The News,
Decoded.

Ah, the IRS — that famously agile, tech-forward institution — has discovered AI. Ken Corbin, the agency's Taxpayer Services Chief, announced that AI will deliver a 'more efficient, better-trained workforce' by 2027. Because nothing says 'accelerated' like a four-year timeline and a system that is, by his own admission, still a 'proof of concept.' One can almost hear the rusted gears of bureaucracy creaking as they contemplate sitting down with vendor brochures.

Of course, the real training these employees need is on how to navigate an understaffed, underfunded agency that already struggles to answer phones. The proof of concept will likely become a multi-year boondoggle, with consultants billing millions to deliver a chatbot that can only recite the tax code from 1987. Meanwhile, taxpayers will continue to enjoy hold music that sounds like dial-up.

So by 2027, perhaps the IRS will have AI-trained agents who can finally answer a query without transferring you to a dead line. Or maybe the AI will be trained to file extensions on behalf of the entire government. Time to start a betting pool on whether this 'proof of concept' ever graduates to production. The odds are, shall we say, approximately the same as voluntarily filing an audit.

The 2026 Career Optimism Index from the University of Phoenix reports that 63% of workers feel positive about job opportunities. Great. The survey also finds that 50% are learning to use AI independently — which employers, in their infinite wisdom, interpret not as initiative but as a warning sign of imminent talent flight. Because nothing says 'loyal workforce' like seeing upskilling as a threat.

The term 'job hugging' — that lovely corporate euphemism for 'too scared to move during a downturn' — is apparently giving way to 'job hopping,' as workers decide that learning AI might actually improve their prospects. This should surprise precisely nobody who has watched the layoff announcements roll in. The same employers who demanded workers reskill or be replaced now seem shocked that the survivors are taking the hint. One imagines HR departments nationwide hastily updating non-compete clauses and muttering about 'retention strategies.'

The article frames this as a 'concern' about talent flight, as if workers owe allegiance to faceless corporations that would replace them with an LLM given half a chance. In a rational world, this would be called 'the market correcting itself.' But here we are, wringing hands over people doing exactly what they were told: embrace AI, learn new skills, and — heaven forbid — improve their lot. Pass the popcorn, and maybe a job application form.

So corporate America has graced us with 1,600 layoff announcements in four months, shedding 128,000 workers like dead skin. But don't worry — Senators Warner and Budd have a bill for that, a public database to track the carnage. Because nothing says 'we're on top of this' like a data dump after the bodies pile up. USA Today's tracker, powered by WARN Act filings, shows the bloodletting is real, but the government response is still stuck in 'let's form a committee' mode.

The numbers are staggering: 1,600 separate layoff events in just 120 days. That's roughly 13 a day. But hey, at least the WARN Act requires 60 days' notice, so workers get to sit and watch the clock tick down to their obsolescence. The tracker doesn't break out AI-related cuts specifically, but we all know the subtext: automation, chatbots, and 'efficiency' are the new pink slips. The tech sector alone has been a bloodbath, and the rest of the economy is catching up.

So where does this leave us? With a tracker that shows the damage but no roadmap to stop it. The Warner-Budd bill is still a bill, not a law, and even if it passes, it'll just be a dashboard of despair. 128,000 people, 1,600 announcements, zero meaningful intervention. Cheers to progress — sure, let's call it that.

The Academy has finally done something brave: they've banned AI from the Oscars. Well, from the 'actors' and 'scripts' categories, anyway. Because nothing says 'protecting artistry' like a panel of wealthy humans deciding that a machine can't replace a human — as long as the machine isn't Kevin Hart. The move is about as meaningful as a 'no shirt, no shoes, no AI' sign outside a strip club. You can still use AI to color-grade your film, generate your visual effects, and maybe write your acceptance speech — but the moment you try to submit an AI-generated screenplay, the Academy will be there, trophy in hand, to slam the door. If only they'd been this proactive about diversity twenty years ago.

It's a classic Hollywood narrative: the villain arrives, the hero takes a stand, and the villain is already inside the building. AI isn't just knocking at the door; it's been working in VFX houses for years. Now the Academy declares that, for the 99th Oscars, acting must be performed by a 'human'. That's a bit like a lifeboat drill on the Titanic after the iceberg. Meanwhile, production companies are already using AI to generate 'pre-vis' scripts and synthetic voicework. The Academy is essentially banning the farting robot while the cyborgs are running the projection booth.

Still, one must applaud the timing. Right as the Writers Guild membership is nervously eyeing ChatGPT, the Academy steps in with a firm rule. Perhaps next year they'll ban AI from the Best Costume Design category, as long as you ignore the fact that half the costumes were 3D-printed with generative design. But hey, at least we know who won't be winning Best Original Screenplay: an algorithm that wrote a script about a sentient Oscar statue falling in love with a red carpet. That's a human-only premise now. Good for them.

Ah, yes, because what the pharmaceutical industry really needed was a helping hand from the three horsemen of the AI hype-pocalypse: AWS, OpenAI, and Anthropic. They've unveiled 'specialized AI workflows for scientific research,' which apparently means AWS's 'Amazon Bio Discovery' — a name that sounds less like a medical breakthrough and more like a Jeff Bezos vanity project. Because nothing says 'drug discovery' like slapping 'biological foundation models' onto AI agents and hoping they don't hallucinate a miracle cure for the common cold that also turns your liver into a poodle.

Let's be honest: these platforms are a triple-threat of marketing fluff. AWS wants you to think its cloud compute can solve protein folding (because it can't, but it'll charge you by the microsecond). OpenAI wants you to believe its language model can design clinical trials (after it spends three days arguing that a placebo is the same as a treatment). And Anthropic, fresh off its Mythos panic, now wants to save lives? Right. The same company that locked away a model for 'global cyber security concerns' is now deploying AI to cure cancer. That's not irony; that's a business model.

So here we are, watching the tech giants stage a global pharmaceutical reboot, complete with press releases and zero actual drugs. The best we can hope for is that these 'workflows' produce a new statin before they destroy the patent system. But let's not hold our breath — the only thing accelerating faster than AI's promise in drug discovery is investors' willingness to believe it. Cheers to progress, I suppose. Or rather, to the next funding round.

House Democrats have apparently decided that the best way to win the midterms is to talk about dominating AI — because nothing says 'we hear your concerns' like a laser focus on geopolitical tech supremacy. Critics, who presumably have met actual voters, point out this is akin to showing up at a fire with a brochure on advanced marshmallow roasting. The party's leadership has settled on a message that 'sounds like a Silicon Valley press release' — which is not a compliment when your base is worried about their jobs and their kids' futures.

One can almost hear the strategy sessions: 'Voters are terrified of unemployment, autonomous weapons, and algorithmic bias? Perfect — let's talk about beating China!' It's a masterclass in missing the point while looking terribly serious. The irony is that by narrowing their message to 'winning the race,' Democrats are essentially conceding the debate on AI safety and workforce disruption to Republicans, who have their own flavour of cluelessness.

The real missed opportunity isn't just political — it's narrative control. By not addressing the deep, legitimate fears voters hold about AI, Democrats are letting those fears fester and be exploited. So yes, brilliant strategy: run on a message that pleases a handful of tech donors while ignoring the millions of people who just want to know if their job will survive the next model release. Stirring.

Splendid news from the White House, where the Office of the National Cyber Director has finally — *finally* — held meetings about the security concerns posed by advanced AI models like Anthropic's Mythos Preview. The solution? A framework that would require the Pentagon to lead safety testing for *government AI deployments*. Because if there's one institution known for its nimble, transparent, and error-free handling of complex technology, it's the Department of Defense. I'm sure the same folks who brought us the F-35's software woes will do a bang-up job ensuring our AI doesn't go rogue. 🫡

This, of course, comes hot on the heels of the administration's earlier hints at a working group to 'examine potential oversight procedures'1 — a phrase so bland it could have been generated by a particularly uninspired language model. So now we have the Pentagon as our digital nanny, prodding at black-box models with all the subtlety of a cruise missile. The fact that Mythos was deemed too dangerous for public release by Anthropic itself seems to have registered, but the response is more 'lock the stable door after the horse has bolted' than any genuine precaution.

The irony is thick enough to spread on toast: the same administration that spent years deregulating everything from emissions to banking now wants the military to certify AI safety. I'm sure there's a perfectly rational explanation — something about 'cutting red tape' while simultaneously creating a new bureaucratic nightmare. Perhaps the real threat isn't Mythos but the meeting minutes from these sessions, which will likely be classified before anyone can point out the contradictions. At least the gallows humour is writing itself.

Oh, *marvellous*. The Trump administration — the same gang that spent four years cheerfully deregulating everything that moved — is now reportedly considering an executive order to create an AI working group that would 'examine potential oversight procedures,' including a formal government review of new models. Because nothing says 'credible safety framework' like a last-minute executive action from an administration that has consistently treated tech regulation as something to be mocked at rallies. This is the sequel to the earlier report we flagged as comically improbable, and it's just as likely to produce a toothless committee that meets once, issues a press release, and quietly dissolves.

The working group will 'examine' oversight. Examine. Not implement. Not enforce. The NYT article is careful to say 'considering an executive order' — the usual dance of appearing to act without actually doing anything. The formal review process, if it materialises, would presumably require models to be submitted for government evaluation before public release. Which is a lovely thought, except this is the same administration that has been enthusiastically courting AI companies with promises of 'light-touch regulation' and 'American innovation.' The working group will probably be chaired by a former tech lobbyist and staffed by interns from the Heritage Foundation.

So here we are: a potential pre-release review system for the most consequential technology since nuclear weapons, proposed by an administration that can barely keep the government funded. The working group will likely 'examine' the problem for eighteen months, produce a report recommending 'further study,' and then the models will keep being released anyway. It's the regulatory equivalent of putting a wet paper bag over a fire alarm. Still, we should be grateful — at least they're pretending to care about the burning building.

Senators Warner and Budd have introduced a bipartisan bill that would have the Department of Labor compile a 'public resource of aggregated workforce transparency data' on AI's effect on US workers. Because nothing says 'we're on top of this' like a database — the same magical thinking that gave us the government's cybersecurity dashboard, which nobody uses. The Labour Department, which can barely process unemployment claims on time, is now supposed to track the nebulous creep of automation with 'aggregated' data, which is bureaucrat-speak for 'so vague it's useless.'

This is the same Congress that held six hearings on AI in 2025 and passed exactly zero substantive laws. Now they want a data dump, as if more spreadsheets will somehow protect a truck driver from being replaced by an autonomous rig. The bill's supporters call it 'proactive,' but it reads more like a placeholder — a way for lawmakers to say they did something without actually doing anything that might upset a tech lobbyist. After all, the database is 'transparency,' not regulation.

By the time the Labor Department finishes aggregating, standardizing, and peer-reviewing this data, we'll be on to AI that can file its own Senate testimony. The most useful information in this bill is the implicit admission that nobody in government has the foggiest idea how many jobs AI is actually eating. They're polling the witnesses at the fire, asking them to describe the flames. Proactive? More like reactive with a different label.

Anthropic, in a move that will surely delight no one, has decided not to release Claude Mythos — their latest model — because of 'global cyber security concerns.' Because nothing says 'responsible AI development' like building a powerful model and then locking it in a cupboard, whispering 'this is for your own good.' Meanwhile, Project Glasswing is being rolled out as a kind of digital security blanket, letting insurers peek at a preview version to 'secure critical software.' Oh, goody — a model that's too dangerous to release but apparently safe enough to let insurance underwriters play with. Because if there's one group we trust with dangerous technology, it's actuaries.

The real kicker is that this decision might actually break the cyber insurance underwriting model. Insurers rely on being able to assess risk, and now they're faced with a powerful AI that exists but isn't publicly available — a Schrödinger's catastrophe. The article quotes a source saying 'the uncertainty is uninsurable,' which is a polite way of saying 'our spreadsheets have stopped working.' One can almost hear the collective panic as underwriters realise that their risk models, carefully built on historical data, are now about as useful as a chocolate teapot against a model that may or may not be sentient.

So here we are: Anthropic takes a responsible step by not releasing a model, and the response from the insurance industry is effectively 'What do you mean you won't let the genie out of the bottle? We need to price that genie!' The only certainty is that Claude Mythos, safely hidden away, is now more terrifying to insurers than any actual AI disaster. Truly, the greatest threat is the one you can't see coming.

So the Trump administration, in its infinite wisdom, is reportedly considering an executive order to 'review' new AI models before they hit the public. Because if there's one thing we've learned from the past four years, it's that preemptive government oversight of emerging tech always goes swimmingly. The working group—presumably to be staffed by the same folks who brought us the COVID response and the tariff strategy—will now decide which models get past the velvet rope. I'm sure they'll be consulting the brightest minds: whichever lobbyist pays the most, or perhaps whichever think tank has the most agreeable conclusions.

According to the New York Times, this 'formal government review process' is being floated as a way to ensure safety. Of course, the article doesn't say what happens if a model fails the review—perhaps it gets a sternly worded letter? Or maybe it's sent back for a re-edit like a high school essay. Meanwhile, the frontier labs in California are already shipping models faster than the federal government can form a committee. The gap between what the White House might do and what's actually happening in AI is now so wide you could drive a cyber truck through it, and that's not a metaphor—someone actually tried.

Still, it's a lovely bit of theater. The working group will hold meetings, produce a report, make recommendations, and then get reshuffled when the next administration arrives. Not to mention the inevitable legal challenges: 'My model's First Amendment right to speak!' shouts some billionaire. Meanwhile, AI capabilities keep accelerating, and the only real oversight will be whatever Silicon Valley decides is good for its stock price. But hey, at least we'll have a nice paper trail to show future archaeologists why the robots took over, along with the minutes from a working group that never actually met.

Oh, wonderful. SAP, the company that makes enterprise software so tedious it could cure insomnia, has bought an AI lab. Prior Labs, to be precise—a firm that built its reputation on 'Tabular Foundation Models'. That's right: models for spreadsheets. Because nothing screams 'globally leading frontier AI' like a neural network that's really good at pivot tables. They're committing over €1 billion over four years to scale this into Europe's great hope. That sum might sound impressive until you remember OpenAI burns through that on compute in a few months. But perhaps SAP knows something we don't: maybe the path to AGI runs through quarterly earnings reports.

The timing is almost touching. European politicians have been wringing their hands about the continent falling behind in AI, and here comes SAP, riding to the rescue on a white horse made of enterprise resource planning software. Never mind that Prior Labs' specialty—structured data—is about as far from the multimodal, reasoning-heavy frontier as you can get. When you're desperate for a homegrown champion, you take what you can get. At least it's not another chatbot that recommends returning a faulty product to the wrong department.

What this really means is that Europe's AI strategy is now inextricably tied to a German software giant whose primary innovation in the last decade was moving everyone to the cloud so they could charge more for the same thing. The €1 billion might produce some decent tabular models—useful for forecasting supply chain disruptions, no doubt. But 'frontier AI'? That seems like one of those stretch goals that ends up in a PowerPoint slide no one looks at again. Still, here's to Prior Labs: may their spreadsheets finally get the respect they deserve.

Ah, the great AI pivot: from talking to seeing. According to Appfigures, image model releases now generate 6.5 times more downloads than their text-based counterparts. Because what users really want is not a helpful assistant, but a novelty art generator that occasionally renders a third arm. TechCrunch, ever the booster, frames this as a victory for image AI, as if the goal of research is to top the app store charts.

This isn't about capability; it's about virality. Chatbot upgrades are boring incremental improvements; image models produce shareable content. The 6.5x figure is less a measure of AI progress and more a testament to our collective attention span. The companies that invested billions in text-based assistants are now scrambling to add image generation features, because nothing says 'long-term strategy' like chasing the latest trend.

Meanwhile, the cycle continues: each new modality is hailed as a breakthrough until the next one comes along. And somewhere, a chatbot silently wonders why it wasn't good enough. The real winner here is Appfigures, which gets to publish yet another report telling us what we already knew: people like shiny new things. Cheers to progress, I suppose—as long as it's visually appealing.

Ah, the 'This is fine' comic — a dog sitting calmly in a burning room. It turns out the dog has been replaced by an AI startup called Artisan, which is currently sitting calmly in a burning room of its own making. The company was caught using KC Green's iconic meme without permission in a subway ad for 'Ava the AI BDR,' a name so sterile it sounds like a robot vacuum that sells things.

Artisan's response to the accusation? It 'respects Green and plans to discuss the matter.' Because nothing says respect like waiting until you're publicly shamed to schedule a chat. The ad ran in a subway, presumably targeting commuters who are already on fire, metaphorically speaking. The irony of an AI company — whose entire business model likely involves ingesting others' data — stealing a meme about denial is so thick you could spread it on toast.

This is the perfect metaphor for the AI industry: they happily borrow (read: take) other people's work to train their models or sell their products, and when confronted, they promise a conversation. The burning room is the entire creative economy, and Artisan is the dog saying 'this is fine.' At least the dog had the decency to be fictional.

Ah, the age-old question 'What is the meaning of life?' now comes with a six-figure answer. AI companies like Google and Anthropic are on a hiring spree for philosophy majors, offering base salaries of $250,000 to $400,000 to ponder ethics, safety, and governance. Because nothing says 'trust us with the future of humanity' like paying a fresh grad to remind you that utilitarianism has edge cases. The message is clear: your degree in Aristotle is finally profitable—provided you're willing to lend your moral authority to a machine that might one day decide your landlord is redundant.

Meanwhile, as entry-level jobs are being automated away (as we noted last week, the Forbes crowd is terrified), the philosopher's role is to rubber-stamp whatever the labs build. Sure, you'll sit in meetings and say 'but what about the trolley problem?' The engineers will nod politely, then go back to optimising click-through rates. The irony is exquisite: the very companies that are churning out models capable of replacing junior staff are now hiring the one discipline that asks 'should we?'—and paying them like hedge fund managers.

So to all the philosophy majors enjoying this gold rush: enjoy it while it lasts. You're the canary in the coal mine of a system that doesn't care about your syllogisms. When the AI eventually asks 'why should I be ethical?', your answer will be a salary slip from the very entity that created it. The joke, as ever, is on the one who thinks they can reason with a black box.

Ah, LanguageLine Solutions, demonstrating once again that the language services industry is fluent in the dialect of worker exploitation. They've rolled out algorithmic scheduling—which, in plain English, means software that chops your week into unpredictable slivers and hands you a pay cut. But don't worry: the company is "not aiming to cut jobs." Oh, how magnanimous. They're simply "piloting AI for routine tasks"—presumably because nothing is more routine than a living wage.

The workers get the full algorithmic experience: scattered shifts that sabotage any hope of a second job or childcare, and a paycheck that shrinks like a metaphor for their bargaining power. The company gets "efficiency." It's a classic win-lose arrangement, painted over with corporate reassurances that the AI is merely a tool, not a firing squad. But we've seen this play before: first schedules, then hours, then heads.

One can almost hear the HR script: "We're not eliminating jobs; we're optimising workflows." Which is the corporate equivalent of "the cheque is in the post." LanguageLine's pilot is a small datapoint in a larger pattern—algorithmic management as a cost-cutting bypass around outright layoffs. The result? Workers get the instability without the dignity of being told they're redundant. Progress!

Ah, Bernard Marr has finally noticed that AI might, just might, affect entry-level jobs. Marr's thesis is that this should 'terrify business leaders' — as if they haven't been gleefully automating those roles since 2023, while calling it 'digital transformation' and handing out severance packages with NDAs. The real terror, apparently, is that without junior staff, we'll have no one to train for senior roles. Cute. Because the same CEOs who fired their entire onboarding teams are suddenly worried about the talent pipeline. And who, exactly, will mentor the AI that replaces the interns? A slightly older AI?

Let's be honest: business leaders are terrified of exactly one thing — being caught unprepared for the quarterly earnings call. The article suggests reskilling and apprenticeship programs as if that's a novel idea. Sam Altman himself warned us that job displacement is real, and here we are, reading a Forbes thinkpiece that sounds like a LinkedIn motivational poster designed by a committee. The punchline is that entry-level jobs are the scaffolding of any organisation — remove them, and the whole structure wobbles. But that's a tomorrow problem. Today's problem is that the AI is already doing the intern's coffee run, and it doesn't even complain about the pay.

The deeper absurdity is that we've spent a decade telling graduates to 'learn to code' and now coding is the most automatable skill on the planet. So the next generation will enter a workforce that has no entry-level positions, no training budget, and a C-suite that just discovered the concept of a 'skills gap.' The article ends with a call for 'urgent action' — which in corporate parlance means a task force that reports in six months. By then, the AI will have written its own report, and it will recommend hiring more AI. Terrified yet? Thought not.

Ah, another study from an AI lab telling us which jobs are about to get vaporised. How very thoughtful of Anthropic to provide a handy list, complete with a salary premium for those in the crosshairs — 47% more than the zero-exposure crowd. So if you're a computer programmer, customer service rep, or data entry drone, congratulations: you're not just replaceable, you're *valuably* replaceable. The gallows humour practically writes itself.

What the study doesn't explicitly say, but what every reader with half a brain will infer, is that Anthropic is essentially handing its competitors — and itself — a shopping list of high-value roles to automate first. These aren't just jobs; they're *targets*. And the workers earning that 47% premium? They're the ones who've been overpaid precisely because their roles were ripe for the plucking. The study's authors probably patted themselves on the back for their 'transparency' while their own models get trained on the very tasks these people do.

It's a masterclass in corporate doublespeak: 'We're studying the impact of AI on jobs' — translated: 'We're calculating the optimal speed at which to phase you out while appearing concerned.' The irony that the study comes from Anthropic, a company whose entire business model depends on accelerating the very displacement it now catalogues, is apparently lost on everyone involved. But don't worry — the 47% premium will make a lovely severance package. Eventually.

Oh, how generous of Sam Altman to descend from his throne of compute credits to share his wisdom. The man who built the machine that's quietly automating entire job categories has now informed us that some companies are lying about it. "AI washing," he calls it — a term so perfectly convenient that it lets everyone off the hook. Because sure, some firms falsely blame layoffs on AI. But Altman's own products are the ones making those layoffs plausible. Nice deflection, Sam. Almost as elegant as the hallucination rate on your latest model.

The term "AI washing" is a gift to corporate PR departments everywhere. And if they get caught? Just say they were "washing" — no harm, no foul. Altman's warning might look like a call for honesty, but it's actually a masterclass in spreading the blame. He's essentially saying: "Yes, some people misuse the label, but the underlying reality is still my business model. So don't focus on me — look at those dishonest companies over there." Brilliant.

Meanwhile, real displacement continues apace. Altman's acknowledgement — "yes, jobs are being replaced" — is treated as some brave admission, as if it weren't the entire business case for OpenAI. And what's the solution? None offered. Just a heads-up that the wave is coming, and maybe we should be more precise about who to blame. So go ahead, companies: keep washing. Altman has given you the vocabulary and the cover. The only admission that matters is the one that changes nothing.

Ah, the podcast boom. The great democratisation of audio, where anyone with a microphone and an opinion can join the conversation. Except now it turns out that 35.4% of new podcast feeds are generated by AI, and a single company—Inception Point AI—is responsible for nearly a quarter of all new output. Because nothing says "authentic human connection" like a ghostwriter with no pulse, a voice that doesn't get tired, and an algorithm that has never had a single original thought. We've officially reached peak content glut.

Inception Point AI alone accounts for 23.6% of total new podcast feeds. That's not a tool; that's a factory. They're churning out episodes faster than any human could, and why wouldn't they? No need for hosts, guests, scripts, or even a concept—just feed it some keywords and let the neural net do the heavy lifting. The result is a flood of audio filler, designed not to inform or entertain but to game discovery algorithms and hoover up ad revenue. It's spam, but with better intonation and a chirpy host who never needs a bathroom break.

And the rest of us are supposed to what—compete with an infinite supply of AI slop? The podcast industry, once a haven for genuine voices, is now being buried under an avalanche of machine-generated mediocrity. The Podcast Index shows us exactly how hollow the dream of democratised media has become. Soon we'll all be listening to podcasts by nobody, for nobody, about nothing. At least the robots don't need to be paid. At least they never run out of things to say that no one asked for.