Microsoft CEO Laments Criticism Of “AI Slop,” Causing The Whole Internet To Double Down On Criticism Of “Microslop”

Overhype

from the have-you-considered-no-longer-being-terrible dept

We’ve noted more than a few times how Microsoft’s use of AI in journalism has been an embarrassing mess. Microsoft’s steadily deteriorating MSN websites have been criticized for years for the lazy use of AI slop, resulting in numerous false headlines, fake stories, and low-quality engagement trash. Like Google and others, the pursuit of impossible scale has made quality and usefulness an afterthought.

Microsoft’s also been broadly criticized elsewhere when it comes to its rushed adoption of AI, whether it’s the privacy implications of the company’s Windows 11 “recall” feature, or forcing the install of Microsoft’s Copilot AI assistant on smart TV owners who never wanted it and can’t uninstall it. Microsoft also adores forcing copilot integration into Windows 11 in ways, again, nobody asked for and often can’t disable.

Copilot may very well be useful to some people; but like most tech companies, Microsoft’s rushed, ham-fisted adoption has been a bit of a tone-deaf mess. And it actively undermines the stuff that LLMs can actually accomplish. This is before you get to the environmental impact of AI, or its quickly-expanding, guardrail-optional use in global military imperialism at the hands of insane autocrats.

This all recently resulted in some fairly significant backlash for Microsoft CEO Satya Nadella. Nadella recently shared a fairly innocuous end-of-year post at LinkedIn.

Most of the short post isn’t really all that interesting or incorrect; he notes that AI is stumbling through a phase where we’re beginning to sort between “spectacle” and “substance,” something that’s likely to result in a big bubble pop this year due the chasm between real-world usefulness and broad tech company misrepresentation of AI (he doesn’t really acknowledge that latter part, of course).

Where Nadella got into trouble was apparently this part, where he fairly innocuously laments the rising criticism of “AI slop.” It was first highlighted by Windows Central:

“We need to get beyond the arguments of slop vs sophistication,” Nadella laments, emphasizing hopes that society will become more accepting of AI, or what Nadella describes as “cognitive amplifier tools.” “…and develop a new equilibrium in terms of our “theory of the mind” that accounts for humans being equipped with these new cognitive amplifier tools as we relate to each other.”

Nadella’s problem here is he dismissively puts the onus on the consumer when it comes to “getting beyond” concerns about AI slop. That dodges any responsibility for the very rich people and companies dictating the entire trajectory of AI to start using it more responsibly.

They aren’t so far; most wealthy tech leaders see AI largely as a way to undermine labor and create a giant lazy badly-automated ouroboros of shallow clickbait garbage that shits out ad engagement cash with very low lift. Often these efforts redirect money away from human artists and journalists and creators into the pockets of some very sleazy people operating with clearly zero ethical guardrails.

The press aggregation machine (much of it ironically now badly automated) latched on to Nadella’s demand that people stop calling it AI slop, immediately resulting in people doubling down on AI slop criticism in a way that made “Microslop” trend across the internet.

Automation, broadly, certainly has its uses and is, generally, not going away. The backlash to AI is, in many ways, tethered tightly and unavoidably to a growing disdain for wealth disparity at the hands of the authoritarian-simping extraction class keen on eliminating literally all ethical oversight of industry.

A great way for billionaires like Nadella to diffuse this growing animosity about their rushed, clumsy, non-transparent, integration of language learning models into everything (whether you like it or not) in ways that aren’t ethical or useful is to, you know, stop doing that. Another great step might be to stop kissing the ass of authoritarians who are actively destroying democracy, civil rights, and the rule of law?

It sounds like many people might be willing to get over AI slop once the billionaires in charge of its development, trajectory, and implementation stop doubling down on AI slop, and stop being tone deaf, irresponsible assholes.

Filed Under: ai, ai slop, automation, billionaires, journalism, llms, msn, satya nadella
Companies: microsoft

Politico’s Union Journalists Win Key Ruling In Battle Against Lazy, Undercooked AI

(Mis)Uses of Technology

from the I'm-Sorry-I-can't-do-that,-Dave dept

The rushed integration of half-cooked automation into the already broken U.S. journalism industry simply isn’t going very well. There have been just countless examples where affluent media owners rushed to embrace automation and LLMs (usually to cut corners and undermine labor) with disastrous impact, resulting in lots of plagiarism, completely false headlines, and a giant, completely avoidable mess.

Earlier this year, we noted how Politico was among the major media companies rushing to embrace AI without really thinking things through or ensuring the technology actually works first. They’ve implemented “AI” systems –without transparently informing staff — that generate articles rife with all sorts of gibberish and falsehoods (this Brian Merchant post is a must read to understand the scope).

Politico management also recently introduced another AI “report builder” for premium Politico PRO subscribers that’s supposed to offer a breakdown of existing Politico reporter analysis of complicated topics. But here too the automation constantly screws up, conflating politicians and generating all sorts of errors that, for some incoherent reason, aren’t competently reviewed by Politico editors.

Actual human Politico journalists are understandably not pleased with any of this, especially because the nontransparent introduction of the new automation was in direct violation of the editorial union’s contract struck just last year. So unionized Politico employees spent much of this year battling with Politico via arbitration. And they just won a key battle in the fight, the first of its kind:

“The arbitrator ruled that Politico officially violated the collective bargaining agreement by failing to provide notice, human oversight, or an opportunity for the workers to bargain over the use of AI in the newsroom.

“If the goal is speed and the cost is accuracy and accountability,” the arbitrator wrote in his decision, “AI is the clear winner. If accuracy and accountability is the baseline, then AI, as used in these instances, cannot yet rival the hallmarks of human output, which are accuracy and reliability.” He also confirmed that the report-building product contained “erroneous and even absurd” AI-generated materials.

Politico leadership have made all sorts of crazy claims in the run up to this ruling, including Politico deputy editor-in-chief Joe Schatz claiming that AI can’t and shouldn’t be held to the same ethical standards as actual journalists, because it was technically created by programmers and not journalists.

In a statement, unionized Politico workers hope this sets a precedent at other news organizations:

“We are going to continue holding the line. This ruling is a great example of the important role unions play in ensuring workers have a say over working conditions–including the rollout of new technologies. I hope it emboldens our colleagues at other news shops across the country fighting AI deployments that similarly degrade ethical standards, and I hope it sends a message to managers at POLITICO and news executives everywhere that adopting new technology cannot come at the cost of accuracy and accountability.”

These aren’t “AI doomers.” They’re people who believe AI can be a useful tool, they just want it implemented competently and transparently, within the lines of existing union agreements.

There are, of course, caveats. Most U.S. journalists aren’t protected by a union, and we live in a country where labor regulators are being steadily lobotomized. And Politico itself, owned by yet another weird rich, Trump-friendly zealot, engages in a lot of false equivalency (“both sides,” “view from nowhere”) journalism with or without the help of undercooked automation.

By and large it’s pretty clear what the extraction class ownership of U.S. media want to build: a lazy, badly-automated, clickbait engagement ouroboros that shits out ad engagement and subscription money without the pesky need to pay so many annoying humans for things like health insurance. A system that basically just props up all of billionaire-ownerships’ laziest priors without interference by the plebs.

But, if nothing else, it’s refreshing to see some effective, organized resistance against the rushed implementation of under-cooked automation by the kind of rich assholes for whom informed consensus and the public interest are the very last thing on their minds.

Filed Under: ai, automation, backlash, collective bargaining, journalism, llms, media, unions
Companies: politico

Trump Withholding Billions In Grants From States That Engage In Corporate Oversight

Failures

from the zero-oversight-of-corporate-power dept

Hoping to repay corporate America’s feckless support of authoritarianism, the Trump administration is once again attempting to illegally ban all state and federal oversight of corporate power. Both via executive order, and by withholding already awarded grants from states that refuse to play along.

The Trump administration has already done generational damage to federal consumer protection and corporate oversight. Now the rich donors pulling the strings are doing their best to take direct aim at any states that might try and fill the void on environmental, labor, or consumer protection.

The Trump administration has tried several times this year to push an unsuccessful blanket ban on “regulating AI.” They like keeping the press attention on “regulating AI,” to push the narrative that they’re protecting American innovation from the mean old government. As opposed to trying to impose a corrupt, blanket ban on all state or federal oversight of unchecked corporate power.

Case in point: earlier this year, Senator Ted Cruz came up with the idea of withholding billions in already awarded infrastructure broadband grants from any state that “regulated AI.” But Cruz’s effort also attempted to punish any state that attempted to enforce their own net neutrality laws, or even make sure that taxpayer-subsidized broadband was affordable.

Ted Cruz’s effort to include these restrictions in this year’s spending bill didn’t work. So the Trump administration is back again with a new executive order that attempts to, once again, withhold already awarded broadband grants from states that try to “regulate AI”:

“Trump’s draft order apparently would apply to about half of the funding available from the $42 billion program, which was created to deploy broadband to homes and businesses without modern access.”

By “regulate AI” it’s again important to understand the Trump administration means “do absolutely anything that upsets corporate America.” While the Supreme Court and circuit courts have done an impressive job destroying federal oversight of corporate America, state autonomy still remains a bit of a wild card in the Project 2025 and corporate quest for total immunity from literally all public accountability.

This isn’t about “protecting innovation from burdensome regulation.” It’s about completely destroying the state and federal government’s ability to protect labor, consumers, markets, or the environment from unchecked corporate power. I feel compelled to annoyingly repeat myself on this point because it’s so often buried in press coverage that tries to normalize corrupt anti-democratic extremism.

In addition to the hijacking of the courts to ensure all corporate oversight efforts fail (see the 5th Circuit’s recent decision to let AT&T off the hook for spying on Americans and selling their location data, the 8th Circuit attack on FTC consumer protection, or the entire Supreme Court Loper Bright mess), the administration has increasingly been hijacking already awarded taxpayer funds for states that don’t play along.

The poster child for this effort has been the $42.5 billion BEAD (Broadband, Equity, Access, and Deployment) broadband grant program created by the 2021 infrastructure bill. Republicans repeatedly demonized and voted against this bill, but love taking credit for its improvements.

Despite the fact that Republicans made a huge election season stink about how long it was taking BEAD to deliver broadband, the program was recently completely rewritten to ensure that Elon Musk and Jeff Bezos get billions in taxpayer dollars for doing absolutely nothing differently, introducing significant new delays for states that were finally on the cusp of oodles of fiber broadband deployment.

Republicans also stripped away any and all language requiring that taxpayer-funded broadband is actually affordable to the public. And they redefined core definitions to make the program generally less useful. Hijacking already awarded funds doled out by Congress is not, you may be surprised to learn, legal. But that’s generally not reflected in press coverage of the program’s sabotage.

As Ars Technica notes, Trump’s latest Executive Order also tries to magically imbue FCC boss Brendan Carr with the regulatory authority to punish states that try and regulate AI:

“The draft order would also require the Federal Communications Commission and Federal Trade Commission to take action against state AI laws. The FCC chairman would be directed to “initiate a proceeding to determine whether to adopt a Federal reporting and disclosure standard for AI models that preempts conflicting State laws.”

Again, that’s… not how any of this works.

With one hand, the Trump administration likes to insist that regulators have zero power to tell corporations what to do. They’ve made very clear progress in defanging all regulatory autonomy when it comes to protecting consumers, labor, or markets.

But with their other hand, the Trump administration likes to pretend they have all manner of vast regulatory authority to tell companies or states what they can or cannot do.

You’ve seen this reflected in the way FCC boss Brendan Carr routinely insists the government has no authority to crack down on Comcast’s shitty behavior, but all the authority in the world to regulate TikTok, punish media companies that engage in journalism that’s critical of Donald Trump, or harass companies that aren’t suitably racist or sexist enough for the president’s liking.

But U.S. courts (so far) have generally found that when the federal government abdicates its authority over federal consumer protection, it can’t then just turn around and tell states what they can or can’t do. This was most notable on the net neutrality front, when the FCC was repeatedly told by courts it couldn’t ignore consumer protection, then ban states from enforcing state net neutrality laws.

The corporate press buries the lede (because most affluent media owners really like this war on the regulatory state), but the goal here is a complete ban of government oversight of billionaires and corporate power.

The nation’s richest certainly don’t want states like Tennessee trying to prevent Elon Musk from engaging in rampant data center pollution of minority neighborhoods, they also don’t want states enforcing labor protections, policing consumer fraud, enforcing “right to repair” laws, punishing predatory telecom monopolies, or anything else.

The Trump election season lie that he’d be a Lina Khan populist antitrust enforcer was pushed by MAGA and assorted useful idiots. Instead we’ve seen a generational assault on state and federal corporate oversight. This has been broadly dressed up as sane policy by the corporate press, “free market” Libertarians and authoritarian zealots, but it’s really just anti-democratic corporatist extremism that’s going to leave a generation of suffering, chaos, and carnage in its wake.

Filed Under: ai, automation, brendan carr, consumer protection, donald trump, fcc, regulation, state rights, states, ted cruz

Study: AI Models Trained On Clickbait Slop Result In AI ‘Brain Rot,’ ‘Hostility’

(Mis)Uses of Technology

from the you-are-what-you-eat dept

While “AI” certainly has some useful applications, a lot of the folks in charge of the trajectory of LLMs clearly want to use it to build a giant, badly automated ouroboros of lazy internet slop that shits out ad money without the need for pesky labor. You see this most profoundly in media, where a bunch of far-too-clever lads rushed to integrate under-cooked, broadly misunderstood LLMs with disastrous results.

These folks could be using AI to make work more efficient; instead they’re using it to cut corners, undermine labor, and fill the internet with a parade of mindless, pointless, low-quality clickbait slop. The sort of lazy engagement bait that hoovers ad money and attention away from folks who actually have something useful to say or contribute.

As it turns out, training LLMs on this kind of slop doesn’t work out well for anybody.

A new joint study by researchers at Texas A&M University, University of Texas at Austin, and Purdue University took a closer look at what happens when you train LLMs on the kind of engagement slop our modern internet gatekeepers are keen to create.

To see how these models would “behave” after subsisting on a diet of clickbait sewage, the researchers cobbled together a sample of one million X posts and then trained four different LLMs on varying mixtures of control data (long form, good faith, real articles and content) and junk data (lazy, engagement chasing, superficial clickbait) to see how it would affect performance.

Their conclusion isn’t too surprising; the more junk data that is fed into an AI model, the lower quality its outputs become and the more “hostile” and erratic the model is:

“All four models tested—Llama3 8B, Qwen2.5 7B/0.5B, Qwen3 4B—showed some forms of cognitive decline. Meta’s Llama proved the most sensitive to the junk, seeing drops in its reasoning capabilities, understanding of context, and adherence to safety standards. Interestingly, a much smaller model, Qwen 3 4B, proved more resilient, though still suffered declines. It also found that the higher the rates of bad data, the more likely a model was to slip into “no thinking” mode, failing to provide any reasoning for its answer, which was more likely to be inaccurate.”

You are what you eat.

They also found that after being fed a bunch of ex-Twitter slop, the models didn’t just get “dumber”, they were (shocking, I know) far more likely to take on many of the nastier “personality traits” that now dominate the right wing troll platform:

“More than just getting “dumber” in its thinking, though, the researchers found the inclusion of junk also resulted in an interesting effect: it led to changes in the model’s “personality,” succumbing to what the researchers called “dark traits.” For instance, the Llama 3 model displayed significantly higher levels of narcissism and became less agreeable. It also went from displaying nearly no signs of psychopathy to extremely high rates of the behavior.”

And by “dumber” and “narcissistic” they of course mean a vague simulacrum of those personality traits, because modern LLMs don’t understand anything, much less adopt real personalities. You’ll often see people (even prominent NYT tech journalists) attributing malicious intent and understanding to language learning models, inadvertently advertising the fact they don’t know how any of this works.

There’s been so much misrepresentation of what these models are capable of (by both companies and the tech media), this comment below needs to be projected onto the moon:

You see this a lot in breathless articles about LLMs that are trying to “resist being shut off” or somehow “blackmail their operators.” It’s simply not how this technology actually works. It’s part of a con suggesting these models are just a few weeks and another billion away from HAL 900 sentience.

Again, none of this is to say LLMs don’t have very useful applications, such as examining vast troves of scientific data to look for patterns and facts that humans might miss. Or creating more efficient, “intelligent” software that can be predictive of the user’s needs or inputs. Or automating basic customer service inquiries in a world full of already-low quality outsourced support.

The problem with AI generally is a decidedly human one: the terrible, unethical, and greedy people currently in charge of it’s implementation (again, see media, insurance, countless others) — folks who have cultivated some unrealistic delusions about AI competency and efficiency (see this recent Stanford study on how rushed AI adoption in the workforce often makes people less efficient).

This is before you even get to the climate and energy impact of these models, or the fact that the underlying financials are a hot mess poised to cause some serious economic tumult next year as the outer layer of hype and misrepresentation burns off. Even then, this quest to turn the internet into an ocean of lazy and uncurated ad engagement slop will remain a centerpiece of the movement.

Filed Under: ai, automation, clickbait, engagement bait, journalism, llms, study

Stanford Study: ‘AI’ Generated ‘Workslop’ Actually Making Productivity Worse

Studies

from the I'm-sorry-I-can't-do-that,-Dave dept

Automation undeniably has some useful applications. But the folks hyping modern “AI” have not only dramatically overstated its capabilities, many of them generally view these tools as a way to lazily cut corners or undermine labor. There’s also a weird innovation cult that has arisen around managers and LLM use, resulting in the mandatory use of tools that may not be helping anybody — just because.

The result is often a hot mess, as we’ve seen in journalism. The AI hype simply doesn’t match the reality, and a lot of the underlying financial numbers being tossed around aren’t based in reality; something that’s very likely going to result in a massive bubble deflation as the reality and the hype cycles collide (Gartner calls this the “trough of disillusionment,” and expects it to arrive next year).

One recent study out of MIT Media Lab found that 95% of organizations see no measurable return on their investment in AI (yet). One of many reasons for this, as noted in a different recent Stanford survey (hat tip: 404 Media), is because the mass influx of AI “workslop” requires colleagues to spend additional time trying to decipher genuine meaning and intent buried in a sharp spike in lazy, automated garbage.

The survey defines workslop as “AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.” Somewhat reflective of America’s obsession with artifice. And it found that as use of ChatGPT and other tools have risen in the workplace, it’s created a lot of garbage that requires time to decipher:

“When coworkers receive workslop, they are often required to take on the burden of decoding the content, inferring missed or false context. A cascade of effortful and complex decision-making processes may follow, including rework and uncomfortable exchanges with colleagues.”

Confusing or inaccurate emails that require time to decipher. Lazy or incorrect research that requires endless additional meetings to correct. Writing full of errors that requires supervisors to edit or correct themselves:

“A director in retail said: “I had to waste more time following up on the information and checking it with my own research. I then had to waste even more time setting up meetings with other supervisors to address the issue. Then I continued to waste my own time having to redo the work myself.”

In this way, a technology deemed a massive time saver winds up creating all manner of additional downstream productivity costs. This is made worse by the fact that a lot of these technologies are being rushed into mass adoption in business and academia before they’re fully cooked. And by the fact the real-world capabilities of the products are being wildly overstated by both companies and a lazy media.

This isn’t inherently the fault of the AI, it’s the fault of the reckless, greedy, and often incompetent people high in the extraction class dictating the technology’s implementation. And the people so desperate to be innovation-smacked, they’re simply not thinking things through. “AI” will get better; though any claim of HAL-9000 type sentience will remain mythology for the foreseeable future.

Obviously measuring the impact of this workplace workslop is an imprecise science, but the researchers at the Stanford Social Media Lab try:

“Each incidence of workslop carries real costs for companies. Employees reported spending an average of one hour and 56 minutes dealing with each instance of workslop. Based on participants’ estimates of time spent, as well as on their self-reported salary, we find that these workslop incidents carry an invisible tax of $186 per month. For an organization of 10,000 workers, given the estimated prevalence of workslop (41%), this yields over $9 million per year in lost productivity.”

The workplace isn’t the only place the rushed application of a broadly misrepresented and painfully under-cooked technology is making unproductive waves. When media outlets rushed to adopt AI for journalism and headlines (like at CNET), they, too, found that the human editorial costs to correct and fix all the problems, plagiarism, false claims, and errors really didn’t make the value equation worth their time. Apple found that LLMs couldn’t even do basic headlines with any accuracy.

Elsewhere in media you have folks building giant (badly) automated aggregation and bullshit machines, devoid of any ethical guardrails, in a bid to hoover up ad engagement. That’s not only repurposing the work of real journalists, it’s redirecting an already dwindling pool of ad revenue away from their work. And it’s undermining any sort of ethical quest for real, informed consensus in the authoritarian age.

This is all before you even get to the environmental and energy costs of AI slop.

Some of this are the ordinary growing pains of new technology. But a ton of it is the direct result of poor management, bad institutional leadership, irresponsible tech journalism, and intentional product misrepresentation. And next year is going to likely be a major reckoning and inflection point as markets (and people in the real world) finally begin to separate fact from fiction.

Filed Under: ai, automation, bubbles, hype, llms, productivity, workslop

AI Slop Startup To Flood The Internet With Thousands Of AI Slop Podcasts, Calls Critics Of AI Slop ‘Luddites’

Overhype

from the badly-made-gibberish-as-far-as-the-eye-can-see dept

So look, I’m not one of these people who thinks “AI” has no useful applications. Just this week I had an efficient conversation with a Gemini chatbot when trying to cancel a Google subscription. I used ChatGPT to help me fact check my own work debunking false claims made by a different AI (an aggregation AI analysis newsbot) while doing research on broadband policy. Isn’t the future grand.

But I do think there’s useful automation, and then just a massive layer of hype, bullshit, fraud, fake profitability estimates, and vast product misrepresentation by the kind of VC hustlebros who profit off the front end of hype cycles, then disappear when the check comes due. These additional layers surrounding “AI” is where the coming bubble pop will happen, something Gartner analysts call the “trough of disillusionment,” which they expect to hit the sector hard sometime next year.

Meanwhile, the rushed application of undercooked automation is having hugely problematic impacts across privacy, energy, climate, propaganda, mental health, public safety, and labor. Often thanks to the kind of people in power who are shaping AI’s application across the culture. A lot of these folks (see: major media owners) aren’t looking to make our lives better, they’re looking to leverage automation as a way to attack labor, mislead people, or create a badly automated ouroboros of ad-engagement bullshit.

Case in point: a new startup named Inception Point AI is preparing to flood the internet with a thousands upon thousands of LLM-generated podcasts hosted by fake experts and influencers. The podcasts cost the startup a dollar or so to make, so even if just a few dozen folks subscribe they hope to break even:

“The company is able to produce each episode for $1 or less, depending on length and complexity, and attach programmatic advertising to it. This generally means that if about 20 people listen to that episode, the company made a profit on that episode, without factoring in overhead.”

Of course just because you can do something, doesn’t mean you should. Podcasting is already a very saturated space full of a lot of useless noise. Flooding the zone with just an endless parade of human simulacrum isn’t going to do great things for the Internet’s already hugely problematic signal to noise ratio, or the public’s ability to differentiate the wheat from the chaff.

And that’s before you factor in the extreme energy and climate costs of generating that noise.

Inception Point CEO Jeanine Wright seems a little sensitive about whether her company is engaged in anything useful or good, quickly dismissing critics of the plan to flood the Internet with focus-group-tested, homogenized slop “Luddites”:

“We believe that in the near future half the people on the planet will be AI, and we are the company that’s bringing those people to life,” said CEO Jeanine Wright, who was previously chief operating officer of podcasting company Wondery, which has recently had to reorganize under the changing podcast landscape.”

And by “reorganize,” The Hollywood Reporter means they recently fired a bunch of human beings in a “pivot to video,” a common dysfunctional siren song across badly managed modern media empires (see Vice and countless others) trying desperately to be relevant in ever-shifting media markets. It’s very possible this “pivot to video” ends like the rest, but many of the questions it presents still stand.

I desperately want to believe that flooding the Internet with homogenized, focus-group-tested blather probably isn’t a winning strategy. I very much want to believe this approach will create a premium value on real people, artists, creators, and journalists who actually have something real to say. But I’ve met many of my fellow Americans, and I’m simply not sure that’s going to be the case.

Inception Point CEO is just one of hundreds of companies flooding this space with cheaply produced simulacrum. What happens when you have an internet packed with quickly made, cheap gibberish? In an era when expertise and real journalism are already under fire by an unholy alliance between corporate power and modern authoritarianism?

Will people flock to informed, intelligent quality? Or will they simply get lost in a maze of badly-automated lazy engagement porn built by people whose singular interest is making money at unmanageable scale with zero concern about the ethical impact (see: Mark Zuckerberg), making informed consensus and factual reality harder to collectively grasp than ever?

I’m not sure anybody knows yet. You’re certainly not being a “Luddite” if you ask. Meanwhile, Inception Point AI already has more than 5,000 shows across its Quiet Please Podcast Network and produces somewhere around 3,000 episodes a week, with 10 million downloads since September 2023.

Filed Under: ai, automation, bubble, hype, llm, podcasts, simulacrum
Companies: inception point

Business Insider Pulls 40+ Essays After Getting Conned By AI-Using Scammers

(Mis)Uses of Technology

from the I'm-sorry-I-can't-do-that,-Dave dept

Earlier this month, we noted how Wired and Business Insider were among a half-dozen or so major news organizations that were busted publishing fake journalism by fake journalists using AI to make up completely bogus people, narratives, and stories. The Press Gazette found that at least six outlets were conned by a fraudster going by the name of “Margaux Blanchard.”

A week later and the scandal is much bigger than originally stated.

Business Insider has had to pull upward of 40 stories offline for being fabricated. Washington Post and Daily Beast have found that “Margaux Blanchard” appears to be part of a much larger operation using “AI” to defraud news outlets and mislead the public. Most of the pieces were fake personal essay type writing for experiences that were completely made up, by a rotating crop of different fake authors.

And most of this stuff should have been caught by any competent editor before publication:

“The Beast’s review found several red flags within the since-deleted essays that suggest the writing did not reflect the authors’ lived experiences. This included contradictory information in separate essays by the same author, such as changing the gender and ages of their supposed children, and author-contributed photos that reverse-image searches confirm were pulled from elsewhere online.”

Recall that back in May, Business Insider executives celebrated the fact they had laid off another 21 percent of their workforce as part of a rushed pivot toward automation. But not only does that automation have problems with doing basic things (not plagiarizing, writing basic headlines, and citations), it’s opened up new problems in relation to propaganda and fraud.

Again, early LLM automation has some potential. But the kind of folks who own (or fail upward into positions of management at) major corporate media outlets primarily see AI as a way to lazily cut corners and undermine already underpaid and mistreated labor. As you see at places like Business Insider and Politico, these folks don’t appear to genuinely really care whether AI works or makes their product better. In large part because they’re exceptionally terrible at their jobs.

There’s automation and what it can actually do. And then there’s a deep layer of fatty fraud and representation by hucksters cashing in on the front end of the AI hype cycle. That latter part is expected to have a very ugly collision with reality over the next year or so (it’s something research firms like Gartner call the “trough of disillusionment.”) Others might call it a bubble preparing to pop.

Most extraction class media owners have completely bought into the hype, in part because they really desperately want to believe in a future where they can eliminate huge swaths of their payroll with computers. But they’re not apparently bright enough to actually see the limitations of the tech through the haze of hype, despite no limit of examples of the hazards of rushed adoption of undercooked tech.

Filed Under: ai, automation, brunchlords, fraud, generative ai, hype, journalism, llms, media, scam
Companies: axel springer, business insider

Politico Management Insists “AI” Shouldn’t Be Held To Any Sort Of Human Editorial Standards Because It’s Built By Coders, Not Journalists

(Mis)Uses of Technology

from the I'm-Sorry-I-Can't-Do-That,-Dave dept

The rushed integration of half-cooked automation into the already broken U.S. journalism industry simply isn’t going very well. There’s been just countless examples where affluent media owners rushed to embrace automation and LLMs (usually to cut corners and undermine labor) with disastrous impact, resulting in lots of plagiarism, completely false headlines, and a giant, completely avoidable mess.

Earlier this month, we noted how Politico is among the major media companies rushing to embrace AI without really thinking things through or ensuring the technology actually works first. They’ve implemented “AI” systems –without transparently informing staff — that generate articles rife with all sorts of gibberish and falsehoods (this Brian Merchant post is a must read to understand the scope).

Politico management also recently introduced another AI “report builder” for premium Politico PRO subscribers that’s supposed to offer a breakdown of existing Politico reporter analysis of complicated topics. But here too the automation constantly screws up, conflating politicians and generating all sorts of errors that, for some incoherent reason, isn’t reviewed by Politico editors.

Actual human Politico journalists are understandably not pleased with any of this, especially because the nontransparent introduction of the new automation was in direct violation of the editorial union’s contract struck just last year. So unionized Politico employees have since been battling with Politico via arbitration.

On July 11, the PEN Guild (which has about 250 Politico union members) and Politico held an arbitration hearing to determine whether the publication had broken its collective bargaining agreement. Nieman Lab obtained access to the arbitration hearing transcript, at which Politico higher up editors tried to claim that automation shouldn’t be held to the same editorial standards as humans.

Specifically asked about the problems with Report Builder, deputy editor-in-chief Joe Schatz insisted that because Report Builder was technically built by coders, and its output isn’t reviewed by professional editors (which is insane) it shouldn’t have to adhere to the site’s broader editorial standards:

“He went on to argue that Report Builder sits “outside the newsroom,” since Politico’s product and engineering teams built the tool and editorial workers don’t review its outputs. As a result, he said, the AI-generated reports should not be held to the newsroom’s editorial standards.”

That’s… incoherent. LLMs are tools, they’re not inherently exempt from editorial standards and material reality just because management is bullish on AI. The CEO of Politico Owner Axel Springer, Mathias Döpfner, recently introduced a company wide mandate that every single employee in the organization has to not only use AI, but consistently file reports justifying why they don’t. It’s rather… cultish.

This tap dancing around what constitutes “newsgathering” is effectively a way for Politico management to try and tap dance around their contract with union employees, since said contract plainly states:

“If AI technology is used by Politico or its employees to supplement or assist in their newsgathering, such as the collection, organization, recording or maintenance of information, it must be done in compliance with Politico’s standards of journalistic ethics and involve human oversight.”

Again, most U.S. media is owned by affluent older, white, Conservative men who generally see AI not as a way to make their products or employees’ lives better or more efficient, but as a way to cut corners and undermine already underpaid labor. Men like Döpfner, who like our authoritarian President, and whose editorial standards and relationship with labor were pretty fucking shaky to begin with.

These men want to create a fully automated ad engagement ouroboros that effectively shits money without having to pay humans a living wage, and that goal is evident everywhere you look.

In an ideal world this would result in surging demand for intelligent, savvy journalism and analysis by competent, experienced people who actually have something to say. But this isn’t an ideal world, and increasingly the kind of folks dictating the trajectory of U.S. media (and automation) are routinely demonstrating they lack any sort of ethical competency for the honor.

Filed Under: ai, automation, generative ai, journalism, labor, llms, media, newsrooms, politico, unions
Companies: axel springer, politico

Politico’s Rushed Adoption Of Half-Cooked ‘AI’ Continues To Go Terribly

(Mis)Uses of Technology

from the I'm-sorry-I-can't-do-that,-Dave dept

We’ve noted repeatedly how early attempts to integrate “AI” into journalism have proven to be a comical mess, resulting in no shortage of shoddy product, dangerous falsehoods, and plagiarism. It’s thanks in large part to the incompetent executives at many large media companies, who see AI primarily as a way to cut corners, assault unionized labor, and automate lazy and mindless ad engagement clickbait.

The folks rushing to implement half-cooked AI at places like Red Ventures (CNET) or G/O Media aren’t competent managers to begin with. Now they’re integrating “AI” with zero interest in whether it actually works or if it undermines product quality. They’re also often doing it without telling staffers what’s happening, revealing a widespread disdain for their own employees.

This sort of behavior has been particularly problematic at the DC gossip rag Politico, where ownership continues to implement “AI” systems that don’t really work all that well, constantly introduce new errors human editors have to correct, and engage in “behavior” that violates editorial standards. All without the input and knowledge of actual journalists or editors.

This rundown on the Politico AI mess by Brian Merchant is worth a read. He documents how in one instance, Politico Editorial staff were told just an hour before a new AI product was introduced, given zero chance to ask questions about how it would work, why it was there, or why it was being launched. The tech then immediately proceeded to make a bunch of embarrassing, rookie mistakes:

“The AI promptly generated a post that misspelled Kamala Harris’s mother’s name. The entry was taken down without comment or correction from an editor, in apparent violation of Politico’s editorial standards. Weeks later, Politico’s management deployed the AI tool again, this time in an even higher-profile setting: The vice presidential debate between JD Vance and Tim Walz. The feature again trampled editorial guidelines, this time transcribing verbatim Vance’s comments about “illegal immigrants”—a term that Politico writers are not allowed to use, and editors are not supposed to publish.”

Politico management introduced another AI “report builder” for premium Politico PRO subscribers. It’s supposed to offer a breakdown of existing Politico reporter analysis of complicated topics. Apparently the “AI” sucks at doing that, as well:

“It’s wholly behind the paywall, but when we have asked it things, it’s giving us back some pretty glaring errors,” [Politico journalist Ariel] Wittenberg says. “I asked it about ‘The Impact of President Biden’s Oil Policies,’ and it wrote me a whole page-and-a half thing, and every single policy it mentioned was a policy of Trump’s. And it cited real stories at the very bottom, from our members, the implication being that if someone is reading this, and it’s erroneous, not only does our AI not know the difference between Biden’s policies and Trump’s, but maybe the authors of the cited articles didn’t, either.”

Great stuff! This reflects the same experiences with other major media outlets that expect LLMs to genuinely understand their own outputs. You’ll recall that Apple had to pull its AI news synopses system because the AI routinely introduced glaring mistakes; VC “AI” marketing has many execs believing we’re just a few steps from full sentience, when these systems are still struggling with the very basics.

We’ve seen the same nonsense over at Microsoft, which was so keen to leverage automation to lower labor costs and glom onto ad engagement that they rushed to implement AI across the entirety of their MSN website, never really showing much concern for the fact the automation routinely produced false garbage. Google’s search automation efforts have been just as sloppy and reckless.

Again, the “automation” in this instance is also a direct reflection of the quality of Politico’s ownership, who likes Trump and actively embraces lazy “both sides” journalism that buries the truth in pursuit of fake ideological objectivity. It’s not any sort of coincidence that owners who don’t care about journalism, transparency, labor, or factual reality introduce broken tools that harm all four.

In this case, the introduction of the new automation wasn’t just rushed and lazy, it was in direct violation of the editorial union’s contract struck just last year. So union employees have since been battling with Politico via arbitration:

A lot of affluent media owners have also just completely drunk the marketing Kool-Aid on modern “AI” as just a few skips away from full sentience; they genuinely believe modern LLMs are more capable than they actually are. And they’re soo keen on using this emerging technology to cut corners, “save money” and undermine and replace pesky unionized labor, they’re blind to the fact it often doesn’t work.

The CEO of Politico Owner Axel Springer, Mathias Döpfner, recently introduced a company wide mandate that every single employee in the organization has to not only use AI, but consistently file reports justifying why they don’t. This sort of stuff goes way past useful technological adoption and teeters into delusional religion, and the technology becomes a window into very ordinary human failures.

Filed Under: ai, automation, errors, journalism, labor, llms, mathias dopfner, media, politico, unions
Companies: axel springer, politico

Our National Robocall Nightmare Is Getting Worse Under Donald Trump

(Mis)Uses of Technology

from the this-is-why-we-can't-have-nice-things dept

According to the latest data on robocalls from the YouMail Robocall Index, the scale of the U.S. robocall problem has grown by another eleven percent year over year. U.S. consumers received just over 4.8 billion robocalls in May. We’ve normalized ceding our primary voice communications platforms to corporations, debt collectors, and scammers, and there’s every indication it’s going to get worse under Donald Trump.

While the federal government had been making some progress in getting wireless companies to belatedly adopt anti-spoofing technology, the Trump administration’s decision to lobotomize whatever was left of U.S. regulatory independence and consumer protection will indisputably leave regulators flat-footed in the ongoing battle to reclaim U.S. voice networks from scumbags.

The FCC still technically exists, but under Trump it’s become a weird and pointless grievance machine run by zealots. Its primary function during Trump’s term so far has been to harass companies for not being sexist or racist enough, or threaten media companies that dare do journalism critical of King Dingus.

Consumer groups like the National Consumer Law Center have repeatedly warned Congress that the key reason our robocall problem never gets fixed is because Congress and regulators routinely fixate on scammers and not on the “legit” companies like debt collectors that use the same tactics and routinely undermine reform and enforcement efforts.

YouGov’s latest study found that “just” 14 percent of May’s robocall total was from “scammers.”

Even before Trump, a corrupted court system had consistently limited the FCC’s authority to combat robocalls. Corrupt lawmakers and regulators, cowed into blind obedience by a massive, generational, cross-industry-lobbying campaign, like to keep the focus on scammers, when many “legit” companies, again, leverage the exact same tactics as scammers.

As a result, federal regulators refuse to hold large phone companies accountable for their lagging efforts to combat fraud and spam. Case in point: Truecaller’s U.S. Spam and Scam Report found that half of all major U.S. phone companies earned a D or F in their efforts to combat annoying robocalls and scams. Functional, developed countries (even many less developed ones) don’t have these problems.

So while the FCC is supposed to enforce robocall offenses and levy fines, terrible court rulings mean they aren’t allowed to collect fines. That’s left to the DOJ, which routinely just… doesn’t bother. As a result a comically small volume of the overall fines levied are ever actually collected. For example between 2015 and 2019 the FCC issued $208.4 million in robocall fines, but collected just $6,790.

And again, this is all before Trump 2.0. And before largely unregulated AI.

Trump FCC boss Brendan Carr has been promising to take a hatchet to whatever is left of U.S. corporate oversight as part of his “delete, delete, delete” deregulatory initiative. Big telecoms and robocallers have been making it very clear they’re very excited about it. Debt collectors in particular are very eager to roll back already flimsy rules governing how badly they can harass people they already know can’t pay.

Like so many systemic U.S. problems, the robocall menace isn’t something that gets fixed without first embracing much broader corruption, campaign finance, lobbying, and legal reforms. That is, obviously and indisputably, not something that’s happening under Trump and his sycophantic regulators and telecom industry-coddling courts.

Filed Under: automation, corruption, cramming, fraud, phone calls, robocalls, scam, scammers, telecom