Stop Asking Whether It Was Made by AI The better question is: What did the human contribute?

Recently, I came across a reflection by Dr. Ahmed Omar Hawsawi that immediately connected with a series of articles I have been writing about AI, authorship and authenticity.

He described a situation that I suspect many of us are beginning to encounter.

Someone presents an impressive presentation.

It is clear, beautifully structured and professionally designed.

Then comes the comment:

“Obviously this was made by AI.”

And sometimes there is an unspoken second sentence:

“Therefore, it is somehow less valuable.”

That is where I think our conversation about artificial intelligence has taken a wrong turn.

Because increasingly, “This is AI” is being used not as a description of a tool, but as a criticism of the person who used it.

We Are Judging the Tool Instead of the Work

Imagine that employee presenting the slides.

Perhaps AI created the visual layout.

Perhaps it reorganized the bullet points.

Perhaps it summarized twenty pages of research.

Perhaps it helped the employee find a better way to explain a complicated idea.

Or perhaps the employee simply gave AI a prompt and accepted everything it produced.

Those are radically different scenarios.

Yet the dismissive phrase—

“It's AI.”

—collapses all of them into one judgment.

This is precisely the problem I explored in my earlier articles, “Generative AI: A Tool, Not a Shameful Shortcut,” “The Watermark Changes Nothing: AI Is Still a Tool, Not the Author,” and more recently in my discussion of AI watermarking and intellectual provenance.

We are trying to answer a complex question with a binary label:

Human or AI?

But increasingly, that is the wrong question.

Nobody Asks Whether Excel Made the Financial Model

Think about how strangely we apply this standard.

An analyst produces a sophisticated financial model.

We don't say:

“That's Excel.”

A designer produces a beautiful building.

We don't dismiss it by saying:

“That's AutoCAD.”

A researcher discovers an obscure but important source through Google.

We don't say:

“Google did the research.”

A photographer produces an extraordinary photograph after significant digital processing.

We generally understand that software participated in the process.

We still ask whether the photographer produced something worthwhile.

AI feels different because it can generate language, images, analysis and increasingly reasoning-like outputs.

It therefore appears to cross a psychological boundary that calculators, spreadsheets and search engines did not.

But the principle remains remarkably similar.

A powerful tool does not eliminate the contribution of the person using it.

What matters is what that person contributed.

There Is Bad AI Use—and We Should Call It Out

None of this means that every use of AI should be defended.

Quite the opposite.

There is an enormous difference between using AI to extend your capabilities and using AI to conceal the absence of capability.

If you submit a report you do not understand, that is a problem.

If AI provides a statistic and you don't verify it, that is a problem.

If it invents a reference and you publish it, that is your problem.

If you upload confidential corporate information into an inappropriate AI service, that is a serious problem.

If you present an AI-generated recommendation to management but cannot explain the assumptions behind it, that is a problem.

And if AI effectively did all the thinking while you merely put your name on the output, questions about authorship are entirely legitimate.

But notice something important.

These are failures of judgment, not failures caused simply by using AI.

That distinction matters.

The Opposite Problem Is Also Emerging

We should also recognize the strange inverse assumption:

Human = authentic.

That isn't necessarily true either.

Humans plagiarize.

Humans recycle other people's ideas.

Humans manipulate statistics.

Humans write superficial reports.

Humans create terrible PowerPoint presentations.

And humans confidently present things they don't understand.

A poorly researched human-written report does not become valuable because no AI touched it.

Likewise, a carefully researched, fact-checked and intellectually rigorous report does not suddenly become worthless because AI helped improve its structure and language.

This is why I increasingly believe that authenticity cannot be determined by the origin of individual sentences alone.

So What Is Authenticity?

This question has become more important to me as my own use of AI has evolved.

For me, authenticity is increasingly about intellectual ownership.

Did you originate or meaningfully develop the idea?

Do you understand it?

Did you challenge it?

Did you bring your experience to it?

Did you verify the evidence?

Did you decide what stayed and what was removed?

Can you explain the argument without opening ChatGPT?

Can you defend it when challenged?

And are you prepared to take responsibility if it turns out to be wrong?

If the answer is yes, then AI participation does not automatically make the work intellectually artificial.

This is what I have previously described as the difference between content provenance and intellectual provenance.

Content provenance asks:

Who—or what—generated these words?

Intellectual provenance asks:

Where did the thinking come from?

The second question is much harder.

It is also much more important.

From AI Detection to AI Literacy

Perhaps our organizations need to spend less energy trying to catch employees using AI and more energy teaching them how to use AI well.

The professional skills of the AI era will not simply be prompting.

They will include verification.

Source evaluation.

Privacy awareness.

Critical thinking.

Understanding model limitations.

Recognizing hallucinations.

Knowing when AI should not be used.

And, increasingly, knowing when human expertise must override an apparently convincing machine-generated answer.

In other words, the most valuable employee will not necessarily be the person who avoids AI.

Nor will it be the person who generates everything with AI.

It will be the person who understands where AI creates leverage and where human judgment must remain decisive.

Imagine the Workplace Five Years From Now

Imagine walking into an office and asking someone:

“Did you use AI to prepare this?”

The question may eventually sound almost as strange as asking:

“Did you use a computer?”

AI will increasingly disappear into the applications we already use.

It will sit inside office productivity software, CRM platforms, analytics systems, search engines, development environments, design applications and enterprise platforms.

At that point, distinguishing between “AI work” and “non-AI work” may become practically meaningless.

The meaningful distinction will be between good work and bad work.

Between verified and unverified.

Between thoughtful and thoughtless.

Between responsible and irresponsible.

Between original thinking augmented by technology and intellectual dependency disguised as productivity.

Don't Surrender Your Mind to the Machine

This brings me back to Dr. Hawsawi's final thought, which I find particularly important:

Use AI—but don't abandon your mind.

That captures the balance we need.

I am strongly in favor of using AI.

I use it.

I write about it.

I experiment with it.

I believe it will become one of the most important productivity and intellectual tools of our generation.

But precisely because these systems are becoming so capable, our responsibility as users becomes greater, not smaller.

The better AI becomes at generating convincing answers, the more important our ability becomes to question those answers.

The faster AI allows us to produce content, the more important it becomes to decide whether that content deserves to exist.

The more AI can speak for us, the more important it becomes to make sure that what it says actually represents what we think.

And the easier AI makes professional work appear, the more important genuine expertise becomes beneath the surface.

So the next time we see an excellent presentation, report, analysis or article, perhaps we should resist the reflexive comment:

“This is AI.”

Instead, ask:

Is it accurate?

Is it useful?

Is there real thinking behind it?

Can the person presenting it explain and defend it?

And are they willing to take responsibility for it?

Those questions tell us much more about the quality of the work than knowing which tools were used to produce it.

AI is becoming part of the workplace.

That battle is essentially over.

The challenge ahead is not learning how to work without AI.

It is learning how to work with AI without surrendering the very human capabilities that make our work valuable: judgment, experience, curiosity, ethics, responsibility and independent thought.

Perhaps that should become our new standard:

Use the machine. Keep the mind. Own the result.

#GenerativeAI #ArtificialIntelligence #ResponsibleAI #HumanAI #FutureOfWork #AIandCreativity #AIAssistedWork #DigitalTransformation #ThoughtLeadership #CriticalThinking #AIAtWork #DigitalLiteracy

---

Originally published in the VerbionPulse newsletter on LinkedIn: Stop Asking Whether It Was Made by AI The better question is: What did the human contribute?.