Human or Machine — Does It Matter Who Created It?

Human or Machine — Does It Matter Who Created It?

Imagine drinking an espresso in a café in Naples. Perfect crema, exactly the right temperature. Then you learn: this espresso wasn't made by a barista but by a fully automated machine. No human tamped the grounds.

Does it taste worse now?

Rationally, you know: no. The espresso is the same. And yet something shifts in your perception. That "something" is at the core of a debate sweeping nearly every industry — from software to art and traditional crafts.

The functional truth

At IJONIS in Hamburg, we encounter this debate daily — in client projects, in our own content production, in software development. The answer we've arrived at is more nuanced than most expect. Let's start with an uncomfortable observation: most work output is functional. It exists to serve a purpose. A landing page should convert. A contract draft should be legally sound. An API should deliver data reliably. A blog post should inform and rank.

If an AI agent creates a landing page that converts 12% better than the human-written one — does the CEO care who wrote the copy? Generally, no. And that's not dystopia. That's pragmatism.

The same logic applies to code. In our article on Vibe Coding, we describe how AI-assisted programming enables productivity gains of 30–80%. The code works. It passes the tests. The software runs. Whether a human or an AI wrote the code, the end user can't tell — and doesn't care.

This is the functional truth: when the result serves its purpose, the creator is irrelevant.

At least at first glance.

Why we resist it anyway

A study from Columbia Business School reveals a fascinating paradox. When participants evaluate artworks without knowing their origin, they prefer AI-generated pieces in nearly 45% of cases. But once they learn a piece was made by AI, its perceived value drops by an average of 62%. The work hasn't changed — only our knowledge of it.

Why? Because we project something onto human-made work that goes beyond the result: effort. Intent. Choices. Sacrifice.

When a carpenter builds a chair, it contains more than a piece of furniture — it holds years of learning, cut fingers, knowledge of wood species, the deliberate choice of a particular joint technique. The chair carries a story. And that story has value — not because it makes the chair function better, but because it makes it human.

This explains why certain professions react particularly fiercely when AI enters their territory.

The industries that push back hardest

The strongest resistance doesn't come from where functional quality suffers most — but from where identity is most tightly bound to craft.

Illustration and design. When Marvel Studios promoted the title sequence of Secret Invasion as AI-generated, the backlash was immediate — including from artists who had worked on the show. It wasn't about the quality of the sequence. It was about the message: your work is replaceable.

Photography. Product photos, property images, headshots — AI can already replace them in many cases. But a wedding photographer will tell you: I was there in that moment. I captured that look. No machine can do that. And she's right — not because a machine couldn't technically produce the image, but because the presence of a human is part of the value.

Copywriting and journalism. In Hollywood, this debate led to the Writers' Strike with concrete regulations: AI cannot write literary material and receives no writing credits. Not because the texts would be bad — but because writing is considered a deeply human act.

The common thread: in all these fields, the end product isn't the only carrier of value. The process, the person, the intent — they are part of the product. Ignoring this means confusing value with function.

Where AI genuinely falls short

Beyond the perception question, there are areas where AI output is actually qualitatively behind human work — not because of insufficient computing power, but because of missing experience. This distinction matters because it's objectively measurable and not based on feelings alone.

Emotional depth in storytelling. AI can reproduce patterns of emotional language — but it doesn't understand why a particular story needs to be told. It lacks intentionality.

Human writers write because something compels them: an experience, a conviction, an anger. AI writes because it's prompted to. You can tell — not always at first glance, but in the depth.

Cultural sensitivity and nuance. AI regularly fails at sarcasm, cultural undertones, and the subtle shifts in meaning that a word takes on in different contexts. A German "Na ja" can mean agreement, resignation, or irony — depending on tone, context, and relationship. To an AI, it's a string of characters.

The unexpected. The most radical creative breakthroughs don't come from optimising what exists but from breaking rules. Punk wasn't an optimised rock pattern. Brutalism wasn't refined architecture. AI can remix and recombine — but it doesn't break rules because it doesn't understand rules. It only knows probabilities.

Craft as physical experience. A handmade leather belt feels different from a machine-produced one — not just metaphorically, but literally. The irregularities aren't defects; they're signatures. In luxury goods, this "beautiful imperfection" is actively sought: making shoes by hand requires intuition, sensitivity, and experience that AI cannot replicate.

Result vs. experience: where AI wins and where humans remain irreplaceable

The following overview shows where AI-generated work is equal or superior — and where human authorship makes the decisive difference:

The real question

The "human vs. AI" debate is misleading because it sets up a false dichotomy. The more productive question is: what exactly am I paying for?

If you're paying for a result — a working app, an SEO text, a contract draft — then the creator is as relevant as the name of the mechanic who fixed your car. Does it work? Good.

If you're paying for an experience — a handcrafted piece of furniture, a wedding photo, a novel — then the human creator is part of the value. Not as romantic idealisation, but as a real component of what you're acquiring.

The problem arises when we confuse the categories:

• Defending human labour on functional tasks just because it feels right — even though AI would be faster, cheaper, and sometimes better.
• Deploying AI on experience-oriented tasks because it seems more efficient — even though the human element is exactly what's being paid for.

Both mistakes happen. Both cost money, time, or trust.

What this means for businesses

For mid-market companies currently developing their AI strategy, this distinction has concrete consequences:

1. Automate what's functional. Internal reports, code reviews, data analyses, first drafts of documents — wherever the result matters and the process doesn't, AI isn't just acceptable, it's superior.

2. Protect what must remain human. Client conversations, creative brand work, craft with signature character — here, the human element isn't a cost factor, it's a differentiator.

3. Be transparent. Research is clear: transparency about AI use is the single most important factor for trust. Passing off AI content as human-made risks more than credibility — in regulated industries, it risks compliance.

4. Make it a strength. AI visibility and human authenticity aren't mutually exclusive. On the contrary: companies that use AI intelligently for efficiency while emphasising human quality where it counts hold a strategic advantage.

Frequently Asked Questions About AI-Created Work

Is AI-generated content worse than human-created content?

Not universally. For functional tasks like SEO copy, code, or data analysis, AI delivers equivalent or better results. For creative work requiring emotional depth, cultural nuance, or personal experience, human work remains superior.

Do I have to disclose when AI contributed to a piece of work?

Legally, the EU doesn't yet mandate general labelling for AI content — the EU AI Act primarily regulates high-risk systems. Strategically, however, transparency is the single most important trust factor. Getting caught concealing AI involvement costs more than any efficiency gain.

Can customers and users tell the difference between AI and human work?

Often not. Studies show that evaluators without origin labels prefer AI works nearly as often as human ones. The difference becomes relevant only when the origin is revealed — then perceived quality drops significantly.

Which industries resist AI the most?

Illustration, photography, copywriting, and luxury craftsmanship show the strongest pushback. The common thread: in these industries, professional identity is tightly bound to the creative process, and the result is seen as inseparable from the person who made it.

"AI doesn't change what we can create — it changes what it means to have created something." — Jamin Mahmood-Wiebe, IJONIS

The conclusion is uncomfortable — and that's the point

The question "human or machine?" has no universal answer. And that is the answer.

Yes, there are domains where it genuinely doesn't matter whether a human or a machine produced the result. Insisting on human authorship in those domains isn't virtue — it's inefficiency.

And yes, there are domains where the human creator is irreplaceable. Not out of sentimentality, but because the human origin is a real, measurable part of the value.

The art lies in honestly distinguishing which category you're in. And the uncomfortable truth is: most of us overestimate how often we're in the second one.

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This article was written entirely by AI. If that surprises you — read it again.