Made by a Human: The Question Behind the Label

We spent years using technology to make humans look less human. Now we're using it to make machines look more human. Somewhere in between, authenticity got hard to locate.

I saw something on Substack this week that felt particularly timely given this article I had already started. Before the author began his piece, he included this preface:

“This publication was human made.”

He explained that he was intentionally leaving it raw and imperfect, including some typos, grammatical mistakes, filler words and rough edges. His point was that these are part of being human, and he wanted more of that in the way we write and communicate with one another.

I found the declaration itself more interesting than the imperfections.

For most of our lives, we have used technology to make our work more polished. Spellcheck catches our mistakes. Editing tools improve our grammar. Cameras correct the lighting. Filters smooth our skin. We have steadily gotten better at removing the flaws.

Now we are beginning to see people deliberately leave some of them in.

I had been thinking about Made by a Human as a possible future designation. Perhaps we would see it on the cover of a book, attached to a song or photograph, or somewhere beside an article. Maybe it would eventually function a little like handmade or locally produced, telling us something about how something was created.

But here it was, already being used.

Are we heading toward a world where typos become proof of authenticity or polished writing becomes suspicious? I hope not. I like smooth edges. But some of what we’re seeing suggests we may be heading in that direction. And I think this tells us something about the emotional response beginning to form around AI-generated content.

People want to know. Was this written by a person? Was that image created by an artist? Is that actually someone’s voice? How much of what I am seeing came from the person whose name is attached to it?

And increasingly, what are we supposed to do with the answer?

That last question interests me most because I don’t think human-made and AI-made divide neatly into good and bad. I use AI in my writing and editing process, and I believe it can add tremendous value. At the same time, I have purchased books that seemed so obviously generated by AI that I felt cheated by what I had bought.

Both things can be true.

What We’re Actually Buying

I have been thinking about this as an author.

When I wrote The Imposter Lies Within, I woke up at five o’clock nearly every morning for nine months. I wrote. Rewrote. Deleted. Researched. Questioned what I thought I knew. Changed my mind. Put things back. Took them out again.

I birthed that book, so I have to admit that I have a reaction when I hear someone proudly announce that they wrote a book in an afternoon or over a weekend using AI. Part of me bristles. And when I’m the consumer, it goes beyond that. I’ve purchased books that seemed so obviously generated by AI, with so little thought or substance behind them, that I felt cheated.

It’s not because I’m anti-AI. Anyone who knows me knows that’s not true. I build AI. I believe deeply in its potential. And I believe AI can have a legitimate and enormously valuable place in the writing and editing process.

So what exactly bothers me? Nine months of work doesn’t automatically make a book good, and producing something quickly doesn’t make it bad. We shouldn’t romanticize struggle or decide that creativity only counts when enough blood, sweat and tears went into it.

Efficiency isn’t the enemy of creativity. And AI itself isn’t the dividing line.

Writers have always used tools, and they have always relied on other humans to edit, question and improve their work. That doesn’t make the writing less human. Neither does using AI to challenge an argument, organize research, identify a weakness or help us see something differently.

Are we heading toward a world where typos become proof of authenticity or polished writing becomes suspicious? I hope not. I like smooth edges.

Perhaps the question we should each wrestle with isn’t whether AI participated. It’s whether we did. What did the human bring to the work?

The idea? The experience? The point of view? The judgment? The curiosity? The choices? The willingness to stand behind what was ultimately produced? When I buy a book, I don’t believe I am purchasing only the words. I am purchasing access to someone’s thinking. And that may be the implicit contract generative AI is beginning to disrupt.

We Were Already Becoming Suspicious of Perfect

Generative AI didn’t create our complicated relationship with authenticity. Social media got there first. For years, we have watched ourselves become progressively more polished on screens. Filters smoothed skin, brightened eyes, reshaped faces, erased wrinkles and transformed ordinary moments into carefully manufactured ones.

At first, the technology helped us make photographs look better. Then the altered version began to become normal. And eventually, something interesting happened: “No filter” became something worth announcing.

Think about how strange that is. We created technology capable of improving the image, and then began using the absence of that technology as evidence of authenticity. The imperfect image acquired a different kind of value precisely because perfection had become so easy to manufacture.^[i]

AI is taking that tension far beyond our photographs.

We shouldn’t romanticize struggle or decide that creativity only counts when enough blood, sweat and tears went into it.

We spent years using technology to make humans look less human. Now we are using technology to make machines look, sound and feel more human. Somewhere between those two movements, authenticity became harder to locate.

The Vanishing Human Contribution

There is now a term for some of what people are reacting to: AI slop. It’s not a particularly elegant phrase, but it has caught on. Merriam-Webster chose slop as its 2025 Word of the Year. And the emotion behind it may be more interesting than the phrase itself.^[ii]

AI slop generally refers to the flood of low-quality, repetitive or minimally considered content that can now be produced at enormous scale using generative AI. Images. Videos. Articles. Books. Music. Social posts. Presentations. And increasingly, entire websites.

But I think we need to be careful with the definition. AI-generated content and AI slop are not the same thing. There is extraordinary work being created with the help of AI. Artists are experimenting with it. Filmmakers are using it. Writers are incorporating it into their process. Musicians are finding ways to create things that weren’t previously possible. Dismissing all of that as slop would be both inaccurate and, frankly, not very interesting.

The issue seems to be less about whether AI was used and more about what happened to the human contribution along the way. And people are having surprisingly strong feelings about it.

Some of that may simply be fatigue, or it may have something to do with our natural inclination toward efficiency. We are wired to conserve effort when we can.^[iii] And AI gives us a very compelling opportunity to do exactly that.

When something appears on the screen almost instantly, beautifully written, polished and seemingly complete, it is easy to accept it as finished. Why wrestle with a sentence that already sounds good? Why challenge an argument that seems convincing? Why spend three hours thinking through something AI can produce in thirty seconds?

Except some of that wrestling and wrangling is where the human contribution happens. It’s where we decide what we actually think. Where we question, disagree, make choices, change direction and eventually make the work ours.

When it becomes possible to produce hundreds of images, articles or songs in the time it once took to make one, the economics of content change dramatically. The effort required to produce more and more content can become remarkably small. The time required to consume it does not. Our attention is still human, and that may explain at least part of the backlash.

When I give ten minutes of my life to reading something, listening to something or watching something, there is an implicit exchange taking place. Someone created something they thought was worth my attention, and I am giving them some of mine.

What happens to that exchange when almost no attention was required on the other side?

AI-generated content and AI slop are not the same thing.

I don’t think that automatically makes the work worthless. A person could use AI brilliantly in ten minutes and create something far more valuable than something another person labored over for ten months. We come back to the same problem we encountered with books: effort isn’t a reliable measure of value.

But intention might be. Judgment might be. Having something to say might be.

And perhaps that is part of what people are responding to when they use the word slop. We are being asked to spend our human attention consuming things that may have required very little human attention to create.

The backlash is already moving beyond individual annoyance. Platforms, publishers, musicians, artists and other creative industries are beginning to wrestle with real-world consequences. With attention at a premium, what happens when the market is flooded with synthetic content? Humans have a limit to what they can consume. AI content seems limitless. So who’s watching out for the human creators?

But there is another side to this. Sometimes AI isn’t replacing something because it can do it better. We’re simply using it because we can.

The Backlash Is Getting Complicated

I had my own small experience with this recently. I was participating on an AI panel and was asked to send a photograph for the promotional materials. I sent a high-resolution headshot taken by a professional photographer.

When the promotion came out, someone had used AI to regenerate my photograph. It was obviously me, but it wasn’t my photograph anymore. And, frankly, the original was better. I didn’t say anything, but it bothered me. Mostly, I wondered why it had been done at all. There was nothing wrong with the image I sent. It didn’t need to be recreated.

Maybe this is another part of what we are figuring out. Once a tool can do almost anything, it becomes very easy to use it for everything.

At the same time, the backlash against AI-generated content is creating problems of its own. Substack recently introduced an AI-detection feature using Pangram. Readers can scan a post or Note and receive an estimate of how much of the writing is human or AI-assisted.^[iv] The response among writers has been anything but settled. Some welcome the transparency. Others have questioned its accuracy and whether an algorithm should be passing judgment on who wrote something in the first place.^[v]

LinkedIn has taken a different approach. Users can now flag a post or comment with “Seems like AI slop.”^[vi] No detector required. No proof required. It is feedback based on whether the content feels generic, repetitive or lacking in substance. LinkedIn says the feedback alone does not determine whether a post is removed or constitute a policy decision.

I understand what LinkedIn is trying to do. I also find it a little unsettling.

What happens when sounding too polished becomes suspicious? When a certain sentence structure, vocabulary or writing style is enough for someone to decide that the work isn’t yours? We could end up in the strange position of asking humans to prove they are human while AI keeps getting better at sounding like us.

There is another problem here. If deciding what qualifies as AI slop becomes a matter of human judgment, that judgment can be wrong too. It can also be manipulated. A creator could find themselves defending work they actually wrote simply because enough people decided it sounded like AI.

Which leaves us with an uncomfortable problem. On Substack, we can ask whether an algorithm should be deciding what is human. On LinkedIn, we can ask whether other humans should. I’m not sure either one gets us where we need to go.

And that takes us somewhere beyond AI slop.

The problem isn’t simply how we identify what AI created. We haven’t even agreed on what should count as AI-created in the first place.

If I write an article and use AI to challenge my argument, am I the author? I believe I am. If AI edits my grammar, helps with research or suggests a better organization, is that cheating? What if it writes a paragraph that I substantially rewrite? What if I give it my ideas and it writes the entire article?

Somewhere along that continuum, the nature of authorship changes. I don’t know that we have agreed on where.

Perhaps a label like Made by a Human will eventually help us answer that question. But before we can label it, we may need to decide what we mean by it.

The Reputation Cost

There is another consequence I have been thinking about, and it has less to do with the content than with the person whose name is attached to it.

I notice it in the comments on my own posts. Sometimes I read a comment and suspect that most, if not all, of it was generated by AI. The comment isn’t necessarily bad. It may be complimentary, relevant and perfectly well written. But I find myself less inclined to respond.

That’s interesting to me because my reaction isn’t really to the words. It’s to the possibility that the person didn’t put much of themselves into them. If I’m going to take the time to think about what you said and respond to you, I want to feel that I’m actually in a conversation with you.

And this goes well beyond social media. People are using AI to write cover letters, answer application questions, respond to prospective employers, communicate with potential investors and make introductions. Again, using AI isn’t necessarily the issue. I use it too.

But what happens when the person receiving that communication begins to wonder how much of the thinking actually belongs to the person sending it? I wonder if we’re underestimating the reputational risk. If everything under our name becomes polished, articulate and instant, but people begin to suspect that very little of it actually came from us, what exactly are we signaling about ourselves?

This becomes particularly important when someone is evaluating us. An employer isn’t only evaluating the quality of an application. An investor isn’t only evaluating the language in a pitch. A prospective partner isn’t only evaluating an email. They are trying to understand the person behind it.

AI can help us communicate our thinking more clearly. But if we hand over too much of the thinking itself, we may inadvertently make it harder for other people to know who they’re evaluating.

Maybe that’s another reason the human contribution matters. It isn’t only about protecting the integrity of the work. Sometimes the work is how other people decide whether to trust us.

Why We Care How Things Are Made

There was a time when calling something handmade would have been fairly meaningless. Almost everything was. Industrialization changed that. Mass production made goods less expensive, more consistent and available to far more people. Those were enormous advances, and few of us would want to give them up.

But once mass production became ordinary, handmade began to tell us something that it hadn’t needed to tell us before.

If everything under our name becomes polished, articulate and instant, but people begin to suspect that very little of it actually came from us, what exactly are we signaling about ourselves?

We see versions of that distinction everywhere now. Artisan. Small batch. Locally made. Farm-to-table. Original. They don’t necessarily tell us that something is better. A handmade chair can be poorly made. A mass-produced one can be exceptional.

They tell us something about where something came from and, sometimes, how it was made. That may be closer to what we are looking for with Made by a Human.

The comparison isn’t perfect. AI is not an assembly line, and writing a book isn’t the same as making a chair. More importantly, most creative work today already involves technology. The question isn’t whether technology touched it. It’s how much of the human remained in the process.

The Authorship Question

I’m not sure there is an easy answer. Spellcheck doesn’t change authorship. Neither does an editor suggesting a clearer sentence. And if I use AI to research a question, challenge my thinking or point out something I’ve missed, I still consider myself the author.

But somewhere along that continuum, things get murkier.

If I give AI a topic and ask it to write an article, then make a few changes and put my name on it, is that Made by a Human? What if the ideas were mine but most of the words weren’t? What if AI came up with the ideas too?

We could try to solve this with percentages. How much was written by AI, and how much by a person? But I’m not convinced word count tells us very much about authorship. A person can write every word of something without bringing much original thought to it. Another person can spend hours developing an argument, drawing from years of experience, questioning assumptions and making decisions about what they want to say, then use AI extensively to help express it. Those are very different creative acts.

Perhaps the more useful questions are about agency. Who had something to say? Who shaped the thinking? Who made the choices? Who decided what stayed and what went? And who is willing to put their name on the finished work and stand behind it?

Even those questions won’t give us a perfect dividing line. Maybe we don’t need one.

But I do think we’re going to need better language for the differences.

The Case for a Label

Maybe we do. We’re already experimenting with versions of one.

Amazon distinguishes between AI-generated and AI-assisted content.^[vii] Pinterest gives users some control over how much generative AI content they see.^[viii] Substack is experimenting with detection. LinkedIn is asking users to identify content that feels like AI slop.

None of these approaches settles the question, and some create entirely new problems. But the fact that they exist tells us something. For most of the history of publishing, music, photography and art, we didn’t need a label telling us a human was involved. We assumed it. We can’t assume that anymore.

I’m not convinced word count tells us very much about authorship.

I don’t know whether Made by a Human will eventually appear on books, music, art, photographs or anything else as a recognized designation. And I’m not sure I’d want a world neatly divided into human and AI categories. The most interesting work may very well come from people who learn how to use these tools without handing over the parts of the process that make the work theirs.

Maybe what we will want isn’t proof of technological purity. We may simply want some transparency about who, or what, we’re engaging with.

Made by a Human

Which brings me back to that Substack preface.

I still don’t think we should have to leave typos in our writing to prove that we’re human. I’m keeping my spellcheck. I like my smooth edges. But I understand the impulse differently now.

The writer I mentioned wanted his readers to know that there was a person behind what they were about to read. Someone had thought about it, decided what he wanted to say and put his name on it.

As AI becomes part of more of what we create, I think we’re going to want to know more about the role the human played.

I don’t know whether Made by a Human will ever become an actual label. But I understand why someone would want to say it. We want to know where the human was in the process. We want to know whether there was thought behind the words, intention behind the image, judgment behind the choices.

Maybe the question isn’t whether AI helped create it.

It’s whether the person whose name is on it can still say, this is mine.

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^[i] Double reminders, double standards: how other-use and self-use reminders of AI beauty filters shape observer reactions | Internet Research | Emerald Publishing

^[ii] SLOP Definition & Meaning - Merriam-Webster

^[iii] The transdiagnostic structure of mental effort avoidance | Scientific Reports

^[iv] How can I detect AI on Substack? – Substack, Inc

^[v][v] Substack’s Pangram AI Detector Accuracy: My 159,002-Word Test

^[vi] Best practices for content created with the help of AI | LinkedIn Help

^[vii] Content Guidelines

^[viii] Pinterest rolls out new tools to give users more control over GenAI content | Pinterest Newsroom