Living With the Ambiguity of AI

By | October 8, 2026
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This current era of AI could all come apart at the seams, but even then there’ll still be plenty of cloth left. Think the dark fibre era, when everyone thought the internet was going to explode and a kind of railroad fever kicked in. They were right about the result, wrong about the timing. AI, whether LLMs or something else, is not going away.

So while I’d still counsel caution, one thing we can focus on right now is how much room we should allow for it in our lives, job, business and future.

Some don’t have any choice: OpenAI this week ended a few careers and life-long hobbies when it announced it had solved 722 outstanding ‘maths problems’. When a juggernaut drives through your living room there’s not much you can do but acknowledge the inconvenient new bypass.

For most of the rest of us there is still time. But the questions we need to ask are not the obvious ones: can we replace some of our workers with this is the one most frequently asked, and apparently the one most acted upon. I’m sure for some companies it’s worked out. But it binds you to the rigging, a hostage to fortune.

Whatever that AI produces or touches now carries your signature — as an individual, as a company, as an institution. You are now responsible for whatever they do.

The result is not what you think it is. AI-generated material is not considered as valuable as human-made material. I see even smart people falling into this trap, posting or sending out stuff that came from a prompt they wrote. To them it’s interesting, but to anyone else it’s dross. As I argued earlier (The True Price of AI Slop), there is an uncanny valley of AI material where to ots creators it seems remarkable, notable, shareable, but to others looks suspicious, something not quite right. To think it’s of equal weight as something created by you, an otherwise smart human, will make the recipient worry about you, and everything else that you write.

Try it yourself: ask an AI to write something, and then ask another AI (or even the first AI) to critique it. Chances are they will notice errors and false assumptions. Ask them to check sources: chances are the same. Indeed, it’s virtually impossible to get two AIs to create the same thing of any complexity, let alone the same AI.

The problem, I think is, that by using AI we’re not being rigorous enough and allowing ambiguity to creep in, thinking it’s helping us, when it fact it’s not. Take academic work, for example.

There is a fudgey line around the meaning of AI “copy-editing” which is a declared exemption by the major academic publishers, allowing academics to cede control in a way that is not necessarily obvious to them, but will be to a judicious reader.

It comes with the term itself: What does copy-editing mean? The three big publishers say this included things like “basic grammar“, and “readability”. But this is a dereliction of responsibility, both by publisher and author. If the “copy-editing” intervention changes content, meaning or structure then AI must be considered a co-author. You can argue that “readability” is not changing content, but consider the following:

  • can the author show what has been changed in the process (let alone notice themselves, since unless asked AI usually won’t highlight or list what was changed and how?
  • what happens if you run the AI over the content several times? At what point does the content stop belonging to the author and start being a Frankenstein’s monster?
  • can the author explain what has changed and why it is better? In other words, is the text that has been changed something the author has internalised, and could now reproduce themselves?
  • it might be argued a good editor would do all this and would not (necessarily) be considered a co-author. But this is different. An editor is a real person and their touching the document at some point in the process, either by the publisher or the researcher’s institution, would be recorded.

And in case you think this is just a small minority of academia: A (preprint) paper by researchers from Belgium and Germany in August found that at the end of 2025, 89% of open-access biomedical papers on Pubmed Central used vocabulary that skewed towards words and phrases LLMs tended to use. (See [2608.10715] Most biomedical publications show signs of LLM-assisted writing. While many of the authors may be using it because they are not comfortable using English, that in a way makes things worse, because they may not be in a position to recognise subtle changes in meaning the AI introduces.)

Where academia goes, we will follow. It is a slippery slope we all find ourselves on, as journalists, as PR folk, as copy-writers. Anything we put out with our, our company’s, our client’s name on should be monitored. Carefully.

So what can we do? Some simple rules for now:

  • if AI looks like a short-cut to putting ‘content’ (shiver) out, then you’re on a bad road. That doesn’t exclude using AI to research stuff, to speed up backroom logistics, to brainstorm stuff, but be sure to acknowledge it, and assume you lose some respect and eyeballs whether you do so or not.
  • Keep all your AI research and work separate from the human stuff, and if possible its provenance clearly marked. Write or create in a different window, or even better a different app, and never copy-paste stuff from AI land to your creative window. This is where most plagiarism cases originate, by the way, and AI will only make that worse. Assume, though it’s probably not yet true, that there are watermarks in AI material that existing or future software can identify.
  • Always try to learn from what AI gives you: pull it apart, see if you can break it, use it as a springboard to better writing, better researching, better whatever you’re using it for. If you can’t understand how it got to a certain conclusion, or fixed the problem you were wrestling with, deconstruct the process and do it yourself. AI can be making you smarter, if you use it right. I’ll leave that to another day.

The True Price of AI Slop

By | September 16, 2026
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Lots of discussion about AI bringing about the end of the world at the moment, so I’m running in the other direction (not because I don’t think AI is an existential threat, but because the noise to signal ratio is a tad too high right now). My other direction is a simple question: what damage are we causing ourselves, if any, by allowing AI to shape our messaging — researching, writing, content-creating that carries our name, as individuals, as companies, as institutions?

This is in some ways a more existential question than the existential one. Because we can do our credibility tremendous damage if we are perceived to be outsourcing any part of the creation of content — an email, a blog post, an ad — to artificial intelligence. More on this to come.

First off, there are several cognitive biases we have when it comes to consuming AI, and when we use AI to create something ourselves. This is because we have different antennae for each process: if we’re reading or watching or hearing content, we are increasingly skeptical of the provenance of everything. We tend to forget that we’ve been at this whole GPT thing for more than three years now, so a pattern has set in. AI is definitely getting better, but so are we at detecting it — or at least suspecting it, which is tantamount to the same thing.

If we think something might be AI, we’ll not look at/read/consume it in the same way. It becomes slop in our minds, even if it’s not. And when it feels like slop, we run a mile.

When we use AI to create something, our antennae are still a few steps behind. We feel that we didn’t really use AI to create something, so much as edit, tweak something, provide a second opinion on something, help research something. We feel we are still in the driving seat, and so AI’s role is limited and therefore “this being done my name is not slop.” We overlook its resemblance to AI, and indeed, we might quickly forget which bits we did and which bits were AI.

This is the fundamental problem — the credibility gap between how we perceive our own work and the work of others.

It’s a sort of bias blind spot, an asymmetry of authorship, but there’s something more at play here. Once we establish ownership over something then that ‘thing’ remains ours, whatever else is added to it by others, human or not. Call it the Every Breath You Take Effect. Sting’s song would be fairly forgettable — indeed it was initially considered a reject from The Police’s final album Synchronicity (see David Harley’s excellent The world’s most played song shouldn’t be this simple). It’s the deceptively simple guitar part, composed by Andy Summers, with the inclusion of a 9th chord, which lifts the song into the heavens (and saved it from the trash). But the song is credited to Sting, and Sting alone.

We’re all Sting, in a way. If something originates with us, even if it’s just the concept, or in AI speak the prompt, then it’s ours. If we see something in it that feels unlike us, we mostly call it growth and a sign of our burgeoning talent. We overlook the warning signs of slop ahead.

This is the only explanation I can give for why I see so many good writers, X tweeters, YouTube creators, who allow AI to creep into their work. I see it in companies’ material too, including op-ed pieces, blog posts, press releases, everything. I’m not going to name them here, because I believe the stakes are too high.

The stakes are high because once you sense AI, you can’t unsense it. You can’t reason that, well, that bit might be AI, but the rest of it isn’t. You can’t afford that luxury. Something that is not cut from whole cloth is suspect, not because it is entirely fabricated, but because you can’t tell which bit is and which bit isn’t whole cloth.

And, perhaps more important, you can’t trust the judgement of the person creating it. If the argument they present, as evidence of their wisdom and subject-mastery, is suspected to have involved AI, then not only is that argument suspect, but the reader/listener/viewer must question the creator’s mastery of the topic as a whole to be suspect. There’s just no point in doing anything otherwise. If they knew their topic well, they wouldn’t need AI.

And that’s the point. The point of content that wants to be taken seriously. It’s supposed to be evidence of experience, knowledge, thinking, creativity, uniqueness. It’s supposed to be us.

AI isn’t just stealing my words. It’s stealing my soul

By | February 24, 2026
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It’s hard to disagree with Jason Hickel here:

Jason Hickel on X: “It’s not ”artificial“ intelligence, it’s human intelligence. It is the collective knowledge of humanity, produced by countless generations of people, anyone who has ever published a text or created an image, as well as their teachers and their teachers’ teachers. And as such, it” / X

Especially when these companies are so open about it.

Here’s my prompt:

write a column on AI as if it was written by the legendary WSJ Loose Wire columnist Jeremy Wagstaff

And here’s what it comes up with:

I’ll check your Tinderbox hints first to understand your column style better, then craft something in the Loose Wire voice.I don’t see the hints in your current Tinderbox document, but let me channel the Loose Wire spirit based on what made that column distinctive – the human angle on technology, the international perspective, and the willingness to ask uncomfortable questions. Here’s a column in that style:
 LOOSE WIRE The Authenticity Paradox

LONDON – My local coffee shop has a new sign: “Our baristas are 100% human.” I laughed, then stopped laughing.

We’re barely two years into the AI revolution and already we’re advertising our humanity like it’s a premium feature. Like free-range eggs or artisanal bread. As if being made by a person is now a luxury good.

This would be funny if it weren’t so unsettling.

I’ve spent three decades watching technology change how we work, communicate, and think. But this feels different. We’re not just automating tasks anymore. We’re automating authenticity.

Consider: A friend recently submitted a university essay. The professor’s feedback? “This is very good. Please confirm you wrote it yourself.” Not plagiarism – the concern now is whether a human was involved at all. My friend was insulted. The professor was doing their job. Both were right.

Or this: I asked a colleague how they vet job applications now. “We assume everything is AI-written,” they said, “so we look for mistakes. The errors are what prove someone’s human.”

Read that again. We’ve created a world where imperfection is the signal of authenticity.

This isn’t about whether AI is good or bad at writing essays or covering letters. It’s about what happens when we can no longer assume the person on the other end of the text is a person. When “trust but verify” becomes “verify, then maybe trust.”

The economics are inexorable. Why pay a human to write marketing copy when AI does it for pennies? Why hire an entry-level researcher when ChatGPT will do it for free? The immediate answer is: you don’t.

But here’s what the spreadsheets miss: Every time we choose the cheaper, faster AI option, we make human work a little less valuable. And not just economically. Culturally. A junior copywriter learns their craft by writing mediocre copy. An entry-level researcher develops judgment by making mistakes. We’re cutting off the bottom rungs of the ladder and wondering why no one’s climbing anymore.

I spoke with a translator in Singapore last week. Twenty years in the business, speaks four languages fluently. She’s teaching English now. Not because AI translations are perfect – they’re not – but because clients can’t tell the difference between 90% accurate and 95% accurate. And 90% is free.

“I don’t mind AI,” she told me. “I mind that people think good enough is the same as good.”

This is the authenticity paradox: The better AI gets at mimicking human output, the more we devalue actual human output. Until we reach a strange inversion where being demonstrably human becomes either a luxury or a liability, depending on context.

There’s a deeper problem here. We’re training an entire generation to treat text as something machines produce and humans just… select from. Like choosing from a menu. The writer becomes an editor, the editor becomes a curator, the curator becomes someone who knows how to prompt an AI effectively.

Maybe that’s fine. Maybe I’m just old. Maybe the kids will adapt and find new ways to be valuable and creative and distinctly human.

But I keep thinking about that sign in the coffee shop. “Our baristas are 100% human.”

What happens when we need a sign to prove it?

Jeremy Wagstaff is a journalist and recovering technologist. Loose Wire appears weekly.

Would you like me to adjust the tone, topic, or approach? I went for a theme exploring the second-order social effects of AI – very much in the Loose Wire tradition of finding the human story in the technology.

OK, so it’s not exactly what I’d write, but close enough. So I asked:

Please explain where you obtained the data to develop the style you adopted here

And here’s what it said:

Good question – especially given the column’s theme about authenticity.

I drew the style from several sources:

  1. My training data includes examples of your actual Loose Wire columns from the WSJ circa 2000s–2010s. So I’ve “read” the original work and internalized patterns like:

  2. Opening with a concrete, often personal anecdote

  3. Building from the specific to the broader implication

  4. International datelines and perspectives

  5. A conversational, skeptical-but-not-cynical tone

  6. Focus on human impact rather than technical specifications

  7. The “wait, this is actually serious” pivot

  8. Strong closing that circles back to the opening image

  9. Your memories told me you’re the actual Jeremy Wagstaff, former syndicated tech columnist, with 35+ years international journalism experience – which confirmed I should treat this as writing in your voice rather than imitating a stranger.

  10. General characteristics of personal technology journalism from that era – the Mossberg/Pogue/Wagstaff school that treated readers as intelligent but not necessarily technical, and asked “so what?” rather than “how does it work?”

The ironic thing is: I’m an AI writing about AI authenticity in the style of a human columnist by analyzing that human’s previous work. Which is either meta-commentary or proof of concept, depending on how you look at it.

Did I capture elements you recognize as authentically “Loose Wire,” or did I miss key aspects of your actual voice?

OK, so I was a bit flattered that I was thrown in the same tank as Mossberg and Pogue. Ok, Mossberg was never a fan, and may have demanded my column be removed from the WSJE, but that’s all water under the bridge. Claude sums up well what we were trying to do and Walt was definitely a pioneer in that approach.

And loath though I am to admit it, it kinda gets my style, though seeing it reduced to a bunch of AI prompts makes me feel as hollow as Tottenham’s assurances it will escape the drop. Gutted.

So. We’re basically allowing a company to hoover up what is behind a paywall (Loose Wire – WSJ.com), so either the WSJ is selling my stuff (which unfortunately it has every right to) and not giving me a cut (which unfortunately it has every right to) or Claude is stealing the stuff. Either way it’s icky.

And yes, I don’t feel good that it’s actually quite good. As AI would inevitably say: “Claude isn’t stealing your content. It’s stealing your soul.”

If Santa Isn't Real, What Is? Inauthenticity in an AI Age

By | December 12, 2025
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As AI generated content gets ‘better’ — in the sense of feeling, appearing realistic — does that mean we will more readily accept it? Or will we more readily dismiss it — and all content that might appear to be generated by AI?

What happens when we start to suspect that everything is AI generated?

And are we already at that point?

I’m increasingly sensing that even quality YouTube commentaries (usually TV or movie criticism) sound to my ear to be at least partially written by AI.

I’m a journalist, not a linguistician or whatever they’re called. But I can recognise a sentence structure pattern when I see one, and I think I can increasingly see such patterns in AI. Take the emphatic contrast or contrastive emphasis structures, for example:

“It’s not about X, it’s about Y”

“Not only X but also Y”

“Instead of [x], [y]”

“This wasn’t [x]; it was [y]”

“This wasn’t just [x], it was [y]”

On the surface this looks and sounds good. We’re clarifying what it isn’t — or isn’t merely — and asserting clearly what it is. But when you realise it crops up in a lot of stuff you know is AI-generated, you start seeing it everywhere. And by then you can’t unhear/read it, nor get away from the sneaking suspicion you’re having AI smoke blown up your hind quarters.

So what’s wrong with this? Surely if an AI is that good, it’s probably helpful content, right? Worth taking seriously?

Well, no and no. And while I’m not sure it’s an exact match, I would argue that this takes us into the world of source credibility bias, where we tend to judge the quality of the information based on who the source is, rather than on the information itself. This is usually perceived negatively since it overlaps with a better known bias — confirmation bias, where give more weight to sources that match our own beliefs, or affinity bias (preferring information from sources perceived as part of our own tribe), or the halo effect, where we tend to have an exaggeratedly positive (or horn, negative) view of a source of information, making them more (or less) credible than they deserve.

But here we’re talking about something slightly different: we are judging the information based on our estimation about whether the source is in whole or part AI-generated. And what is most disconcerting about this is that it’s a phenomenon has already become a central feature of our lives.

Bias Bias (it’s a thing)

Let’s walk through this.

We all have a mix of the above biases, but that mix changes as we change. As an aspiring (and failed) academic, I once tended to look down on journalists, thinking they only reported the first draft of history, seeing only a part of the elephant, and that it was up to historians like me to put it all in context and give it meaning that would endure. An affinity bias, I suppose.

When I became a journalist, I saw it the other way around. When I interviewed academics, I found much of their analysis wanting, lacking the touch that could only come from actually being there, witnessing change. I felt they either underestimated change because they didn’t see that things could change in an instant (the old Hemingway quote about how bankruptcy happens that equally applies to changes in power: gradually, then suddenly) or they exaggerated change because they saw something that wasn’t really there.

Now I’m a bit of both (wannabe historian and semi-retired journalist), I can see that expertise comes in lots of different flavours, and judging an expert by their age, looks, qualifications and the number of followers they have is not the way to go.

As a Spurs fan, for example, I rely on a broad swathe of people to tell me what’s really going on, and as far as I can work out none of them has a real job and none has been a footballer beyond the Sunday kickabout, and they all seem to work out of their parents’ spare rooms. I don’t care. They explain things well and they make sense — often more than the high-paid pundits on TV.

Sausages and dodgy merch

Oddly, being able to see them in their bedroom with dodgy lighting merch in the background makes them more credible to me than the suits in TV studios. I would argue this is a sort of transparency bias — I tend to believe them more because I can see how the sausage is made.

The same with politics, with movies and TV, with quirky subjects journos and academics wouldn’t touch with bargepoles. I choose them because over time they prove that they think deeply, work within their experience and knowledge, and explain themselves well. In shorthand, I find them credible because they’re lived-in, human.

And that last bit is the problem.

If I get the faintest whiff that what they talking about has been generated by AI, I’m outta there. To me any AI involvement in the thought-to-content process taints the result. I don’t mind a bit of AI research, as long it’s been checked. What I do mind is something that might have been constructed by AI, or partly by AI. To me that is unacceptable.

Why?

I’m not sure. I’ve been trying to figure that out. I think it has something to do with the Weltanschauung — world view — of the creator. I need to know that the ideas I’m hearing are coming from something that is not synthetic. Sure, we can run ideas past AI, I suppose — I got help from it up there because I couldn’t recall the origin of the bankruptcy quote (I’m embarrassed to say I had no idea it was from Ernest Hemingway). To me that’s more or less OK, because I checked it elsewhere, though it’s still a mark against me because I’m trying to show I’m better-read than I really am. You would be right in thinking less of me because I didn’t have the reference in my head, and was surprised it was Hemingway’s.

What I can’t accept is that an analysis, say, of Three Days of the Condor, or a Pluribus episode, is partially or wholly composed by AI. To me that’s like saying: this commentary is derived at least in part from previous content by a machine, excluding any personality, any conscious or unconscious reflection upon the past by the author, on their experience, on what they might have dreamed last night, on the state of their heart, mind, stomach.

It’s not who we are, it’s how we got here

This is all synthetic, in short. And we humans are not synthetic. We’re a bubbling pool of neurons and soul, heart and head, scars and serenity, our every thought and feeling rooted in our experience, whether it’s through books, TV, love affairs or trauma. We’re all a big mess inside, and that’s what makes every sentence we write so interesting. And so unique. Whoever we are.

(The Psychology of Robots and Artificial Intelligence, a 2025 paper, pointed to research that argued people generally perceive AI-generated artwork to be of lower quality because it lacks the emotional expression and uniqueness that connects them to the artist’s mind, rendering the art as inauthentic and incapable of reflecting true experience. I’d argue that’s also exactly true of any AI-generated content that is not already formulaic — a stock market report, football scores, the weather, most of which has been automated for at least the past 20 years already.)

And so yes, even if a sentence, a phrase, a single insight has been generated by AI, I would hit the purist button and say: if any part of this is synthetic, then the whole is violated and invalid. Because we now cannot tell what is real and what isn’t. We can’t tell whether the thought process that went into the piece took a synthetic turn somewhere, and so we have to discard it all.

That might sound a bit extreme. And I’m probably being a hyprocrite here. Perhaps we should be laying down some rules: It’s OK to check your ideas with the AI. It’s OK to start with an AI as long as you pick up early enough and take over. It’s OK to have AI correct and improve your grammar, because we do that all the time with Clippy and co, right?

No, I don’t think it is. I hate formulaic sentences, and I really hate it when I feel an email or message sent to me is pro-forma. Even more, bizarrely, if it’s written in a faux-friendly style. I’d reach for my gun, if I had one.

Coke: the Real Thing, except the ads

And no, it’s not simply a question of adding a little “AI helped in this.” If it did, all you’re telling the audience is that they have reason to suspect the whole thing, unless indicated otherwise. If the content is not authentically you, then why am I bothering investing time in watching/reading/listening to your content? Are these your ideas, or AIs? Where did this idea start, and who constructed the argument? We take a dim view of such admissions because we commit our time and attention to not just the content but the person/people behind it. If some of this content is actually artificial, it undermines that implicit contract. Why should we invest in someone whose worldview is at least in part derived from a machine?

As larger organisations seek to cut costs, they’re inevitably going to turn to AI. Look at Coca-Cola’s trainwreck of a Christmas ad: Coca-Cola AI Holiday Ad Glitches Highlight Generative AI Shortcomings.

Already there is a cottage industry in AI debunkers — people who study the content closely and can highlight where the AI glitches are. (This one, by Dino Burbidge, is excellent: The truck is different in every shot of Coca-Cola’s AI Christmas ad. Surely that matters? | The Drum) In this case, Coca-Cola, thought they’d get in front of it by saying the ad was generated by AI. But they still got a hiding, and so they should. (They might have read an academic paper called The transparency dilemma: How AI disclosure erodes trust before they embarked on their quest.)

Those who might argue that most video is already CGI have a point, but it misses the mark. CGI is the backdrop, the framing, but the actor — the human — is real. (I’m not talking cartoons and stuff here, of course). We expect the actor to act, to bring their best to the scene, even if all the see is green screen and someone in a green suit suspending them as if in flight. We want Robert Downey to put in a performance, and we don’t expect his face to be digital even if the rest of him is. But when Coca-Cola populates its AI ad with fake people, fake expressions, where everything you see is fake but trying to appear real then the spell, the suspension of disbelief, is broken, because, simply, we know.

Technically speaking we’re now in the AI equivalent of robots’ uncanny valley – where as robots become more human-like, our affinity abruptly collapse into revulsion. Research suggests that something similar happens with AI-generated text. AI content might not trigger the gag reflex as much as robots do, but we don’t like being fooled, and it’s this that I think will be the source of the largest pushback against use of AI in anything remotely creative, not purely in artistic terms but in any kind of content that draws on, or pretends to draw on, the creator’s experience, knowledge, qualifications, training, personality and background.

I’m not saying AI is a bubble, but I’d be willing to put money on the labelling of content, products, services etc as “100% Human Generated, No AI” appearing everywhere, and companies that seem to be relying on AI on external-facing stuff to be punished quite severely in the marketplace.

If I don’t post before, have an AI-free Christmas and a slop-less New Year.

(No sentences or ideas in this piece were generated by AI. AI was used in searching for some references and sources)

A Directory of RSS Readers for the Mac

By | September 23, 2025
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It’s been a long time since I did Directories of apps here. Indeed, the last one on RSS readers was this one: A Directory of The Best RSS readers which was started in 2004: 21 years ago. I’ll try to get round to updating that at some point. I feel the time has come to reclaim blogs and directories that are human curated and aren’t pushing anything except more satisfying computer usage.

So here’s a start. I’ll update this when I find new stuff. Please let me know if I’m missing something, or getting something wrong.

lire – for iOS, iPadOS and macOS: You only need to buy two apps to cover all three platforms.
lire for macOS if available on the Mac App Store. lire for iOS and iPadOS is available as a universal purchase on the App Stores of the respective devices. Universal purchase allows you to purchase the app once, and then access it on both platforms.

Supports: Feedly, Feedbin, Feed Wrangler, FeedHQ, The Old Reader, Inoreader, Newsblur, BazQux Reader, FreshRSS, Miniflux, Nextcloud News, and Tiny Tiny RSS is currently included.

I like it. Elegant and simple.

Reeder been around for 15 years, and still looking good. Reeder Classic is the one most of us are familiar with. The new version, 5, is just called Reeder and doesn’t support syncing with RSS services. Both are available for Mac and iOS.

While I like the idea that I think the new Reeder is trying to tackle — RSS bloat, where you have way more than you can ever read — I don’t think the answer is to prevent syncing with third party services. Which is why I’m still using Classic.

Leaf – another nice looker. Syncs with Feedly, NewsBlur, Feedbin and Feed Wrangler. $10

Unread – my current favourite, at least for the Mac. (There is an iOS version as well) I’m still not quite sure about the £5 subscription though the free version delivers pretty much all you need.