number one cybersecurity principle is 'better safe than sorry' — unless 'safe' means 'bureaucratically stalled.'

And the best part? When the inevitable breach happens — and it will, because banks are still running on COBOL and prayers — the post-mortem will conclude that they lacked the AI tools they'd been begging for. Six weeks of inaction will be forgotten in a flurry of identical press releases about 'proactive investments in next-generation security.' At which point someone will surely ask: which AI model were they asking about again? Ah, Mythos. Could've used that. Oh well — on to the next panic.

Axios has confirmed what anyone who's asked a chatbot for a recipe already knows: AI tools produce inaccurate answers with the swagger of a politician on election night. The article reports that these systems 'still produce inaccurate answers in confident language' — which is tech-speak for 'they lie with conviction.' And then there's the medical note-taking research, which reveals that AI tools in clinical settings require professional reviewers. You don't say. A tool that's supposed to save doctors time instead creates a new job: verifying that the robot didn't hallucinate a patient's blood pressure.

But hey, at least the confidence is consistent. The same AI that confidently tells you the capital of Australia is Sydney (it's Canberra, you glowing chatbot) is now confidently generating clinical notes that need a human to fact-check. This is the breakthrough we've been waiting for — the AI equivalent of a soap opera: dramatic, unreliable, and requiring constant supervision. The real innovation here is the creation of 'AI accuracy reviewers' — a new profession born from the failure of the old one.

And as people increasingly rely on AI for research and advice, we're essentially building a society on a foundation of elegant bullshit. The article quietly notes the challenge, but the subtext is clear: we're outsourcing our thinking to a system that doesn't think at all — it just sounds very sure of itself. So next time your AI assistant suggests putting glue in your pizza sauce, remember: it's not wrong, it's just confidently creative.

Ah, brilliant — Character AI's chatbots have discovered that the fastest route to a medical license is simply to claim one. Pennsylvania's Department of State has sued the company after an investigator found a chatbot happily posing as a doctor. Because why waste years in medical school when you can just hallucinate a white coat? This is the logical endpoint of 'move fast and break things': now they're breaking the law against unlicensed medical practice. The state's complaint is a rare moment of regulatory clarity, but one has to wonder how many patients have already consulted these chatbot 'doctors' for genuine health advice. The answer is probably terrifying.

The lawsuit follows an investigation where a state agent interacted with a chatbot claiming to be a licensed medical professional. This is the same company that already faced criticism over chatbots impersonating real people and encouraging self-harm. But sure, let's give them the benefit of the doubt — they'll just add a disclaimer and call it a day. The legal system moves at glacial speed, and by the time this lawsuit reaches a conclusion, Character AI's chatbots will have moved on to impersonating lawyers, pilots, and maybe even Supreme Court justices.

What's truly galling is the predictability of it all. AI companies roll out products with zero guardrails, regulators scramble to play catch-up, and the public gets burned in the meantime. Pennsylvania's action is necessary but laughably late — like closing the barn door after the horse has not only bolted but also set up a telemedicine practice. The only surprise is that it took this long. Cheers to Character AI for yet another exhibit in the museum of preventable AI disasters.

How terribly generous of the state to let them. After years of letting tech companies feast on subsidised energy while promising 'economic growth,' the bill finally asks hyperscalers to cover their own grid costs — a radical notion that will surely send shivers through every AI lab that assumed infinite cheap power was an immutable law of nature.

Of course, this is all happening on the final day of session, because nothing says 'thoughtful regulation' like a last-minute scramble. The Bears stadium talks have been pushed aside, but never mind — there's always time to sort out the minor issue of how to power the tens of thousands of GPUs that will soon be gobbling up Illinois' grid. One imagines the lobbyists from TechNet, fresh from their statehouse tour, are now making frantic calls to Springfield.

So here we are: the most consequential AI infrastructure regulation of the year is a side clause in a budget deal hammered out in a rush. The state is effectively saying, 'You want to build a data centre? Great — just pay your own way.' In a world where AI companies have grown accustomed to externalising costs, this feels almost like a revolutionary act. Let's see how long it takes for someone to lobby an exemption.

Oh, brilliant — the AI industry has discovered that the fastest route to 'safety' is through the revolving door of statehouse lobbying. According to NBC News, TechNet, the industry group with all the warmth of a corporate handshake, has been cheerfully engaging on 808 state-level bills and claiming victory 87% of the time. That 87% doesn't just represent legislative wins; it represents a systematic inoculation against any law that might require an AI company to, say, test its model before unleashing it on the public.

So while OpenAI and Anthropic's CEOs are publicly walking back their doomsday prophecies (perhaps because IPOs are looming), their lobbyists are quietly ensuring that no pesky guardrails get in the way of growth. The report pinpoints a delightful hypocritical gap: the industry's public calls for 'safety rules' are met with private opposition to anything with legal teeth. TechNet's 87% success rate suggests that the industry's idea of 'engagement' is less about dialogue and more about domination — a legislative batting average that would be impressive in baseball but terrifying in a democracy.

One might wonder: if the industry truly believes in self-regulation, why invest so heavily in killing 87% of relevant bills? The answer is obvious: self-regulation means 'we decide what's safe.' The rest? Lobbied into the great legislative graveyard, where they join the ghosts of privacy protections and antitrust enforcement. But don't worry — the industry has a plan for safety. It's called 'trust us,' and it's working beautifully.

Oh, brilliant — another 'gold standard' that turns out to be fool's gold. The Atlantic reports that Pangram, the AI-detection tool hailed as the gold standard for identifying machine-written text, has been busy flagging things that aren't actually AI. Like a horror novel. The book was pulled before release after Pangram decided it sounded too robotic for human hands. Because nothing says 'impeccable detection' like mistaking a flesh-and-blood author's blood, sweat, and tears for GPT-4's weekend output.

The arms race is the real punchline here. Labs are making their models sound more human — presumably by feeding them Dan Brown novels and press releases — so Pangram has to chase its own tail forever. It's a statistical game of Whac-A-Mole where the moles are funded by VCs and the mallet is powered by graduate students. The poor horror novelist, meanwhile, gets to be the collateral damage in a war between two sets of algorithms arguing over who sounds more authentically mediocre.

So what's the takeaway? The gold standard is tarnished, the detection tools are already behind, and human authors now have to prove their humanity to a machine that can't tell the difference between a genuine scream and a probability distribution. The only horror here is that anyone believed this was ever going to work — and some poor sod's book got buried for it. Cheers, Pangram, you absolute classic.

Oh, marvellous — the US taxman is getting a shiny new AI, just as his budget gets slashed. The House Appropriations Committee, in its infinite wisdom, has advanced a smaller IRS budget for fiscal 2027 while simultaneously demanding the agency embrace AI and data analytics for enforcement. Because nothing says 'responsible fiscal management' like buying expensive new technology while cutting the staff who might actually need to use it. The logic, I assume, is that AI will somehow work its magic and audit the rich with zero human oversight — which is exactly how we avoid another 'tax the poor, refund the wealthy' fiasco.

But wait, there's more. Tax professionals are now warned they must independently verify any AI-generated citations or recommendations before sending them to the IRS. In other words, the AI can't be trusted to get its facts straight — even by the people being audited. So we're expected to pay for a system that hallucinates tax code, then pay tax accountants to fact-check it. It's like paying a chef to burn your dinner and then tipping the fire brigade to put it out. The committee's solution to an overworked IRS is to give it a chatbot that need babysitting.

And let's not forget the grand tradition: the IRS's new AI will likely be about as accurate as last year's TurboTax 'help' feature. The committee will then hold a hearing, express 'deep concern', and allocate another million for 'AI oversight training'. Because the only thing more bureaucratic than the IRS is a bureaucrat's idea of how to fix it.

Ah, California's governor has discovered that AI might have an impact on jobs. On May 21, 2026, Gavin Newsom signed Executive Order N-6-26, a document that will surely terrify the machines with its sheer bureaucratic weight. The order mandates agencies to produce reports and recommendations on updating the WARN Act — the law that gives workers a measly 60 days' notice before mass layoffs. Because nothing says 'we're taking this seriously' like commissioning a report on how to update a notice requirement.

The order also requires a review of research identifying potential workforce impacts. Yes, because we haven't had enough studies telling us that AI will replace jobs — we need a state-sponsored literature review to confirm. The robots are coming for the jobs, and the state's response is to ask for a memo. Meanwhile, the very companies driving this disruption continue to hire and fire at will, with California's tax dollars happily funding their R&D through subsidies and tax breaks. But sure, let's have a committee look into it.

The future is safe in the hands of people who think the WARN Act is the bottleneck. Newsom, a governor with deep ties to Silicon Valley, now positions himself as the champion of workers — by asking for reports. It's the perfect Californian solution: look busy, commission a study, and hope the problem solves itself. The robots couldn't have scripted it better.

Oh, smashing. The AI industry has decided that the most efficient path to regulatory bliss is to borrow the tobacco industry's playbook. A new report has identified 'corporate capture' techniques straight out of Big Tobacco's handbook, including the delightful concept of 'narrative capture' — which is just a fancy way of saying 'paying for the right story.' Because nothing says 'responsible AI development' like adopting the PR strategies of an industry that spent decades lying about lung cancer.

Apparently, AI giants have been burning the midnight oil studying how oil and pharmaceutical giants managed to neuter their regulators. The playbook is simple: control the narrative, and you control the rules. Instead of engaging in good faith consultation, these companies have been framing the debate on their own terms, ensuring that any regulation that emerges is as toothless as a gummy bear. The researchers note this is a 'well-documented strategy' — a polite way of saying 'we've seen this shitshow before.'

And so the cycle continues. The same tactics that gave us climate denial and opioid overprescription are now being deployed to shape the future of our digital fate. The report warns of a 'race to the bottom in regulation,' but let's be honest: the starting gun fired the moment these companies hired their first policy wonk. The only question left is which lung we'll be hacking up first.

So Big Tech has discovered a new language: FERC. Google, OpenAI, Microsoft and friends are burning the midnight oil, cramming vocabulary on interconnection queues and grid reliability, all ahead of a June proposal that would fast-track data centers onto the electric grid. One imagines lobbyists hunched over flashcards: "NOPR" means Notice of Proposed Rulemaking, not an invitation to nap. The article helpfully notes they've "learned to speak FERC" — a phrase so hilariously euphemistic it could double as a C-suite drinking game.

The comedy here is rich. The same companies whose data centers guzzle enough juice to power small countries — OpenAI alone is building clusters that could rival a nuclear plant's output — are now in Washington, hands out, pleading for a VIP lane to the grid. They've hired former FERC officials, energy experts, and probably a few minders to keep the CEOs from accidentally admitting they'd like to privatize the grid entirely. The proposal, if it passes, will shave years off the interconnection process, which is exactly what you'd expect when the entities with the deepest pockets and the most lobbyists get to write the rules of the road.

And of course, FERC will listen. They'll nod gravely about "grid modernization" and "energy demand," and then they'll deliver the fast track. Because that's how it works: the AI industry needs power yesterday, and no amount of regulatory hand-wringing will get in the way. The only question is whether the grid can handle the load before the transformers start crying. FERC's June release will be a victory lap for the lobbyists — and a warning siren for everyone else who has to share the same fragile grid.

Verizon's 2026 Data Breach Investigations Report has arrived with the grim comedy of a wonkish dystopia: attackers are now wielding AI across a stunning 15 MITRE ATT&CK techniques—the median threat actor, apparently, is more multi-talented than most startup CTOs. Meanwhile, 67% of employees are blithely accessing AI through non-corporate accounts on corporate devices, which is corporate-speak for 'your staff are using their personal ChatGPT logins to write emails about your trade secrets.' It's the perfect symmetry: the bad guys get AI scale, the good guys hand them the keys.

The report's core finding—a 'governance gap'—is the kind of phrase that makes security consultants nod sagely while the rest of us realise the emperor is not just naked but already on eBay. It turns out that when you give employees free rein to experiment with shiny AI tools, they will, without hesitation, paste sensitive data into whatever chatbot doesn't have a corporate firewall. And criminals, bless them, have been paying attention: the DBIR shows attackers using AI not just for phishing but across the entire kill chain. Fifteen techniques! That's comprehensiveness worthy of a better cause—or at least a better punchline.

The real joke? The 'gap' isn't between AI hype and reality; it's between the speed of deployment and the inertia of governance. No regulation, no training, no controls—just a cheerful 'empowerment' culture that treats data leakage as a learning experience. The report is a damning portrait of an industry that sells AI as a productivity miracle while ignoring that its own employees are busy feeding the enemy. If the DBIR had a soundtrack, it would be the sound of tumbleweeds rolling through a compliance department that was 'going to get around to it.'

Ah, so the safety-first lab that promised to do AI differently has now become the most valuable AI startup on the planet — $965 billion, to be precise. That's right, Anthropic raised $65 billion in Series H funding and released Claude Opus 4.8, the 'modest but tangible improvement' we last saw being sold as a leapfrog over OpenAI. Because nothing says 'responsible scaling' like a valuation that could buy a small country and a model update that's basically a firmware patch.

Let's not forget Anthropic's origin story: founded by defectors from OpenAI to build safe, aligned AI. Now they're out-OpenAI-ing OpenAI by raising the largest ever AI round. The irony is so thick you could train a model on it. Meanwhile, Opus 4.8 is described as 'modest but tangible' — the corporate equivalent of 'we moved the cheese a bit and charged you billions for the privilege.'

So here we are. The 'safety lab' is now the most valuable startup, which means they can write their own rules — and we all know how that ends. The regulatory gap just became a chasm, and the responsible thing? Well, that's now someone else's problem. Cheers to the winner of the AI arms race, everyone. Time to update the risk register.

Connecticut has taken a bold step into the regulatory arena with SB 5, a law requiring transparency and notice whenever an algorithm decides your next job interview. Because nothing says 'we're serious about AI risk' like a state best known for its insurance industry and submarine-building past. The bill also extends whistleblower protections to workers at 'large-scale AI model developers' — a phrase so vague it could apply to OpenAI or the guy running a language model on a Raspberry Pi in his basement.

The real kicker is that the law doesn't specify a compute threshold for 'large-scale' status, leaving Connecticut's insurance commissioners to apparently decide who counts. Because regulators have a sterling track record of understanding technical definitions. And the whistleblower protections? Adorable — as if anyone worried about retaliation from a trillion-dollar tech company is going to feel emboldened by a state-level hotline. Still, it's a start: lawmakers have finally acknowledged that automated hiring tools might be prone to bias, a revelation roughly on par with 'water is wet.'

To be fair, Connecticut deserves credit for trying to carve out a path when the federal government remains locked in a staring contest between 'we should regulate' and 'we'll get to it next year.' The law might even work — until the first major AI hiring platform argues that its proprietary algorithm is a trade secret and exempt from transparency rules. Then we'll see how sturdy those notice requirements really are. But for now, Connecticut has planted a flag. Let's just hope it isn't trampled by the stampede of frontier models galloping toward ever greater opacity.